stress modulation of cellular metabolic sensors: …tive of cells, these stress responses are energy...

Stress modulation of cellular metabolic sensors:interaction of stress from temperature and rainfall on theintertidal limpet Cellana toreuma

YUN-WEI DONG, GUO-DONG HAN and XIONG-WEI HUANG

State Key Laboratory of Marine Environmental Science, College of Marine and Earth Sciences, Xiamen University, Xiamen

361102, China

Abstract

In the natural environment, organisms are exposed to large variations in physical con-

ditions. Quantifying such physiological responses is, however, often performed in lab-

oratory acclimation studies, in which usually only a single factor is varied. In contrast,

field acclimatization may expose organisms to concurrent changes in several environ-

mental variables. The interactions of these factors may have strong effects on organis-

mal function. In particular, rare events that occur stochastically and have relatively

short duration may have strong effects. The present experiments studied levels of

expression of several genes associated with cellular stress and metabolic regulation in

a field population of limpet Cellana toreuma that encountered a wide range of temper-

atures plus periodic rain events. Physiological responses to these variable conditions

were quantified by measuring levels of mRNA of genes encoding heat-shock proteins

(Hsps) and metabolic sensors (AMPKs and Sirtuin 1). Our results reveal high ratios of

individuals in upregulation group of stress-related gene expression at high tempera-

ture and rainy days, indicating the occurrence of stress from both prevailing high sum-

mer temperatures and occasional rainfall during periods of emersion. At high

temperature, stress due to exposure to rainfall may be more challenging than heat

stress alone. The highly variable physiological performances of limpets in their natural

habitats indicate the possible differences in capability for physiological regulation

among individuals. Our results emphasize the importance of studies of field acclimati-

zation in unravelling the effects of environmental change on organisms, notably in the

context of multiple changes in abiotic factors that are accompanying global change.

Keywords: heat-shock response, intertidal zone, metabolism, physiological adaptation, salinity

change

Received 26 February 2014; revision received 5 August 2014; accepted 6 August 2014

Introduction

Ongoing climate change has had, and will continue to

have, significant impacts on the structure and function-

ing of ecosystems (Hoegh-Guldberg & Bruno 2010;

Doney et al. 2012; Hooper et al. 2012; IPCC 2013). Over

the past century, both land and ocean surface tempera-

tures have increased, and temperature will keep increas-

ing based on projections of several climate change

models (Folland et al. 2001; Hansen et al. 2006; Burrows

et al. 2011; Lima & Wethey 2012). In addition, rainfall

intensity and pattern may change in accord with changes

in temperature (Kunkel et al. 2013). Although there was

little change in land-based precipitation during the 20th

century, precipitation indices show a tendency towards

wetter conditions in the future and an intensification of

the hydrological cycle (IPCC 2013). There has long been

much attention given to the impacts of changing precipi-

tation and temperature on biodiversity (Schuur 2003;

Hanson et al. 2005; Cowling & Shin 2006; Del Grosso

et al. 2008; Bai et al. 2010), carbon cycling (Wu et al. 2011)

and ecosystem services (Schr€oter et al. 2005). At local and

regional scales, rare events such as extreme rainfall,Correspondence: Yun-wei Dong, Fax: (86) 0592 2880165;

E-mail: [email protected]

© 2014 John Wiley & Sons Ltd

Molecular Ecology (2014) 23, 4541–4554 doi: 10.1111/mec.12882

thermal extremes and drought, which occur stochasti-

cally and have relatively short duration, usually cause

rapid environmental changes that can affect organisms’

physiological status and lead to dramatic ecological

effects (Benedetti-Cecchi 2003; Wethey et al. 2011; Wern-

berg et al. 2013). It is difficult to evaluate the ecological

significance of occasional events in the field because their

impacts on the ecosystem are out of proportion to their

short duration (Jentsch et al. 2007; Denny et al. 2009).

Population- and physiological-level effects can, however,

provide information on the potential ecological impacts

of multiple factors, including occasional events, for

understanding the potential impacts of climate change

(Wernberg et al. 2010).

Physiological analysis can lead to insights into

environmental effects at higher levels of biological

organization, such as ecological and biogeographic

relationships (Helmuth 2009; Somero 2012). When an

organism encounters environmental stresses, a series of

physiological responses occur to maintain cellular

homoeostasis (P€ortner et al. 2006; Han et al. 2013) and

these cellular responses are closely related to popula-

tion dynamics (P€ortner & Farrell 2008). For example,

P€ortner & Knust (2007) found that a mismatch

between the demand for oxygen and the capacity of

oxygen supply to tissues is the first mechanism to

restrict whole-animal tolerance to thermal extremes

and population dynamics in the eelpout, Zoarces vivipa-

rous. The capacity for oxygen delivery has been repeat-

edly shown to be an important factor for setting

thermal tolerance in marine ectotherms (P€ortner 2008,

2012). Thus, when environmental factors depart from

the optimal range of an organism, aerobic scope

declines and a series of stress responses is elicited,

including production of heat-shock proteins (HSP,

molecular chaperones that assist in refolding of stress-

damaged proteins) and enzymes involved in degrading

reactive oxygen species (ROS). The expression levels

and patterns of HSP are closely related to the thermal

tolerance of an organism (Somero 2012). While protec-

tive of cells, these stress responses are energy con-

sumptive and, under stress, more energy is allocated

for coping with cellular damage, leaving less energy

available for growth and reproduction (Sokolova et al.

