Abstract
Organisms inhabiting tidal mixing-front zones in shallow temperate seas
are subjected to large semidiurnal temperature fluctuations in summer.
The ability to optimize energy acquisition to this episodic thermal
oscillation may determine the survival, growth and development of these
ectotherms. We compared the physiological and molecular responses of
Haliotis discus hannai cultivated in suspended cages to fluctuating or
stable temperature conditions. Several physiological indicators
(respiration, excretion rates and O:N) were measured in both
conditions, and alterations in the proteome during thermal fluctuations
were assessed. No summer mortality was observed in abalone cultivated
in fluctuating temperatures compared with that at stable high
temperatures. Metabolic rates increased sharply during stable warm
summer conditions and fluctuated in accordance with short-term
temperature fluctuations (20–26 °C). Ammonia excretion rates during
acute responses were comparable in both conditions. When abalone were
exposed to fluctuating temperatures, enzyme activities were
downregulated and structure-related protein expression was upregulated
compared with that at an acclimation temperature (26 °C), highlighting
that exposure to low temperatures during fluctuations alters molecular
processes. Our results reveal that modulation of physiological traits
and protein expression during semidiurnal thermal fluctuations may
buffer abalone from the lethal consequences of extreme temperatures in
summer.
Subject terms: Proteomics, Ecophysiology
Introduction
The temperature dependence of physiological processes in marine
ectotherms is well recognized^[36]1,[37]2. The metabolic rate of an
animal is a primary physiological process that determines its energy
requirements. A prolonged condition of energy imbalance, in which the
metabolic energy expenditure of an animal exceeds its energy
acquisition (or production), can inhibit growth, reproduction and
performance, and even lead to death^[38]3,[39]4. Because ectothermic
organisms have the physiological plasticity to adapt to thermal
variation in their habitats^[40]5,[41]6, much attention has been paid
to the mechanisms of the physiological adjustments made during their
acclimation (or acclimatization) to changes in environmental
temperatures. In this context, while some marine mollusks maintain
metabolic rates at relatively constant levels during thermal
acclimation^[42]7,[43]8, other ectotherms show a sharp increase in
metabolic costs even after thermal acclimation^[44]2,[45]9. In both
cases, an acute increase in environmental temperatures results in
increases in the metabolic rates of the organisms. Despite a general
consensus among scientists about the thermal dependence of metabolic
rate in marine ectotherms, the acclimatory adjustment of their
physiological activities in response to a short-term periodic (e.g.
diel or semidiurnal) fluctuation in water temperature is still
debated^[46]10.
Marine ectotherms in various temperate coastal sea areas, i.e. tidal
flats, tide pools and tidal-mixing fronts, can experience large
short-term thermal fluctuations. The responses to short-term cyclic
thermal fluctuations vary greatly between ectotherm species and/or
physiological processes^[47]10–[48]12. Such thermally fluctuating
conditions can increase the metabolic energy demands of some
ectotherms, and even result in a failure to maintain physiological
processes and performance traits^[49]10,[50]13,[51]14. However, many
ectotherms can adjust their physiological rates to reduce the thermal
sensitivity of their metabolism and mitigate energetic demands in
response to short-term fluctuations in
temperature^[52]10,[53]15–[54]17, thus increasing their thermal
tolerance by reducing the metabolic cost of exposure to high
temperature^[55]10,[56]18,[57]19. The resultant physiological
compensation for either the increased metabolic demands or the reduced
metabolic costs occurring during wide thermal fluctuations can
accelerate the organism’s growth rate compared with those in
corresponding thermally stable conditions^[58]20,[59]21. Furthermore,
the degree of temperature fluctuation that an organism experiences in
its habitats may also be an important determinant of its physiological
adjustment to short-term thermal variations^[60]21,[61]22. Therefore,
although ectotherms that inhabit habitats exposed to short-term thermal
variations require physiological plasticity to buffer the energetic
demands from the thermally variable conditions to ensure their
survival, growth and development^[62]10,[63]22, it remains difficult to
generalize the patterns of their physiological responses to thermal
variations because thermal tolerance windows differ among
species^[64]4.
Here, we examined the physiological and molecular responses of the
Pacific abalone, Haliotis discus hannai, to thermal variations and
determined whether it could adjust its physiological processes to
reduce energetic costs under variable (semidiurnal) compared with
stable (seasonal) daily temperature conditions. Abalone aquaculture in
the shallow coastal seas around Wando Island off the southwestern coast
of the Korean Peninsula has been expanding since 1970, and the annual
production reached 12,000 tonnes in 2016
([65]https://www.mof.go.kr/statPortal/). The southwestern area of the
sea south of Korea is characterized by a strong tidal front between the
bottom cold water of the Yellow Sea and the stable offshore Tsushima
Warm Current water^[66]23,[67]24, and hence is greatly influenced by
the cyclic intrusion of cold water toward the coastline during the
flood tide after vertical mixing of the surface warm water with the
bottom cold water around the tidal front^[68]25. Therefore, abalone
cultivated in suspended cage nets are exposed to large semidiurnal
fluctuations in environmental temperature, especially in summer. In
recent years, there have been frequent incidences of mass mortality of
the abalone cultivated in this area during summer, leading to
speculation about possible effects of global warming or an acute
temperature variation^[69]25–[70]28. Because of the high commercial
value of the abalone and the feedback effects of farming in ambient
natural environments^[71]29, the capacity of the abalone to adjust
their physiological processes to short-term as well as long-term
variations in environmental temperatures has become the center of
attention.
The measurement of the biological responses of ectotherms to
fluctuating thermal conditions is therefore crucial to evaluate how
they maintain fitness under these conditions. Abalone cultivated in
this shallow coastal water should be ideal for investigating the
physiological responses to semidiurnal and seasonal thermal variations.
