Changes in gene expression associated with acclimation to constant temperatures and fluctuating daily temperatures in an annual killifish Austrofundulus limnaeus
Hopkins Marine Station of Stanford University, 120 Oceanview Boulevard, Pacific Grove, CA 93950-3094, USA
* Author for correspondence at present address: Department of Biology, Portland State University, PO Box 751, Portland, OR 97207-0751, USA (e-mail: jpod{at}pdx.edu)
Accepted 6 April 2004
![]() |
Summary |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Key words: annual fish, Austrofundulus limnaeus, DNA microarray, ephemeral pond, eurytherm, gene expression, high mobility group proteins, transcription
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Annual killifish inhabit ephemeral pond environments in regions of Africa
and South America characterized by distinct dry and rainy seasons
(Myers, 1952;
Bailey, 1972
).
Austrofundulus limnaeus occurs in small, isolated ponds in coastal
desert and savanna regions of northern South America. In these habitats,
A. limnaeus routinely experiences wide daily fluctuations in
temperature, oxygen availability and pH
(Podrabsky et al., 1998
).
Temperatures may change over 20°C on a daily basis and may reach highs
above 40°C. In addition to these daily changes, temperatures are also
likely to become increasingly hot as the dry season approaches and the ponds
evaporate and, eventually, become completely dry. Because of its ability to
thrive in this highly variable environment where daily and seasonal shifts are
extreme, we reasoned that A. limnaeus would be an excellent study
organism for examining shifts in gene expression in response to both rapid and
long-term alterations in body temperature.
To this end, we created a cDNA microarray containing 4992 cDNAs isolated from liver tissue of A. limnaeus. This microarray was used to profile changes in gene expression associated with acclimation to constant temperatures spanning the species' environmental temperature range, and fluctuating, environmentally realistic daily temperature regimes in a laboratory setting. We wished to explore and characterize which parts of the known and well-described physiological responses to temperature acclimation were manifested at the transcriptional level, as well as to explore changes in gene expression associated with aspects of temperature acclimation that had not yet been identified in physiological studies. We were especially interested in characterizing the differences in gene expression that (i) distinguish long-term thermal acclimation to stable temperatures from more rapid daily responses to temperature change and (ii) distinguish relatively rapid responses to thermally induced cellular damage from longer-term responses that restore cellular homeostasis.
![]() |
Materials and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
Preparation of cDNA libraries
Livers were dissected from frozen fish and total RNA extracted using Trizol
according to the manufacturer's instructions (Invitrogen, Carlsbad, CA, USA).
Total RNA from the livers of four fish was pooled for each time point. These
pooled samples of total RNA were used to prepare cDNA for the production of
the microarray and to profile changes in gene expression during temperature
acclimation.
A cDNA library was prepared from total RNA pooled from all fish sampled
during the acclimations. SMART cDNA technology (BD Biosciences, San Jose, CA,
USA) was used to prepare the cDNA prior to cloning into the pTriplEx2
directional cloning plasmid vector (ClonTech). Briefly, total RNA was used as
a template to create a cDNA copy of each mRNA using reverse transcriptase
(Powerscript, ClonTech). The single-stranded cDNA was then amplified
via long-distance polymerase chain reaction (LD-PCR;
Cheng et al., 1994
). The
amplified cDNA was then ligated into the cloning vector. Competent E.
coli (DH10B cells, Invitrogen) were then transformed with the ligated
plasmids via electroporation. Transformed cells were then selected
for presence of a cDNA insert and ampicillin (100 µg l1)
resistance via blue/white screening on LB/agar plates
(Sambrook et al., 1989
). A
total of 4992 cDNA clones were isolated into 384-well microtiter plates and
grown overnight in LB medium (Sambrook et
al., 1989
) supplemented with 10% glycerol. These plates were
replicated and stored at 80°C.
Construction of the cDNA microarray
The cDNA inserts from each isolated clone in the cDNA library were
amplified using polymerase chain reaction (PCR). A PCR master mix was prepared
containing 1x Taq. Polymerase buffer (Promega, Madison, WI, USA), 0.2
mmol l1 dNTPs and 0.2 µmol l1
plasmid-specific primers. A single reaction volume was 25 µl. PCR master
mix was inoculated with a small amount of a single bacterial broth culture
from the 384-well plate using a 96-well plate replicator tool (Nalgene/Nunc,
Rochester, NY, USA). The reactions were then heated to 95°C for 2 min to
lyse the bacteria and release the plasmid DNA as template for the reaction.
Reactions were then exposed to 40 cycles of amplification with a denaturing
step of 95°C for 0.25 min, an annealing step of 56°C for 0.5 min, and
an extension step of 72°C for 2.5 min. One row of reactions from each
96-well plate was randomly checked via agarose electrophoresis to
assure proper amplification of the DNA.
A small amount (7 µl) of the PCR-amplified DNA was then transferred to a 384-well PCR plate corresponding to the original clone location used to seed the reaction. The salt concentration of the PCR reactions was brought to a concentration of 3x SSC (1x SSC contains 150 mmol l1 NaCl, 15 mmol l1 sodium citrate, pH 7.0) by adding 20x SSC directly to the PCR products. Microarrays were printed onto glass slides coated with poly-L-lysine according to standard protocols (www.microarray.org; specific protocols are also available at killifish.pdx.edu/protocols.htm). Poly-L-lysine coated microscope slides were produced using Fisher Scientific (Hampton, NH, USA) Gold Seal microscope slides and Sigma Chemical brand poly-L-lysine solution (see above websites). The slides were then stored in a desiccator for 3 weeks to allow the poly-L-lysine coat to age properly. Microarrays were printed using a homemade robot having a 16 pin configuration (TeleChem Chip Maker II pins, Telechem ArrayIt, Sunnyvale, CA, USA) and printing an 18x18 spot grid pattern with a spacing of 240 µm between spots for each pin. This configuration of pins and salt concentration in the DNA samples resulted in a typical spot size around 140150 µm. Microarrays were post-processed according to standard procedures (see above web sites).
Profiling changes in gene expression using the cDNA microarray
Fluorescent-labeled cDNA probes were prepared from
poly(A)+-enriched RNA samples. poly(A)+RNA samples were
prepared from total RNA samples using an oligo-dT cellulose column. All
poly(A)+RNA samples are a pool of equal quantities of RNA from 4
individuals collected at each time point. 1 µg of the
poly(A)+RNA was used as template to make a single cDNA copy of the
mRNA pool using reverse transcriptase (RT) and anchored oligo-dT15
and pdN6 random hexamer primers in the presence of amino-allyl dUTP
(see above web sites). The RNA template was removed from the completed RT
reactions by incubating at 65°C for 30 min in 0.2 mol l1
NaOH and 0.1 mol l1 EDTA. The single stranded cDNA was then
covalently linked via the amino-allyl UTP to either a Cy3 or Cy5
monoreactive dye according to the manufacturer's instructions (Amersham,
Piscataway, NJ, USA). The labeled cDNA probes were then cleaned using PCR
purification columns according to the manufacturer's instructions (Qiagen,
Valencia, CA, USA) except that the buffer PE was replaced with 80% ethanol.
The probes were prepared for hybridization according to standard procedures
(see above web sites). Briefly, the cleaned probes were brought to a final
volume of 30 µl in a solution containing 25 mmol l1 Hepes
buffer pH 7.0, 0.75 mg ml1 tRNA (Sigma), 3x SSC and
0.2% SDS. The probes were boiled for 2 min and allowed to cool at room
temperature for 5 min prior to starting the hybridizations. Probes were added
to the microarray by placing the LifterSlip (15 mmx15 mm) coverslip over
the array and using capillary action to draw the solution under the cover
slip. Hybridizations were performed at 65°C overnight in Genomic Solutions
(Ann Arbor, MI, USA) hybridization chambers. Each hybridization was performed
once for each comparison. A total number of 55 hybridizations are represented
in the data set. Two daily cycles, separated by 2 weeks, were sampled for
control conditions (26°C). Five temperature cycles were sampled for the
cycling temperature acclimation, resulting in a very consistent pattern of
gene expression during multiple temperature cycles.
