|
| |
|
|
|
|
||||
| Home Help Feedback Subscriptions Archive Search Table of Contents | ||||
First published online August 17, 2007
Journal of Experimental Biology 210, 3107-3116 (2007)
Published by The Company of Biologists 2007
doi: 10.1242/jeb.007351
Thermal preference of Caenorhabditis elegans: a null model and empirical tests
1 Center for Ecology and Evolutionary Biology, University of Oregon, Eugene,
OR 97402, USA
2 Department of Ecology, Evolution and Organismal Biology, Iowa State
University, Ames, IA 50011, USA
3 Department of Biology, University of Washington, Seattle, WA 98195,
USA
Author for correspondence (e-mail:
pphil{at}uoregon.edu)
Accepted 24 June 2007
 |
Summary |
|---|
 TOP Summary IntroductionMaterials and methodsResultsDiscussionReferences |
|---|
17°C). These
differences are not influenced substantially by changes in the starting
position of worms in the gradient, the natal temperature of individuals or the
presence and physiological state of bacterial food. These results demonstrate
the value of an explicit null model of thermal effects and highlight problems
in the standard model of C. elegans thermotaxis, showing the value of
using natural isolates for tests of complex natural behaviours.
Key words: Caenorhabditis elegans, diffusion model, natural variation, null model, thermal gradient, thermal preference
|
Introduction |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
;
Grant and Dunham, 1988;
Rosenzweig et al., 2005).
Moreover, many ectotherms manipulate time of activity, habitat choice and
posture in an attempt to achieve body temperatures, Tb, in
narrow preferred (or `selected') ranges
(Cowles and Bogert, 1944;
Heath, 1965;
Huey et al., 1977;
Christian et al., 1983;
Stevenson, 1985;
Kingsolver, 1987) and thereby
increase the amount of time spent at physiologically optimal temperatures
(Christian and Tracy, 1981;
Huey, 1983;
Kingsolver and Watt, 1983;
Waldschmidt and Tracy, 1983;
Huey et al., 1989;
Hertz et al., 1993;
Angilletta et al., 2002;
Huey et al., 2003). Thermal
preferences are usually measured by placing individuals in laboratory thermal
gradients and then determining the distribution of their
Tb (Licht et al.,
1966; DeWitt and Friedman,
1979; Crawshaw,
1980). This distribution is assumed to represent the preferred or
selected (Pough and Gans,
1982) temperature of the population. However, if part of the
gradient is cold enough to slow or immobilize the animal, the observed
distribution of Tb may be biased by a `cold trap' and thus
not represent a true thermal preference. Similarly, if the time course of the
experiment is too short for ectotherms to disperse to their preferred zone,
observed Tb distributions can again be misleading.
These concerns are generally insignificant for gradient studies with
vertebrate ectotherms such as lizards
(Licht et al., 1966;
Bennett and John-Alder, 1986;
Angilletta et al., 2002),
snakes (Huey et al., 1989;
Blouin-Demers and Weatherhead,
2001) and fish (Beitinger and
Fitzpatrick, 1979; Reynolds
and Casterlin, 1979; Crawshaw,
1980). These ectotherms are large and thus have considerable
thermal inertia (Spotila et al.,
1973; Stevenson,
1985; Christian et al.,
2006). Consequently, they can move around quickly in a laboratory
thermal gradient, and thus their body temperature, and hence speed, will not
change markedly with position in the gradient. Therefore, the distribution of
their Tb should serve as a valid estimate of thermal
preference, assuming temperatures in the cold zone do not trap these
animals.
For microorganisms, however, these concerns are major. Microorganisms have
limited thermal inertia (Stevenson,
1985) and so their temperature and speed will vary with position
on the gradient. Moreover, if they are small relative to the size of the
gradient, they may take a long time to reach preferred zones. The direct
interaction between temperature and locomotion has not been appreciated in
prior thermal preference studies of microscopic ectotherms, and currently no
empirical framework exists for evaluating whether the resulting temperature
distribution is generated by preference or by kinetics or both. Resolving this
issue is important because of widespread interest in thermal preferences of
small and microscopic ectotherms such as Caenorhabditis elegans
(Hedgecock and Russell, 1975;
Mori and Ohshima, 1995;
Ryu and Samuel, 2002;
Yamada and Ohshima, 2003;
Mohri et al., 2005;
Biron et al., 2006;
Luo et al., 2006;
Ito et al., 2006),
Daphnia (Kessler and Lampert,
2004), Escherichia coli
(Salman et al., 2006) and
Dictyostelium discoideum (Poff
and Skokut, 1977).
A resolution to this dilemma can be achieved in several steps. First, one must develop a mathematical null model that predicts the expected (or null) distribution of microscopic ectotherms on a thermal gradient in the absence of thermal preference. In other words, the model is developed to predict the impact of temperature-mediated diffusion of non-regulating organisms. Second, to parameterize the model, one must quantify actual movement rates as a function of temperature. Then, deviations of the actual distribution of ectotherms from the null distribution provide evidence of active thermoregulation.
Null models have long been important to thermal biology. James Heath's
classic beer-can experiment (Heath,
1964), which was probably the first null (experimental) model in
physiological ecology, forced physiological ecologists to re-evaluate evidence
of thermoregulation. Subsequent null models have extended this theme for field
studies (Huey et al., 1979;
Hertz et al., 1993;
Huey et al., 2003).
