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Title: The rapid cold hardening response of Drosophila melanogaster: Complex regulation across different levels of biological organization
Author: Johannes Overgaard

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Journal of Insect Physiology 62 (2014) 46–53

Contents lists available at ScienceDirect

Journal of Insect Physiology
journal homepage: www.elsevier.com/locate/jinsphys

The rapid cold hardening response of Drosophila melanogaster: Complex
regulation across different levels of biological organization
Johannes Overgaard a,⇑, Jesper Givskov Sørensen b, Emmanuelle Com c, Hervé Colinet d
a

Zoophysiology, Department of Biosciences, Aarhus University, C.F. Møllers Alle 3, Building 1131, DK-8000 Aarhus C, Denmark
Genetics, Ecology & Evolution, Department of Biosciences, Aarhus University, Ny Munkegade 114-116, Building 1540, DK-8000 Aarhus C, Denmark
c
Proteomics Core Facility Biogenouest, INSERM U1085 IRSET, Campus de Beaulieu, Université de Rennes 1, 263 Avenue du Général Leclerc CS 2407, 35042 Rennes Cedex, France
d
Université de Rennes 1, UMR CNRS 6553 Ecobio, 263 Avenue du Général Leclerc CS 74205, 35042 Rennes Cedex, France
b

a r t i c l e

i n f o

Article history:
Received 21 November 2013
Received in revised form 27 January 2014
Accepted 29 January 2014
Available online 6 February 2014
Keywords:
Acclimation
Cold tolerance
Glycogen Phosphorylase
Proteomics
Fruit fly

a b s t r a c t
Rapid cold hardening (RCH) is a form of thermal acclimation that allows ectotherms to fine-tune their
physiological state to match rapid changes in thermal environment. Despite progress in recent years,
there is still a considerable uncertainty regarding the physiological basis of RCH in insects. Here we investigated the physiological response of adult Drosophila melanogaster to a gradual reduction of temperature
from 25 to 0 °C followed by 1 h at 0 °C. As expected, this RCH treatment promoted cold tolerance, and so
we hypothesized that this change could be detected at the proteomic level. Using 2D-DIGE, we found that
only a few proteins significantly changed in abundance, and of these, we identified a set of four proteins
of particular interest. These were identified as two different variants of glycogen phosphorylase (GlyP) of
which three spots were up-regulated and another was down regulated. In subsequent experiments, we
quantified upstream events by measuring the GlyP mRNA amount, but we found no marked effect of
RCH. We also examined downstream events by measuring GlyP activity and the level of free sugars.
We found no effect of RCH on GlyP activity. On the other hand, screening of whole animal sugar contents
revealed a small increase in glucose levels following RCH while trehalose content was unaltered. This
study highlights a complex regulation of GlyP in relation to RCH where we found associations between
the cold tolerance, the protein abundance and the metabolite concentrations but no changes in mRNA
expression and enzyme activity. These data stress the necessity of combining the hypothesis-generating
power of an ‘Omics’ approach with subsequent targeted validations across several levels of the biological
organization. We discuss reasons why different biological linked levels do not necessarily change
stoichiometrically.
Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction
The rapid cold hardening response (RCH) in insects represents a
fast acclimatory response thought to play a role for insects’ ability
to respond to natural diurnal temperature variation (Koveos, 2001;
Kelty, 2007; Overgaard and Sørensen, 2008; Lee and Denlinger,
2010). At the organism level RCH is known to improve survival
to acute cold stress, reduce negative effects of cold exposures on
activity and reproduction and decrease the temperature of chill
coma (Lee et al., 1987; Kelty and Lee, 1999; Shreve et al., 2004;
Overgaard et al., 2007; Lee and Denlinger, 2010; Teets and Denlinger, 2013). The mechanisms underlying this response have therefore been widely studied in insects, including Drosophila
⇑ Corresponding author. Address: University of Aarhus, C.F. Møllers Allé, Building
1131, 8000 Århus C, Denmark. Tel.: +45 8942 2648; fax: +45 8942 2586.
E-mail address: biojo@biology.au.dk (J. Overgaard).
http://dx.doi.org/10.1016/j.jinsphys.2014.01.009
0022-1910/Ó 2014 Elsevier Ltd. All rights reserved.