Following hybridization, the arrays were briefly and gently washed to remove any unbound dye and then rapidly dried by centrifugation (www.microarray.org). Briefly, the slides were placed flat into a solution of 0.6x SSC and 0.03% sodium dodecylsulfate (SDS) and the coverslip was gently washed off the slide. The slides were then transferred to a slide rack and gently dipped 10 times in a fresh 500 ml container of the same wash solution. The slides were then transferred individually and gently dipped 10 times in a second 500 ml of wash solution containing 0.06x SSC. Following this wash the slides were dipped 5 times into 500 ml of deionized water and then spun dry in a centrifuge at low speed. The washed slides were scanned using an Axon GenePix 4000B microarray scanner (Axon Instruments, Union City, CA, USA). Data were extracted from the scanned images using GenePix 4.0 software (Axon Instruments). The data were then entered into the Stanford Microarray Database (SMD). Data filtering and sorting were accomplished within the SMD database. Upon entry into the database, all data were normalized to balance the overall levels of Cy5 and Cy3 to a 1:1 ratio using a simple correction factor applied to the Cy5 data. For each spot on each array, data were selected for analysis only if they had a Cy5/Cy3 fluorescence regression coefficient of >0.6 and had a signal intensity of 2.5 times background. These spots are termed `fair' data. This method of normalization and definition of `fair' data were the default settings in SMD.
Data analysis and presentation
Gene expression levels were determined at each time point by comparing the
amount of mRNA transcript present in the experimental sample (pooled from four
fish at each time point) compared to a reference sample (pooled from over 400
fish used in the experiment). The use of a reference sample allowed the
comparison of the relative amount of each transcript at each time point to a
common sample. Reference samples were routinely labeled with Cy3 while
experimental samples were labeled with Cy5. However, dye reversal experiments
were performed for the first two daily temperature cycles (12 samples) to
investigate possible Cy Dye bias in our data and to assess variation in the
data (Fig. 2). These dye
reversal experiments indicate a very high correlation between duplicate
hybridizations (r=0.96), for cDNA clones that experience changes in
gene expression greater than twofold compared to the reference samples
(Fig. 2).
|
Although use of a reference sample provided a common basis of comparison for each experimental sample, the data expressed in this format are not necessarily biologically relevant because each comparison is of an experimental sample compared to the mean level of each transcript that was expressed during the entire experiment. Interpretation of these data is difficult and thus we chose to further adjust the data to a biologically relevant standard. There are several avenues for adjusting data for this purpose, each of which has its own strengths and weaknesses.
A commonly used technique is to adjust the gene expression data so that the
median level of expression is equal to 0 on a log2 scale for each
spot on the array across all treatments (i.e. a 1:1 ratio); this method is
termed `median centering' (Eisen et al.,
1998). This method is logical for comparisons of different cell
types or cells under different steady state conditions, but in our opinion was
not suitable for presentation of time-course data because of the underlying
assumption that the median expression level of a given gene should be 0 on a
log2 scale. For instance, if a gene is strongly induced in all time
points sampled, this strong induction would be represented as the median level
of gene expression and would probably cause the true pattern of expression to
be largely attenuated after median centering. We observed this type of pattern
for many molecular chaperones in this study.
Another possibility, and perhaps the most logical for time-course data, is to adjust all of the expression ratios to be relative to t=0. This method assumes that the initial time point represents some steady state physiological condition in the organism that must be adjusted in response to the experimental treatment. However, gene expression data presented in this manner are dependent on high quality data for the t=0 time point. Additionally, if data are missing for the t=0 time point then it is impossible to adjust the other time points. These problems can be largely avoided by replicating the t=0 hybridizations and using the average of these replicates to adjust the rest of the data set. In our case we used the average of two hybridizations from the control (26°C, t=0 and t=336 h) to adjust the data set relative to the initial condition. One additional problem with this method is that the effects of temperature are not separated from the effects of normal daily rhythms in the gene expression data for temperature cycling. In many cases the natural rhythms in gene expression under exposure to constant 26°C were strong and masked the effects of temperature on gene expression.
To control for daily changes in gene expression that were not associated with the temperature cycle, we normalized the temperature cycling data to be relative to the control daily patterns of gene expression (an average of two daily cycles at 26°C). This operation in effect `subtracts' the daily rhythms in gene expression not due to temperature from the temperature cycling data. This operation was done by multiplying the Cy5:Cy3 ratio for each experimental time point in the cycling temperature treatment by the Cy5:Cy3 ratio for the corresponding control time point (e.g. cycling t=4 h multiplied by control t=4 h). We have named this permutation of the data `the effect of temperature'. Data presented in this manner illustrate the net effect of temperature on the natural patterns of gene expression. However, these data may be misleading if not properly presented. For instance, if there is a strong circadian rhythm in gene expression that is not affected by temperature, this will result in a flat daily expression pattern when presented in this manner, even though the gene may be changing several-fold each day. Therefore, we have chosen to present the data in two formats in this paper, relative to t=0 and after subtraction of daily rhythms, because each method of data presentation has strengths and illustrates different components of the data set.
Cross correlation analysis (Chatfield,
1989) was used to determine if gene expression patterns were
significantly correlated with the temperature cycle. Using this method it is
possible to identify the phase shift in the data that yields the highest
correlation coefficient, and thus the most significant relationship between
gene expression patterns and temperature patterns. Correlation coefficients
were identified as statistically significant at the level of 0.05.
The gene expression ratio data were clustered according to similarity in
expression pattern using Cluster software
(Eisen et al., 1998). Pearson
non-centered, complete linkage hierarchical clustering was used to organize
the data. Visualization of the clustered data was accomplished using TreeView
software (Eisen et al.,
1998
).
DNA sequencing
Microarray spots with interesting expression patterns were identified by
sequencing the cDNA insert isolated from plasmid DNA from the clone of
interest. Sequencing was accomplished using an ABI 373 sequencer with dye
terminator reaction mix. Plasmid-specific primers were used for the sequencing
reactions. All cDNAs of interest were sequenced from the 5' end to
maximize the possibility of identifying the transcript. Sequences were
identified by homology to known sequences using an NCBI Blastx search of the
GenBank database. The most significant or relevant results of these Blast
searches as well as the GenBank accession numbers for sequenced cDNA clones
presented in this paper are available in supplemental Table 1.
![]() |
Results and Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
|
Changes in gene expression may arise for a variety of reasons, some of which may not be specifically associated with changes in the activity of gene products (e.g. proteins). For instance, transcripts that are highly labile or have a very short half-life may require constant transcription to maintain physiological transcript levels, and this may be exacerbated by changes in the physical environment that destabilize or stabilize the mRNA transcripts. It is also possible to have large changes in gene transcription without changing the level of expressed protein if changes in protein or mRNA stability are associated with the experimental treatment, or if the RNA is the active gene product (antisense RNA is an example). For example, changes in gene expression may simply represent the attempt to maintain the current level of protein in the cell in the face of changes in protein translation or degradation. In this situation, if the coupling of protein degradation and transcription is tight, there may be a large change in transcript abundance without any change in protein abundance. Although in this situation the amount of transcript does not parallel the changes in protein level, it still indicates an important cellular process that must be closely regulated to maintain cellular function. This type of gene regulation may be just as important, possibly even more important, than regulation that results in changes in the protein levels. We, therefore, argue that most changes in transcript abundance, whether they reflect effects of mRNA and protein stability or adaptive alterations in protein concentrations, are likely to be important in the context of temperature acclimation, especially during the initial phases of the process.
Transcript levels do not change in response to temperature in a global
manner that would indicate large changes in rates of synthesis or degradation
of mRNAs across all genes (Fig.
3). In fact, the majority of the cDNAs (>90%) changed less than
twofold, if at all, in response to temperature, which indicates a very tight
regulation of steady state levels of mRNA transcripts during large-scale
temperature changes. Yet rates of transcription elongation in a hibernating
mammal, as measured in nuclear run-on assays, have recently been shown to have
a typical temperature sensitivity (Q1023)
(van Breukelen and Martin,
2002
). This suggests that temperature compensation in rates of
transcription should occur at the level of either transcript initiation,
degradation or both. We provide some evidence that global control of
initiation through activities of high mobility group B1 proteins (HMGB1; see
below, Fig. 3) may play an
important role in the global regulation of transcription in response to
temperature. However, it is important to note that changes in the abundance of
mRNA transcripts in a cell can occur without alterations in rates of
transcription. For instance, changes in mRNA turnover (e.g. stabilization or
destabilization of a transcript) can cause changes in mRNA levels independent
of rates of transcription. Thus, it is not safe to assume that changes in the
relative abundance of mRNA transcripts are due to changes in rates of
transcription. The nature by which specific mRNA levels are changed can only
be addressed by more detailed investigation of each transcript species using
conventional gene-specific approaches.