Given the expected acute responses of abalone to the prevalence of
fluctuating thermal conditions and their mortality across a widespread
cultivation area around Wando Island in summer, we hypothesized that
the physiological responses of abalone to thermal fluctuations would
limit their ability to maintain growth and performance compared with
those acclimated to stable thermal conditions. To test this hypothesis,
we evaluated the thermal dependence of the metabolic rate of the
abalone in response to daily temperature fluctuations under controlled
conditions, comparing this with the responses of those acclimated to
seasonal temperature conditions (Fig. [72]1). We also measured the
catabolic breakdown of proteins stored in tissues as a metabolic fuel
source for energetic costs. We then evaluated changes in the proteome
of H. discus hannai that are indicative of cellular stresses to
determine whether the organism-level responses to short-term thermal
variations correspond with the molecular responses^[73]4. We
anticipated that proteome traits associated with metabolic responses to
semidiurnal temperature fluctuation would allow us to assess the
abalone’s capacity to adapt to short-term fluctuation and thereby
maintain their fitness^[74]30,[75]31. Specifically, we combined
physiological analysis with isobaric tags for relative and absolute
quantitation (iTRAQ)-based quantitative mass spectrometry (MS) of the
abalone proteome to highlight the regulatory molecular mechanisms
behind their physiological performance in response to semidiurnal
temperature fluctuation^[76]32,[77]33.
Figure 1.
[78]Figure 1
[79]Open in a new tab
Experimental design and water temperature regimes. (a) Stable daily
thermal fluctuation in different seasons. For stable daily temperature
(seasonal variation) treatments, water temperatures were adjusted to
3 °C and 8 °C for winter conditions, 13 °C and 18 °C for spring/autumn
conditions, and 23 °C and 28 °C for summer conditions, respectively.
Because of the seasonal variation in water temperature, physiological
measurements were conducted 2 weeks after acclimation to 3, 8, 13, 18,
23 and 28 °C, respectively, depending on the season. (b) Semidiurnal
temperature-fluctuation treatment and timing of abalone tissue
sampling. Specimens for the daily fluctuating treatment were kept under
a summer temperature (26 °C) and then the experimental temperatures
were set to range between 20 °C and 26 °C, based on previous
observations of daily temperature variability in the abalone culture
cages. The water temperature in the water baths fluctuated periodically
at an interval of 6 h and physiological measurements for the
fluctuating-temperature treatments were performed for 144 h. Specimens
for proteomic analysis were randomly sampled at time points of 0, 12,
24, 48, 72, 96, 120 and 144 h (T0–T7, respectively) after the
experiment started.
Results
Water temperature
Three abalone-culture cages recorded about 13%, 2% and no mortality,
respectively, in each month during the summer (August–October 2017),
which allow us to define the high-mortality (HM), the
moderate-mortality (MM) and the control no-mortality (NM) cages. The
daily mean seawater temperature at the sampling sites showed a seasonal
pattern typical of the temperate zone, with a maximum in summer
(August) and a minimum in winter (February, Fig. [80]2a). The HM, MM
and NM cages displayed daily mean temperature ranges of 7.2 to 26.6 °C,
7.0 to 26.4 °C and 8.3 to 27.1 °C, respectively. The three sites
recorded average daily fluctuations of 1.7 ± 0.4 °C (range: 1.2 to
2.2 °C), 1.8 ± 0.8 °C (0.9 to 3.7 °C) and 5.0 ± 1.9 °C (2.1 to 7.5 °C),
respectively, in the warmest period of August (Fig. [81]2b). The daily
temperature fluctuation was largest at the NM of all cages (ANOVA,
F[2,27] = 23.61, P < 0.001; Tukey test, P < 0.05). Except for the
summer months, the daily water temperatures were fairly stable with
ranges of <1 °C in all the cages (Fig. [82]2c).
Figure 2.
[83]Figure 2
[84]Open in a new tab
Thermal variability in the abalone-rearing cages. Temperature profile
from a data logger in 2017 deployed in the cages of three
abalone-culture locations around the archipelago off southwestern
Korea. (a) Seasonal variabilities of water temperatures in cages
representing three localities of high, moderate and no mortality (HM,
MM and NM; green, red and blue, respectively). Thick lines represent
daily mean temperatures; colored areas represent the range of daily
maximum and minimum temperatures. (b) Daily fluctuations of water
temperatures in the three cages in August, the annually warmest period.
(c) Small daily temperature fluctuations in the three cages in May,
November and February, respectively.
Metabolic rate of H. discus hannai
Highly significant and positive relationships were found between the
rate of oxygen consumption (Vo[2], mg O[2] h^−1) and dry tissue weight
(DW, g) under both stable and fluctuating temperature conditions
(Table [85]1). For the stable daily temperature (seasonal variation)
treatments, an analysis of covariance (ANCOVA) showed no significant
difference among the slopes of any of the Vo[2]–DW regressions at the
six experimental temperatures (F[5,42] = 1.140, P = 0.354), which
yielded a common slope of 0.660 (±0.068). However, there was a
significant difference among the intercepts of the six regressions
(F[5,47] = 446.9, P < 0.001). A Bonferroni post hoc test demonstrated a
significant effect of temperature on oxygen consumption (P < 0.05),
with a linear increase in Vo[2] with increasing test temperature
(Fig. [86]3a).
Table 1.
Regression coefficients between physiological rate (Vo[2], mg h^−1 for
oxygen consumption;
[MATH:
VNH4–N
:MATH]
, μg h^−1 for ammonia excretion) and dry tissue weight (DW, g) for
Haliotis discus hannai according to the allometric equation
[MATH: Vo2orVNH4–N
=aDW
b :MATH]
under stable and fluctuating daily temperature treatments.