Surprisingly, however, null models have not been developed or applied for
laboratory studies. In the present study, we integrate observations of
temperature-dependent diffusion of microscopic ectotherms on a thermal
gradient with a mathematical model of temperature-dependent dispersal. In
doing so, we establish a framework for evaluating the potentially biasing role
of temperature-dependent dispersal on thermal preference assays. To
investigate the validity of this solution through simulations, we use
empirical data obtained from the nematode C. elegans and apply our
findings to empirical results for the standard C. elegans laboratory
strain (N2) as well as to the most genetically divergent known strain of
C. elegans (CB4856). We show that N2 displays an ambiguous thermal
response whereas CB4856 is strongly cryophilic.
Caenorhabditis elegans is a very small ectotherm that has been
used extensively to study thermal preference behaviour
(Hedgecock and Russell, 1975;
Mori and Ohshima, 1995;
Ryu and Samuel, 2002;
Yamada and Ohshima, 2003;
Mohri et al., 2005;
Biron et al., 2006;
Luo et al., 2006;
Ito et al., 2006). This
androdioecious (males and selfing hermaphrodites) soil nematode is
approximately 1 mm in length and 0.6 µg as an adult
(Ferris et al., 1995). At this
size, the direct effects of environmental temperature on physiology can be
substantial and wide ranging. Temperature impacts many evolutionarily and
ecologically relevant aspects of C. elegans biology, including
generation time, growth and reproduction rates
(Byerly et al., 1976), rate of
population increase (Venette and Ferris,
1997) and swimming behaviour
(Ryu and Samuel, 2002).
Additionally, allele-specific sensitivity to temperature influences age at
maturity, fertility and growth rate
(Gutteling et al., 2007).
Caenorhabditis elegans, therefore, provides an ideal system for
investigating the underlying ecological and genetic basis of thermal
preference.
A model of dispersion patterns under temperature-sensitive movement rates
To develop a null model of dispersion patterns under the sole and direct
influence of temperature, we consider a random walk model of movement in which
the rate of movement is temperature dependent. Such problems are often
modelled using a diffusion approximation, which considers a population of
identical individuals spreading out across a continuous spatial landscape
(Berg, 1993;
Murray, 1993). In general,
diffusion models of this type assume that animals tend to move from more
crowded areas to less crowded areas. Instead, we will assume that animals move
in a random, Brownian fashion, but at a temperature-dependent rate. If rates
of locomotion increase with temperature, then we might expect animals in cool
sections of the gradients to tend to stay there, whereas many of those at
warmer temperatures would tend to stream into cooler areas, resulting in an
apparent cold preference even in a non-thermoregulator.
When movement rate depends on temperature, the equation for the change in
density at a point in one-dimensional space is:
 | (1) |
)]. For simplicity, we assume that temperature varies only
with spatial position, not with time, as would be the case for a stable
thermal gradient. This equation can be applied to a two-dimensional case as
long as temperature is constant in the second dimension and we integrate
density over the second dimension for each point on the first dimension.
For a specific function c(x), we can solve
Eqn 1 numerically to track the
change in density with time. If the population is restricted to a finite
spatial domain of [0,L], as it often is experimentally, then we have
no-flux boundary conditions where
f(t,0)/t=f(t,L)/t=0.
In addition to tracking changes in density over time, we can also solve for
the steady-state distribution that animals will eventually achieve. For a
stable thermal gradient, we can write the steady-state condition as:
 | (2) |
We can evaluate this somewhat surprising result by using
Eqn 2 to check other possible
steady-state solutions, noting that it gives a differential equation for
f in terms of the diffusion function whose solution is:
 | (3) |
|
Materials and methods |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
After an individual's location was changed, its new temperature (and thus the probability distribution for future locomotion) was determined by its new location (assuming that Tb equilibrated instantaneously). Simulations were also conducted at fixed temperatures so that the simulated diffusion process could be checked against the actual diffusion process. In the simulation results presented below, null distributions were estimated by simulating the movement of individual nematodes on the gradient for 20 000 replicate experiments.
Nematode strain maintenance
The C. elegans natural isolate CB4856 and wild-type Bristol
strain, N2, were obtained from the Caenorhabditis Genetics Center
(University of Minnesota, Minneapolis, MN, USA) and inbred by selfing for 10
generations to generate isogenic lines that were immediately frozen.
Independent trails were run on thawed stocks in order to minimize any genetic
changes that might accumulate over time. Stocks were allowed to acclimate for
two generations out of the freezer before use to minimize any direct effects
of freezing per se. Nematodes were maintained at 20°C on nematode
growth medium-lite (NGM-lite; US Biological, Marblehead, MD, USA) seeded with
E. coli strain OP50 unless otherwise indicated
(Brenner, 1974;
Sulston and Hodgkin,
1988).
Dispersal at fixed temperatures
We needed estimates of temperature-dependent locomotion at fixed
temperatures to simulate the dispersal of C. elegans on a thermal
gradient. Therefore, we measured the rate at which worms dispersed from a
common release site at uniform temperatures (14°C, 20°C and 24°C).