2012). Recent studies using ‘-omics’ technologies (ge-

nomics, transcriptomics and proteomics) confirm that

environmental stress can affect global cellular metabo-

lism and alter energy balance (Gracey & Cossins 2003;

Hofmann & Place 2007; Tomanek & Zuzow 2010; To-

manek et al. 2012). Results from dynamic energy bud-

get models (DEB) also indicate that environmental

changes can affect energy allocation and, thereby,

ecological fitness (Freitas et al. 2010; Kearney et al.

2012; Sar�a et al. 2012).

The expression of metabolic sensors that detect cellu-

lar energy status and modulate cellular energy metabo-

lism accordingly can play important roles in stress

responses. Under conditions of low cellular energy sta-

tus, when ATP concentrations may be limiting,

increased expression of AMP-activated protein kinase

(AMPK), a metabolic sensor of the AMP/ATP ratio, can

be induced (Hardie & Sakamoto 2006). Parallel upregu-

lation may occur in histone/protein deacetylase sirtuin

1 (SIRT1), which regulates fat and glucose metabolism

in response to physiological changes in energy levels.

These proteins play crucial roles in regulating the net-

work that controls energy homoeostasis (Cant�o et al.

2009; Houtkooper et al. 2012). Activation of AMPK and

SIRT1 indicates a switching on of catabolic pathways,

including increase of lipid use, upregulation of insulin

secretion and decrease of glycolysis (Cant�o et al. 2009).

Besides the regulations at the transcriptional level, regu-

lation at the translational level and in protein phosphor-

ylation is also important for activities of AMPK and

SIRT1 (Jibb & Richards 2008; Sasaki et al. 2008; Stensløk-

ken et al. 2008; Hardie 2014). Frederich et al. (2009)

found that AMPK mRNA, AMPK protein and AMPK

activity in the crab Cancer irroratus were all closely

related to temperature. Therefore, the upregulation of

these two metabolic sensors can be regarded as an indi-

cation of increased needs for ATP. The close relation-

ship between AMPK, SIRT1 and energy expenditure

makes these two proteins potentially useful biomarkers

for gauging cellular energy homoeostasis and elucidat-

ing stress-related changes in cellular energy demands,

for example, in the face of thermal stress (Han et al.

2013).

Rocky intertidal habitats have been extensively used

for studies of abiotic stress, particularly from tempera-

ture and desiccation, because of the variable and harsh

environmental conditions. There, intertidal species

experience both aquatic and terrestrial conditions due

to their periodic immersion and emersion during tidal

cycles (Raffaelli & Hawkins 1996; Little 2000; Helmuth

et al. 2006; Little et al. 2009). Diverse abiotic stresses

from natural and anthropogenic factors have dramatic

impacts on structure and functioning of intertidal com-

munities (Parmesan & Yohe 2003; Helmuth et al. 2006;

Hawkins et al. 2009; Wittmann & P€ortner 2013). For

example, previous studies have shown that climate

change has a dramatic impact on biogeographic distri-

butions (Sagarin et al. 1999; Mieszkowska et al. 2006),

community composition (Barry et al. 1995; Southward

et al. 1995) and species interactions (Sanford 1999; Polo-

czanska et al. 2008; Harley 2011). Therefore, intertidal

communities serve as early warning systems for under-

standing the impacts of climate change (Southward

et al. 1995; Helmuth et al. 2006).


4542 Y. - W. DONG, G. - D . HAN and X. - W. HUANG

The intertidal limpet Cellana toreuma is an important

grazer in rocky intertidal habitats (Hutchinson & Wil-

liams 2003) and widely distributed in China, Korea and

Japan (Dong et al. 2012). In summer, this species experi-

ences large-scale mortality in many locations (Hong

Kong: Firth & Williams 2009; Wenzhou and Qingdao:

Y.-W. Dong, J. Wang and W. Wang, unpublished data).

Recently, the upper thermal tolerances of limpets were

investigated in different locations. The Arrhenius break

point temperatures of heart rate, the temperature at

which the heart rate decreases dramatically with pro-

gressive heating, in Qingdao (35°580N, 120°300E),Zhangzhou (24°090N, 117°590E) and Hong Kong sum-

mer populations were about 36, 39 and 41 °C, respec-tively (Y.-W. Dong, G.-D. Han and J. Wang,

unpublished data; Dong & Williams 2011). Based on in

situ measurement, the operative body temperatures of

limpets in these locations were frequently beyond their

ABTs. Although the causes of this summer mortality

have not been elucidated, it is reasonable to suggest

that the species may be living close to its thermal limits

during the warmest periods of the year. Physiological

responses, including heart rate and levels of stress pro-

teins and metabolic sensors, are sensitive to environ-

mental stresses, including high temperature (Dong &

Williams 2011; Han et al. 2013) and low salinity (Chel-

azzi et al. 2001; Firth & Williams 2009). These past stud-

ies of phylogeography, physiology and ecology of

C. toreuma indicate that physical stresses play important

roles in its population dynamics and show that molecu-

lar markers of stress, including heat-shock proteins and

metabolic sensors, provide useful indicators of physio-

logical status and have a close relationship to ecological

fitness of intertidal limpets.

The present experiments extend our earlier investiga-

tions of thermal stress on this species (Han et al. 2013) by

examining field populations that encountered a wide

range of in situ temperatures plus periodic rain events

that were predicted to have significant physiological

effects. A primary goal of our study was to determine the

interactions among multiple abiotic stressors and the

existence of interindividual variation in the field inter-

tidal populations. These results will be important to pre-

dict the responses of intertidal species to global change.