Treatments Temperature (°C) Slope b Intercept a r
[MATH: b¯ :MATH]
[MATH: a¯ :MATH]
Vo[2] Stable
Winter 3 0.937 0.006 0.823 0.660 ± 0.068 0.010^a
8 0.635 0.243 0.737 0.232^b
Spring/fall 13 0.640 0.534 0.887 0.517^c
18 0.834 0.541 0.975 0.730^d
Summer 23 0.467 1.194 0.771 0.969^de
28 0.488 1.372 0.862 1.167^e
Fluctuating
T0–T1 20–26 0.718 0.947 0.934 0.589 ± 0.038 1.168
T1–T2 20–26 0.646 0.878 0.940 0.962
T2–T3 20–26 0.528 1.107 0.907 0.936
T3–T4 20–26 0.469 1.198 0.890 0.987
T4–T5 20–26 0.396 1.529 0.925 1.118
T5–T6 20–26 0.525 1.158 0.892 1.045
T6–T7 20–26 0.652 0.912 0.931 1.010
[MATH:
VNH4–N
:MATH]
Stable
Winter 3 0.901 0.394 0.734 0.616 ± 0.081 0.678^a
8 0.476 2.200 0.885 1.568^bc
Spring/fall 13 0.466 1.850 0.768 1.355^b
18 0.539 2.837 0.743 2.322^c
Summer 23 0.845 1.540 0.788 1.844^bc
28 0.575 6.125 0.743 5.509^d
Fluctuating
T0–T1 20–26 0.510 4.661 0.787 0.471 ± 0.052 4.966
T1–T2 20–26 0.480 4.538 0.731 4.606
T2–T3 20–26 0.569 3.497 0.748 4.098
T3–T4 20–26 0.377 6.062 0.845 5.207
T4–T5 20–26 0.561 3.416 0.874 3.954
T5–T6 20–26 0.488 4.383 0.792 4.506
T6–T7 20–26 0.315 6.509 0.761 5.055
[87]Open in a new tab
Nine individuals were used for each treatment. All regressions were
significant at P < 0.001.
[MATH: a¯ :MATH]
, recalculated using a common slope
[MATH: b¯ :MATH]
values of 0.660 and 0.616, respectively, represents Vo[2] (mg O[2] h^−1
g^−1) and
[MATH:
VNH4–N
:MATH]
(μg NH[4]–N h^−1 g^−1) for an individual of 1 g DW. Superscripts
indicate significant differences between intercepts (Bonferroni post
hoc test, P < 0.05).
Figure 3.
[88]Figure 3
[89]Open in a new tab
Rates of oxygen consumption (a,d) and ammonia excretion (b,e), and O:N
ratios (c,f) of Haliotis discus hannai measured under stable and
fluctuating temperature conditions, respectively. Stable temperatures
represent stable daily thermal fluctuation in different seasons (see
Fig. [90]1). Physiological measurements were conducted 2 weeks after
acclimation to 3, 8, 13, 18, 23 and 28 °C, respectively. Fluctuating
temperatures represent semidiurnal temperature-fluctuation (range:
20–26 °C) treatment. Physiological measurements for the fluctuating
temperature treatments were performed over 144 h. T0–T7 indicates each
time point of 0, 12, 24, 48, 72, 96, 120 and 144 h (T0–T7,
respectively) after the experiment started at the acclimated
temperature (26 °C). Data points are recalculated regression intercepts
from Table [91]1. CV, coefficient of variation.
For the fluctuating daily temperature (semidiurnal variation)
treatments, the rates of oxygen consumption displayed a pronounced
semidiurnal pattern in accordance with temperature fluctuation
(Fig. [92]4). ANCOVA revealed no significant differences among the
slopes or intercepts of any of the daily Vo[2]–DW regressions over the
6-day experimental protocol (F[6,49] = 1.559, P = 0.179;
F[6,55] = 0.904, P = 0.499, respectively; Table [93]1). After
recalculation using a common slope of 0.589 (±0.038), no marked changes
were found over 6 d in the daily Vo[2] of an abalone of 1 g DW
(Fig. [94]3d). These daily Vo[2] values were comparable with those in
the corresponding stable temperature (e.g. 23 °C) treatment.
Figure 4.
Figure 4
[95]Open in a new tab
Periodic variation in oxygen consumption rates of Haliotis discus
hannai measured simultaneously with semidiurnal fluctuations of ambient
water temperatures (dashed line) over the 6 d. Points are recalculated
regression intercepts from Table [96]1. The solid line represents the
hourly mean values of respiration rates.
A pronounced increase in metabolic rate with increasing test
temperature was observed, as indicated by the Q[10] (8–28 °C) over the
entire range of temperatures (Table [97]2). The Q[10] displayed reduced
thermal sensitivity at the higher temperatures compared with lower
temperatures under seasonally acclimated conditions. The Q[10]
(20–26 °C) under the fluctuating daily temperatures was slightly higher
than that in the higher temperatures (18–28 °C) of the acclimated
conditions.
Table 2.
Q[10] values for physiological rates (oxygen consumption and ammonia
excretion) of the abalone Haliotis discus hannai in stable or
fluctuating daily temperatures.
Metabolic rate Ammonia excretion rate
Stable daily temperature Q[10] (8–28 °C) 10.06 7.03
Q[10] (8–18 °C) 3.15 1.48
Q[10] (13–23 °C) 1.87 1.36
Q[10] (18–28 °C) 1.60 2.37
Fluctuating daily temperature Q[10] (20–26 °C) 2.67 ± 0.94
[98]Open in a new tab
Note that when Q[10] = 1, there is no change in physiological rate with
changing temperature; when Q[10] < 1, rates decrease with increasing
temperature; and when Q[10] > 1, rates increase with increasing
temperature. At 3 °C, the abalone were quiescent with little metabolic
activity and thus this treatment was not considered in the Q[10]
calculation.