melanogaster (Lee and Denlinger, 2010; Teets and Denlinger,
2013). As a broad generalization studies of RCH have found that
the physiological transitions underlying RCH have clear similarities
to those found during the more profound physiological modification that occur during seasonal cold acclimation in insects (Teets
and Denlinger, 2013). Thus RCH has been associated with changes
in compatible osmolytes (Chen et al., 1987; Michaud and Denlinger, 2007; Overgaard et al., 2007) but see (MacMillan et al.,
2009), alterations of membrane composition or fluidity (Overgaard
et al., 2005, 2006; Lee et al., 2006; Michaud and Denlinger, 2006),
expression of heat shock proteins (Goto et al., 1998; Kelty and Lee,
2001; Nielsen et al., 2005; Li and Denlinger, 2008), improved
ability to maintain and recover ion and metabolic homeostasis
(Overgaard et al., 2007; Armstrong et al., 2012; Teets et al., 2012;
Teets and Denlinger, 2013; Findsen et al., 2013) and prevention
of cold-induced apoptosis (Yi et al., 2007). The physiological
responses associated with RCH are, however, often small and there

J. Overgaard et al. / Journal of Insect Physiology 62 (2014) 46–53

is still a considerable uncertainty and debate regarding the generality and importance of the physiological modifications mentioned
above (Teets and Denlinger, 2013).
In addition to the more hypothesis driven studies of RCH, several studies have utilized ‘Omics’ technologies to uncover putative
genes or metabolites associated with RCH (Qin et al., 2005; Michaud and Denlinger, 2007; Overgaard et al., 2007; Teets et al.,
2012; Vesala et al., 2012). Surprisingly these studies have revealed
that only few or even sometimes no genes are affected by RCH
treatments compared for example to the responses associated with
rapid heat hardening (Sørensen et al., 2005) or with gradual cold
acclimation (Vesala et al., 2012). Overall these results suggest that
elements downstream the transcriptional machinery might be sufficient to carry out RCH. It is becoming increasingly clear that the
relationship across different levels of biological organizations cannot be assumed to be linear, i.e. that a transcriptional change leads
to a comparable translational changes leading to a comparable
change in protein activity, etc. (Feder and Walser, 2005; Suarez
and Moyes, 2012; Malmendal et al., 2013). Thus little is still known
of the relation between transcriptional, translational and organism
responses in relation to insect RCH response. For example, except
from a study of Li and Denlinger (2008) that focused on brain proteins, no study has investigated changes at the proteomic level following RCH. It is an interesting observation that some previous
studies have found transcriptional regulation (Qin et al., 2005)
while others did not (Vesala et al., 2012; Teets et al., 2012). Even
more puzzling is the observation that RCH can take place in D. melanogaster in the absence of protein synthesis since a clear RCH response was found in flies where the translational machinery was
blocked by cycloheximide (Misener et al., 2001).
Together, these incongruent observations prompted us to assess
proteomic response to RCH and to further examine whether upand downstream events are correlated across different levels of
biological organization. The aim of the present study was to decipher the underpinnings of RCH through investigation across different levels of biological organization using proteomics as an
explorative starting point. Here we used 2D-DIGE proteomics to
identify putative changes in protein profile following RCH treatments in D. melanogaster. We further examined if the changes
found at the protein level were consistent with observations across
four levels of biological organization. Thus here we describe for the
first time in one study the consequences of RCH at the level of
mRNA, protein abundance, protein activity, protein product and
whole organismal performance.
2. Materials and methods
2.1. Origin and maintenance of experimental flies
A mass bred laboratory population of D. melanogaster was used
in the experiment. The population was created by mixing flies from
>500 isofemale lines collected in October 2010 at Karensminde
fruit farm at the Danish peninsula of Jutland (flies were kindly
shared by Mads Fristrup Schou and Volker Loeschcke). After establishment of a mass bred population the flies were maintained on a
standard oatmeal-sugar-yeast-agar Drosophila medium under low
to moderately high larval density conditions at 25 °C, relative
humidity (RH) of 50% and 12 h light/12 h dark cycles. Flies used
for experiments also developed and lived under these conditions.
Adult flies from the mass bred population were transferred to
bottles with yeasted media in order to stimulate egg production
( 500 flies on 35 ml media). Flies from these bottles were placed
on spoons with media for egg laying ( 10 pairs/spoon) and 14–
20 h later eggs were collected in batches of 40 eggs that were
transferred to fresh food vials with 7 ml fly food. Vials were placed
at constant 25 °C for development and emerging flies were then