Materials and methods

Measurement of operative body temperature

The integrated, long-term operative body temperatures

of limpets within different microhabitats on the shore

were measured using Robolimpets as described by

Lima & Wethey (2009) with minor modifications. In the

present study, Robolimpets were assembled using shells

of C. toreuma. Before deployment, all Robolimpets were

calibrated using a thermometer (Fluke 54II, Fluke, WA,

USA). The operative body temperatures of limpets were

estimated at a field site on Nanding Island, Fujian,

China (24°090N, 117°590E). A total of 16 Robolimpets

were deployed on a semiwave-exposed shore between

~1.0 and 4.0 m above chart datum (CD; the level from

which depths displayed on a nautical chart are mea-

sured) on both south-facing (sun-exposed) and west-fac-

ing (shaded) rocky surfaces. Operative temperature

recordings were made every 30 min from August 2011

to May 2013.

Analysis of precipitation data

Based on the records from Weather Underground

(www.underground.com), the precipitation data were

analysed in the context of timing of the tidal cycle.

Because rainfall that occurred when limpets were

immersed in seawater had no direct physiological

impacts, only rainfalls that occurred when limpets

emersed in air were regarded as ‘relevant precipitation’

(Fig. S1, Supporting information).

Measurement of population abundance

To determine population dynamics, the abundance of

C. toreuma was recorded every 2 weeks from July 2012

to April 2013 in two transects on the shore in Xiamen,

Fujian, China (24°250N, 118°090E). The total number of

limpets in the two transects was recorded from 2.0 to

3.5 m above chart datum. Each transect was 5 m wide

and was placed vertically from 1.0 to 5.0 m above CD.

Animal collection and measurement of bodytemperature

From September 2011 to April 2013, a total of 445 indi-

viduals of C. toreuma (body length, 21.79 � 3.55 mm;

width, 16.3 � 2.86 mm; height, 4.471 � 1.07 mm) in 23

batches were collected after emersion on a south-facing

shore between ~2.5 m and 3.0 m above CD during

spring tides to avoid possible effects of orientation and

tidal height on physiological responses in Xiamen. Dur-

ing sampling, a thermocouple was inserted into the

shells and the body temperature of each individual

was recorded using a thermometer (Fluke 54II). This

body temperature was used to identify the temperature

at which the physiological responses were elicited cf.

the long-term temperatures to which they had been

exposed. After collection, animals were dissected

immediately and foot muscles were stored in liquid

nitrogen for subsequent use in gene expression quanti-

fication.


IN SITU STRESS RESPONSES OF A LIMPET 4543

Quantifying genes expression

The levels of mRNA of genes encoding two heat-

shock proteins, heat-shock protein 70 (hsp70) and heat-

shock protein 90 (hsp90), and metabolic sensors AMP

kinase-a (ampka), AMP kinase-b (ampkb) and sirtuin-1

(sirt1) were measured using real-time quantitative

PCR followed the methods described in our previous

study (Han et al. 2013). The sequences of primers used

in this study are given in the supplementary material

(Table S1, Supporting information). For normalizing

expression of stress-induced genes, we examined

expression of 18S ribosomal RNA, b-actin, b-tubulin and

calmodulin genes, which typically have relatively stable

expression levels. The expression stability of these

housekeeping genes was evaluated using the GeNorm

Algorithm (Primer Design, Ltd., Southampton Univer-

sity, Highfield Campus, Southampton Hants, UK) as

described by Etschmann et al. (2006). Based on the

expression stability measures (M values), b-actin was

selected as the reference gene for normalizing the

level of expression of stress-induced genes. PCR was

carried out in an ABI 7500 Fast Real-Time PCR Sys-

tem (Applied Biosystems, Bedford, MA, USA), and all

samples were measured in triplicates. Ct (dR) values

were analysed using the ABI 7500 System Software

(Applied Biosystems). The expression of hsp70, hsp90,

ampka, ampkb and sirt1 mRNA was determined rela-

tive to the value of b-actin from a reference individ-

ual, which was collected on 26 September 2011 and

had a body temperature of 27.7 °C at time of collec-

tion. The reason we selected this individual to serve

as the reference was that ~28 °C is the threshold tem-

perature for upregulation of heat-shock response of

C. toreuma (Dong & Williams 2011; Han et al. 2013).

Thus, the reference individual would not be expected

to have significant stress-induced changes in gene

expression.

Statistics and data analysis

The operative body temperatures recorded by Robolim-

pets were analysed, and daily maximum, mean and

minimum operative body temperatures were calculated

from the three Robolimpets that were deployed in the

middle intertidal zone (2.0–3.5 m above CD). The dif-

ferences in expression of genes were analysed as fol-

lows. The correlations between hsp70, hsp90, ampka,ampkb and sirt1 expression levels and body temperature

were analysed using Spearman correlation analysis

using the SPSS 17.0 for Windows statistical package (Chi-

cago, IL, USA). The relationships between temperature

and gene expression were fitted using locally weighted

scatterplot smoothing (Loess) (span = 0.5) with ggplot2

for R (Wickham 2009). The hierarchical clustering algo-

rithm was generated using a Euclidean distance simi-

larity metric after log-transformation and centroid

linkage method (Han et al. 2013). The cluster analysis

was conducted with CLUSTER 3.0 (University of Tokyo,

Human Genome Center). Based on the cluster analysis

result, individuals can be allocated into two groups

(Group I and Group II). Compared with gene levels of

the reference, gene expressions were generally upregu-

lated and downregulated in the Group I and Group II,

respectively. The ratios of individuals in different

groups were calculated on the different dates. The dif-

ference of body temperatures between groups was anal-

ysed using a Kolmogorov–Smirnov test for two

samples, and the correlation between ratios of individu-

als in Group I and Group II (RI/II) and temperature

were analysed using Pearson correlation analysis with

SPSS 17.0.