Age-synchronized populations (Stiernagle,
1999) of nematodes in the final larval stage (L4) were washed from
uncrowded NGM-lite plates with S-basal (0.1 mol l–1 NaCl,
0.006 mol l–1 K2HPO4, 0.044 mol
l–1 KH2PO4, 1 ml of 5 mg
ml–1 cholesterol in ethanol), allowed to settle in
microcentrifuge tubes, and transferred to 1 cm2 Whatman 1.0
Qualitative filter paper (Florham Park, NJ, USA). By briefly inverting the
filter paper onto the bacterial lawn that covered the thermal gels (NGM-lite
prepared in 10.2x17.5x0.5 cm plastic frames backed with
transparency film, seeded with OP50 and incubated overnight at room
temperature), we were able to efficiently transfer approximately 300 readily
motile worms to each thermal gel.
Assays were performed in temperature-controlled incubators at 14°C, 20°C and 24°C. Thermal gels (covered to prevent evaporation) were equilibrated to the appropriate temperature prior to each experiment. Nematode distribution was recorded via pen onto a transparency film with the aid of a stereomicroscope after 10, 60, 160, and 260 min. The data were then scanned to a computer, converted to digital format and analyzed with Image Pro Plus 5.1 (MediaCybernetics Inc., Silver Spring, MD, USA) to determine the location (x,y) of individual worms relative to a central origin.
Thermal gradient
Three thermal gradients, similar in design to that of Yamada and Ohshima
(Yamada and Ohshima, 2003),
were placed in a climate-controlled room with an ambient temperature of
15°C. Each gradient consisted of an aluminium plate (25x45x0.2
cm) secured with clamps to 2 cm2-thick aluminium bases. A 1-cm
channel was drilled through the base (side to side), allowing the continuous
circulation of water or ethylene glycol from external baths controlled at
50°C and 2°C. To facilitate temperature measurements and repeatable
gel placement on the gradient, a thin plastic sheet containing a 1
cm2 grid was secured with clamps to the aluminium plate; a thin
layer of glycerol was placed between the plastic and aluminium, thereby
holding the plastic flat against the plate. Thermal gels, in plastic frames
with the transparency backing intact, were placed directly on the 1
cm2 grid. This setup produced a stable and robust linear gradient
averaging 1.15 deg. cm–1 (s.e.m. 0.013 deg.
cm–1) on each gradient from 10.5 to 29°C (Fig. S1 in
supplementary material). A second frame (14x22x5 cm) of heavy
acetate with detachable lid was used to reduce airflow over the gels.
We mapped the surface temperature of thermal gels on each gradient apparatus to 1 cm2 resolution using a thermistor probe (Omega 408; Stamford, CT, USA) attached to a handheld thermometer (Omega HH41; accuracy ±0.015°C, resolution ±0.01°C). The time course and stability of these readings was verified using temperature data loggers (iButton®, DS1921G; accuracy ±1°C, resolution ±0.5°C; Maxim Integrated Products Inc., Dallas, TX, USA). These data were used to generate a model of the surface temperature of the gels on each gradient using JMP 4.0 (SAS Institute, Cary, NC, USA). Temperature change across this portion of the gradient was highly linear, so a linear model accurately predicted temperature. Using this linear model, we then estimated the temperature experienced by an individual nematode at any given (x,y) coordinate. Relative to past studies, which assign worms to coarsely resolved temperature or location categories, our design allows more accurate measurement of the temperature experienced by each worm.
Thermal preference assay
Age-synchronized populations of naive nematodes (L4) were applied to
thermal gels via filter-paper transfer at a specific location on each
thermal gradient corresponding to 10°C, 20°C or 24°C depending on
the experiment. Thermal gels were equilibrated on the thermal gradients for 1
h prior to the assays. Nematodes were allowed to experience a thermal gradient
for up to 8 h before location of individual worms was recorded onto a
transparency film with the aid of a lighted 5x magnifier. These data
were converted to digital format and analyzed as previously described. Given
the size of an individual nematode (<1 mm), the thermal time constant
(Christian et al., 2006) for
acclimation to the temperature of the agar surface is much less than one
second, thus justifying the assumption that location and temperature of an
individual are equivalent.
Food quality
If nematodes were tested on gradients with live bacteria for food, their
position might be influenced by the effects of temperature on bacterial
metabolism and reproduction and hence density. To ascertain if nematode
distribution was influenced by these effects we assayed thermal preference
using dead bacteria (heat- or UV-killed bacteria). Heat-killed bacteria were
prepared by exposing liquid cultures of E. coli OP50 to 75°C for
1 h (Couillault and Ewbank,
2002). Dead bacterial cells were concentrated and spread onto
thermal gels to approximate a live E. coli lawn and allowed to dry
overnight at room temperature. To prepare UV-killed bacterial lawns, thermal
gels were seeded with OP50 and grown overnight at room temperature, then
irradiated for 4 min at 100 mJ cm–2 in a UV Crosslinker
FB-UVXL-1000 (FisherBiotech, Pittsburgh, PA, USA) and incubated at 37°C
overnight. Thermal gels resulting from these treatments were tested for the
presence of live bacteria by inoculating sterile NGM-lite plates with streaks
from the treated lawns and incubating for 24 h at 37°C. Plates that tested
positive for bacterial growth were eliminated
(Gems and Riddle, 2000).