47

collected and transferred to fresh bottles at 25 °C until sexual maturation. 2–3 days after emergence flies were sexed under CO2
anesthesia and saved in fresh food vials with a density of
25 flies/vial. Flies were placed on fresh media every second day
during the subsequent 5 days before onset of experiments and
sampling.
2.2. Experimental protocol
The purpose of the present study was to investigate putative
physiological mechanisms underlying RCH. Here we used a largescale proteomic assay to reveal proteins modified during the RCH
treatment but importantly we also examined the up- and downstream relations of such proteins at other levels of biological organization (ranging from transcriptional regulation to whole
organism performance). To achieve this we compared a group of
flies exposed to a RCH treatment with an untreated control group.
Changes found at the proteomic level were subsequently related to
transcriptional activity using qPCR and in other experimental series we measured the enzymatic activity and product from a candidate protein to explore the possible downstream events of the
proteomic modifications.
2.3. Cold hardening treatment and assessment of thermal tolerance
Rapid cold hardening was induced using the protocol described
in Overgaard et al. (2005). Flies were gradually ramped down from
25 to 0 °C at a rate of 0.1 °C min 1 followed by 1 h at 0 °C. To assess
the thermal tolerance of the flies, we exposed untreated controls
and rapid cold hardened flies acutely to 1 h at 6 °C in pre-cooled
water bath. For both treatment groups we used ten vials each with
ten female flies which were transferred to empty glass vials before
being acutely cold shocked. Vials were provided with a moist stopper to ensure high humidity. After cold exposure flies were transferred to fresh food vials and survival was evaluated 20 h later
from the flies’ ability to move any body part.
2.4. Sample preparation
Samples for use in subsequent biochemical, proteomic and transcriptional analysis were taken immediately after the RCH treatment and a similar amount was sampled directly from the
constant 25 °C cabinet (to avoid confounding effects of starvation
and desiccation). 300 flies were sampled from each treatment
(14 vials of 25 flies from each treatment). These samples were
transferred directly to liquid nitrogen and placed at 80 °C until
analysis (in some cases 25 flies were adequate for several assays
and each replicate was split accordingly).
In an additional follow-up experiment we reared flies under
similar conditions and exposed them to the same acclimation
treatments (RCH and Control). These flies were also sampled
immediately after treatment, but here we also sampled flies 2
and 6 h after the RCH treatment (and a similar control for time
was taken from 25 °C group). For each time point we sampled flies
for 5 replicates for determination of gene expression, sugar contents (glucose and trehalose) and glycogen phosphorylase (GlyP)
activity (12 vials of 25 flies). These samples were also snap frozen
in liquid nitrogen and saved at 80 °C until later investigations.
2.5. 2D-DIGE proteomics
For both phenotypes (control at 25 °C and RCH), four biological
replicates, each consisting of a pool of 25 females, were used for
proteomics. The protein extraction procedure was performed as
previously described in Colinet et al. (2013). Total protein concentration was determined using the Bradford Protein Assay Kit

48

J. Overgaard et al. / Journal of Insect Physiology 62 (2014) 46–53

(Biorad, Marnes-la-Coquette, France) according to the manufacturer’s instructions. 2D-DIGE experiment was performed as previously described (Colinet et al., 2013). Briefly, 50 lg of protein
extracts from individual biological replicates of control at 25 °C
and RCH phenotypes were labeled with 400 pmol of cyanine dyes
Cy3 or Cy5 (GE Healthcare, Orsay, France), in a reciprocal manner
(i.e. dye swapping) according to a standardized protocol (Com
et al., 2011). The isoelectric focusing (IEF), strip equilibration and
electrophoresis were performed using exactly the same conditions
as previously reported (Colinet et al., 2013). After electrophoresis,
gels were scanned at a resolution of 200 lm (pixel size) using a
Typhoon™ 9400 imager (GE Healthcare). The image analysis was
performed using the DeCyder software (version 5.01) with a
P 6 0.01 (Student’s t-test) threshold for the selection of differentially modulated spots between RCH and 25 °C control. For each
protein, a mean fold change (normalized abundance of RCH over
25 °C) based on the four replicate gels was calculated using the
DeCyder software. All matched proteins were ranked in a volcano
plot according to their statistical P-value and their fold change.
Four hundred micrograms of a mix of protein extracts from all analyzed samples (i.e. internal standard) were loaded on a preparative
gel that was run and analyzed together with the analytical gels.
This preparative gel was stained with LavaPurple and the images
were matched against the spots referenced. The picking list was
exported to Screen Picker (Proteomics Consult, Kampenhout, Belgium) for spot picking. In gel digestion was performed as previously described (Colinet et al., 2013) and tryptic peptides were
then analyzed by nano-LC-MS/MS using nano-LC system Ultimate
3000™ (DIONEX – LC Packings, Amsterdam, The Netherlands)
coupled on-line to a linear ion trap HCT Ultra P™ Discovery
system mass spectrometer (BrukerDaltoniK, GmBh, Germany)
(see Colinet et al., 2013 for experimental settings). MS/MS data
files were processed using the DataAnalysissoftware (version 3.4;
BrukerDaltoniK, GmBh, Germany). The proteinScape 2.1 software
(BrukerDaltonik GmbH) was then used to submit MS/MS data to
the following database: NCBI restricted to Drosophila (June 2011,
223543 sequences) using the Mascot search engine (Mascot server
v2.2; http://www.matrixscience.com). Search parameters were set
as previously (Colinet et al., 2013) and peptide identifications were
accepted if the individual ion Mascot scores were above the identity threshold.
2.6. Gene expression (qPCR)
Gene expression was investigated in four replicates each based
on 15 flies each and run on a Stratagene MX3005P (AH Diagnostics,
Aarhus, Denmark). All procedures and reagents were as described
in (Colinet et al., 2013). The gene investigated in this study was glycogen phosphorylase (GlyP) (Accession No. FBtr0077828, primers,
forward: CCATGTTCGACATTCAGGTG, reverse: TGGGATCCTTCTTGATCCTG). The data presented here was part of a larger data set
comprising 9 genes of which another part is published in (Colinet
et al., 2013) allowing the gene expression data to be normalized
using the algorithm NORMA-gene, which calculates a normalization factor without the use of reference genes (Heckmann et al.,
2011).
2.7. Cryoprotective sugars
Dry mass after flies had been dried at 60 °C for 24 h was measured before extraction. Cryoprotective sugars were extracted from
10 individuals/sample by steel bead homogenization in 0.5 ml 70%
ethanol using a TissueLyser II (Qiagen, Copenhagen, Denmark) at
30 Hz for 2 15 s. The supernatant was transferred to a glass centrifuge vial and the extraction vial was rinsed with another 0.5 ml
ethanol to washout remaining sample. Samples were then