Results

Body temperatures and precipitation

The thermal conditions encountered by limpets were

determined to allow correlations to be examined

between temperature exposure, physiological state and

population abundance. The long-term operative body

temperature data provide an extensive perspective on

environmental temperature conditions experienced by

the limpets (Fig. 1A) compared with the smaller data

set obtained from the specimens that were sampled for

physiological studies (Fig. 1B). The operative body tem-

peratures showed obvious seasonal variations. Highest

temperatures occurred in summer; from July to Octo-

ber, the mean temperatures were above 27.0 °C in the

middle intertidal zone (2.0–3.5 m above CD), and the

maximum temperatures were highly variable and fre-

quently exceeded 45 °C. The lowest temperature

occurred in January and February, and the minimum

temperature was about 10 °C.Body temperatures of specimens sampled for physio-

logical studies were seasonally variable during the

whole experimental period (Fig. 1B). The highest and

lowest average body temperatures occurred in July 2012

(33.00 °C) and January 2013 (13.11 °C), respectively.

Body temperatures among different individuals on the

same day were relatively stable with small coefficients

of variations (CV) (from 1.1% to 15.6%, Table 1).

Based on the records from Weather Underground

(www.underground.com), 3-day accumulated ‘relevant

precipitations’ were 51, 3.9 and 13 mm on 18 June 2012,

30 August 2012 and 10 November 2012, respectively

(Fig. 1C).



Seasonal population dynamics

Abundances of C. toreuma also showed significant sea-

sonal variation between July 2012 and April 2013

(Fig. 2). Population numbers were low during summer

when operative body temperatures were highest (Fig. 1)

and remained at low values until January 2013 when a

large increase in the population commenced. The maxi-

mal abundance during the study period was reached in

April 2013.

Gene expression

Expression levels of the five stress biomarkers (hsp70,

hsp90, ampka, ampkb and sirt1) were highly variable

among specimens collected within and among time

points (Fig. 3). Most CVs of the biomarkers determined

on the same day were higher than 100% (Table 1), and

the magnitudes of CV typically were greatest on days

of highest body temperature. For hsp70, the range of

CVs is from 115.31% to 361.41%, and the ranges of CVs

for hsp90, ampka, ampkb and sirt1 are 88.16–420.20%,

91.44–384.31%, 104.70–412.13% and 88.94–368.66%,

respectively. For all the five biomarkers, the highest

CVs occurred in July and August 2012.

Spearman correlation analysis revealed that the cor-

relations between transcription of the five molecular

markers were statistically significant (P < 0.001,

Table 2), which further confirmed the close relation-

ship in function among these markers. Thermal effects

on transcriptional activity differed somewhat among

the markers (Table 2). The correlation between genes

encoding heat-shock proteins (hsp70 and hsp90) and

body temperature was statistically significant (P <0.001, Fig. 4). The correlations between metabolic sen-

sors (ampka, ampkb and sirt1) and body temperature

are different, and only levels of ampkb showed

significant negative correlation to body temperature

(Fig. 5).

Cluster analysis

The gene expression responses are summarized in the

dendrogram showing the clustering of individuals dur-

ing the experimental period based on the gene expres-

sion pattern. Individuals are clustered using a

hierarchical clustering algorithm, which identified two

major clusters, one upregulation Group (Group I) and

one downregulation Group (Group II), compared to the

control individual (Fig. 6).

The body temperature of individuals allocated into

Group I (n = 133) was higher than those in Group II

(n = 312) (Kolmogorov–Smirnov test for two samples,

P < 0.001) (Fig. 7). The mean body temperatures were

25.98 � 5.74 °C and 22.44 � 6.19 °C in Group I and

Group II, respectively.

The ratios of individuals in Group I and Group II

(RI/II) were analysed for all dates (Fig. 8). RI/IIs were

MaxMeanMin

Tem

pera

ture

(°C

)

60

50

40

30

20

100

08 09 10 11 12 01 0102 0203 0304 0405 0506 07 08 09 10 11 12

2011 2012 2013

Exposed rocky shoreTe

mpe

ratu

re (°

C)

0

10

20

30

40

09-2

6

03-1

002

-22

01-2

4

01-1

0

12-2

412

-10

11-1

010

-26

10-1

209

-15

08-3

0

08-1

407

-30

07-1

507

-01

06-1

8

05-1

805

-06

04-2

4

10-2

6

10-1

0

2011 2012 2013

04-0

803

-25

Prec

ipita

tion

(mm

)

0

5

10

15

20

30

40

22 23 24April2012

16 17 18July

2012

28 29 30August2012

8 9 10November

2012

23 24 25March2013

(A)

(B)

(C)

Fig. 1 (A) Daily maximum, mean and minimum operative

body temperatures in limpets from a mid-intertidal south-fac-

ing rocky slope (2.5–3.0 m above CD) measured using Robo-

limpets, as described by Lima & Wethey (2009). Data were

collected every 30 min between August 2011 and May 2013.