Cultivation temperature and fed vs unfed trials
In addition to testing worms with access to food (above), we also ran tests
for worms without food so that we could compare our results with those of
prior studies, which usually tested unfed worms. We raised replicate N2 and
CB4856 populations at 14°C, 20°C or 24°C for two generations
before assaying thermal preference in fed and in unfed trials. Populations
– age synchronized by transferring eggs in non-crowded conditions to 10
cm NGM plates seeded with E. coli OP50 and grown to the final larval
stage at the appropriate temperature – were assayed as above with the
following exceptions. In unfed trials, thermal gels were not seeded, and assay
duration was reduced to 1 h due to rapid migration of worms off the assay
surfaces.
Statistical analyses
Results were analyzed using a factorial nested analysis of variance with
main effects of strain, cultivation temperature and starting temperature, and
with replicate as a nested effect. Replicate was treated as a random effect,
whereas all other factors were considered fixed. Standard errors were
calculated from the overall model via a least-squares means approach,
with the whole-plate replicate (rather than the individual nematode) as the
unit of sampling variation.
|
Results |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
|
|
Dispersal and preference on a thermal gradient
Temperature-dependent (null) diffusion on a thermal gradient should be
similar to diffusion at a fixed temperature, except that the rate of diffusion
changes differentially with the location (and thus temperature) of an
individual. Using the temperature–diffusion relationship measured above,
we estimated how the distribution of individual nematodes
(non-thermoregulating) would be expected to change during a 24 h period after
a fixed start at 24°C (Fig.
3). Even after 15–30 min, individuals should diffuse over
much of the upper part of the gradient but should take substantially longer to
diffuse throughout the colder regions. Nevertheless, as predicted by the
analytical model, the overall distribution tends to flatten out over time,
although it is still slightly biased towards warmer temperatures even after 24
h (Fig. 3).
|
|
|
Initial starting conditions
The mean thermal preferences of N2 and CB4856 differ by more than 4°C
[Figs 4 and
5; N2, 21.66±0.213 (mean
± s.e.m.); CB4856, 16.97±0.298] under standard assay conditions
(8 h, fed, 24°C start temperature, 20°C cultivation temperature).
Note, however, that mean thermal preferences of N2 were always within a few
degrees of each start temperature that we evaluated
(Fig. 6; 14°C,
14.98±0.239°C; 20°C, 18.68±0.0453), again suggesting
that N2 lack a thermal preference beyond an avoidance of extreme temperatures.
By contrast, CB4856 always migrated towards a preferred temperature range
cooler than the cultivation temperature, regardless of start position
(Fig. 6; 14°C,
14.55±0.341; 20°C, 16.25±0.348). Although the final position
of both strains correlated with start temperature (N2,
F2,6.06=217.22, P<0.0001; CB4856,
F2,12.99=4.98, P=0.025), the effect of start
temperature was much larger in N2 (Fig.
6).
|
|
|
|
Discussion |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
;
Angilletta et al., 2002) and of
thermoregulatory `targets' for field-active animals
(Hertz et al., 1993). Thermal
preferences are typically estimated from the distribution of body temperatures
of animals in a laboratory thermal gradient
(Licht et al., 1966). Prior
studies have implicitly assumed that the distribution of body temperatures
reflects only the organism's thermal preference and is thus not biased by the
direct physiological effects of temperature on its directed movement in the
gradient. This may be reasonable for large organisms that have thermal inertia
and thus can move quickly around in the gradient without a major change in
Tb but is unreasonable for microscopic organisms such as
bacteria, protists and nematodes. Speed of movement of these small ectotherms
will vary with their position in the gradient, potentially leading to
temperature distributions that reflect the thermal dependence of movement as
well as inherent thermal preference. To be able to evaluate the potential
bias, we developed a null model for temperature-dependent diffusion and
explicitly parameterized that model with empirical estimates of
temperature-dependent rates of locomotion. This null model predicts the
temperature distribution of a hypothetical ectotherm with
temperature-dependent movement but without a thermal preference, and it allows
us to rigorously evaluate the hypothesis that body temperatures in a gradient
reflect only thermal preference.
Part of the motivation for generating this null model was our intuition that organisms that ventured into the cold sections of a gradient might simply be becoming `trapped' there because their speed would be reduced. Obviously, if locomotion were to decline to zero at some temperature on the gradient, then individuals that experienced that temperature would indeed be trapped: in this case, low temperature would be an absorbing boundary for a random walk along the thermal gradient. However, as long as coldest temperature in the gradient is above this minimum temperature threshold, our theoretical analysis suggests – contrary to our simple intuition – that individuals moving randomly with respect to temperature (but at a temperature-dependent speed) will eventually spread uniformly over the gradient (Eqn 3). Certainly, for the time scales and diffusion rates of the strains studied here, the slowing of diffusion at low temperatures (Fig. 1) will not cause nematodes to accumulate at low temperatures (Fig. 3). Thus, rapid movement of the Hawaiian natural isolate CB4856 into the low-temperature portion of the gradient indicates true cryophilic behaviour, not low-temperature trapping (Fig. 4). By contrast, the standard lab strain N2 exhibits some tendency to avoid high temperatures but does not move substantially from where it is placed; therefore, N2 does not exhibit a true thermal preference, at least in this environment (Figs 5, 6). These between-isolate results are robust to differences in rearing temperature, food quality and overall food availability. In the absence of an explicit null model, these results would be much more difficult to interpret.