Ammonia excretion by H. discus hannai
All regressions of ammonia excretion (
[MATH:
VNH4–N
:MATH]
, μg NH[4]–N h^−1) against the DW of H. discus hannai were
significantly positive at both stable and fluctuating temperatures
(Table [99]1). For the stable daily temperature treatments, ANCOVA
testing of all these data revealed no significant difference in the
slopes for six temperature treatments (F[5,42] = 0.843, P = 0.527),
with a common slope of 0.616 (±0.081). Significant differences in the
intercepts of the regression were found (F[5,47] = 46.193, P < 0.001)
and a subsequent Bonferroni test demonstrated a significant effect of
temperature on excretion rate (P < 0.05), revealing an abrupt stepwise
increase at the highest test temperature (28 °C) and consistent rates
between 8 °C and 23 °C (Fig. [100]3b).
For the fluctuating daily temperature treatments, there were no
significant differences among the slopes or intercepts of any of the
daily
[MATH:
VNH4−N
:MATH]
–DW regressions for 6 d (F[6,49] = 0.439, P = 0.849; F[6,55] = 0.957,
P = 0.463, respectively; Table [101]1). When recalculated using a
common slope of 0.471 (±0.038), the daily excretion rates of an abalone
of 1 g DW were fairly consistent for 144 h (6 d) (Fig. [102]3e), with
values comparable to that at the highest stable temperature (28 °C)
treatment.
A pronounced thermal sensitivity of the ammonia excretion rate was also
observed (Table [103]2). In contrast to the metabolic rate, the Q[10]
for ammonia excretion increased at the higher temperatures compared
with lower temperatures under seasonally acclimated conditions.
O:N ratio
The ratio of oxygen consumption to ammonia excretion (O:N ratio, by
atomic equivalents) increased with increasing test temperature in the
stable daily temperature treatments (coefficient of variation
[CV] = 68.0). The ratio reached high values of >130 at 13–23 °C but
decreased sharply at 28 °C (Fig. [104]3c). The O:N ratios in the
fluctuating daily temperature treatments remained much more consistent
(mean of 96, CV = 13.6) during the experimental period of 6 d
(Fig. [105]3f).
Proteomic responses
The iTRAQ-based quantitative analysis of the H. discus hannai proteome
with triplicates yielded a total of 9,368 spectra; 317 proteins were
quantified on the basis of 913 unique peptides. Among these proteins,
217 were identified in all three replicates and 160 proteins were
annotated using a BLAST sequence-similarity search (Supplementary
Table [106]S1). Among 40 proteins with significantly changed expression
compared to the acclimation temperature (26 °C) treatment, 20 were
upregulated and 20 were downregulated (Supplementary Table [107]S2).
Hierarchical cluster analysis of the changes in protein expression at
different time points revealed that although the largest quantitative
change occurred at T7, the protein profiles were almost consistent over
the rest of the time points (Fig. [108]5).
Figure 5.
[109]Figure 5
[110]Open in a new tab
Hierarchical clustering analysis of the differentially expressed
proteins in H. discus hannai foot muscle exposed to heat stress for
different times. Each row indicates the functional annotation of the
protein and the columns represent the heat-exposure time points. The
up- and downregulated proteins are indicated in red and blue,
respectively. A deeper color denotes a larger log[2]-transformed change
compared with the control time point (T0).
The proteins with significantly altered expression were classified
based on GO terms. This indicated enrichment of 20, 15 and 9 categories
in the biological process, cellular component and molecular function
domains, respectively (Fig. [111]6). The ratio of the numbers of up-
and downregulated proteins for each GO term was calculated and a cutoff
ratio of 1.5 was applied to enrich up- and downregulated GO terms. For
the biological process domain, cellular component organization or
biogenesis (GO:0071840), locomotion (GO:0040011) and biological
adhesion (GO:0022610) were enriched in the upregulated proteins,
whereas metabolic process (GO:0008152) was enriched in the
downregulated proteins. With regard to the cellular component domain,
upregulated proteins were involved in protein-containing complexes
(GO:0032991), supramolecular complexes (GO:0099080), synapses
(GO:0045202) and cell junctions (GO:0030054), while downregulated
proteins were related to the membrane-enclosed lumen (GO:0031974). For
the molecular function domain, structural molecule activity
(GO:0005198) and molecular function regulator (GO:0098772) were
enriched in the upregulated proteins, whereas catalytic activity
(GO:0003824) was enriched in the downregulated proteins.
Figure 6.
[112]Figure 6
[113]Open in a new tab
GO analysis of differentially expressed proteins. Each annotated GO
term is categorized into biological process, cellular compartment and
molecular function. Left-handed bars represent the number of
downregulated proteins associated with the corresponding GO term,
whereas the right-handed bars indicate the number of upregulated
proteins.
Metabolic pathway analysis
A Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway
analysis identified 15 metabolic pathways that were significantly
associated (adjusted P < 0.05) with up- and downregulated proteins
(Supplementary Table [114]S3), of which 14 were related to
downregulated proteins and one with upregulated proteins. Among the 14
downregulated pathways, three were related to glucose catabolism and
four to amino acid catabolism. Overall, four downregulated proteins
were linked to these seven pathways. To visualize the participation of
the four downregulated proteins in two different catabolic pathways,
two partial pathway maps were generated based on three KEGG pathways of
Lottia gigantea (owl limpet): pyruvate metabolism (ID:00620), valine,
leucine and isoleucine degradation (ID:00280), and alanine, aspartate
and glutamate metabolism (ID:00250) (Supplementary Fig. [115]S1).