evaporated to dryness under nitrogen flow at room temperature
(approximately 90 min) after which they were silylated by adding
900 ll pyridine, 90 ll hexamethyldisilazane (HMDS), and 10 ll
chlorotrimethylsilane (TMCS) and incubated for 2 h in darkness
at room temperature. Samples were centrifuged and the supernatant was transferred to autosampling vials before the GC–MS analysis. Samples of 2 ll were injected in split mode (split ratio 1:5) at
260 °C and the oven was programmed to hold the temperature at
120 °C for 2 min, then increase to 280 °C in steps during a period
of 20 min. Column flow was 0.6 ml min 1 at a pressure of
210 kPa. The GC/MS inter-phase temperature was 200 °C, and the
ion source temperature was 220 °C. The mass spectrometer was
operated in the electron ionization mode. Resulting chromatograms were analysed by the GC–MS software and sugars were
identified and quantified based on standard curves of known
sugars.
2.8. Measurement of glycogen phosphorylase activity
From each time point and each treatment group (RCH and control) we used 5–6 replicates of 10 flies for measurement of glycogen phosphorylase (GlyP) activity. Flies were placed in a 2 ml
eppendorf tube with 0.5 ml of homogenization buffer consisting
of 50 mM Imidazole (pH 7.5); 100 mM NaF; 5 mM ethylene glycol
tetraacetic acid; 1 mM phenylmethylsulfonyl fluoride (protease
inhibitor); 15 mM 2-mercaptoethanol; 0.02% bovine serum albumin and 50% glycerol. The sample was homogenized at 5 °C using
a TissueLyserLT (Qiagen, Copenhagen, Denmark) at 50 Hz for
12 30 s with 30 s on ice between rounds. The homogenate was
centrifuged for 10 min at 5 °C (7000g), and the supernatant transferred to an eppendorf tube for storage at 80 °C until enzymatic
activity was measured.
GP activity was measured spectrophotometrically in a reaction
buffer similar to the protocol described by Koštál et al. (2004). The
reaction buffer contained 56 mM phosphate buffer (pH 6.8);
2.2 mg/mL glycogen; 1.5 mM MgCl2; 0.1 mM EDTA; 3.75 lg/ml
glucose-1.6-diphosphate and 0.5 mM nicotinamide adenine dinucleotide phosphate. Before measurements we added phosphoglucomutase (EC 5.4.2.2) and glucose-6-phosphate dehydrogenase
(nicotinamide adenine-dinucleotide phosphate dependent) (EC
1.1.1.49) to a final concentration of 0.2 U/ml in a total of 1040 ll
of reaction buffer. Following baseline recording of absorbance we
added 20 ll of sample and measured the subsequent change in
absorbance over a 30 min period. The activity of the activated glycogen phosphorylase a (GlyPa) was measured without addition of
50 adenosine monophosphate to the reaction buffer while the total
GP pool (GlyPtotal) was measured by adding 2-mM 50 AMP to the
reaction buffer. Enzymatic activity is reported in Units/min (moles
of substrate converted per minute) and all values are reported relative to measured activity of standards (bovine GlyP) with known
activity (U/ml).
2.9. Statistical analysis
T-tests were used to test for differences with respect to cold
survival and fecundity during cold recovery. Differences in sugar
concentrations, GlyP activity and gene expression levels were
tested with two-way ANOVAs with time (0, 2 and 6 h) and treatment (RCH vs. control) as fixed factors with accompanying post
hoc pairwise comparisons (Bonferroni t-tests). In cases where normality and equal variance could not be verified we employed standard non-parametric tests (Kruskal–Wallis). All statistical tests
were performed using Sigmaplot software. Data are presented as
mean ± standard error and differences are considered significant
at the P < 0.05 level.