Diverse phase patterns in gene expression associated with the temperature cycle
There is a diversity of gene expression patterns associated with
acclimation to cycling temperatures. To examine these patterns, the gene
expression data expressed relative to t=0 were ordered according to
their phase shift relative to the temperature cycle
(Fig. 3). A clustering diagram
of the genes with expression patterns found to have a statistically
significant cross correlation with the temperature cycle is presented in
Fig. 3. Representative
expression patterns from each phase shift cluster are illustrated using line
plots in Fig. 4. These patterns
include changes in the phase pattern of gene expression as well as shifts in
the amplitude and level of expression. The relative abundances of some
transcripts are reduced when temperatures are high (ER membrane protein,
HMGB1) while others such as hydroxymethyl glutaryl coenzymeA synthase (HMG-CoA
synthase) increase. Some transcripts (myosin heavy chain) show a complex
pattern with two negative peaks occurring as a result of temperature cycling.
This pattern merges into a single negative peak associated with high
temperatures after 2 weeks of continuous temperature cycling. Other
transcripts show a clear cycling pattern with temperature and also show a
shift in overall transcript abundance (complement protein C7, apolipoprotein
E, the heat shock protein 70 kDa). Some transcripts show very little response
during the first few temperature cycles and then develop a cycling pattern
over time (unidentified clone LU07B24). Many transcripts that change in
relative abundance in response to a cycling temperature regime return to the
control pattern (e.g. unidentified clone LU05K02, HMG-CoA synthase) after 2
weeks of temperature cycling, while others develop new patterns (myosin heavy
chain, ER membrane protein). Surprisingly few genes are simply turned off or
on in response to cycling temperatures and it appears that the expression of
many genes may be altered on a hourly basis under temperature cycling
conditions.
Temperature and daily rhythms
A number of transcripts found to have temperature-dependent patterns of
expression also have strong daily rhythms under constant temperatures (Figs
3,
4). In almost all cases, these
patterns are modulated by temperature in a consistent manner. For instance,
the ER membrane protein and myosin heavy chain transcripts show opposite
patterns of expression in response to temperature compared to the normal daily
rhythm. These data indicate that natural daily rhythms of expression are
likely to be strongly modulated by the temperature cycle in A.
limnaeus. Some of the rhythms observed under control conditions may be a
consequence of the feeding regime used during the study (fish were fed once
daily at 09:00 h). This hypothesis is supported by the number of transcripts
associated with energy metabolism (e.g. lipid and glucose metabolism) that
exhibit strong daily rhythmic patterns under control and temperature cycling
conditions (Fig. 5). It has
recently been reported that circadian rhythms observed in mammalian liver can
be entrained to the feeding cycle, independent of the light cycle
(Stokkan et al., 2001). Our
data suggest that daily rhythms of gene expression under natural conditions
are likely to be the result of multiple environmental and nutritional inputs
in the liver and that variation in environmental temperature is likely to have
a strong influence on this integrated response.
Daily versus long-term gene expression responses to temperature: general principles and background data
The majority of laboratory temperature acclimation experiments force
constant conditions upon organisms that typically occur in thermally variable
environments in which daily changes in temperature occur. The need to study
such short-term thermal fluctuations is apparent based on the findings of
studies that have shown that acclimations to fluctuating and constant thermal
environments result in different physiological phenotypes
(Lowe and Heath, 1969;
Feldmeth et al., 1974
;
Otto, 1974
;
Shrode and Gerking, 1977
;
Woiwode and Adelman, 1992
;
Heath et al., 1993
). Most of
these studies focused on thermal tolerance or thermal preference. In almost
all cases, acclimation to fluctuating environments resulted in a higher
thermal tolerance or an increased range of thermal tolerance compared to
acclimation to constant conditions that approximated the mean temperature of
the fluctuating acclimation. These data indicate that the physiological state
of a fish exposed to fluctuating temperatures is indeed unique when compared
to fish acclimated to constant environments. Gene expression data presented in
this paper support the general conclusion that constant and fluctuating
environments elicit different transcriptional and likely physiological
responses.
The different responses in gene expression during acclimation to constant and fluctuating temperatures discussed below may have broad implications for other species of aquatic organisms that live in both constant and fluctuating environments. For instance, many marine intertidal organisms spend part of their day in the relatively thermally stable conditions of the ocean, and other parts of the tidal cycle exposed to air and more variable temperatures. Much of what is known about the temperature biology of these species is from acclimations to constant conditions, and a very different perspective might be gained from looking at acclimation to daily fluctuations in temperature. Additionally, the differences in transcriptional responses observed in constant versus fluctuating temperatures may indicate differences in organismal responses to daily versus seasonal changes in temperature. While there are likely to be daily fluctuations in temperature during all seasons, the mean temperature levels will be likely to change, as will the amplitude of the fluctuation. Constant acclimation regimes may mimic seasonal changes in daily mean temperature and thus may be eliciting changes in gene expression associated with adjustments needed for long-term survival or for seasonal changes in reproduction and feeding. In contrast, large-scale fluctuation in temperature on a daily basis may require more immediate changes in gene expression that are required for short-term survival and thus the fish respond via more temporary mechanisms that are not associated with long-term adjustments in physiology.
Gene expression grouped by cellular function
In order to explore the biochemical and molecular pathways that are
affected by temperature on either daily or long-term time scales we organized
the data according to cellular functions
(Fig. 5). Fig. 5 illustrates the
diversity of cellular pathways that are affected by temperature at the
transcriptional level. For each cellular function we discuss the changes in
transcription that we feel are most instructive for evaluating the effects of
temperature on the function in question. By placing focus on a subset of the
transcriptional changes we do not intend to imply that other changes in gene
expression are without significance for the process in question.
Molecular chaperones
Upon initial exposure to temperature cycling, a number of molecular
chaperones are strongly induced (Fig.
5A). However, the transcript levels of most of these chaperones
return to control levels after 2 weeks of temperature cycling. Transcripts of
the small heat-shock proteins Hsp27 and Hsp22 are strongly induced (four- to
fivefold induction) by the initial temperature cycles whereas the larger
heat-shock proteins Hsc70 and Hsp90 are only mildly induced (>twofold)
after several temperature cycles. However, transcripts encoding for Hsc70 and
Hsp90 are strongly induced by chronically elevated temperatures. These
differences in the kinetics of induction among different classes of heat-shock
proteins indicate a complex transcriptional response to temperature cycling
that is distinct from constant exposure to elevated temperatures. Transcripts
for the other major types of molecular chaperones, such as protein disulfide
isomerase (PDI) or calreticulin, which are initially induced by temperature
cycling, are also induced and maintained by exposure to 37°C. These data
taken together suggest that for A. limnaeus chronic high temperatures
may be more `stressful', i.e. cause more protein damage, than exposure to
constantly changing temperatures. This conclusion is consistent with the
variable natural habitat in which the fish are found to thrive
(Fig. 1A). The apparent
importance of the small heat-shock proteins to the survival of A.
limnaeus in its thermally variable and extreme desert habitat is in
agreement with the data of Hightower et al.
(Norris et al., 1997;
Hightower et al., 1999
) for
the survival of desert fishes from Mexico. These authors suggest that Hsp27
may play a role in signal transduction to the cytoskeleton during temperature
stress (Norris et al.,
1997
).
Cholesterol and fatty acid synthesis membrane structure
The maintenance of membrane integrity (homeoviscous and homeophasic
adaptation) is known to be a crucial part of the acclimatory response to
temperature and to involve major alterations in the lipid compositions of
membranes (Hazel, 1995;
Hochachka and Somero, 2002
).
Thus, we predicted that a number of genes related to lipid biosynthesis would
alter their expression in response to fluctuating or long-term acclimatory
temperatures. Indeed, this prediction was fulfilled
(Fig. 5B). Two transcripts, one
for a
6-fatty acyl desaturase and the other for a polyunsaturated fatty
acid elongase, were found to be induced by constant acclimation to 20°C
and repressed by chronic exposure to 37°C. If these changes in transcript
levels are reflected in protein levels, then these data are completely
consistent with homeoviscous adaptation theory, which predicts an increase in
long-chain polyunsaturated fatty acids at lower temperatures. However, these
two transcripts are not strongly regulated during exposure to cycling
temperatures. It appears that membrane restructuring during temperature
cycling may be accomplished by alternate means.