Pyruvate dehydrogenase (PDH) and dihydrolipoyl dehydrogenase (DLD) are
associated with the pyruvate catabolism pathway, while
3-hydroxyisobutyrate dehydrogenase (HIBADH) and glutamate dehydrogenase
(GDH) are involved in the amino acid catabolism pathway. Among the
significantly changed proteins, the pathway analysis found that only
GDH was directly correlated with ammonia excretion via catalysis of
oxidative deamination of glutamic acid.
Discussion
The present study demonstrated that large daily temperature
fluctuations adjacent to a tidal-mixing front area are episodic events
that occur in summer months. We examined the acute physiological
responses of abalone to exposure to semidiurnal cyclic fluctuations
over a range of environmental temperatures (20–26 °C) rather than using
the rate–temperature curves at different exposure temperatures
following acclimation to those temperatures^[116]8,[117]34 or to
fluctuating temperatures^[118]10,[119]11. Abalone experiencing thermal
oscillations were unable to reduce the thermal sensitivity of their
metabolism compared with those acclimated to the high temperatures of
summer–autumn, but their metabolic rates fluctuated in parallel with
the temperature fluctuations. In contrast, their ammonia excretion
rates were similar between fluctuating and stable high temperatures.
Thus, the energy demands required as a consequence of the abalone’s
acute response to short-term temperature variations appear to be
sustained by an allocation of resources through protein catabolism.
These results likely support our initial hypothesis, and suggest that
short-term temperature fluctuations will increase the metabolic demands
observed at high temperatures in summer. However, contrary to our
expectation, different patterns of protein expression in abalone under
fluctuating and acclimated (26 °C) temperatures demonstrated a cellular
response that reduced mobilization of metabolic reserves under
thermally variable conditions, which probably explains why no mortality
was observed at the cage site exposed to the largest daily fluctuations
in temperature.
In response to an increase in seasonal temperatures, abalone showed no
evidence of an acclimatory adjustment of their metabolic rate, which
increased sharply during the warm conditions of summer^[120]2,[121]34.
This result is inconsistent with those obtained for other gastropods
(e.g. Crepidula fornicate^[122]8 and Haliotis corrugata^[123]35), whose
metabolic rate is independent of temperature. Furthermore, the acute
response of abalone to thermal fluctuations led to a clear circatidal
rhythm in their metabolism coincident with the thermal oscillations
(Fig. [124]4). Indeed, tidal-based endogenous rhythms, similar to the
sleeping-and-waking-based circadian rhythms in the metabolism of highly
evolved organisms^[125]36, have been observed in marine
ectotherms^[126]37. However, there is little evidence in marine
ectotherms for an endogenous circatidal rhythmicity based on short-term
thermal oscillations. Our results demonstrate that the physiological
traits of abalone show a strong temperature dependence in response to
both seasonal and short-term fluctuations in environmental
temperatures.
Metabolism of ectotherms is a major energy-demanding process that
provides energy for maintenance, growth, development and
performance^[127]2,[128]11. In this study, we showed that the metabolic
costs of abalone are highly temperature dependent. In the absence of
mechanisms to reduce the thermal sensitivity of their
metabolism^[129]11 or to compensate for the increased cost of
metabolism^[130]2 during the summer, organisms will experience a
metabolic deficit that may suppress maintenance and further growth. It
is generally accepted that gastropods become quiescent as environmental
temperatures decrease (below 7–8 °C in the case of H. discus
hannai)^[131]38,[132]39, allowing them to reduce their metabolic rate.
Indeed, higher Q[10] values indicate that the metabolic rates of
abalone are more rapidly reduced at lower temperatures than would be
predicted from their response to higher temperatures. The metabolism of
abalone acclimated to high temperatures (18–28 °C) displayed reduced
thermal sensitivity compared with those at low temperatures and across
a range of temperatures; this may be a mechanism by which abalone
buffer their high metabolic costs during the peak temperatures of
summer. In contrast, although abalone exposed to fluctuating
temperatures showed little evidence of a reduction in the thermal
sensitivity of their metabolism at stable high temperature, the thermal
sensitivity of their metabolism was still much lower in fluctuating
temperatures than that across the entire range of temperatures
experienced. This may result from a daily metabolic rate that is
broadly comparable with that predicted by the mean temperature during
thermal oscillations.
During both acclimation to different temperatures and exposure to
fluctuating thermal conditions, temperature affected the ammonia
excretion rate of abalone. Without a compensatory adjustment (e.g. an
increase in food consumption), the increased energy demands of abalone
exposed to high temperatures and thermal oscillations may deplete their
tissue energy in summer. Our finding that abalone experience food
shortages under cage-cultivation conditions was unexpected. Their food
consumption is temperature dependent, increasing with temperature to
20 °C and decreasing above this temperature^[133]38,[134]40. Given that
our physiological measurements were conducted in starved abalone, our
results for metabolic and excretory rates would represent the basal
requirements for maintenance under conditions of restricted food
consumption at high or fluctuating temperatures in summer. In both
cases, elevated ammonia excretion will give rise to a depletion of
tissue energy reserves because of increased maintenance requirements
and the resultant mismatch between metabolic demand and energy intake,
resulting in disturbed maintenance and a reduction in growth.