J. Overgaard et al. / Journal of Insect Physiology 62 (2014) 46–53

49

3. Results
As expected, RCH promoted cold tolerance of the flies. This was
manifested by a significant increase in survival rate following acute
cold shock where survival increased from 27% to 63% in control and
RCH-treated flies, respectively (Fig. 1, t-test, P < 0.001). We hypothesized that this marked organismal response could be detected at
the proteomic level and thus we conducted a large-scale explorative study using 2D-DIGE.
The 2D-DIGE patterns revealed 1121 spots (matched in all replicates) corresponding to a D. melanogaster proteome with molecular
masses ranging from 10 to 250 kDa, and isoelectric points between
3 and 10. Twenty-three proteins exhibited a significant difference
in normalized spot abundance (P < 0.01), though most of them
exhibited minor fold change and were therefore not considered.
Among the twenty-three significant proteins, only seven exceeded
a cutoff value of 1.3-fold-change between the two experimental
groups (control and RCH). Proteins are presented in a volcano plot,
where they are ranked according to their statistical P-value (y-axis)
and their relative difference of abundance (x-axis) (Fig. 2). Among
these seven candidates of interest, three were discarded as they
appeared too faint or fused in the preparative gel. A cluster of four
spots was therefore selected for identification based on the magnitude of the response (exceeding 1.3-fold cutoff) and their statistical
significance (P < 0.01) (Fig. 2). The differential expression of these
proteins is illustrated in Fig. 3. Three (spots #1, #2 and #3) were
more abundant and one (Spot #4) less abundant after the RCH
treatment relative to the control group. The four selected spots
were all successfully identified by the mass spectrometry analysis
and were found to represent two different isoforms of the same
protein: Glycogen phosphorylase (GlyP). Identified proteins related
to spots numbers are summarized in Table 1. The reason why two
isoforms can produce 4 spots (horizontal train) is likely related to
some form of posttranslational modification of the protein, in such
a way that molecular weights remain similar but the isoelectric
points are different (i.e. charge variants).
In a subsequent set of experiments we went downstream of the
protein level to quantify the amount of GlyP transcripts and in parallel with this we also examined upstream events in the form of
GlyP activity and abundance of free sugars. We found that the
mRNA expression level of GlyP was only very slightly affected by
the RCH treatment along the temporal profile (Fig. 4). Maximal fold
change differences were around 1.3 but statistical analysis showed
no significant effects of either time or treatment.
We then tested whether the GlyP modulation would translate
into change in the protein activity. Like for the mRNA expression,
we found no differences related to time or treatment in neither
the activated form (GlyPa) nor the total pool (GlyPtotal) (Fig. 5).
Finally, since GlyP catalyzes the breakdown of oligosaccharides,
we also tested whether sugar content would be affected by RCH

100

Survival (%)

80

Control
RCH

60
40
20
0

Fig. 1. Survival (mean ± SEM) of D. melanogaster scored 20 h following a 1 h acute
exposure to 6 °C. Cold hardened flies were gradually cooled from 25 to 0 °C at a
rate of 0.1 °C/min and maintained at 0 °C for 1 h before the cold shock.

Fig. 2. Volcano plot of quantitative proteomics data showing identified proteins
ranked according to their statistical P-value (y-axis) and their relative abundance
ratio (log2 fold change) between control and RCH treated animals (x-axis). Offcentred spots are those that vary the most between groups with positive x-axis
values indicating up regulation and negative values down regulation following RCH
treatment. All matched spots are represented (symbol s) together with the 4 spots
selected and identified (red symbol) with mass spectrometry. Cutoff values are
illustrated by dotted horizontal (P < 0.01) and vertical (1.3-fold) lines. (For
interpretation of the references to colour in this figure legend, the reader is
referred to the web version of this article.)