(B) Body temperatures measured using thermocouples on the

dates of collecting specimens. During sampling, a thermocou-

ple was inserted into the shells and the body temperature of

each individual was recorded using a thermometer (Fluke

54II). (C) The ‘relevant precipitation’ data recorded during the

experiment. Arrows represent the date for limpet collection.



highly variable (from 0.04 to 2.20). On 18 June 2012, 30

August 2012 and 10 November 2012, the RI/IIs were

higher than 1.0, indicating half or more of individuals

were allocated into the upregulation Group (Group I).

The RI/IIs for the rainy days were significantly higher

than those in the sunny days when rain did not occur

(unpaired t-test, P = 0.005) (Fig. 9). On sunny days, there

was a positive relationship between RI/IIs and body

temperature (Pearson correlation, r = 0.72, P = 0.002,

Fig. 10). On rainy days, there was no statistical significant

relationship between RI/IIs and body temperature

(Pearson correlation, r = 0.67, P = 0.11).

Discussion

Interactions of thermal stress and rainfall in the filedacclimatization processes

Our study is to examine whether laboratory acclimation

studies involving a single abiotic factor like temperature

can provide unambiguous insights into field acclimati-

zation processes in which several potentially interacting

abiotic and biotic variables may influence an organism’s

physiological status in situ. Our previous study of

C. toreuma found that transcription of genes encoding

heat-shock proteins (hsp70, hsp90) and metabolic sensors

(ampka, ampkb and sirt1) was responsive to laboratory

thermal stress and that interindividual variations in

Table 1 The coefficients of variation of gene expression and body temperature in the same population of the limpet Cellana toreuma

collected from 2011 to 2013

Date hsp70 hsp90 ampka ampkb sirt1 Body temperature

2011

09–26 155.53 126.72 100.08 84.59 106.25 5.77

10–10 236.60 227.61 173.97 146.72 152.07 4.91

10–26 274.55 220.50 197.07 261.09 221.81 1.14

2012

04–24 223.55 158.34 173.83 214.90 161.86 1.67

05–06 177.38 176.75 163.35 218.68 173.64 7.55

05–18 234.20 146.11 140.23 123.11 139.26 1.79

06–18 250.08 184.30 161.83 121.21 134.61 2.58

07–01 224.41 175.99 135.99 130.96 139.80 4.68

07–15 214.97 147.61 384.31 147.65 253.12 2.88

07–30 361.41 420.20 315.66 412.13 347.42 1.52

08–14 275.71 301.69 228.25 192.18 368.66 2.91

08–30 337.79 307.34 267.60 315.56 234.56 3.65

09–15 177.56 162.01 149.48 219.56 146.87 2.90

10–12 156.24 162.00 98.89 148.25 109.22 6.59

10–26 117.32 119.01 107.00 114.00 103.94 4.21

11–10 115.31 132.15 109.77 167.80 124.78 2.13

12–10 135.72 129.09 122.11 154.89 117.45 7.14

12–24 166.92 162.96 110.99 151.73 103.47 15.61

2013

01–10 300.94 214.96 135.59 132.09 141.96 3.45

01–24 231.80 147.28 120.76 187.50 145.57 7.44

02–22 265.10 255.87 283.79 306.32 273.82 5.04

03–10 177.03 135.90 88.40 104.70 88.94 6.50

03–25 174.39 138.19 174.63 169.43 165.20 3.68

04–08 158.43 88.16 91.43 119.80 90.97 1.89

0

10

20

30

40

50

Abu

ndan

ce (i

nd.)

07-15

07-30

08-14 04

-0803

-2503

-1002-22

01-2401

-1012

-2412

-1011-10

10-2610

-1209

-2709

-1508

-30

2012 2013

Fig. 2 The abundance of the limpet Cellana toreuma in the

study site from July 2012 to April 2013. The total numbers of

limpets in the two transects were recorded from 1.0 to 5.0 m

above chart datum.



expression levels of the five genes were relatively small.

Most coefficients of variations for the five genes in dif-

ferent temperature treatments (from 22 to 42 °C) were

below 100% (Table S2, Supporting information, Han

et al. 2013). In contrast, however, expression levels of

the same genes in the field specimens examined in the

present study were highly variable on the same shore

at the same collection day or at the same temperature.

Although the present study cannot fully account for the

wide range of physiological responses observed in the

in situ exposed individuals, the high variation in the

data indicates that multiple factors, not only body tem-

perature, probably contributed to the physiological sta-

tus of the specimens. Based on previous studies, among

the factors that can influence the physiological status of

intertidal animals are quantity of food (Dowd et al.

2013) and variations in salinity (Little & Stirling 1984;

Evans & Somero 2010; Lockwood & Somero 2011) as

well as thermal history (peak temperatures reached and

duration of thermal stress) (Hochachka & Somero 2002;

Sanford & Kelly 2011), which can be influenced by solar

exposure conditions. Thus, although temperature has

been shown in laboratory studies to have a prominent

effect on expression of stress-related genes, multiple

environmental factors should be examined to establish

an integrated, multistressor perspective on physiological

status in situ.