The O:N ratio represents the relative proportion of resources (proteins
vs. carbohydrates and lipids) catabolized for maintenance metabolism by
marine ectotherms^[135]2,[136]41. The O:N ratio displayed a sudden
decrease at the highest temperature studied (28 °C). Given that lowered
O:N ratios indicate a relative enhancement of protein catabolism
compared with overall oxidative energy metabolism^[137]41, stable
high-temperature stress caused a metabolic shift from carbohydrate and
lipid catabolism to protein catabolism. The daily mean O:N ratios of
abalone exposed to fluctuating temperature regimes were comparable with
that at stable high temperature (28 °C). However, the acute change in
metabolic rates in accordance with temperature fluctuations suggest
that it is reasonable to infer that the greater thermal sensitivity of
ammonia excretion at high temperatures may make O:N ratios highly
variable during thermal oscillations. Although the mean values of
Vo[2],
[MATH:
VNH4–N
:MATH]
and O:N ratios were comparable in fluctuating temperatures and at
stable high temperature, these increased costs may have been associated
with the high temperatures experienced during thermal fluctuations.
Evidence for such responses of physiological traits to short-term
thermal fluctuations comes from the different patterns of synthesis and
utilization of reserves as evidenced by different protein profiles in
abalone exposed to stable and fluctuating temperatures, as discussed
below.
One of the most interesting results of this study was that there was a
notable discrepancy between protein expression in abalone exposed to
fluctuating temperatures and those exposed to high acclimation
temperature (26 °C). The hierarchical clustering analysis of the
abalone proteome under exposure to fluctuating temperatures revealed
limited changes during the experimental period and differential
expression compared with the control (Fig. [138]5). The GO analysis of
the molecular function category revealed that a large proportion of
downregulated proteins (75%) was associated with the catalytic activity
term (GO:0003824) and half (50%) the upregulated proteins were
associated with the structural molecular activity term (GO:0005198)
(Fig. [139]6). These results imply that the majority of downregulated
proteins are metabolic enzymes, whereas the majority of upregulated
proteins are structural. It is thus not surprising that the largest
number of significantly changed KEGG metabolic pathways were correlated
with downregulated proteins (Supplementary Table [140]S3). In this
context, of four downregulated proteins (PDH, DLD, HIBADH and GDH),
only GDH, which produces energy through deamination of glutamate to
α-ketoglutaric acid, had a direct effect on the rate of ammonia
excretion (Supplementary Fig. [141]S1). Given that the deamination
cycle of GDH is known to be a major pathway of ammonia excretion in
marine invertebrates^[142]42, the mean O:N ratio observed under the
fluctuating temperature stress may reflect the result of a
downregulation of GDH expression below that seen at the high control
temperature.
The analysis of the time course of changes in protein expression under
fluctuating temperatures demonstrated a significant decrease of GDH at
the time point T7 (Supplementary Fig. [143]S2a). To investigate the
correlation between the time course of expression of GDH and muscle
constituents, a pairwise Spearman’s correlation analysis was performed
between GDH and eight proteins annotated with the GO term of structural
molecule activity. Among these eight muscle-related proteins, four
proteins that are major components of muscle myofibril^[144]43 showed a
strong negative correlation with GDH expression (Spearman’s ρ < −0.7)
(Supplementary Fig. [145]S2b). With respect to dynamic nitrogen
homeostasis, muscle myofibril can act as an ‘amino acid deposit’,
because it is synthesized under high concentrations of amino acids and
degraded under low amino-acid concentrations^[146]44. The lysosome
pathway is considered a major route of protein degradation in muscle
tissue, and given that it is significantly downregulated under
fluctuating temperature stress (adjusted P < 0.05) (Supplementary
Table [147]S3), suppressed lysosomal proteolytic activity is likely to
be responsible for the increased expression of muscle myofibril
proteins^[148]45.
The significant negative correlations between GDH and muscle myofibril
proteins can be explained by suppression of lysosomal proteolysis
because of an increased free amino acid concentration as a result of
downregulation of GDH. Cellular free amino acids in muscle tissue are
considered to be major regulators of lysosomal proteolysis^[149]46 via
the mammalian target of the rapamycin (mTOR) protein complex-mediated
signaling pathway^[150]47,[151]48. Glutamine and arginine, which are
negatively regulated by glutamate dehydrogenation of
GDH^[152]49,[153]50, are known to positively regulate mTOR
phosphorylation, leading to a downregulation of lysosome-mediated
proteolysis^[154]51,[155]52. Thus, the downregulation of GDH in abalone
exposed to fluctuating temperatures may result in high concentrations
of free glutamine and arginine in their muscle cells, shifting the net
balance of protein metabolism from catabolic to anabolic. Additional
quantitative analyses would offer more solid evidence of the
time-course correlation between GDH downregulation and muscle myofibril
proteins. For instance, quantitation of free amino acids including
glutamine and arginine could demonstrate the correlation between GDH
and amino acid catabolism, and quantitative phosphoproteome analysis of
the mTOR-related pathway could provide evidence of altered lysosomal
proteolysis activity.
The metabolic pathway analysis provided a plausible explanation for the
correlation between physiological properties and differential protein
expression. The downregulation of metabolic enzyme activity (PDH, DLD,
HIBADH and GDH) in abalone exposed to fluctuating temperatures did not
correspond with the high metabolic rate that would be predicted by the
mean temperature during thermal oscillations or at high control
temperature. This indicates high maintenance costs and suggests that
exposure to low temperatures during thermal oscillation alters
metabolic enzyme activity, inducing a reduction in metabolism and
protein catabolism compared with that at the high control temperature.
The consistency between the responses of physiological processes and
metabolic enzyme activity to fluctuating temperatures highlights a
close interaction between physiological responses and cellular-level
molecular processes. Together with downregulation of metabolic enzymes,
upregulation of structure-related proteins may provide a greater
metabolic scope that would help meet the metabolic demands for growth
under fluctuating temperatures^[156]10. Therefore, when abalone are fed
in cultivation cages, the energetic consequences of exposure to low
temperatures during thermal oscillations may have a synergistic effect
on growth, with the most active feeding capacity being at around
20 °C^[157]38,[158]40. Accelerated growth under daily fluctuating
temperature conditions has been clearly demonstrated for other marine
ectotherms including fish and invertebrates^[159]15,[160]20.