Thermal preference in C. elegans
In pioneering research on thermal preference in C. elegans,
Hedgecock and Russell (Hedgecock and
Russell, 1975) observed that well-fed worms move towards –
but starved worms disperse away from – their cultivation temperature
when assayed on a laboratory thermal gradient. These observations have served
as the backbone of thermotaxis research in this important model organism and
have facilitated advances in the identification of thermotaxis-related genes
(Cassata et al., 2000;
Colosimo et al., 2004;
Satterlee et al., 2004;
Mohri et al., 2005;
Tanizawa et al., 2006;
Inada et al., 2006), the study
of learning and memory (Samuel et al.,
2003; Mohri et al.,
2005; Kodama et al.,
2006) and characterization of the neural network for thermotaxis
(Mori and Ohshima, 1995;
Zariwala et al., 2003;
Samuel et al., 2003;
Clark et al., 2006). However,
the definitive roles of cultivation temperature and feeding state (i.e. fed
versus starved) in C. elegans thermal preference, although
supported in several recent studies (Mori
and Ohshima, 1995; Mohri et
al., 2005; Ito et al.,
2006), are controversial
(Yamada and Ohshima, 2003;
Luo et al., 2006). Neither of
the strains we evaluated (N2 and CB4856) conform to the standard expectation.
Rather, N2 demonstrates thermal preference only in the sense that it avoids
extreme high temperatures (Fig.
5), but otherwise it conforms closely to the null model and thus
shows thermal neutral behaviour in a gradient. This outcome is consistent with
the results of Yamada and Ohshima, who propose that avoidance of extreme
temperatures is more important than cultivation temperature in dictating N2
dispersal on a thermal gradient (Yamada
and Ohshima, 2003). This is also qualitatively consistent with the
data of Ryu and Stewart (Ryu and Stewart,
2002) and Clark et al. (Clark
et al., 2007a), who find that N2 exhibits an initial cryophilic
response followed by isothermal tracking, although we do not find a strong
role for cultivation temperature. Ryu and Stewart do find that N2 will exhibit
isothermal tracking at a wide variety of temperatures, however
(Ryu and Stewart, 2002).
N2 appears to lack preference for a specific temperature or range and thus
differs from CB4856 as well as other organisms. Thus, the behaviour of N2 on a
thermal gradient deviates from a canonical notion
(Reynolds and Casterline,
1979) of thermal preference as representing single and narrow
preferred temperature range. The behaviour of N2 in our assays is not easily
explained by the three factors predicted to determine ectotherm distribution
on thermal gradients: thermal preference behaviour, temperature-dependent
physiological rates (Fig. 1)
and time (Fig. 5). N2 appears
to be `unmotivated' to disperse from any moderate temperature on a thermal
gradient when food is present, even though it is fully capable of locomotion
at all temperatures found in our gradient and can cover substantial distances
in the time allotted on the gradient (Fig.
1). Importantly, the behaviour of N2 is consistent over a range of
cultivation temperatures, start temperatures, food quantities and food
quality: thus, the results obtained here are unlikely to be artefacts of
different assay designs between this and previous studies.
Historically, most thermal preference assays for C. elegans have
been conducted without food. However, when well-fed nematodes are moved to
food-free environments they swim up to 10-fold faster than when on food
(de Bono and Bargmann, 1998;
Sawin et al., 2000) and
exhibit dispersal behaviour within approximately 40 min of starvation
(Gray et al., 2005;
Wakabayashi et al., 2004).
This increased dispersal probably represents food seeking with temperature
serving as a cue and likely confounds traditional thermal preference assays
performed without food. Part of our motivation for testing for thermal
preference in the presence of food, which is a new paradigm in C.
elegans, is that we hypothesized that thermal preference in the presence
of food might be different (and more ecologically relevant in terms of the
long-term physiological response of the nematodes) than the apparent food cue
or food-seeking behaviour traditionally observed for thermal preference in the
absence of food. To our surprise, we did not see a strong influence of the
presence or absence of food on thermal preference
(Fig. 8).
Striking differences in the thermal behaviour of CB4856 versus N2
(Figs 4,
5) indicate that thermal
preference differs between strains of C. elegans. Prior research on
thermotaxis in C. elegans focused almost exclusively on N2 or on
mutants in an N2 background. However, the behaviour of N2 in a gradient
(Fig. 6) is clearly atypical of
other ecotherms and even of `wild' strains of C. elegans such as
CB4856 and other strains (L.A., J.L.A., R.B.H. and P.C.P., unpublished). We
suspect that the atypical behaviour of N2 evolved as a consequence of its
unusual and extensive cultivation history. N2 was collected prior to 1956 near
Bristol, UK (Nicholas et al.,
1959) and was maintained in unusual axenic laboratory conditions
for nearly a decade (Dougherty et al.,
1959; Nicholas et al.,
1959) before being received by S. Brenner in 1964
(Brenner, 1974). During its
long history of laboratory cultivation, N2 has experienced thousands of
generations of evolution at room temperature: during this time, N2's normal
thermoregulatory behaviours might well have decayed via mutation
accumulation (Ajie et al.,
2005), or even have become maladaptive in a homogeneous and
constant thermal environment.
Given the strong and mounting evidence regarding the genetic and
neurological basis of thermotaxis in C. elegans (e.g.
Mori and Ohshima, 1995;
Zariwala et al., 2003;
Mohri et al., 2005;
Clark et al., 2007b), it is
clear that N2 does in fact respond to temperature. However, specific results
have varied from laboratory to laboratory. This could be a reflection of
differences in laboratory apparatus, laboratory-specific environmental
conditions, and/or slight genetic differences between particular laboratory N2
strains [such differences have been observed in longevity studies (e.g.