The most novel discovery in the present study con-

cerns the issue of how acclimation and acclimatization

might differ in their effects on physiology. That is, we

discovered that rain is a crucial factor affecting the

physiological performances of limpets on the shore, a

result that would not have been possible in laboratory

studies of temperature alone. Based on the cluster

analysis result, more individuals were allocated into

the upregulation Group (Group I) on rainy days, espe-

cially in summer (Fig. 9). This result indicates that

rainfall can induce upregulation of genes encoding

molecular chaperones and proteins of energy regula-

tion. Due to the importance of the heat-shock response

and energy regulation for thermal adaptation, rain can

be regarded as an important factor that may interact

with temperature’s effects to modify physiological sta-

tus. This interaction is important in the field, even

though rain is episodic and usually only lasts for

hours to a few days.

The interactive effects of thermal stress and rainfall

are shown especially clearly by the RI/II values; on

rainy days, when temperature was over 25 °C, these

0.0001

0.001

0.01

0.1

1

10

100

1000 hsp70

0.0001

0.001

0.01

0.1

1

10

100

1000 hsp90

0.0001

0.001

0.01

0.1

1

10

100

1000 ampkα

0.0001

0.001

0.01

0.1

1

10

100

1000 ampkβ

0.0001

0.001

0.01

0.1

1

10

100

1000 sirt1

09/2

610

/10

10/2

604

/24

05/0

605

/18

06/1

807

/01

07/1

507

/30

08/1

408

/30

09/1

510

/12

10/2

611

/10

12/1

012

/24

01/1

001

/24

02/2

203

/25

04/0

8

03/1

0

2011 2012 2013

Gen

e ex

pres

sion

(RU

)(A)

(B)

(C)

(D)

(E)

Gen

e ex

pres

sion

(RU

)G

ene

expr

essi

on (R

U)

Gen

e ex

pres

sion

(RU

)G

ene

expr

essi

on (R

U)

Fig. 3 Levels of (A) hsp70, (B) hsp90, (C) ampka, (D) ampkb and

(E) sirt1 mRNA in Cellana toreuma collected on different dates

from September 2011 to April 2013.



values were higher (>1.0) than those of limpets on

rainy days at low temperatures. For example, the max-

imal RI/II value occurred on 18 June 2012. Before speci-

men collection, there was continuously heavy rain

from the 16th–18th. The ‘relevant precipitations’ on

June 16th and June 17th were 38 and 10 mm, respec-

tively, and on June 18th, body temperatures were

beyond 30 °C. This result can be supported by a previ-

ous study about the combined effects of temperature

and rain on the physiological response in a congeneric

species, C. grata (Williams et al. 2011). In that study,

the authors found significant interactive effects of high

temperature and rain on protein expression. Therefore,

the physiological responses of invertebrates on the

rocky shore can be affected by both continuous stress

from high temperature and occasional stress from rain-

fall in summer. Laboratory studies that attempt to sim-

ulate conditions of in situ stress thus must take both

temperature and rainfall into account. The cumulative

effect of the past experience of rainfall exposure also

possibly affects the physiological responses. A recent

laboratory experiment by us showed that levels of

hsp70 and hsp90 expression after a third freshwater

exposure were significantly higher than those at the

first two freshwater sprays (S. Zhang and Y.-W. Dong,

unpublished data).

Effect of temperature on gene expression in field-acclimatized specimens

The role of temperature in governing gene expression

in field-acclimatized specimens is demonstrated by the

following results: (i) with increase of body temperature,

expression levels of the hsp70 and hsp90 generally kept

Table 2 Spearman correlation analyses: correlations between the five molecular markers (hsp70, hsp90, ampka, ampkb and sirt1) and

body temperature

ampka ampkb hsp70 hsp90 sirt1 Temperature

ampka

Coefficient 0.773 0.606 0.824 0.952 �0.048

Sig. (one-tailed) <0.001 <0.001 <0.001 <0.001 0.160

ampkb

Coefficient 0.474 0.695 0.774 �0.105

Sig. (one-tailed) <0.001 <0.001 <0.001 0.014

hsp70

Coefficient 0.818 0.676 0.539

Sig. (one-tailed) <0.001 <0.001 <0.001hsp90

Coefficient 0.855 0.269

Sig. (one-tailed) <0.001 <0.001sirt1

Coefficient 0.050

Sig. (one-tailed) 0.148

0

2

–2

10 15 20 25 30 35 40

2

1

0

–1

–2

10 15 20 25 30 35 40

(A) hsp70

(B) hsp90

Log 1

0 ge

ne e

xpre

ssio

n (R

U)

Lo

g 10

gene

exp

ress

ion

(RU

)

Temperature (ºC)

Fig. 4 Levels of (A) hsp70 and (B) hsp90 mRNA of Cellana

toreuma at different temperature. Lines are Loess curves

(Spazn = 0.5).



increasing; (ii) there were significant correlations

between temperature and expression levels of three

genes (hsp70 and hsp90) across the range of exposure

temperatures (Table 2); (iii) the patterns of body tem-

perature at time of measurement in Group I (upregula-

tion group) and Group II (downregulation group) were

different, and the mean body temperature in Group I

was higher than that of Group II; and (iv) there was a

positive relationship between RI/IIs and temperature on

sunny days. These results further confirm that tempera-

ture has significant effects on gene expression and

physiological performance of this species.