To conclude, this study reveals a potential mechanism by which exposure
to fluctuating temperatures allows abalone to deal with the challenges
associated with summer temperature extremes. The abalone exhibited the
capability to regulate protein expression and thereby adjust their
physiological traits to fluctuating temperatures in a way that allows
them to reduce the elevated energetic costs of summer peak
temperatures. As previously reported for temperature stress^[161]27,
exposure to high temperatures of more than 26 °C for several days
severely affected the survival, falling rate, histological structure of
the foot, and antioxidant and stress-response systems of H. discus
hannai, whereas no biological and molecular effects were detectable in
abalone exposed to temperatures lower than 22 °C. Such biological
responses to high-temperature stress were dependent upon the exposure
time. In this context, fluctuating thermal regimes may mitigate the
potential biological risk of summer peak temperatures by reducing
exposure time and increasing the upper thermal limits^[162]10. Overall,
our results suggest that acute regulation of physiological traits and
protein expression by semidiurnal thermal fluctuations may buffer
abalone from the lethal consequences of extreme temperatures in summer
and actually allow their long-standing cultivation.
Methods
Sample collection, acclimation and experimental design
Additional details of the abalone aquaculture at the sampling site are
given in the supplementary material.
Specimens of the Pacific abalone Haliotis discus hannai for the
experiments were collected in a cultivation facility off Wando Island,
on the southwestern coast of Korea (34°18′N and 126°63′E). Because of
the known mortality of the cultivated abalone and to establish the
experimental conditions, seawater temperatures were measured in 2017 at
three culture cages with different degrees of daily temperature
variation throughout the year. The three sites included a
moderate-mortality site (MM), a high-mortality site (HM) and a
no-mortality site (NM). Temperature data were recorded every half hour
using a HOBO Water Temperature Pro v2 Data Logger (Bourne, MA)
installed in the submerged culture facility
([163]http://www.nifs.go.kr/risa/). The numbers of individuals that
survived in the cultivation cages were counted every month to estimate
monthly mortality at the geographical locations of the study area.
Because of the regular seasonal fluctuation of water temperature in
this area, 40 specimens on each seasonal sampling occasion were
randomly collected in May, August and November 2017, and February 2018.
Immediately after collection, all of the individual abalone were put
into a container of natural seawater saturated with oxygen by a
portable air generator and transferred to 200 L water tanks in the
laboratory. The tanks were filled with filtered seawater with a
continuous flow system and aeration. 20 animals were gradually
acclimated to the experimental temperatures (3, 8, 13, 18, 23 or 28 °C,
respectively) covering the seasonal variation observed in situ and the
temperature change was controlled at a rate of 1 °C per day to minimize
the potential effects of acute temperature changes on physiological
state (Fig. [164]1a). Specimens for the daily fluctuating treatment
were kept under summer temperature (26 °C) (Fig. [165]1b). All abalone
were kept on a 14 h:10 h (light:dark) photoperiod. During the 7-day
acclimation to ensure full thermal adaptation to the fortnightly
spring–neap tidal cycle, the abalone were fed fresh sea mustard
(Undaria pinnatifida) daily and then were starved for 24 h prior to the
experiments to reduce the associated physiological responses. The
animals were transported to experimental chambers and acclimated again
for 6 h under the chamber conditions before the commencement of
measurements of physiological activities.
For stable daily temperature (seasonal variation) experiments, 350 ml
flow-through closed cylindrical chambers equipped with a magnetic
stirrer were used to measure the oxygen consumption and urine excretion
rates of the abalone. Nine individual experimental chambers each
accommodated a single abalone and one was used as a control without an
abalone. Seawater was continuously supplied to individual chambers from
an aerated water tank by a peristaltic pump equipped with a 10-channel
pump head (BT 100–1 L, Longer Precision Pump Co. Ltd, Baoding, China).
Flow rates in individual chambers were adjusted to approximately
20 ml min^−1 to maintain the oxygen concentration at over 80%
saturation^[166]53. For each experiment, the chambers were completely
immersed in a water bath in which water temperature was kept constant
at that required for individual experiments (3, 8, 13, 18, 23 or 28 °C;
Fig. [167]1a). Physiological measurements were performed over 24 h.
After the experiments, the specimens were carefully dissected using a
stainless steel knife. Shells were dried at 60 °C in a drying oven.
Soft tissues were lyophilized and then weighed.
For fluctuating daily temperature treatments, two series of experiments
were performed. Nine individual experimental chambers and one control
chamber, as described above, were placed in a water bath for
physiological measurements and approximately 50 abalone were placed in
another water tank for measurements of molecular responses. The
experimental temperature was set to range between 20 and 26 °C
(Fig. [168]1b), based on previous observations of daily temperature
variability in the abalone culture cages^[169]25. A comparison of
temperature data reading at half-hour intervals at two locations
adjacent to our sampling sites from 2005 to 2009 showed that mean
values and fluctuating ranges of daily temperatures fluctuation were
highest in August. The full range of daily temperatures was much larger
(up to 8.5 °C) in deep offshore area, where tidal front is formed, than
that (<1 °C) in the shallow coastal area. The daily temperature ranges
were closely associated with fortnight tidal cycle and horizontal
temperature gradient. To reproduce the thermal variability during
semidiurnal tidal cycles, the water temperature in the water baths was
changed periodically at intervals of 6 h, increasing or decreasing by
0.3–0.4 °C every 20 min. Because of the observed period of high daily
temperature fluctuations in summer^[170]25, physiological measurements
for the fluctuating temperature treatments were performed over 144 h.