Gems and Riddle, 1996)].
Whatever the causes of these differences, they suggest that defining
thermosensory behaviour within the standard lab strain may be noisy and that
the field could benefit from a more robust model. Certainly in our assays, the
magnitude of the response in thermal preference is much stronger in CB4856
than in N2. In any case, our results suggest that long-established laboratory
stocks such as N2 may be inappropriate subjects as experimental models of
normative behaviours. Natural isolates appear better suited for studies of
complex behaviours such as thermotaxis.
|
Acknowledgments |
|---|
|
Footnotes |
|---|
* Present address: Department of Zoology, University of Florida, Gainesville,
FL 32611, USA 
|
References |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
Ajie, B. C., Estes, S., Lynch, M. and Phillips, P. C.
(2005). Behavioral degradation under mutation accumulation in
Caenorhabditis elegans. Genetics
170,655
-660.
Angilletta, M. J., Hill, T. and Robson, M. A. (2002). Is physiological performance optimized by thermoregulatory behavior? A case study of the eastern fence lizard, Sceloporus undulatus. J. Therm. Biol. 27,199 -204.[CrossRef]
Beitinger, T. L. and Fitzpatrick, L. C. (1979). Physiological and ecological correlates of preferred temperature in fish. Am. Zool. 19,319 -329.
Bennett, A. F. and John-Alder, H. (1986). Thermal relations of some Australian skinks (Sauria, Scincidae). Copeia 1986,57 -64.[CrossRef]
Berg, H. C. (1993). Random Walks in Biology. Princeton, NJ: Princeton University Press.
Biron, D., Shibuya, M., Gabel, C., Wasserman, S. M., Clark, D. A., Brown, A., Sengupta, P. and Samuel, A. D. T. (2006). A diacylglycerol kinase modulates long-term thermotactic behavioral plasticity in C. elegans. Nat. Neurosci. 9,1499 -1505.[CrossRef][Medline]
Blouin-Demers, G. and Weatherhead, P. J. (2001). An experimental test of the link between foraging, habitat selection and thermoregulation in black rat snakes Elaphe obsoleta obsoleta. J. Anim. Ecol. 70,1006 -1013.[CrossRef]
Brenner, S. (1974). The genetics of
Caenorhabditis elegans. Genetics
77, 71-94.
Byerly, L., Cassada, R. C. and Russell, R. L. (1976). Life-cycle of nematode Caenorhabditis elegans. 1. Wild-type growth and reproduction. Dev. Biol. 51, 23-33.[CrossRef][Medline]
Cassata, G., Kagoshima, H., Andachi, Y., Kohara, Y., Durrenberger, M. B., Hall, D. H. and Burglin, T. R. (2000). The LIM homeobox gene ceh-14 confers thermosensory function to the AFD neurons in Caenorhabditis elegans. Neuron 25,587 -597.[CrossRef][Medline]
Christian, K. A. and Tracy, C. R. (1981). The effect of the thermal environment on the ability of hatchling Galapagos land iguanas to avoid predation during dispersal. Oecologia 49,218 -223.[CrossRef]
Christian, K., Tracy, C. R. and Porter, W. P. (1983). Seasonal shifts in body-temperature and use of microhabitats by Galapagos land iguanas (Conolophus pallidus). Ecology 64,463 -468.[CrossRef]
Christian, K. A., Tracy, C. R. and Tracy, C. R. (2006). Evaluating thermoregulation in reptiles: an appropriate null model. Am. Nat. 168,421 -430.[CrossRef][Medline]
Clark, D. A., Biron, D., Sengupta, P. and Samuel, A. D. T.
(2006). The AFD sensory neurons encode multiple functions
underlying thermotactic behavior in Caenorhabditis elegans. J.
Neurosci. 26,7444
-7451.
Clark, D. A., Gabel, C. V., Gabel, H. and Samuel, A. D.
(2007a). Temporal activity patterns in thermosensory neurons of
freely moving Caenorhabditis elegans encode spatial thermal
gradients. J. Neurosci.
27,6083
-6090.
Clark, D. A., Gabel, C. V., Lee, T. M. and Samuel, A. D.
(2007b). Short-term adaptation and temporal processing in the
cryophilic response of Caenorhabditis elegans. J.
Neurophysiol. 97,1903
-1910.
Colosimo, M. E., Brown, A., Mukhopadhyay, S., Gabel, C., Lanjuin, A. E., Samuel, A. D. T. and Sengupta, P. (2004). Identification of thermosensory and olfactory neuron-specific genes via expression profiling of single neuron types. Curr. Biol. 14,2245 -2251.[CrossRef][Medline]
Couillault, C. and Ewbank, J. J. (2002).
Diverse bacteria are pathogens of Caenorhabditis elegans. Infect.
Immun. 70,4705
-4707.
Cowles, R. B. and Bogert, C. M. (1944). A preliminary sudy of the thermal requirements of desert reptiles. Bull. Am. Mus. Nat. Hist. 83,261 -296.
Crawshaw, L. I. (1980). Temperature regulation in vertebrates. Annu. Rev. Physiol. 42,473 -491.[CrossRef][Medline]
de Bono, M. and Bargmann, C. I. (1998). Natural variation in a neuropeptide Y receptor homolog modifies social behavior and food response in C. elegans. Cell 94,679 -689.[CrossRef][Medline]
DeWitt, C. B. and Friedman, R. M. (1979). Significance of skewness in ectotherm thermoregulation. Am. Zool. 19,195 -209.