Insertion of cholesterol into lipid bilayers has multiple effects on
membrane structure, and, in general, increased levels of cholesterol are
associated with increased temperatures
(Robertson and Hazel, 1997).
The relative abundance of a transcript for an enzyme in the cholesterol
biosynthetic pathway, 3-hydroxy-3-methylglutaryl-CoA synthase (HMG-CoA
synthase) (cytoplasmic form), is strongly and positively correlated with the
temperature cycle (Figs 3,
4,
5). This suggests a role for
cholesterol in the maintenance of membrane integrity during temperature
cycling. After 2 weeks of cycling, the expression levels of the HMG-CoA
synthase transcript return to control levels. This return to control levels of
transcripts after 2 weeks of temperature cycling suggests that either a new
steady state level of cholesterol has been achieved that is sufficient to
maintain membrane integrity in the face of temperature cycling, or that other
mechanisms, such as changes in the content of polyunsaturated fatty acids, may
be employed during extended periods of exposure to cycling temperatures.
The pattern of HMG-CoA synthase transcript appears to have a daily rhythm
that may be associated with the daily feeding pattern (see discussion above).
HMG-CoA synthase transcript levels are highest about 3.5 h after feeding (at
12:30 h) under control conditions (26°C,
Fig. 4). However, during
temperature cycling, levels of this transcript peak strongly 8 h after feeding
(4 h after peak temperature) and are highly correlated with the first four
temperature cycles. It is worth noting that regulation of cholesterol
biosynthesis is typically attributed not to HMG-CoA synthase but to HMG-CoA
reductase. In this study transcript levels of HMG-CoA reductase are slightly
induced during chronic cold acclimation (20°C) and repressed during
acclimation to chronic temperature elevation (37°C), suggesting the lack
of an appropriate transcriptional response to temperature that would be
consistent with the role of cholesterol in current homeoviscous adaptation
theory (Robertson and Hazel,
1997; Zehmer and Hazel,
2003
). However, this enzyme is known to be regulated by allosteric
and post-translational modifications and may not require a transcriptional
response to effect a change in gene activity. The many biological roles of
cholesterol in organismal physiology, and the complex control of sterol
synthesis, suggest that the expression pattern of this gene is a result of the
interplay between many converging pathways.
The expression pattern of the transcript encoding adipose
differentiation-related protein (ADRP, Fig.
5B) provides additional evidence that cholesterol is probably
important for the maintenance of membrane integrity during temperature
cycling. When transcript levels of HMG-CoA synthase are high, ADRP transcript
levels are low. Increased mRNA levels of ADRP are associated with increased
storage of cholesterol and polyunsaturated fatty acids (PUFA) in lipid
droplets of mammalian cells (Atshaves et
al., 2001; Brown,
2001
). ADRP binds tightly to cholesterol and is thought to be a
critical regulator of cholesterol and PUFA storage and release from lipid
droplets (Brown, 2001
). Thus,
decreased levels of ADRP mRNA transcripts would likely lead to the
mobilization of cholesterol and PUFA stores for transport to the plasma
membrane.
Recent studies suggest that the plasma membrane is organized into discrete
lipid and lipid/protein domains. (Ikezawa,
2002; Morandat et al.,
2002
). The glycosylphosphatidylinositol (GPI)-anchored proteins
are associated with specific plasma membrane subdomains called membrane
`rafts', which are rich in cholesterol and sphingolipids
(Ikezawa, 2002
;
Morandat et al., 2002
). These
rafts are thought to be critical sites for many membrane-associated functions
including cellular signaling. We observed a strong induction of transcripts
for the GPI-anchored membrane protein p137 during exposure to chronically
elevated temperatures, and a mild induction after several temperature cycles.
These data suggest that increases in membrane raft proteins may play a role in
the stabilization of the plasma membrane rafts and the maintenance of membrane
functions during exposures to elevated temperatures. Recent studies suggest
that homeoviscous adaptation of plasma membranes may occur primarily in these
rafts and that cholesterol plays an especially important role in adjusting the
physical properties of the rafts (Zehmer
and Hazel, 2003
). Thus our data support a role for both raft
proteins and lipids in the adaptation of membranes to temperature.
Solute carriers
A number of transcripts that encode solute transporters and transmembrane
proteins have strong daily expression rhythms that are not strongly modulated
by temperature (Fig. 5C). These
genes include aquaporin 1, and solute carriers found in the plasma membrane as
well as in mitochondrial membranes. These genes seem to be temperature
independent in their transcriptional regulation across a wide range of
temperatures. The reason for this strong daily rhythm and temperature
independence is not known, but may be due to action of the proteins encoded by
these transcripts in the digestion and assimilation of food. For instance,
aquaporins have recently been identified as being important for proper
secretion of bile in hepatocytes (Huebert
et al., 2002). The protein encoded by the gene for solute carrier
family 3, member 2 (SLC3A2) is thought to be an amino acid transporter with
high affinity (µmol l1 range) for dibasic and
zwitterionic amino acids (Palacin et al.,
1998
). Anion transport function similar to that of the band 3
anion transporter from mammalian erythrocytes has been found in kidney tubules
and may be important in solute transport across kidney tubules. Perhaps a
similar function is required for transport and secretion of substances by
hepatocytes during digestion.
Carbohydrate metabolism
Glucose is an important fuel source for many cell types in vertebrates and
is supplied largely through the circulatory system. The liver plays an
essential role in blood glucose homeostasis by balancing uptake and release of
glucose (Nordlie et al.,
1999). Changes in transcript levels for a number of genes critical
for regulation of carbohydrate metabolism and blood glucose concentrations
occur in response to temperature. Notably, glucokinase has a highly variable
expression pattern that is nearly identical to that for another enzyme
critical to gluconeogenesis, phosphoenolpyruvate carboxykinase
(Fig. 5D). These genes are
almost always expressed in parallel during temperature cycling and,
importantly, are almost always expressed in an opposite manner to
glucose-6-phosphatase, the major regulator of glucose transport from cells
into the bloodstream. Glucokinase has also been shown to play a role in the
regulation of glucose metabolism and is often found in the nucleus of cells,
where it is thought to act as a glucose sensor. The regulation of glucokinase
and glucose-6-phosphatase is very complex and includes many effectors
(Nordlie et al., 1999
). Gene
expression data from the present study indicate that blood glucose levels are
likely to be highly responsive to nutritional status and strongly affected by
temperature.
Two additional transcripts that encode for enzymes that are important regulators of glucose and glycogen metabolism, glycogen synthase and pyruvate kinase, show different responses to acclimation to chronic high temperatures, but do not exhibit strong changes in transcript levels during temperature cycling. The increase in glycogen synthase transcripts and decrease in pyruvate kinase transcripts during acclimation to 37°C would indicate that glycogen synthesis should be favored during acclimation to chronic high temperatures. The absence of a strong transcriptional response in these transcripts during temperature cycling is not surprising considering the many post-translational mechanisms for regulating these proteins on short time scales.
Intermediary metabolism
The transcript levels of carbonic anhydrase and creatine kinase genes
appear to be affected by temperature in a similar manner
(Fig. 5E). These proteins have
both been implicated in the regulation of cellular energetics through their
contributions to phosphotransfer networks that can act to couple spatially
separated ATP-consuming and ATP-producing metabolic pathways
(Dzeja and Terzic, 2003). The
transcripts for these genes are both mildly upregulated after the coldest part
of the temperature cycle (near t=0,
26°C), when compared to
the normal circadian expression pattern. This may indicate a need to increase
the capacity of the phosphotransfer networks during cold periods in the face
of continually changing environmental temperatures in order to maintain tight
coupling of catabolic and anabolic processes.
The pentose phosphate shunt enzyme 6-phosphogluconate dehydrogenase appears
to be strongly affected by temperature cycling during the first three
temperature cycles. This transcript is upregulated when compared to the normal
daily expression pattern at 26°C, but is downregulated during acclimation
to 37°C (Fig. 5E). Previous
studies indicate that the activity of this enzyme is responsive to temperature
acclimation, being upregulated during exposure to reduced temperatures
(Seddon and Prosser, 1997).