The specimens were carefully dissected for biometric measurements as
described above. For proteomic analysis, three specimens were randomly
sampled from the water tank in which 50 abalone were situated at each
time point of 0, 12, 24, 48, 72, 96, 120 and 144 h (T0–T7,
respectively) after the experiment started.
Physiological measurements
The metabolic rate of the abalone was determined by measuring oxygen
consumption inside the control and experimental chambers. Oxygen
concentrations inside the measurement chambers were recorded every
second using oxymetric probes (Oxy-10 micro, PreSens-Precision Sensing
GmbH, Regensburg, Germany). The measurements were performed for 24 h
(for constant temperature treatments) or 144 h (for fluctuating
temperature treatments). The oxygen consumption of the specimens was
then calculated from the differences in oxygen concentration between
the control and the experimental chambers. Details of the procedures
used to determine oxygen consumption by continuous monitoring have been
described elsewhere^[171]54.
The rate of ammonia excretion was determined from the increase in
ammonia concentrations between the outflows of the control and
experimental chambers. Water samples from the outflows of the chambers
were collected 4–5 times during the 24-hour experiments. Ammonia
concentration was analyzed using the oxidation method with hypochlorite
in an alkaline medium^[172]55.
Statistics of physiological data
Differences in the daily fluctuations of water temperatures for abalone
rearing cages were tested by an analysis of variance (ANOVA) after
checking normality (Shapiro–Wilk test) and homogeneity of variance
(Levene’s test).
The physiological measures (i.e. rates of oxygen consumption and
ammonia excretion) and dry weight (DW) of the abalone for individual
experimental conditions were fitted to the allometric equation:
[MATH:
Y=aWb :MATH]
, where Y is the physiological rate, W is DW, and a and b are the
fitted constants. The fitted constants were determined by the
intercepts (a) and slopes (b) of least-squares regression between
physiological rates and DW values of the specimens based on the
logarithmic transformation (base 10) of those variances. The
significance of the differences in slopes and intercepts of regression
equations was tested by analysis of covariance (ANCOVA). When no
significant differences were detected among these estimated slopes
(P > 0.05), the intercepts were recalculated using a common slope (
[MATH: b¯ :MATH]
). The intercepts of the various sets of regression equations were
compared by a Bonferroni post hoc multiple-comparison test. The
commercially available SPSS software package (v. 22.0, IBM Corp.,
Armonk, NY) was used to perform the statistical analyses.
The thermal sensitivity of physiological rates for metabolism and
ammonia excretion were calculated as
[MATH:
Q10=<
msup>(R2/R1)(10/(T2−T1)) :MATH]
, where R represents the rates at temperature (T) 1 and 2. Thermal
sensitivities were calculated for the entire range of test
temperatures, the lower (8–18 °C) to upper (18–28 °C) temperature
ranges and for the fluctuating daily temperature range.
Proteomic analysis
Details of the procedures for proteomic analysis are presented in the
supplementary material. Immediately after collection of triplicate
specimens for determination of cellular molecular responses to
semidiurnal temperature fluctuation, the foot tissues of specimens were
rapidly excised and frozen in liquid nitrogen (−80 °C). After
purification and digestion of cellular proteins, equal amounts of
peptides (50 μg) from each replicate were treated for iTRAQ labeling.
Peptides derived from samples at each time point, T0–T7, were labeled
with iTRAQ tags 113, 114, 115, 116, 117, 118, 119 and 121,
respectively. The iTRAQ labeling peptides were fractionated by an
in-house nano-LC system interfaced with a Q-Exactive Hybrid
Quadrupole-Orbitrap Mass Spectrometer equipped with a preconditioned
capillary column (0.075 × 150 mm, C18, 3 μm particle size, 200 Å pore
size, Phenomenex, Torrance, CA).
Proteome Discoverer version 2.1 (Thermo Scientific, Waltham, MA) was
used to search the peptide MS/MS data against the ORF-based protein
database of H. discus hannai^[173]56. A peptide sequence was assigned
to the tryptic peptide sequence using the SEQUEST search engine. For
the entire peptide ID list, the false discovery rate (FDR) was
calculated by applying the PeptideProphet software using a reverse
decoy database and a discriminant score cutoff was set to an FDR of
less than 1% to identify peptides. The identified proteins were
relatively quantified based on the iTRAQ reporter ion intensity
corresponding to each sampling time point by comparing intensity at a
time point Tn (n = 1–7) (I(Tn)) to that of the control (I(T0)). The
functional annotation of proteins was performed by BLAST sequence
similarity searches against the whole-organism UniProt/Swiss-Prot
database (E-value < 1 × 10^−20). The protein fold change at the nth
time point (Tn/T0) was calculated for the time points from T1 to T7. To
identify significant changes, the following criteria were applied:
Student’s t-test over biological triplicates (P < 0.05) and the
absolute cutoff of an average fold change >1.20 or <0.83 for up- or
downregulated proteins, respectively. Log[2]-transformed iTRAQ ratios
were used to evaluate differential protein expression^[174]57 and were
visualized by a hierarchical clustering heat-map matrix. The biological
processes and molecular functions of the regulated proteins were
functionally annotated in the context of their gene ontology (GO) using
Blast2GO (v. 5.2.5, BioBam, Valencia, Spain)^[175]58. Furthermore,
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment
analysis for differentially expressed proteins was performed in KOBAS
3.0^[176]59 to identify significantly enriched pathways.
Supplementary information
[177]Supplementary Information^ (118.6KB, docx)
[178]Supplementary Table S1^ (89.3KB, xlsx)
[179]Supplementary Table S2^ (16.7KB, xlsx)
[180]Supplementary Table S3^ (13.3KB, xlsx)
Acknowledgements