treatment. For trehalose, we found no evidence of variation neither
according to RCH treatment nor to the time or the interaction
(Fig. 6). For glucose, we detected a slight but significant effect of
the RCH treatment (F(1,24) = 25.9, P < 0.001) but not of the time
(F(2,24) = 0.8, P = 0.48) or the interaction between them
(F(2,24) = 3.0, P = 0.07). Post hoc pairwise comparisons (Bonferroni
t-tests) revealed significant differences between RCH-treated and
controls at 0 h (t = 3.2, P = 0.004) and 2 h (t = 4.5, P < 0.001) while
no difference was detected at 6 h (t = 1.1, P = 0.3) after RCH (Fig. 6).
4. Discussion
In a recent review of RCH, Teets and Denlinger, 2013 summarized the physiological and metabolic alterations associated with
RCH and seasonal cold acclimation. They reported that seasonal
and rapid acclimation are distinct responses but that a number
of physiological responses are shared between both types of acclimation. These responses include modification of membranes, regulation of ion-homeostasis and mobilization of cryoprotectants,
although it is clear that the physiological modifications associated
with RCH are often much smaller in magnitude (Overgaard et al.,
2005, 2007; Lee and Denlinger, 2010; Teets and Denlinger, 2013).
In the present study, we examined changes in protein abundance
associated with RCH in D. melanogaster and found that despite
clear effects on organismal performance, RCH only elicited few
changes in the abundance of detectable proteins. Thus only seven
proteins exhibited a significant difference in abundance above
1.3-fold change following RCH. This weak response is consistent
with previous transcriptomic studies which have not found major
shift in gene expression during or even following RCH treatment
(see Sinclair et al., 2007 and Teets et al., 2012 for discussion). For
instance, Teets et al. (2012) did not observe any differentially expressed transcript during the RCH treatment and Vesala et al.
(2012) only found a few transcripts (3 or 0) modulated by RCH
in D. montana and D. virilis, respectively. In contrast, Qin et al.
(2005) found 37 transcripts that had a modulated expression in

50

J. Overgaard et al. / Journal of Insect Physiology 62 (2014) 46–53

Fig. 3. Decyder output of the four identified proteins. Graphs show the normalized spot volumes from four replicate gels comparing 25 °C with RCH phenotypes for spot #1–4
(A–D). Representative image of the separation of D. melanogaster proteins on a 2D-DIGE gel is also shown (E and F). On these merged image (Cy2, Cy3 and Cy5), the RCH group
was labeled either with Cy3 (green) in two replicated gels (E) or Cy5 (red) on the two other replicated gels (F), following dye swapping design. Corresponding proteins are
annotated on the preparative gel (G) with their respective spot number. (For interpretation of the references to colour in this figure legend, the reader is referred to the web
version of this article.)

Table 1
List of modulated proteins with RCH identified in D. melanogaster by nano-LC-MS/MS. The Following information is displayed: accession (NCBI accession number), protein
(protein name), scores (individual mascot ion score), peptides (No. of matched peptides), FC (fold change), P-value (the probability that the observed match is a random event).
Spot No.

Accession

Protein

#1
#2
#3
#4

gi|4689100
gi|4689100
gi|24581010
gi|24581010

Glycogen
Glycogen
Glycogen
Glycogen

phosphorylase
phosphorylase
phosphorylase CG7254-PA, isoform A
phosphorylase CG7254-PA, isoform A

1,6

Relative gene expression

1,4
1,2
1,0
0,8
0,6
0,4
0,2
0,0
h
h
h
-0
-2
-6
ol
ol
ol
r
r
r
t
t
t
n
n
n
Co
Co
Co

H
RC

h
h
h
-0
-2
-6
H
H
C
C
R
R

Fig. 4. Gene expression levels of the glycogen phosphorylase (GlyP) gene in control
(open bars) and rapid cold hardened (hatched bars) female flies measured by qPCR.
Cold hardened flies were gradually cooled from 25 to 0 °C at a rate of 0.1 °C/min and
maintained at 0 °C for 1 h before return to control conditions. Expression levels are
relative to control levels at the start of the experiment (time 0 h). Expression was
assayed immediately after the RCH treatment and after 2 h and 6 h recovery at
25 °C.

relation to RCH, however, in this latter study the flies were given a
30 min recovery at 25 °C following RCH before the transcriptome
was assessed and it is therefore possible that the transcriptome

Scores

Peptides

FC

P-value

156.3
554.8
1960.4
1953.6

3
8
26
30

1.33
1.38
1.35
1.34

0.0017
0.0006
0.0022
0.0026

included transcripts expressed only after rewarming. Thus, by contrast to the major shift in genes and proteins expression that
accompany rapid heat acclimation (Sørensen et al., 2005), and
gradual cold acclimation (Colinet and Hoffmann, 2012; Vesala
et al., 2012; Colinet et al., 2013); it seems that rapid cold acclimation activates a much subtle transcription and translation machinery (Qin et al., 2005; Sinclair et al., 2007; Teets et al., 2012; Vesala
et al., 2012). Thus, our data confirm previous observations from D.
melanogaster where only few changes in gene expression and protein abundance are found following RCH. Nevertheless, the role of
these changes is still equivocal and our results as well as previous
studies suggest that regulation of existing genes and proteins
might be sufficient for an effective RCH response. Indeed, previous
results from D. melanogaster have shown that RCH may not depend
on de novo protein synthesis as the benefits of RCH occur even
when the protein synthesis is substantially reduced with cycloheximide (Misener et al., 2001). It should, however, be mentioned that
a quite strong proteomic response (38 out of 370 proteins) has
been detected in the flesh fly in response to RCH (Li and Denlinger,
2008); which indicates that the RCH response may involve synthesis of several new products in some species or specific tissues. The
study of Li and Denlinger (2008) identified changes in brain proteins while most studies, including ours, used whole-animal screen
which could dilute and mask organ or tissue specificity that is
likely occurring. Moreover, the observation that only few transcriptomal changes are found could relate to our experimental design.