Increased activity of the pentose phosphate shunt would be expected to support
increased biosynthesis of fatty acids by providing reducing equivalents for
biosynthetic reactions. Others have suggested a link between pentose phosphate
shunt activity and antioxidant protection via glutathione
(Winkler et al., 1986
).
However, in our study, expression of at least one enzyme involved in
glutathione-based detoxification of oxygen radicals,
glutathione-s-transferase, is not similar to that for 6-phosphogluconate
dehydrogenase, which suggests that expression of the latter is more likely to
be involved in control of biosynthesis and overall redox balance in the
cytoplasm and not responsive to oxidative damage per se. Additional
support for this conclusion comes from expression patterns of the cytosolic
isoform of isocitrate dehydrogenase. This enzyme has been found to play an
important role in defense against oxidative stress in cultured NIH3T3 cells
(Lee et al., 2002
). Transcript
levels for this enzyme are downregulated during temperature cycling and during
acclimation to 37°C, and upregulated during acclimation to 20°C. This
transcriptional response is much more consistent with temperature compensation
of metabolic function than a need to cope with oxidative damage.
Dihydropyrimidine dehydrogenase catalyzes the rate-limiting step in
pyrimidine catabolism, converting uracil to 5,6-dihydrouracil (KEGG website,
http://www.genome.ad.jp/kegg/).
This conversion eventually yields ß-alanine or a number of other
pyrimidine-derived metabolites. The transcript level of dihydropyrimidine
dehydrogenase is upregulated strongly after repeated temperature cycling
(Fig. 5E). The upregulation of
this transcript could indicate an increased need for the metabolism of
pyrimidines due to increased turnover of RNA and DNA, perhaps even due to cell
damage after repeated temperature cycling. An alternative hypothesis is that
temperature cycling induces the production of ß-alanine as an organic
osmolyte. ß-alanine is a known organic osmolyte in prokaryotes and
various animal lineages, including marine elasmobranchs
(Hochachka and Somero, 2002).
It is possible that accumulation of organic osmolytes (see discussion below)
could help to mediate temperature stress by stabilizing protein structure in
the face of fluctuating temperatures.
Nitrogen metabolism
A number of transcripts that encode for proteins in nitrogen metabolism are
differentially regulated during acclimation to constant and fluctuating
temperatures (Fig. 5F). The
transcript for betaine homocysteine methyltransferase is downregulated under
constant cold temperatures and upregulated under constant warm temperatures
(Fig. 5F). Levels of this
transcript are highly variable under temperature cycling conditions. These
data may indicate that methylamine metabolism is important for temperature
acclimation, and suggest that levels of methylamines may be elevated at high
temperatures and reduced at low temperatures, which would be consistent with
data emerging that indicate that methylamines, especially glycine betaine, can
act as `chemical chaperones' and have a stabilizing effect on proteins during
exposures to combined high salt and temperature stress in E. coli
(Diamant et al., 2001). These
authors suggest that organic osmolytes, especially glycine betaine and, to
some extent, proline, may regulate the activity of macromolecular chaperones
such as the major heat-shock proteins. Interestingly, levels of transcripts
for the proteins arginase and ornithine aminotransferase are also elevated
during acclimation to 37°C and temperature cycling. These enzymes are both
involved in proline biosynthesis (KEGG website,
http://www.genome.ad.jp/kegg/).
We predict, based on these data, that proline and glycine betaine levels are
likely to increase during acclimation to chronic high temperatures and cycling
temperatures. Elevated levels of organic osmolytes may help to offset the need
for molecular chaperones on a long-term basis and may also explain why
transcript levels of heat-shock proteins return to control values after
several temperature cycles. The use of organic osmolytes to enhance protein
stability would seem to be an economical way to deal with variable
environmental conditions without continually mounting a heat-shock response.
We note that protein-stabilizing methylamine solutes have been shown to
accumulate to high concentrations in deep-sea fishes and invertebrates and to
be effective in counteracting the destabilizing effects of high pressure on
protein structure and function (Yancey et
al., 2002
).
Cytoskeletal elements and contractile proteins
A number of genes that encode cytoskeletal proteins and proteins involved
in contractile functions are variably expressed in relation to temperature
(Fig. 5G). The mRNA transcript
for -tubulin appears to be especially variable during temperature
cycling. Transcripts for myosin heavy chain and light chain are also strongly
affected by temperature and share almost identical expression patterns. The
reasons for these expression patterns are not yet clear, but may be related to
a need to stabilize the cytoskeleton in response to changing temperatures.
This hypothesis is supported by the increased levels of expression for ficolin
1 and other actin binding proteins as well as microtubule associated proteins.
These data should indicate that normalization of mRNA levels to cytoskeletal
genes such as tubulin, a standard procedure, can likely result in misleading
or false interpretation of mRNA levels in situations of fluctuating
temperatures.
Protein turnover
Acclimation to constant low or high temperatures appears to induce
alterations in transcription that may affect levels of protein synthesis and
degradation (Fig. 5H). Two
translation elongation factors, a tRNA synthase, and at least one ribosomal
protein all have increased levels of expression, while there is a slight
decrease in the amount of transcript for a regulatory subunit of the 26S
proteosome (part of the ubiquitin-dependent proteolysis system) in response to
chronic elevated temperatures. These data suggest an increase in protein
turnover during exposure to chronic high temperatures, and an attempt by the
organism to maintain protein levels by increasing the capacity for protein
synthesis and decreasing the capacity for protein degradation. During
acclimation to cold conditions, there is a strong upregulation of the
regulatory subunit of the 26S proteosome, but transcript levels for proteins
involved in the protein synthetic machinery remain unchanged or are slightly
downregulated after 2 weeks of acclimation. Temperature cycling appears to
elicit a very weak induction of transcripts for proteins involved in protein
synthesis. In contrast, transcript levels of regulatory subunit for the 26S
proteosome appear to be highly responsive to temperature cycling, and may
indicate that regulation of protein degradation is critical during short-term
fluctuations in temperature. These data on key components of the protein
turnover machinery indicate that certain aspects of protein turnover are
likely to be regulated at the transcriptional level during temperature
acclimation, and the response to constant conditions is unique when compared
to those for exposures to temperature cycling.
The acute phase response, complement and innate immunity
Several transcripts that encode for proteins involved in the acute phase
response are differentially regulated during temperature acclimation
(Fig. 5I). Many of the
components of the acute phase response are initially upregulated during
temperature cycling and then downregulated after 5 days of cycling. These
transcripts are also strongly upregulated by exposures to chronic high
temperatures and more weakly to acclimation to 20°C. While these results
may appear inconsistent initially, upon closer examination they are consistent
with what is known about the acute phase response and, in particular, what is
known about the complement proteins in fish.
The complement proteins are a major part of the innate immune system of all
vertebrates (Sunyer and Lambris,
1998). Complement proteins are known effectors of the inflammation
response to tissue damage and infection, and activation of the complement
pathway results in the marking of target cells (opsonization) with complement
proteins, activation of leucocytes, and lysis of target cells via the
formation of a membrane attack complex (MAC) comprising complement proteins
that self-insert into the plasma membrane
(Roitt et al., 1993
). The
activity of complement proteins and the marking of target cells are largely
regulated by the activation of the C3 complement protein through two
alternative pathways. One of these pathways, the alternate pathway, is
regulated by the hydrolysis of a thiol-ester bond within the C3 protein
itself, by the C3 convertase enzyme. This bond is known to react with water
spontaneously at a low level, so that this pathway is always slightly
activated (Roitt et al.,
1993
). The activation of C3 and thus the complement pathway are
amplified by a positive feedback loop that is regulated largely by the
presence or absence of a non-self surface for opsonization. Complement
proteins can bind to both self and non-self surfaces but are retarded from
binding to self surfaces by specific proteins. The activation of the
complement pathway has been shown to contribute to tissue damage after
ischemic injury to cardiac tissues (Roitt
et al., 1993
), which indicates that the complement pathway must be
carefully regulated to function in the immune response without causing major
damage to self tissues.
The initial upregulation of transcripts encoding several complement
proteins upon exposure to high or cycling temperatures may be the result of an
increased activation of the complement pathway via spontaneous
activation of the C3 protein due to increased thermal energy, or via
signals originating from tissue damage. In either case, the response would be
counterproductive in the long-term, and is downregulated after several
temperature cycles in the fluctuating acclimation regime. However, high levels
of transcript are maintained during exposure to chronic high temperature,
which may be a sign of continued tissue damage, or a maladaptive immune
response similar to that observed following ischemia
(Roitt et al., 1993). The
slower upregulation kinetics of complement protein transcripts during cold
acclimation is probably a temperature compensatory mechanism to boost innate
immune function, which is consistent with earlier findings that the classical
immune response (antibody mediated) is attenuated in fish at low temperatures
(Bayne and Gerwick, 2001
).