Dougherty, E. C., Hansen, E. L., Nicholas, W. L., Mollett, J. A. and Yarwood, E. A. (1959). Axenic cultivation of Caenorhabditis briggsae (Nematoda: Rhabditdae) with unsupplemented and supplemented chemically defined media. Ann. N. Y. Acad. Sci. 77,176 -217.[CrossRef]
Ferris, H., Lau, S. and Venette, R. (1995). Population energetics of bacterial-feeding nematodes – respiration and metabolic rates based on CO2 production. Soil Biol. Biochem. 27,319 -330.[CrossRef]
Gems, D. and Riddle, D. L. (1996). Longevity in Caenorhabditis elegans reduced by mating but not gamete production. Nature 379,723 -725.[CrossRef][Medline]
Gems, D. and Riddle, D. L. (2000). Genetic,
behavioral and environmental determinants of male longevity in
Caenorhabditis elegans. Genetics
154,1597
-1610.
Grant, B. W. and Dunham, A. E. (1988). Thermally imposed time constraints on the activity of the desert lizard Sceloporus merriami. Ecology 69,167 -176.[CrossRef]
Gray, J. M., Hill, J. J. and Bargmann, C. I.
(2005). A circuit for navigation in Caenorhabditis elegans.Proc. Natl. Acad. Sci. USA
102,3184
-3191.
Gutteling, E. W., Riksen, J. A. G., Bakker, J. and Kammenga, J. E. (2007). Mapping phenotypic plasticity and genotype-environment interactions affecting life-history traits in Caenorhabditis elegans. Heredity 98, 28-37.[CrossRef][Medline]
Heath, J. E. (1964). Reptilian
thermoregulation: evaluation of the field studies.
Science 146,784
-785.
Heath, J. E. (1965). Temperature regulation and diurnal activity in horned lizards. Univ. Calif. Publ. Zool. 64,97 -136.
Hedgecock, E. M. and Russell, R. L. (1975).
Normal and mutant thermotaxis in the nematode Caenorhabditis elegans.Proc. Natl. Acad. Sci. USA
72,4061
-4065.
Hertz, P. E., Huey, R. B. and Stevenson, R. D. (1993). Evaluating temperature regulation by field-active ectotherms – the fallacy of the inappropriate question. Am. Nat. 142,796 -818.[CrossRef]
Huey, R. B. (1983). Natural variation in body temperature and physiological performance in a lizard. In Advances in Herpetology and Evolutionary Biology: Essays in Honor of Ernest E. Williams (ed. A. G. J. Rhodin and K. Miyata), pp.484 -490. Cambridge: Museum of Comparative Zoology.
Huey, R. B. and Bennett, A. F. (1987). Phylogenetic studies of coadaptation – preferred temperatures versus optimal performance temperatures of lizards. Evolution 41,1098 -1115.[CrossRef]
Huey, R. B., Pianka, E. R. and Hoffman, J. A. (1977). Seasonal variation in thermoregulatory behavior and body temperature of diurnal Kalahari lizards. Ecology 58,1066 -1075.[CrossRef]
Huey, R. B., Schoener, T. W. and Pianka, E. R. (1979). A biogeographic extension of the compression hypothesis: species in narrow sympatry. Am. Nat. 113,295 -298.[CrossRef]
Huey, R. B., Peterson, C. R., Arnold, S. J. and Porter, W. P. (1989). Hot rocks and not-so-hot rocks – retreat-site selection by garter snakes and its thermal consequences. Ecology 70,931 -944.[CrossRef]
Huey, R. B., Hertz, P. E. and Sinervo, B. (2003). Behavioral drive versus behavioral inertia in evolution: a null model approach. Am. Nat. 161,357 -366.[CrossRef][Medline]
Inada, H., Ito, H., Satterlee, J., Sengupta, P., Matsumoto, K.
and Mori, I. (2006). Identification of guanylyl cyclases that
function in thermosensory neurons of Caenorhabditis elegans.Genetics 172,2239
-2252.
Ito, H., Inada, H. and Mori, I. (2006). Quantitative analysis of thermotaxis in the nematode Caenorhabditis elegans. J. Neurosci. Methods 154, 45-52.[CrossRef][Medline]
Kessler, K. and Lampert, W. (2004). Fitness optimization of Daphnia in a trade-off between food and temperature. Oecologia 140,381 -387.[Medline]
Kingsolver, J. G. (1987). Evolution and coadaptation of thermoregulatory behavior and wing pigmentation pattern in Pierid butterflies. Evolution 41,472 -490.[CrossRef]
Kingsolver, J. G. and Watt, W. B. (1983). Thermoregulatory strategies in Colias butterflies – thermal-stress and the limits to adaptation in temporally varying environments. Am. Nat. 121, 32-55.[CrossRef]
Kodama, E., Kuhara, A., Mohri-Shiomi, A., Kimura, K. D.,
Okumura, M., Tomioka, M., Iino, Y. and Mori, I. (2006).
Insulin-like signaling and the neural circuit for integrative behavior in
C. elegans. Genes Dev.
20,2955
-2960.