Among the five biomarkers measured in the present

study, hsp70 and hsp90 are genes encoding molecular

chaperones that are important for refolding of dena-

tured proteins at the expense of energy consumption

(Feder & Hofmann 1999) and proteins encoded by sirt1

and ampk are important for regulation of energy

metabolism (Cant�o et al. 2009; Ruderman et al. 2010;

Revollo & Li 2013). We note that sirt1 and ampk can

also be regulated by post-translational modification, so

alterations in the mRNAs for these proteins are only a

first level of regulatory response to stress. Levels of

hsp70 and hsp90 kept increasing with temperature

increase; however, there was no clear trend in the lev-

els of ampk and sirt1 expression with temperature

2

1

0

–1

–2

10 15 20 25 30 35 40

0

2

–2

10 15 20 25 30 35 40

0

2

–2

10 15 20 25 30 35 40

(A) ampkα

(B) ampkβ

(C) sirt1

Temperature (ºC)

Log 1

0 ge

ne e

xpre

ssio

n (R

U)

Lo

g 10

gene

exp

ress

ion

(RU

)

Log 1

0 ge

ne e

xpre

ssio

n (R

U)

Fig. 5 (A) ampka, (B) ampkb and (C) sirt1 mRNA of Cellana

toreuma at different temperature. Lines are Loess curves

(Span = 0.5).

Group I

Group II

ampkβ ampkα sirt1 hsp70 hsp90

–3.00 0.00 3.00

Fig. 6 Heat map of the normalized expression (log-transformed

data) of individuals collected from September 2011 to April

2013. Individuals are clustered using a hierarchical clustering

algorithm, which identified two major clusters, Group I and

Group II. The colour scale bar indicates log-transformed data,

with green indicating downregulation, red upregulation and

black no change compared with the control sample which were

collected at 27.7 °C 26 September 2011.



increase. This result indicates that at least at the tran-

scriptional level, high temperature can induce the

upregulation of heat-shock proteins, but that metabolic

sensors may not show a parallel response. These dif-

ferences in temperature dependence of transcription

between heat-shock proteins and metabolic regulatory

proteins are consistent with the frequent observation

that, at the highest temperatures at which protein syn-

thesis occurs in a species, preferential translation of

mRNAs for heat-shock proteins occurs (Tomanek &

Somero 1999). Under extreme heat stress, heat-shock

proteins may be the only proteins synthesized; thus,

curtailment of transcription of genes whose mRNAs

would not be translated under extreme conditions is

likely to occur, as seen in our study. Because selective

translation of mRNAs of heat-shock genes and curtail-

ment of synthesis of other classes of proteins generally

commences a few degrees below acute upper lethal

temperatures, the temperature-dependent gene expres-

sion patterns we observed suggest that spikes in body

temperature above ~40 °C may be lethal for this spe-

cies. The low abundances of C. toreuma during the hot-

test time of year could thus be the result of heat-

driven mortality (or heat- and rain-driven), although

seasonal variation in food supply and predation might

also contribute to changes in population size over the

course of the year. The increase in abundances of the

limpet in January 2013 should be due to the popula-

tion recruitment.

12 14 16 18 20 22 24 26 28 30 32 34 36 380

5

10

15

20

25

Temperature (°C)

Perc

enta

ge (%

)

12 14 16 18 20 22 24 26 28 30 32 34 36 380

5

10

15

20

25

Group I

Group II

Perc

enta

ge (%

)

Temperature (°C)

(A)

(B)

Fig. 7 The body temperature frequencies of individuals allo-

cated into Group I (n = 133) and Group II (n = 312). The mean

body temperature in Group I was significantly higher than that

of Group II (Kolmogorov–Smirnov test, P < 0.001).

0.0

0.5

1.0

1.5

2.0

2.5

0

10

20

30

40Ratio Temperature

09/2

610

/10

10/2

604

/24

05/0

605

/18

06/1

807

/01

07/1

507

/30

08/1

408

/30

09/1

510

/12

10/2

611

/10

12/1

012

/24

01/1

001

/24

02/2

2

03/2

504

/08

2011 2012 2013

03/1

0

Rat

io o

f upr

ugul

atio

nan

d do

wnr

ugul

atio

n Temperature (°C

)

Fig. 8 The ratios of individuals in Group I and Group II (RI/II)

on all dates. The mean body temperatures are also shown.

Arrows represent the occurrence of rain events.

Sunny

Rain0.0

0.5

1.0

1.5

2.0

2.5

Rat

io o

f upr

egul

atio

nan

d do

wnr

ugul

atio

n

Fig. 9 The ratios of individuals in Group I and Group II (RI/II)

on rainy days and sunny days. RI/II on rainy days was signifi-

cantly higher than on sunny days (unpaired t-test, P = 0.005)

0 10 20 30 400.0

0.5

1.0

1.5

2.0

2.5 SunnyRain

Temperature (°C)

Rat

e of

upr

egul

atio

nan

d do

wnr

egul

atio

n

Fig. 10 The relationship between ratios of individuals in Group

I and Group II (RI/II) and body temperature. On sunny day,

there was a positive relationship between RI/II and body tem-

perature (Pearson correlation, r = 0.72, P = 0.002). However,

the correlation between RI/IIs and body temperature was not

statistically significant in rainy days (Pearson correlation,

r = 0.67, P = 0.11).



Physiological responses to rainfalls

Salinity change related to rainfall could be an important

cause of physiological disturbance. As previous studies

have described, salinity change can dramatically affect

mantle water content (Williams & Morritt 1995), hae-

molymph osmolality (Williams et al. 2011), metabolism

(De Pirro et al. 1999) and physiological responses in

both transcriptional and post-transcriptional levels

(Evans & Somero 2010; Dong & Williams 2011; Lock-

wood & Somero 2011; Williams et al. 2011) of intertidal

limpets and bivalves. Rain can also cause large-scale

mortality of the sea cucumber Apostichopus japonicus in

the intertidal–subtidal zone (Meng et al. 2009). Death in

this species is partly due to the rapid decrease of osmo-

tic pressure in the coelomic fluid during hypo-osmotic

stress. Although upregulation of mRNA for the molecu-

lar chaperone Hsp70 is a useful way for maintaining

protein stability, this adaptive response can only pro-

vide short-term protection for A. japonicus against salin-

ity decrease (Meng et al. 2009).