There is also evidence suggesting that gene expression patterns associated
with liver regeneration and the acute phase response are similar
(Milland et al., 1990). It is
possible that the initial exposure to temperature cycling and chronic exposure
to high temperatures induced cellular damage and cell death in a subpopulation
of liver cells and the activation of complement proteins is in response to
cellular damage. Other evidence supporting the possibility of conditions
causing cell damage is the upregulation of haptoglobin gene expression, which
is known to be important in binding and scavenging hemoglobin from ruptured
red blood cells (Dobryszycka,
1997
).
Cell growth and proliferation
A number of transcripts that encode proteins that regulate cell growth and
proliferation have changing expression patterns during acclimation to constant
and cycling temperatures (Fig.
5J). For instance, two tumor suppressor genes, arginine-rich
protein (ARP; Shridhar et al.,
1997) and quiescin Q6 (Coppock
et al., 1998
), are induced by high temperatures, with ARP strongly
induced during the initial temperature cycles and quiescin Q6 slowly induced
after several cycles. Quiescin Q6 is strongly induced during exposure to
chronic high temperatures, while ARP is only weakly induced. Quiescin Q6 has
been shown to be strongly induced during entry into reversible cellular
quiescence in mammalian cells and is expressed at very low levels in actively
proliferating cells (Coppock et al.,
1998
). These data suggest that cell proliferation is probably
arrested during temperature cycling and during exposure to chronic high
temperatures, but perhaps through different pathways. The transcript for a
putative oncogene, Mig-6 (Makkinje et al.,
2000
; Tsunoda et al.,
2002
), known to be critical to stress-activated protein kinase
signaling (SAPK/JNK; Makkinje et al.,
2000
) also appears to be regulated by temperature. Mig-6 is
induced during the first temperature cycle, but has a highly variable
expression pattern in general. There is evidence that Mig-6 may be involved in
the sustained activation of SAPK/JNK-induced changes in gene expression
(Makkinje et al., 2000
). This
sustained activation leads to cellular hypertrophy due to increased cell
growth but not cell division in some mammalian chronic diseases. The variable
expression pattern of the Mig-6 transcript during temperature cycling may be a
way to carefully titer the activity of the SAPK/JNK signaling pathways and
thus avoid the problems associated with chronic activation of this pathway.
The relative abundance of TIEG-1 mRNA, which encodes a TGF-ß early
response gene (Cook and Urrutia,
2000
; Hefferan et al.,
2000
) decreases during the initial temperature cycles. TIEG-1 mRNA
has been shown to be rapidly induced by TGF-ß signaling and is generally
associated with a decrease in cell growth and proliferation in pancreas cells
(Cook and Urrutia, 2000
). The
data presented here indicate that TGF-ß signaling is probably not
initially activated by temperature cycling, but may be activated by chronic
exposure to cold temperatures (20°C) and during the cold parts of the
daily temperature cycle (Fig.
5J). Anintegrated view of the above data suggests that temperature
cycling activates the SAPK/JNK pathway and represses TIEG-1 expression,
leading to increased cellular growth, while induction of ARP and quiescin Q6
indicates a cessation of cellular proliferation. These data suggest that
different parts of the cell growth and proliferation cycle may be entrained to
temperature. The partitioning of different parts of the cell cycle into
different temperature conditions may have profound influences on the
energetics and physiology of organisms exposed to cycling temperatures in
nature, and may dictate when complex behaviors such as gamete synthesis or
reproduction are favorable.
Unknown transcripts
A number of cDNAs that have no homology to known sequences or have unknown
function were identified as responsive to temperature acclimation in this
study (Fig. 5K). These cDNAs
may represent critical parts of the acclimation response that have not yet
been identified or studied. Further interrogation of these sequences and their
expression patterns in response to temperature and other environmental factors
is likely to result in the discovery of new genes and gene functions that are
critical for survival of environmental variation.
Global regulation of transcription
The high mobility group protein HMGB1 transcript exhibits one of the most
striking patterns of gene expression associated with cycling temperatures
(Figs 3,
4,
5J). The relative abundance of
this transcript is highly negatively correlated with temperature
(Fig. 4). The HMGB1 transcript
changes over tenfold during the daily temperature cycle and both the pattern
and magnitude of the expression are consistent over the entire 2-week period
of temperature cycling. Further, this transcript does not show any changes in
expression on a daily basis under constant temperature conditions. The unique
properties of the HMGB1 protein, coupled with the expression pattern presented
in this paper, lead us to propose that the HMGB1 protein may be a critical
part of a compensatory transcriptional response to temperature and may indeed
be a highly sensitive temperature sensor.
The HMGB1 protein is in many ways the perfect candidate as an immediate
effector of transcription in response to temperature. HMGB1 is a small (28
kDa) and abundant protein that is highly conserved and ubiquitous among the
vertebrates (Wolffe, 1999;
Thomas and Travers, 2001
).
HMGB1 can bind DNA in a structure-specific manner with a preference for single
stranded, bent or supercoiled structures
(Hamada and Bustin, 1985
;
Stros, 2001
;
Thomas and Travers, 2001
). It
has been shown to partner with many important transcription factors such as
p53, HoxD9 and steroid hormone receptors through specific interaction domains
(Wolffe, 1999
;
Thomas and Travers, 2001
). The
protein is also very `sticky' in nature and is able to bind to a variety of
other proteins, including cytoskeletal elements and extracellular matrix
proteins, and to various classes of lipids
(Einck and Bustin, 1985
). It
is generally agreed that HMGB1 has an integral role in assembly of numerous
nucleoprotein complexes that are critical to cell function such as V(D)J
recombination and the formation of enhanceosome complexes
(Stros and Reich, 1998
;
Wolffe, 1999
;
Ellwood et al., 2000
;
Thomas and Travers, 2001
).
HMGB1 is known to increase the affinity of the TATA binding protein TBPII for
the TATA box by over 20-fold (Das and
Scovell, 2001
). Overexpression of HMGB1 in mammalian cell lines
results in a global stimulation of transcription (gene- and
polymerase-independent) that is associated with a generalized decondensation
of chromatin structure (Aizawa et al.,
1994
; Ogawa et al.,
1995
). Additionally, injection of antibodies against HMGB1
inhibits transcription in Xenopus oocytes
(Ogawa et al., 1995
). These
data taken together indicate a key role for HMGB1 in the global regulation of
transcription.
The thermal stability and biochemical properties of HMGB1 protein suggest
that the protein should be very sensitive to temperature in vivo.
HMGB1 has a very broad thermal melting curve under dilute acidic conditions
(Ramstein et al., 1999). The
protein begins to melt at 20°C and is not completely denatured until
65°C, giving the protein a melting range of over 40°C. This broad
melting range is likely due to the differing thermal stabilities of different
domains within the protein (Ramstein et
al., 1999
). This point is critical because it indicates that one
part of the protein may be stable and functional while the other part is
denatured at physiologically relevant temperatures near 37°C.
Additionally, these proteins may be post-translationally modified
(Einck and Bustin, 1985
) by
the addition of several moieties, and the thermal stability of the protein can
be modulated by as many as 5°C by these modifications
(Stemmer et al., 2002
). This
property would allow for seasonal adjustments in the thermal stability of the
HMGB1 protein. We hypothesize that the melting of this protein at
physiologically relevant temperatures disrupts the ability of the HMGB1
protein to maintain the nucleoprotein complexes associated with transcription
initiation and causes a global change in the rate of transcription, especially
for those genes that contain a TATA box in their promoter. This mechanism is
hypothesized to be important for modulating the level of transcription in a
very general manner, while still allowing for specific changes in gene
expression to be induced or repressed by regulatory transcription factors or
enhancers and silencers. The patterns of transcript abundance presented in
this report are consistent with this theory if the HMGb1 gene is
autoregulated by its own activity. This is likely to be the case since the
hypothesized mechanism is global and not gene specific. Additionally, in order
for this model to work, HMGb1 transcripts need to have a very short
half-life in the cell. Our data are consistent with a high turnover rate for
this transcript in vivo, simply because a stable transcript would
probably not show such large fluctuations in relative abundance on an hourly
basis. Interestingly, the 3'UTR of the HMGB1 transcript is highly
conserved among all vertebrates (Bustin et
al., 1990
), which strongly suggests a regulatory role because
3'UTR regions are classically highly variable.