J. Overgaard et al. / Journal of Insect Physiology 62 (2014) 46–53

Enzymatic activity (Units/fly)

0,12

GPa
GPtotal

0,10
0,08
0,06
0,04
0,02
0,00

Co

ro
nt

l-

0h
Co

ro
nt

l-

2h
ro
nt
Co

l-

6h
H
RC

h
-0

H
RC

-2

h
H
RC

-6

h

Fig. 5. Activity of the glycogen phosphorylase enzyme in control (solid bars) and
rapid cold hardened (hatched bars) female flies. The native activity of the enzyme
(Grey bars) was measured in the absence of 50 AMP while activity of the entire pool
of glycogen phosphorylase (white bars) was measured with 2 mM 50 AMP in the
reaction buffer. Cold hardened flies were gradually cooled from 25 to 0 °C at a rate
of 0.1 °C/min and maintained at 0 °C for 1 h before return to control conditions.
Enzymatic activity (mean ± SEM U/fly) was assayed immediately after the RCH
treatment and after 2 h and 6 h recovery at 25 °C.

Glucose
Trehalose

-1

Concentration of sugars (µg mg dm )

4

3

2

1

0
0h
2h
6h
lllro
ro
ro
t
t
t
n
n
n
Co
Co
Co

H
RC

-0

h
H
RC

-2

h
H
RC

h
-6

Fig. 6. Content of trehalose (grey bars) and glucose (white bars) in control (open
bars) and rapid cold hardened (hatched bars) female flies measured by GC–MS. Cold
hardened flies were gradually cooled from 25 to 0 °C at a rate of 0.1 °C/min and
maintained at 0 °C for 1 h before return to control conditions. Sugar content
(mean ± SEM lg/mg dry mass) was assayed immediately after the RCH treatment
and after 2 h and 6 h recovery at 25 °C.

Because our measurements are only measuring at one time point
we cannot exclude the possibility that there are important proteomic adjustments occurring at other times, nor can we exclude that
some small scale changes can be of great functional importance.
Accordingly our conclusions are mainly addressing the generalized
and larger organismal proteomic changes occurring immediately
after the RCH treatment and the subsequent discussion should be
viewed in this light.
When examining the seven proteins that were differentially
regulated we found that four of these proteins represented different isoforms and modifications of the same enzyme (glycogen
phosphorylase, GlyP). The analysis of the peptides underlying protein identification revealed that the four proteins were representatives of two different isoforms of GlyP each of which existed in two
different charge variants (Table 1). It is likely therefore that the
four versions of GlyP are generated from the two different forms