Population dynamic face with multiple abiotic stresses

The high-resolution measurement of in situ operative

body temperature and the relatively long-term on-site

physiological responses of limpets provide good oppor-

tunities for studying the relationship between environ-

mental temperature and temperatures at which

physiological disturbances occur. In mid- and low-inter-

tidal zones where C. toreuma is naturally distributed,

the maximum operative body temperatures during

emersion, which frequently exceeded 30 °C, were close

to or higher than the temperature at which limpets

express heat-shock responses and shifts in expression of

genes that might regulate their energy budget. Due to

the high variation of physiological data in the present

study, however, it is difficult to identify how close the

limpets live to their upper thermal limit in their natural

habitats and to accurately evaluate the impact of high

temperature on population dynamics. However, upreg-

ulation of genes encoding heat-shock proteins and met-

abolic sensors occurred in more individuals in summer,

especially on rainy days, indicating more energy should

be used for coping with thermal stress in these individ-

uals. In summer, animals on the shore have to experi-

ence continuously high temperature episodes for

months and frequently suffer from monsoonal rainfalls.

Hence, it is reasonable to speculate that large amounts

of energy are necessary for surviving through summer

for most individuals. A recent study of the activities of

enzymes in populations of the intertidal mussel Mytilus

californianus collected over a 5-day period from four mi-

crosites where temperature and emersion times differed

found that food availability was more important than

temperature for determining physiological status (Dowd

et al. 2013). Physical stresses could affect the producer–

consumer balance in intertidal biofilms, and the low

abundance of biofilms in summer played an important

role in bottom-up controlling intertidal community (Hill

& Hawkins 1991; Thompson et al. 2004). Thus, a short-

age of energy in summer could be an important cause

for large-scale mortality of invertebrates, including lim-

pets, on the shore, if insufficient energy can be pro-

vided for repair processes subsequent to physiologically

damaging stress from temperature and rainfall.

In conclusion, the highly variable physiological states

of limpets at a given sampling time, as measured by

expression of genes related to stress and metabolic

organization, suggest that a suite of factors may govern

the degree of environmental stress individuals experi-

ence under field conditions. Variations in environmental

temperature, while leading to significant changes in

gene expression in a population, may lead to different

effects among individuals due to such factors as their

dietary state and microhabitat conditions [e.g. tidal

height and exposure to solar radiation (Dowd et al.

2013)]. Imposition of osmotic stress, especially during

hot periods, may significantly increase abiotic stress

and the energy costs entailed in addressing stress-

induced cellular damage. Whereas a single environmen-

tal variable like temperature may on its own lead to sig-

nificant effects in laboratory studies, the co-occurrence

of changes in other environmental variables like rainfall

under natural field conditions, when paired with differ-

ent physiological states of individuals, is certain to lead

to wide interindividual variation in stress responses.

Thus, acclimation studies are not likely to reveal the

magnitude of stress nor the degree of variation among

individuals of populations in stress effects under natu-

ral conditions. Therefore, field studies that recognize

the interactions among multiple abiotic stressors and

the existence of interindividual variation due to either

acclimatization or genetic differences should be an

increasingly important component of studies performed

to predict the responses of species to global change.

Acknowledgements

This work was supported by grants from National Natural Sci-

ence Foundation of China (41076083, 41276126), Nature Science

funds for Distinguished Young Scholars of Fujian Province,

China (2011J06017), the Fundamental Research Funds for the

Central Universities and Program for New Century Excellent

Talents of Ministry of Education, China. We sincerely thank

Prof. George Somero, Prof. Colin Little and Dr. Bayden Russell

and anonymous referees for their constructive suggestions. We

also thank Dr. Bingzhang Chen for his helps in Loess analysis.

The authors declare no conflict of interest.



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Y.-W.D. designed the research, G.-D.H., X.-W.H. and

Y.-W.D. performed the research, Y.-W.D. wrote the

paper with contributions from all authors. All authors

read and approved the manuscript.

Data accessibility

The operative body temperature data recorded by Rob-

olimpets, body temperature recorded by thermal cou-

ples, precipitation data and gene expression data are

available in the DRYAD data depository (doi: 10.5061/

dryad.14 m55).

Supporting information

Additional supporting information may be found in the online ver-

sion of this article.

Fig. S1 a scheme shown the relationship between rainfall and

tidal cycle. Red arrow ‘d’ represents the time for specimen col-

lection. Black arrows showed the events of rainfall. Rainfall ‘a’

and ‘c’ occur during low tide and rainfall ‘b’ occurs at high

tide. Because rainfall ‘b’ has no direct impact on physiological

response of limpet, it does not be regarded as freshwater

stress. Therefore, rainfall ‘a’ and ‘c’ are regarded as ‘relevant

precipitations’. The shaded area represents the tidal range for

limpet collection.

Table S1 Primers used for real-time PCR amplification.

Table S2 The coefficients of variations (CV) of gene expression

in different temperatures in a laboratorial experiment. Data

were from Han et al. (2013).



stress modulation of cellular metabolic sensors: …tive of cells, these stress responses are energy...

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