We have identified the HMGB1 protein as a putative global regulator of
transcription in response to temperature. If this hypothesis is supported by
additional studies of protein function, this model could help resolve many
unexplained phenomena associated with temperature acclimation. For example,
seasonal shifts in thermal tolerance may be associated with changes in
post-translational modification of the HMGB1 protein. The replacement of the
linker histone H1 with HMGB1 during early development
(Nightingale et al., 1996;
Ner et al., 2001
) may also
explain the extreme temperature sensitivity of early embryos due to a loss of
chromatin architecture, as HMGB1 proteins are easily denatured at biologically
relevant temperatures. We believe that further investigations into the role of
HMGB1 in temperature acclimation are likely to lead to a new understanding of
how eukaryotic cells maintain homeostasis in the face of an ever-changing
thermal environment.
In conclusion, these studies illustrate the utility of cDNA microarray
approaches in both hypothesis-driven and `discovery-based' experimentation in
environmental physiology (Gracey and
Cossins, 2003). In the former context, microarray studies can
unravel the alterations in gene expression that are conjectured to underlie
known physiological responses to temperature, e.g. in expression of heat-shock
proteins and in the restructuring of cellular membranes. Of equal, if not
greater, importance in microarray studies is the discovery of new facets of
physiological responses that are not anticipated by the investigator, for
instance potential global regulators of environmentally induced gene
expression and interplay between normal circadian patterns of gene expression
and alterations in gene expression made in response to fluctuations in
temperature. Microarray technologies thus allow a type of exploration in
`molecular natural history' (Brown and
Botstein, 1999
) that seems certain to open up critical new areas
for study in ecological and evolutionary physiology
(Feder and Mitchell-Olds,
2003
).
![]() |
Acknowledgments |
---|
We dedicate this paper to the memory of Dr Peter W. Hochachka in recognition of his contributions to the study of biochemical adaptation to the environment.
![]() |
Footnotes |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Aizawa, S., Nishino, H., Saito, K., Kimura, K., Shirakawa, H. and Yoshida, M. (1994). Stimulation of transcription in cultured cells by high mobility group protein 1: Essential role of the acidic carboxyl-terminal region. Biochemistry 33,14690 -14695.[Medline]
Atshaves, B. P., Storey, S. M., McIntosh, A. L., Petrescu, A.
D., Lyuksyutova, O. I., Greenberg, A. S. and Schroeder, F.
(2001). Sterol carrier protein-2 expression modulates protein and
lipid composition of lipid droplets. J. Biol. Chem.
276,25324
-25335.
Bailey, R. G. (1972). Observations on the biology of Nothobranchius guentheri (Pfeffer) (Cyprinodontidae), an annual fish from the coastal region of east Africa. Afr. J. Trop. Hydrobiol. Fish. 2,33 -43.
Bayne, C. J. and Gerwick, L. (2001). The acute phase response and innate immunity of fish. Dev. Comp. Immun. 25,725 -743.[CrossRef][Medline]
Brown, D. A. (2001). Lipid droplets: Proteins floating on a pool of fat. Curr. Biol. 11,R446 -R449.[CrossRef][Medline]
Brown, P. O. and Botstein, D. (1999). Exploring the new world of the genome with DNA microarrays. Nat. Genet. 21,33 -37.[CrossRef][Medline]
Bustin, M., Lehn, D. A. and Landsman, D. (1990). Structural features of the HMG chromosomal proteins and their genes. Biochim. Biophys. Acta 1049,231 -243.[Medline]
Chatfield, C. (1989). The Analysis of Time Series: An Introduction. New York, Chapman and Hall.
Cheng, S., Fockler, C., Barnes, W. M. and Higuchi, R. (1994). Effective amplification of long targets from cloned inserts and human genomic DNA. Proc. Natl. Acad. Sci. USA 91,5695 -5699.[Abstract]
Cook, T. and Urrutia, R. (2000). TIEG proteins join the Smads as TGF-ß regulated transcription factors that control pancreatic cell growth. Am. J. Physiol. 278,G513 -G521.
Coppock, D. L., Cina-Poppe, D. and Gilleran, S. (1998). The quiescin Q6 gene (QSCN6) is a fusion of two ancient gene families: Thioredoxin and ERV1. Genomics 54,460 -468.[CrossRef][Medline]
Das, D. and Scovell, W. M. (2001). The binding
interaction of HMG-1 with the TATA-binding protein/TATA complex. J.
Biol. Chem. 276,32597
-32605.
Diamant, S., Eliahu, N., Rosenthal, D. and Goloubinoff, P.
(2001). Chemical chaperones regulate molecular chaperones in
vitro and in cells under combined salt and heat stress. J.
Biol. Chem. 276,39586
-39591.
Dobryszycka, W. (1997). Biological functions of haptoglobin new pieces to an old puzzle. Eur. J. Clin. Chem. Clin. Biochem. 35,647 -654.[Medline]
Dzeja, P. P. and Terzic, A. (2003).
Phosphotransfer networks and cellular energetics. J. Exp.
Biol 206,2039
-2047.
Einck, L. and Bustin, M. (1985). The intracellular distribution and function of the high mobility group chromosomal proteins. Exp. Cell Res. 156,295 -310.[Medline]
Eisen, M. B., Spellman, P. T., Brown, P. O. and Botstein, D.
(1998). Cluster analysis and display of genome-wide expression
patterns. Proc. Natl. Acad. Sci. USA
95,14863
-14868.
Ellwood, K. B., Yen, Y.-M., Johnson, R. C. and Carey, M.
(2000). Mechanism for specificity by HMG-1 in enhanceosome
assembly. Mol. Cell. Biol.
20,4359
-4370.
Feder, M. E. and Hofmann, G. E. (1999). Heat-shock proteins, molecular chaperones, and the stress response: evolutionary and ecological physiology. Annu. Rev. Physiol. 61,243 -282.[CrossRef][Medline]
Feder, M. E. and Mitchell-Olds, T. (2003). Evolutionary and ecological functional genomics. Nat. Rev. Genet. 4,649 -655.[CrossRef]
Feldmeth, C. R., Stone, E. A. and Brown, J. H. (1974). An increased scope for thermal tolerance upon acclimating pupfish (Cyprinodon) to cycling temperatures. J. Comp. Physiol. 89,39 -44.
Fujita, J. (1999). Cold shock response in mammalian cells. J. Mol. Microbiol. Biotechnol. 1, 243-255.[Medline]
Gracey, A. Y. and Cossins, A. R. (2003). Application of microarray technology in environmental and comparative physiology. Annu. Rev. Physiol. 65,231 -259.[CrossRef][Medline]
Hamada, H. and Bustin, M. (1985). Hierarchy of binding sites for chromosomal proteins HMG1 and 2 in supercoiled deoxyribonucleic acid. Biochemistry 24,1428 -1433.[Medline]
Hazel, J. R. (1995). Thermal adaptation in biological membranes- is homeoviscous adaptation the explanation? Annu. Rev. Physiol. 57,19 -42.[CrossRef][Medline]
Heath, A. G., Turner, B. J. and Davis, W. P. (1993). Temperature preferences and tolerances of three fish species inhabiting hyperthermal ponds on mangrove islands. Hydrobiologia 259,47 -55.
Hefferan, T. E., Subramaniam, M., Khosla, S., Riggs, B. L. and Spelsberg, T. C. (2000). Cytokine-specific induction of the TGF-ß inducible early gene (TIEG): regulation by specific members of the TGF-ß family. J. Cell. Biochem. 78,380 -390.[CrossRef][Medline]
Hightower, L. E., Norris, C. E., Di Iorio, P. J. and Fielding, E. (1999). Heat shock responses of closely related species of tropical and desert fish. Am. Zool. 39,877 -888.
Hochachka, P. W. (1967). Organization of metabolism during temperature compensation. In Molecular Mechanisms of Temperature Adaptation, vol. 84 (ed. C. L. Prosser), pp. 177-203. Washington, DC: American Association for the Advancement of Science.