51

of transcripts generated by the gene GlyP (Tick et al., 1999). Modifications of the different GlyP isoforms can be due to different
forms of posttranslational regulation (i.e. phosphorylation, acetylation, methylation, etc.) and in the case of GlyP, we speculated that
this could also be related to the phosphorylation that is responsible
for activation of the enzyme (Steele, 1982; Johnson, 1992). Regulation of GlyP activity has often been reported to be associated with
cold tolerance in insects due to the GlyP’s central role in the conversion of glycogen to different forms of compatible osmolytes.
Thus it is commonly found that GlyP is activated by phosphorylation in response to cold whereby it changes from the inactive
GlyPb to the active form GlyPa (Steele, 1982; Churchill and Storey,
1989; Storey et al., 1990; Storey and Storey, 1991; Koštál et al.,
2004; Rider et al., 2011). Such activation of GlyP has even been observed previously for rapid cold treatments of the flesh fly Sarcophaga crassipalpis (Chen and Denlinger, 1990) where the fraction of
activated enzyme almost doubled within 1 h at 0 °C in non-diapausing adults. As illustrated in Fig. 3 of the present study both versions of one GlyP isoform increased in abundance while the other
GlyP isoform showed a different response where one variant
increased and another decreased in abundance. This pattern indicates a complex and possibly organ specific regulation of the different GlyP isoforms although our experimental design cannot
discriminate if this is the case. When we examined the activity level of GlyP we found no significant changes associated with RCH in
either total activity or level of activation of the enzyme (Fig. 5).
These results suggest that the global changes in protein abundance
of different isoforms are not directly transferable to changes in
global activity although it is obviously possible that our findings
under in vitro conditions are not directly transferable to in vivo
conditions. The degree of GlyP activation is, for example, affected
by intracellular [Ca++] (Heilmeyer et al., 1970) which has been also
reported to increase in response to RCH in Eurosta solidaginis and
Sarcophaga bullata (Teets et al., 2013). Given these equivocal
results we cannot rule out the possibility that modification of this
enzyme is important for the RCH response in D. melanogaster,
particularly since activation of this enzyme has also been reported
in another chill sensitive insect in response to RCH (Chen and
Denlinger, 1990).
Glucose concentrations increased slightly after RCH which
would be consistent with altered in vivo GlyP activity (Fig. 6). With
respect to mobilization of cryoprotectants we previously found
that some sugars (incl. glucose) increased in response to RCH in
D. melanogaster (Overgaard et al., 2007) and similar findings have
been made for other insects exposed to RCH (Chen et al., 1987;
Michaud and Denlinger, 2007), fluctuating thermal regimes
(Lalouette et al., 2007) or longer cold acclimation (Koštál et al.,
2011; Colinet et al., 2012). In all cases mentioned above, the
changes in cryoprotectant concentration are moderate and in other
studies there has been a lack of support for this response in association with RCH (Kelty and Lee, 1999, 2001; MacMillan et al.,
2009). We found that glucose levels increased less than 20% and
there was no change in trehalose levels suggesting that it would
be entirely irrelevant in terms of any hypothetical colligative effect.
However, even small alterations in compatible osmolytes have,
been proposed to have beneficial effects for membrane function
(Gekko, 1981; Leslie et al., 1995; Yancey, 2005; Cacela and Hincha,
2006; Overgaard et al., 2007). Moreover, Yoder et al. (2006) demonstrated that cold, anoxia or dehydration all caused small increments in glycerol concentration in S. bullata larvae and that these
increases were always associated with significantly increased chill
tolerance. Nonetheless, our data here are merely correlative and it
is obviously possible that the changes observed are in other ways
related to altered metabolic flux or on a greater reliance on carbohydrate metabolism (Michaud and Denlinger, 2007; Teets and
Denlinger, 2013) although previous studies have failed to find

52

J. Overgaard et al. / Journal of Insect Physiology 62 (2014) 46–53

changes in overall metabolic rate associated with RCH (Shreve
et al., 2004; Basson et al., 2012).
The starting point for the present study was a comprehensive
proteomic investigation of the RCH response in D. melanogaster.
‘Omics’ technologies are powerful hypothesis-generating tools,
but suffer from some limitations. First, levels of truly functional
molecules such as proteins and metabolites are the result of a
range of processes, ranging from gene expression and protein
translation, in addition to a number of other regulatory steps
(Feder and Walser, 2005; Suarez and Moyes, 2012). Thus, global
profiles of different hierarchical linked levels of biological organization such as mRNA and protein levels do not necessarily change
stoichiometrically (Feder and Walser, 2005), although in some
cases the correlation is high (e.g. Crawford and Oleksiak, 2007).
Furthermore, ‘Omics’ in general provide snapshot of the molecular
physiology, which do not reflect the flux of the involved processes
(Suarez and Moyes, 2012). In the present study, we examined the
consequence of a treatment (RCH) across five levels of biological
organization (organism tolerance, metabolite concentration, enzyme activity, protein abundance and mRNA level) and found that
this approach suggested that the relationship between these levels
were far from ‘‘linear’’. Our findings suggested connections between the organism performance, the protein abundance and the
metabolite levels (see discussion above), while this link was absent
when considering the mRNA expression levels (Fig. 4) and the
enzyme activity. Thus the proteomic results suggested a complex
regulation of GlyP where some isoforms were up-regulated and another was down regulated. We could, however, not confirm this
when activity of the protein was measured on whole animal
homogenates. Although our approach leaves us with more unanswered than answered questions, we believe that the strength of
the present study lies in combining the hypothesis generating
power of an ‘Omics’ approach with subsequent targeted validations across several levels of the biological organization. The
results also underlines that caution should be exercised in the
interpretation of ‘Omics’ studies as candidates are not necessarily
modulated from genes to active molecules in the same fashion
(Malmendal et al., 2013). The following steps to elucidate the role
of GlyP in RCH would require targeted functional studies using for
example RNAi knock down and over-expression experiments targeting GlyP or tissue-specific expression studies.
Acknowledgements
This study was supported by Sapere Aude DFF-Starting Grants
(JO & JGS) from The Danish Council for Independent Research: Natural Sciences and The Centre National de la Recherche Scientifique
– CNRS (HC). We are grateful to Mads Fristrup Schou and Volker
Loeschcke for sharing the flies and access to the laboratory, to
Guével Blandine for help with proteomics, Lise Lauridsen for help
with sugar measurements and Kirsten Kromand for help with
enzymatic assays. The authors declare no conflicts of interest.
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