Licht, P., Dawson, W. R., Shoemaker, V. H. and Main, A. R. (1966). Observations on the thermal relations of western Australian lizards. Copeia 1966,97 -110.[CrossRef]
Luo, L. J., Clark, D. A., Biron, D., Mahadevan, L. and Samuel,
A. D. T. (2006). Sensorimotor control during isothermal
tracking in Caenorhabditis elegans. J. Exp. Biol.
209,4652
-4662.
Mohri, A., Kodama, E., Kimura, K. D., Koike, M., Mizuno, T. and
Mori, I. (2005). Genetic control of temperature preference in
the nematode Caenorhabditis elegans. Genetics
169,1437
-1450.
Mori, I. and Ohshima, Y. (1995). Neural regulation of thermotaxis in Caenorhabditis elegans.Nature 376,344 -348.[CrossRef][Medline]
Murray, J. D. (1993). Mathematical Biology. Heidelberg: Springer-Verlag.
Nicholas, W. L., Dougherty, E. C. and Hansen, E. L. (1959). Axenic cultivation of Caenorhabditis briggsae (Nematoda: Rhabditidae) with chemically undefined supplements; comparative studies with related nematodes. Ann. N. Y. Acad. Sci. 77,218 -236.[CrossRef]
Poff, K. L. and Skokut, M. (1977). Thermotaxis
by pseudo-plasmodia of Dictyostelium discoideum. Proc. Natl. Acad.
Sci. USA 74,2007
-2010.
Pough, F. H. and Gans, C. (1982). The vocabulary of reptilian thermoregulation. In Biology of the Reptilia. Vol. 12 (ed. C. Gans and F. H. Pough), pp. 17-23. London: Academic Press.
Reynolds, W. W. and Casterlin, M. E. (1979). Behavioral thermoregulation and the final preferendum paradigm. Am. Zool. 19,211 -224.
Rosenzweig, M., Brennan, K. M., Tayler, T. D., Phelps, P. O.,
Patapoutian, A. and Garrity, P. A. (2005). The
Drosophila ortholog of vertebrate TRPA1 regulates thermotaxis.
Genes Dev. 19,419
-424.
Ryu, W. S. and Samuel, A. D. T. (2002).
Thermotaxis in Caenorhabditis elegans analyzed by measuring responses
to defined thermal stimuli. J. Neurosci.
22,5727
-5733.
Salman, H., Zilman, A., Loverdo, C., Jeffroy, M. and Libchaber, A. (2006). Solitary modes of bacterial culture in a temperature gradient. Phys. Rev. Lett. 97, 118101.[CrossRef][Medline]
Samuel, A. D. T., Silva, R. A. and Murthy, V. N.
(2003). Synaptic activity of the AFD neuron in Caenorhabditis
elegans correlates with thermotactic memory. J.
Neurosci. 23,373
-376.
Satterlee, J. S., Ryu, W. S. and Sengupta, P. (2004). The CMK-1 CaMKI and the TAX-4 cyclic nucleotide-gated channel regulate thermosensory neuron gene expression and function in C. elegans. Curr. Biol. 14,62 -68.[CrossRef][Medline]
Sawin, E. R., Ranganathan, R. and Horvitz, H. R. (2000). C. elegans locomotory rate is modulated by the environment through a dopaminergic pathway and by experience through a serotonergic pathway. Neuron 26,619 -631.[CrossRef][Medline]
Spotila, J. R., Lommen, P. W., Bakken, G. S. and Gates, D. M. (1973). A mathematical model for body temperatures of large reptiles: implications for dinosaur ecology. Am. Nat. 107,391 -404.[CrossRef]
Stevenson, R. D. (1985). The relative importance of behavioral and physiological adjustments controlling body-temperature in terrestrial ectotherms. Am. Nat. 126,362 -386.[CrossRef]
Stiernagle, T. (1999). Maintenance of C. elegans. In C. elegans (ed. I. A. Hope), pp.51 -67. Oxford: Oxford University Press.
Sulston, J. and Hodgkin, J. (1988). Methods. In The Nematode Caenorhabditis elegans (ed. W. Wood), pp.587 -606. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press.
Tanizawa, Y., Kuhara, A., Inada, H., Kodama, E., Mizuno, T. and
Mori, I. (2006). Inositol monophosphatase regulates
localization of synaptic components and behavior in the mature nervous system
of C. elegans. Genes Dev.
20,3296
-3310.
Venette, R. C. and Ferris, H. (1997). Thermal constraints to population growth of bacterial-feeding nematodes. Soil Biol. Biochem. 29,63 -74.[CrossRef]
Wakabayashi, T., Kitagawa, U. and Shingai, R. (2004). Neurons regulating the duration of forward locomotion in Caenorhabditis elegans. Neurosci. Res. 50,103 -111.[CrossRef][Medline]
Waldschmidt, S. and Tracy, C. R. (1983). Interactions between a lizard and Its thermal environment – implications for sprint performance and space utilization in the lizard Uta stansburiana. Ecology 64,476 -484.[CrossRef]
Yamada, Y. and Ohshima, Y. (2003). Distribution
and movement of Caenorhabditis elegans on a thermal gradient.
J. Exp. Biol. 206,2581
-2593.
Zariwala, H. A., Miller, A. C., Faumont, S. and Lockery, S.
R. (2003). Step response analysis of thermotaxis in
Caenorhabditis elegans. J. Neurosci.
23,4369
-4377.
| ||||||