Hochachka, P. W. and Somero, G. N. (2002). Biochemical Adaptation. Mechanism and Process in Physiological Evolution. New York: Oxford University Press.
Huebert, R. C., Splinter, P. L., Garcia, F., Marinelli, R. A.
and LaRusso, N. F. (2002). Expression and localization of
aquaporin water channels in rat hepatocytes. J. Biol.
Chem. 277,22710
-22717.
Ikezawa, H. (2002). Glycosylphosphatidylinositol (GPI)-anchored proteins. Biol. Pharmacol. Bull. 25,409 -417.[CrossRef]
Lee, S. M., Koh, H. J., Park, D. C., Song, B. J., Huh, T. L. and Park, J. W. (2002). Cytosolic NADP(+)-dependent isocitrate dehydrogenase status modulates oxidative damage to cells. Free Radical Biol. Med. 32,1185 -1196.[CrossRef][Medline]
Lowe, C. H. and Heath, W. G. (1969). Behavioral and physiological responses to temperature in the desert pupfish Cyprinodon macularius. Physiol. Zool. 42, 53-59.
Makkinje, A., Quinn, D. A., Chen, A., Cadilla, C. L., Force, T.,
Bonventre, J. V. and Kyriakis, J. M. (2000). Gene 33/Mig-6, a
transcriptionally inducible adapter protein that binds GTP-Cdc42 and activates
SAPK/JNK. J. Biol. Chem.
275,17838
-17847.
Milland, J., Tsykin, A., Thomas, T., Aldred, A. R., Cole, T. and Schreiber, G. (1990). Gene expression in regenerating and acute-phase rat liver. Am. J. Physiol. 259,G340 -G347.[Medline]
Morandat, S., Bortolato, M. and Roux, B. (2002). Cholesterol-dependent insertion of glycosylphosphatidylinositol-anchored enzyme. Biochim. Biophys. Acta 1564,473 -478.[Medline]
Myers, G. S. (1952). Annual fishes. Aquarium J. 23,125 -141.
Ner, S. S., Blank, T., Travers, A. A., Grigliatti, T. A.,
Becker, P. B. and Travers, A. A. (2001). HMG-D and histone H1
interplay during chromatin assembly and early embryogenesis. J.
Biol. Chem. 276,37569
-37576.
Nightingale, K., Dimitrov, S., Reeves, R. and Wolffe, A. P. (1996). Evidence for a shared structural role for HMG1 and linker histones B4 and H1 in organizing chromatin. EMBO J. 15,548 -561.[Abstract]
Nordlie, R. C., Foster, J. D. and Lange, A. J. (1999). Regulation of glucose production by the liver. Annu. Rev. Nutr. 19,379 -406.[CrossRef][Medline]
Norris, C. E., Brown, M. A., Hickey, E., Weber, L. A. and Hightower, L. E. (1997). Low-molecular-weight heat shock proteins in a desert fish (Poeciliopsis lucida): Homologs of human Hsp27 and Xenopus Hsp30. Mol. Biol. Evol. 14,1050 -1061.[Abstract]
Ogawa, Y., Aizawa, S., Shirakawa, H. and Yoshida, M.
(1995). Stimulation of transcription accompanying relaxation of
chromatin structure in cells overexpressing high mobility group 1 proteins.
J. Biol. Chem. 270,9272
-9280.
Otto, R. G. (1974). The effects of acclimation to cyclic thermal regimes on heat tolerance of the western mosquitofish. Trans. Amer. Fish. Soc. 1974,331 -335.
Palacin, M., Estevez, R., Bertran, J. and Zorzano, A.
(1998). Molecular biology of mammalian plasma membrane amino acid
transporters. Physiol. Rev.
78,969
-1054.
Podrabsky, J. E., Hrbek, T. and Hand, S. C. (1998). Physical and chemical characteristics of ephemeral pond habitats in the Maracaibo basin and Llanos region of Venezuela. Hydrobiologia 362,67 -78.
Ramstein, J., Locker, D., Bianchi, M. E. and Leng, M.
(1999). Domain-domain interactions in high mobility group 1
protein (HMG1). Eur. J. Biochem.
260,692
-700.
Robertson, J. C. and Hazel, J. R. (1997). Membrane constraints to physiological function at different temperatures: does cholesterol stabilize membranes at elevated temperatures? Global Warming: Implications for Freshwater and Marine Fish, vol.61 (ed. C. M. Wood and D. G. McDonald), pp.25 -49. Cambridge: Cambridge University Press.
Roitt, I., Brostoff, J. and Male, D. (1993). Immunology. London, Mosby.
Sambrook, J., Fritsch, E. F. and Maniatis, T. (1989). Molecular Cloning. A Laboratory Manual. New York: Cold Spring Harbor Press.
Seddon, W. L. and Prosser, C. L. (1997). Seasonal variations in the temperature acclimation response of the channel catfish, Ictalurus punctatus. Physiol. Zool. 70, 33-44.[Medline]
Shridhar, V., Rivard, S., Wang, X., Shridhar, R., Paisley, C., Mullins, C., Beirnat, L., Dugan, M., Sarkar, F., Miller, O. J., Vaitkevicius, V. K. and Smith, D. I. (1997). Mutations in the arginine-rich protein gene (ARP) in pancreatic cancer. Oncogene 14,2213 -2216.[CrossRef][Medline]
Shrode, J. B. and Gerking, S. D. (1977). Effects of constant and fluctuating temperatures on reproductive performance of a desert pupfish, Cyprinodon n. nevadensis. Physiol. Zool. 50,1 -10.
Stemmer, C., Schwander, A., Bauw, G., Fojan, P. and Grasser, K.
D. (2002). Protein kinase CK2 differentially phosphorylates
maize chromosomal high mobility group B (HMGB) proteins modulating their
stability and DNA interactions. J. Biol. Chem.
277,1092
-1098.
Stokkan, K.-A., Yamazaki, S., Tei, H., Sakaki, Y. and Menaker,
M. (2001). Entrainment of the circadian clock in the liver by
feeding. Science 291,490
-493.
Stros, M. (2001). Two mutations of basic residues within the N terminus of HMG-1 B domain with different effects on DNA supercoiling and binding to bent DNA. Biochemistry 40,4769 -4779.[CrossRef][Medline]
Stros, M. and Reich, J. (1998). Formation of large nucleoprotein complexes upon binding of the high-mobility-group (HMG) box B-domain of HMG1 protein to supercoiled DNA. Eur. J. Biochem. 251,427 -434.[Abstract]
Sunyer, J. O. and Lambris, J. D. (1998). Evolution and diversity of the complement system of poikilothermic vertebrates. Immunol. Rev. 166, 39-57.[Medline]
Thomas, J. O. and Travers, A. A. (2001). HMG1 and 2, and related `architectural' DNA-binding proteins. Trends Biochem. Sci. 26,167 -174.[CrossRef][Medline]
Tsunoda, T., Inokuchi, J., Baba, I., Okumura, K., Naito, S.,
Sasazuki, T. and Shirasawa, S. (2002). A novel mechanism of
nuclear factor B activation through the binding between inhibitor of
nuclear factor-
B
and the processed NH2-terminal
region of Mig-6. Cancer Res.
62,5668
-5671.
van Breukelen, F. and Martin, S. L. (2002). Reversible depression of transcription during hibernation. J. Comp. Physiol. B 172,355 -361.[Medline]
Winkler, B. S., DeSantis, N. and Solomon, F. (1986). Multiple NADPH-producing pathways control glutathione (GSH) content in retina. Exp. Eye Res. 43,829 -847.[Medline]
Woiwode, J. G. and Adelman, I. R. (1992). Effects of starvation, oscillating temperatures, and photoperiod on the critical thermal maximum of hybrid striped x white bass. J. Therm. Biol. 17,271 -275.[CrossRef]
Wolffe, A. P. (1999). Architectural regulations and HMG1. Nat. Genet. 22,215 -217.[CrossRef][Medline]
Yancey, P. H., Blake, W. R. and Conley J. (2002). Unusual organic osmolytes in deep-sea animals: adaptation to hydrostatic pressure and other perturbants. Comp. Biochem. Physiol. 133A,667 -676.
Zehmer, J. K. and Hazel, J. R. (2003). Plasma
membrane rafts of rainbow trout are subject to thermal acclimation.
J. Exp. Biol. 206,1657
-1667.
Related articles in JEB: