Absolute transcript levels of thioredoxin- and glutathione-dependent redox systems in Saccharomyces cerevisiae: response to stress and modulation with growth.

Abstract

We report the co-ordinated fine-tune of mRNA molecules that takes place in yeast (Saccharomyces cerevisiae) in response to diverse environmental stimuli. We performed a systematic and refined quantification of the absolute expression patterns of 16 genes coding for thioredoxin- and glutathione-dependent redox system components. Quantifications were performed to examine the response to oxidants, to sudden temperature upshifts and in association with metabolic changes accompanying culture growth and to explore the contribution of mRNA decay rates to the differences observed in basal expression levels. Collectively, these quantifications show (i) vast differences in the steady-state amounts of the investigated transcripts, cTPxI being largely overexpressed compared with GPX1 during the exponential phase and GPX2 beyond this growth stage; (ii) drastic changes in the relative abundance of the transcripts in response to oxidants and heat shock; and (iii) a unique temporal expression profile for each transcript as cells proceed from exponential to stationary growth phase, yet with some general trends such as maximal or near-maximal basal amounts of most mRNA species at early growth stages when glucose concentration is high and cells are actively growing. Moreover, the results indicate that (i) the half-lives of the investigated transcripts are longer and distributed within a narrower range than previously reported global mRNA half-lives and (ii) transcriptional initiation may play an important role in modulating the significant alterations that most mRNAs exhibit in their steady-state levels along with culture growth.

Full text

Page 1

Biochem. J. (2004) 383, 139–147 (Printed in Great Britain)
139
Absolute transcript levels of thioredoxin- and glutathione-dependent
redox systems in Saccharomyces cerevisiae: response to stress
and modulation with growth
Fernando MONJE-CASAS, Carmen MICH´AN and Carmen PUEYO1
Departamento de Bioqu´ ımica y Biolog´ ıa Molecular, Campus de Rabanales, edificio Severo Ochoa, planta 2a, Carretera Madrid-C´ adiz Km 396-a, Universidad de C´ ordoba,
14071 C´ ordoba, Spain
We report the co-ordinated fine-tune of mRNA molecules that
takes place in yeast (Saccharomyces cerevisiae) in response to
diverseenvironmentalstimuli.Weperformedasystematicandre-
finedquantificationoftheabsoluteexpressionpatternsof16genes
coding for thioredoxin- and glutathione-dependent redox system
components. Quantifications were performed to examine the re-
sponse to oxidants, to sudden temperature upshifts and in asso-
ciationwithmetabolicchangesaccompanyingculturegrowthand
toexplorethecontributionofmRNAdecayratestothedifferences
observed in basal expression levels. Collectively, these quantific-
ations show (i) vast differences in the steady-state amounts of the
investigated transcripts, cTPxI being largely overexpressed com-
pared with GPX1 during the exponential phase and GPX2 beyond
this growth stage; (ii) drastic changes in the relative abundance
of the transcripts in response to oxidants and heat shock; and
(iii) a unique temporal expression profile for each transcript as
cells proceed from exponential to stationary growth phase, yet
with some general trends such as maximal or near-maximal basal
amountsofmostmRNAspeciesatearlygrowthstageswhengluc-
ose concentration is high and cells are actively growing. More-
over, the results indicate that (i) the half-lives of the investigated
transcripts are longer and distributed within a narrower range
than previously reported global mRNA half-lives and (ii) trans-
criptional initiation may play an important role in modulating the
significant alterations that most mRNAs exhibit in their steady-
state levels along with culture growth.
Key words: absolute mRNA level, gene expression, glutathione,
growth phase, thioredoxin, yeast.
INTRODUCTION
The survival of living cells depends on their ability to sense
changes in the environment and to respond appropriately to the
new situation. The imbalance in the redox status of cells towards
an oxidized state is known as oxidative stress. Saccharomyces
cerevisiae has evolved an effective and intricate network of
enzymic as well as non-enzymic defences to protect itself from
the harmful effects of ROS (reactive oxygen species) [1].
Glutathione and thioredoxin are two of the most important and
abundant cellular antioxidants, which play key roles in maintain-
ing the redox homoeostasis of the cell (see [2] for a review). In
S. cerevisiae, the GSH1 gene product (γ-glutamylcysteine syn-
thetase) catalyses the first and rate-limiting step for GSH bio-
synthesis.Thesecondenzyme(glutathionesynthase),encodedby
GSH2,isdispensablefornormalgrowth,confirminganimportant
role for the γ-glutamylcysteine dipeptide in replacing GSH in es-
sentialfunctions[3].Glutathionereductase(theproductofGLR1)
catalyses an NADPH-dependent reaction for the regeneration
of GSH. Two thioredoxins (encoded by TRX1 and TRX2), one
thioredoxin reductase (TRR1) and NADPH as reductant, operate
in yeast cytoplasm as a general disulphide reductase pathway [2].
Additional mitochondrial species (TRX3 and TRR2) have also
been identified, which offer protection against oxidative stress
generated during mitochondrial metabolism [4].
ThioredoxinandGSHarealsorequiredforthedetoxificationof
ROS by providing the reducing equivalents for TPxs [thioredoxin
(or thiol) peroxidases] and GPxs (glutathione peroxidases). Quite
a large number of TPxs have been found in yeast, including cyto-
plasmic(codedforbythecTPxI,cTPxII andcTPxIII genes),mito-
chondrial (mTPx) and nuclear (nTPx) species [5]. The mitochon-
drialproteinappearstousethemitochondrialthioredoxinpathway
as electron donor [6]. So far, three gene products (GPX1, GPX2
and GPX3) with significant homology to mammalian GPxs have
been identified from the S. cerevisiae genome [7]. Although these
three enzymes are required for yeast resistance against phos-
pholipid and non-phospholipid hydroperoxides [7,8], the GPX3
product seems to serve the predominant role of hydroperoxide
receptor and redox transducer in gene activation mediated by the
transcriptionfactorYap1p[9].Becauseofthisregulatoryfunction
inYap1pactivation,Gpx3phasbeenrenamedrecentlyas‘oxidant
receptor peroxidase 1 (Orp1p)’ [9].
Control of mRNA levels is crucial in regulating protein pro-
duction in eukaryotes. Current knowledge on transcript amounts
of the 16 yeast genes mentioned above has emerged from ex-
periments using methods that generate relative data. Given that
modulation of transcription can be much better understood in
absolute quantitative terms, we present here, for the first time,
valuable new information on the basis of actual mRNA molecule
numbers. To this end, we used a quantitatively rigorous approach
based on reverse transcription followed by a combination of
multiplexedPCR(MPCR)andreal-timePCRamplifications[10].
We performed a systematic and comprehensive investigation of
absolute expression patterns in response to oxidizing agents, to
suddentemperatureupshiftsandinassociationwiththemetabolic
changes accompanying culture growth. Since the stability of
individualmRNAscontributessignificantlytothedifferentialcon-
trol of gene expression, decay rates of the investigated transcripts
Abbreviationsused:GPx,glutathioneperoxidase;MD,menadione;MPCR,multiplexedPCR;ROS,reactiveoxygenspecies;TPx,thioredoxinperoxidase.
1To whom correspondence should be addressed (email bb1pucuc@uco.es).
c ?2004 Biochemical Society

Page 2

140
F. Monje-Casas, C. Mich´ an and C. Pueyo
were also determined. Aside from its inherent value, the inform-
ation given here provides a more complete picture of how a co-
ordinated fine-tune of mRNA levels might be important for the
cell to respond effectively to diverse environmental stimuli.
EXPERIMENTAL
Yeast strains and growth conditions
S. cerevisiae Y00000 (MATa his3?1 leu2?0 met15?0 ura3?0)
was used as the wild-type. Strain Y262 (MATα ura3-52 his4-539
rpb1-1), with a temperature-sensitive mutation in the gene en-
coding the largest subunit of RNA polymerase II [11], was used
for mRNA decay quantifications. Cells were grown in YPD me-
dium [1% (w/v) yeast extract/2% (w/v) peptone/2% (w/v)
glucose] or SD medium [bacto yeast nitrogen base without amino
acids (6.7 g/l) and glucose (20 g/l)] [12]. Minimal medium was
supplementedwithappropriateaminoacidsandbases(20 mg/l L-
histidine, 100 mg/l L-leucine, 20 mg/l L-methionine and 20 mg/l
uracil). Growth was monitored by measuring the absorbance A
at 600 nm (A600). Cells were inoculated into YPD medium and
incubatedfor20 h.Theseovernightcultureswerethendilutedinto
fresh YPD or minimal SD medium (A600 0.05) and incubated
until they reached the absorbance specified in individual Figures.
Unless otherwise indicated, incubations were performed at 30◦C
with constant agitation (125 rev./min).
RNA isolation and reverse transcription
Total RNA was extracted using the hot-phenol method described
previously [13]. The RNA sample was then treated for 90 min
at 37◦C with RNase-free DNase I (?5 units/µg of RNA) to
remove contaminating DNA. The quality of RNA sample was
checked electrophoretically, and quantification was performed
spectrophotometrically. Standard RNA and cDNA were syn-
thesized as detailed in [14]. Absence of genomic DNA contamin-
ationwascheckedbyPCRamplificationofRNAsampleswithout
priorcDNAsynthesis.AtleasttwoindependentRNApreparations
were isolated for each experimental condition, each RNA sample
being retrotranscribed on three separate occasions.
Primers
Sequences of genes for primer design were obtained from
Saccharomyces Genome Database (www.standford.edu). Primers
with high Tm values (?82◦C) and optimal 3?-?G values
(?−9.5 kcal/mol; 1 kcal≈4184 J) were prepared with Oligo
6.1.1/98 (Molecular Biology Insights, Plymouth, MN, U.S.A.)
program,asdetailedin[15].Primersforamplificationofthetarget
mRNAs (total of 16) were distributed into two sets, because of
the large number of sequences and the restricted parameters used
in primer selection [15]. Set A included primer pairs for ampli-
fication of TRX1 (YLR043C), TRX2 (YGR209C), TRX3
(YCR083W), TRR1 (YDR353W), TRR2 (YHR106W), cTPxIII
(YLR109W),GSH1(YJL101C)andGLR1(YPL091W),whereas
set B included primer pairs for amplification of cTPxI
(YML028W), cTPxII (YDR453C), mTPx (YBL064C), nTPx
(YIL010W), GPX1 (YKL026C), GPX2 (YBR244W), GPX3
(YIR037W) and GSH2 (YOL049W). Sets A and B also included
primer pairs for the amplification of ACT1 (YFL039C) and PDA1
(YER178W) mRNAs. ACT1, which codes for actin (a cytoskele-
ton component), and PDA1, which codes for the E1α subunit of
the pyruvate dehydrogenase complex, are commonly used as
internal standards for quantifying mRNA in S. cerevisiae [16].
Forward primers were labelled with 4,7,2?,4?,5?,7?-hexachloro-
6-carboxyfluorescein for MPCR. The primer sequences are
available from the authors on request.
Real-time PCR and MPCR
Real-time PCRs were performed in quadruplicate as detailed in
[14]. No primer dimers were detected, and the investigated tran-
scripts showed optimal PCR efficiencies. An absolute standard
curve was constructed with an external standard in the range of
102–109RNA molecules. The number of mRNA molecules was
calculated from the linear regression of the standard curve, as de-
scribed previously [14]. MPCR conditions were optimized as
detailed in [15] to ensure that the amplifications were in the ex-
ponential phase and the efficiencies remained constant in the
course of the PCR. Components of the reaction mixture were de-
scribed previously [15]. For both set A and set B, 25 cycles of
amplification were performed. Relative quantification of the
MPCR products was performed as described in [15]. MPCR
data were from an average of six MPCR amplifications. Absolute
measurements(mRNAmolecules)wereinferredfromtherelative
expression ratios given by MPCR, as we have described recently
[10].
Statistical analysis
Results are the means+−S.E.M. for n?6 determinations. Statis-
tical significance was evaluated using ANOVA followed by post-
hoc multiple comparison according to the Student–Newman–
Keuls method. P?0.05 was considered significant.
RESULTS
Quantification of the response to oxidative stress
A key requirement of the current analysis is the ability to detect
reproducibly,identifyandquantifyaccuratelybothhigh-andlow-
abundance mRNAs. Hence, we first determined the steady-
state amounts of the investigated transcripts in wild-type cells
cultured in minimal SD medium to reach an A6001. Under this
particular growth condition, vast differences in abundance were
detected(Figure1a).Forinstance,cTPxI mRNAwaslargelyover-
expressedcomparedwithGPX1mRNA(124 molecules/pgversus
0.21 molecule/pg). The former was as abundant as the house-
keeping ACT1 mRNA but more abundant than the PDA1 mRNA
(results not shown).
Our second goal was to quantify the abundance of the investi-
gated transcripts under an oxidizing environment. To this end,
wild-type cells were challenged with H2O2through both dosage
and time-course experiments (results not shown). Quantifications
made at 100 µM H2O2for 10 min are shown in Figure 1(b). The
steady-stateamountsofninetranscriptswerereadilyup-regulated
by H2O2. In contrast, no significant variation of other mRNA
levels was detected under any of the H2O2exposure conditions
investigated herein.
The relative increments calculated in Figure 1(b) highlight the
importance of the absolute measurements reported in the pre-
sent study. For instance, although a relative increment of approx.
3-foldinbothcTPxI andcTPxIII mRNAlevelsmightlookinsigni-
ficant compared with the 123-fold increase in cTPxII mRNA,
the actual scenario is that, after H2O2 exposure, cTPxI and
cTPxIII mRNAs are still present in higher amounts compared
with cTPxII mRNA (406 and 283 molecules/pg versus 148 mol-
ecules/pg). In short, absolute quantifications make us realize that
even small increments in highly abundant transcripts may have
moreinfluenceontheantioxidativecapacityofthecellwhencom-
pared with huge increments of poorly transcribed genes.
To compare the response of yeast to H2O2with its response to
other oxidants, the expression profiles of the investigated genes
were quantified in response to challenges posed by t-butylhydro-
peroxide or the superoxide anion generated by the redox cycling
c ?2004 Biochemical Society

Page 3

Thioredoxin- and GSH-dependent redox systems in yeast
141
Figure 1Induction of gene expression by oxidative stress
Wild-typecellsweregrowninminimalSDmediumtoreachanabsorbanceA6001andthentreated
for10 minwith100 µMH2O2(b).Untreatedcellsservedasreference(a).Themeans+
of mRNA molecules/pg of total RNA were plotted for the different genes. Some error bars are
not visible because of small S.E.M. values. To facilitate the comparison of relative and absolute
quantifications,thedatafromH2O2-treatedcells weredividedbythoseofuntreatedcells.These
fold increments are given in parentheses. Only statistically significant increments are indicated.
−S.E.M.
agent MD (menadione). With both oxidants (results not shown),
the responding genes were the same as those in Figure 1(b).
However,whereassimilarup-regulationlevelswereobtainedwith
t-butylhydroperoxide, the order of mRNA abundance for the up-
regulated genes, after exposure to MD, changed to cTPxI >
cTPxIII > TRX2 ∼ TRR1 > GPX2 > cTPxII ∼ mTPx>GLR1>
GSH1, compared with that in Figure 1(b).
The lack of both cytoplasmic thioredoxins (?trx1?trx2) in-
creased (relative to the parental wild-type) the steady-state levels
of the nine transcripts that were up-regulated under oxidative
stress conditions (results not shown). Of note is the observation
that basal transcript amounts quantified in ?trx1?trx2 mutant
cells (single mutants showed no significant effect) were strikingly
similar to the induced amounts quantified in the wild-type after
exposure to MD (100 µM for 10 min).
Transcript levels along with culture growth
Regulation of gene expression is an integral and dynamic com-
ponent of the yeast life cycle [1]. In the present study, we quanti-
fied the absolute amounts of the investigated transcripts through-
Figure 2Growth curve of wild-type yeast in YPD medium
Wild-type cells from an overnight culture (late-exponential phase) in YPD were diluted in
fresh medium (starting with A6000.05) and incubated at 30◦C with shaking at 125 rev./min.
Culture growth was monitored by measuring the A600. The glucose content of the medium was
determined using the glucose (hexokinase) assay kit (Sigma–Aldrich, St. Louis, MO, U.S.A.).
Samples were collected at the indicated time intervals (indicated by arrowheads) for total RNA
isolation. Growth phases: early exponential (1–2), mid-exponential (3), late-exponential (4),
diauxic shift (5), post-diauxic (6–7) and stationary (8). Doubling time during the exponential
phase of growth was estimated in 1.56 h based on A600measurements. Glucose concentration
decreased to 0.1% at the onset of the diauxic shift. The diauxic arrest lasted from 14 to 17 h
after inoculation.
Figure 3ACT1 and PDA1 mRNA levels at different stages of growth
Samples were collected at the growth stages mentioned in the legend to Figure 2. Results are
the mean values of mRNA molecules/pg of total RNA (n ?6).
out the growth curve in YPD medium. As indicated in Figure 2,
quantifications were performed in samples collected at different
stages of the exponential fermentative growth phase; next, when
the glucose has become limiting and the cells have to reset
their metabolism from fermentation to respiration (diauxic shift);
subsequently, when the cells resume growth at a much lower
rate using ethanol and other by-products from the former glucose
catabolism (post-diauxic phase); and later, during the stationary
phase. ACT1 and PDA1 mRNAs have been used as internal
standards for relative quantification of transcript levels under a
wide range of growth stages and conditions (see e.g. [16,17]).
Quantifications of both mRNAs demonstrated that their levels
do not remain constant along the growth curve but decrease
significantly (Figure 3). It follows that, under these experimental
conditions,theuseofACT1orPDA1transcriptasreferencewould
seriously overestimate the quantification of any investigated
mRNA that would be present at detectable levels. In this context,
it is noteworthy that the absolute expression profiles reported in
Figure 4 are not normalized and, therefore, do not assume that a
reference is steadily expressed.
All of the 16 target mRNAs show detectable alterations in their
steady-state levels throughout the different stages of growth. For
c ?2004 Biochemical Society

Page 4

142
F. Monje-Casas, C. Mich´ an and C. Pueyo
Figure 4Levels of 16 target mRNAs at different stages of growth
Samples were collected at the growth stages mentioned in the legend to Figure 2. Results are the mean values of mRNA molecules/pg of total RNA (n ?6). Arbitrary expression patterns referred to
in the text are given in brackets.
simplicity, seven distinct temporal patterns of expression were
distinguished, although no two profiles were identical in terms
of magnitude and the choreography of expression. In pattern 1
(TRX1, TRR1 and GPX2), the mRNA accumulated from early
to mid-exponential phase and then decreased to show the lowest
expression level at the stationary phase. In pattern 2, the accu-
mulated mRNA remained at a high level after mid-exponential
phase, i.e. to the onset of the diauxic shift (TRX2) or, even later,
during the post-diauxic phase (GPX3). In pattern 3 (cTPxI and
cTPxIII), the mRNA level was maximal somewhat earlier than
mid-exponential phase. In pattern 4, maximal mRNA amount
was sustained during early and mid-exponential phases (nTPx)
and even during late-exponential phase (GLR1). In pattern 5, the
mRNA accumulation took place from early exponential to the di-
auxic shift (cTPxII and mTPx) and took place even further, till
earlypost-diauxic(GPX1).Inpattern6(TRX3andTRR2),thisup-
regulationwasprecededbyadecrease.Finally,inpattern7(GSH1
and GSH2), the mRNA level decreased throughout all the growth
stages investigated in the present study, from early exponential to
stationary phase.
The absolute quantitative results presented in this study are
largely in disagreement with previous studies that monitored
relative transcript abundances or activities of reporter fusion con-
structs at different growth stages. One illustrative discrepancy is
as follows: TRX1 mRNA increased 1.5-fold (21.5 molecules/pg
versus 32.6 molecules/pg) from early to mid-exponential phase
and then decreased 24-fold to show the lowest amount (1.4 mol-
ecules/pg) at the stationary phase (Figure 4). Contrary to this
absolute mRNA profile, TRX1 expression remained largely un-
changed according to microarray hybridization [18,19] or in-
creased 6-fold after entry into the stationary phase according to a
TRX1::lacZ construct [20].
CulturingofS.cerevisiaeonminimalorrichmedia[Figure1(a)
versus 9 h data in Figure 4] had little effect (?2-fold variation) on
the steady-state levels of the investigated transcripts and therefore
on their relative abundance. In contrast, the relative abundance of
the mRNAs quantified in the present study showed significant
changes along the growth curve (Figure 4). For instance, the
order of mRNA abundance for the related TPx isoenzymes was
cTPxI >cTPxIII >nTPx∼mTPx>cTPxII duringearlyandmid-
exponential phases, but cTPxI >mTPx>cTPxII >cTPxIII >
nTPx at the diauxic transition. Remarkably, cTPxI mRNA was
the most abundant of all studied target transcripts under any
of the investigated growth conditions (media and growth phase),
in agreement with the current idea that cTPxIp is an abundant
(as it constitutes 0.7% of total soluble protein of yeast grown
aerobically) and critical antioxidant in vivo [5,21]. In contrast, the
less abundant transcript was GPXI, throughout the exponential
growth, and GPX2 during the rest of the monitored growth
period.
c ?2004 Biochemical Society

Page 5

Thioredoxin- and GSH-dependent redox systems in yeast
143
Figure 5 Time-course effect of thiolutin on mRNA levels
Wild-type cells were grown in YPD medium to reach an A6000.5. Cells were then treated with 87 µM thiolutin dissolved in DMSO. Samples were collected at the indicated times after drug addition.
Results are the means+
Some error bars are not visible because of small S.E.M. values. All transcripts were quantified, but only those mRNAs for which statistically significant increases were observed at a given thiolutin
exposure time are shown. The remaining genes were transcriptionally inhibited by thiolutin, and their mRNAs exhibited the half-life values shown in Table 1. For each transcript, the maximal fold
increment is given in parentheses.
−S.E.M. of mRNA molecules/pg of total RNA. Data at 0 min represent the steady-state levels of solvent control cells. No time-related effect was noted in these control cells.
mRNA decay profiles
The main determinants of mRNA concentration in S. cerevisiae
are transcriptional initiation and mRNA decay. The half-life of
an mRNA species determines the number of times an individual
transcriptcanbetranslated,which,inturn,affectsthetotalamount
of protein that can be produced by a gene at a given rate of
transcriptional initiation. Current procedures for determining
the half-lives of individual yeast mRNAs include inhibition of
transcription by specific drugs or thermal inactivation of a tem-
perature-sensitive RNA polymerase II [22,23].
We first inhibited total mRNA synthesis by the use of thiolutin,
an effective inhibitor of all yeast RNA polymerases both in vitro
and in vivo [24,25]. Surprisingly, the levels of eight (Figure 5)
out of nine mRNAs that were up-regulated under oxidizing
conditions(Figure1b)increased(notdecreased)aftertheaddition
of the transcriptional inhibitor. In contrast, the rest of the mRNAs
decayedwithhalf-livesrangingfrom72.9 min(TRX1)to12.0 min
(GPX1) (Table 1). These results suggest that thiolutin induces
the oxidative stress response under conditions in which the trans-
criptionofothergenesisblocked.Inthisway,wehypothesizethat
the high half-life value (Table 1) calculated for GLR1 mRNA (up-
regulatedinresponsetooxidants,e.g.Figure1b)isoverestimated.
The moderate decrease in GLR1 mRNA levels in the presence
of thiolutin is most probably the result of a modest induction
paralleling the blocking transcription.
In our effort to quantify accurately the decay rates of the
investigated mRNAs, we next considered the possibility of using
the RNA polymerase II mutant rpb1-1 for a rapid cessation of
mRNA synthesis in exponentially growing cells [11]. Given the
thiolutin effect on the genes responding to oxidizing conditions,
our first step was to assess the consequences that the temperature
Table 1Decay rates of mRNAs
Wild-type (wt) or rpb1-1 mutant cells were grown in YPD to reach an A6000.5 (exponentially
growing, expG) or to the onset of the diauxic arrest (0.1% glucose). Transcription was shut-off
asdetailedinFigure5(thiolutin)orFigure6(temperatureupshift).EachmRNAdecayprofile(see
e.g. Figure 7) was plotted as the log10(relative concentration of mRNA) versus time. The half-
life of mRNA was calculated from the equation of the decay line for the full 90 min of chase.
Half-lifevaluesofmRNAthatmightbeoverestimatedorunderestimated(asdiscussedinthetext)
aregiveninparentheses.Thearrow(↑)indicatesthatthemRNAlevelincreased(notdecreased)
in the presence of thiolutin or at the non-permissive temperature; n.d., not determined. The
half-lives and the 95% percentage confidence intervals (in parentheses) previously obtained
by using DNA microarray [23] are included for comparison. The microarray data should be in
agreement with the half-life values quantified in expG-phase cells.
Thiolutin (wt)
ExpG
Temperature upshift (rpb1-1)
Transcript ExpGDiauxic Microarray
TRX1
TRX2
TRX3
TRR1
TRR2
cTPxI
cTPxII
cTPxIII
mTPx
nTPx
GPX1
GPX2
GPX3
GSH1
GSH2
GLR1
PDA1
72.9
↑
29.6
↑
34.9
↑
↑
↑
↑
12.7
12.0
↑
32.5
↑
16.0
(87.6)
44.3
69.0
↑
27.6
18.7
30.4
43.5
↑
39.5
↑
12.6
↑
(4.8)
34.3
(9.6)
20.1
33.5
43.9
n.d.
51.1
27.8
n.d.
32.4
n.d.
(39.0)
n.d.
(20.4)
n.d.
(11.1)
38.9
n.d.
(5.3)
n.d.
n.d.
n.d.
Poor signal
68 (50–100)
Poor signal
15 (14–17)
34 (29–42)
34 (30–38)
37 (33–43)
78 (68–92)
Poor signal
22 (17–29)
Poor signal
12 (10–15)
60 (48–76)
15 (12–19)
20 (16–23)
31 (26–36)
46 (37–50)
c ?2004 Biochemical Society

Page 6

144
F. Monje-Casas, C. Mich´ an and C. Pueyo
Figure 6Time-course effect of temperature upshift on mRNA levels
Wild-type cells were grown in YPD medium at 24◦C to reach an A6000.5. The temperature was then abruptly shifted to 37◦C by transferring the culture to a new flask containing an equal volume of
YPD medium that had been prewarmed to 49◦C. Results are the means+
upshift. No time-related effect was noted in these control cells for the full 90 min of chase. The Figure shows those mRNAs for which statistically significant increases or decreases were observed at
a given time after the temperature upshift. For each transcript, the maximal fold variation is given in parentheses.
−S.E.M. of mRNA molecules/pg of total RNA. Data at 0 min represent the steady-state levels in cells before the temperature
upshift might have on the mRNA levels of wild-type cells. As
shown in Figure 6, shifting cells from 24 to 37◦C resulted in the
altered expression of six genes. Partial overlap with the thiolutin
(i.e. oxidative stress) response (Figure 5) was detected. Differ-
ences were the up-regulation of the GPX1 gene (not responding
to thiolutin) and the down-regulation of GPX2 and GSH1 genes
(up-regulated by thiolutin exposure). Distinctions in the up-
regulation kinetics were also observed. Heat shock resulted in
transcript abundance increments within the first 10 min of the
shock. Then the mRNA levels gradually adjust to the levels seen
in unstressed cells (Figure 6). In contrast, the thiolutin response
lasted longer (Figure 5).
Theheat-shockresponsequantifiedinwild-typecells(Figure6)
raisedthequestionastohowthetemperatureupshiftcaninfluence
the decay profiles of mRNAs in the conditional mutant strain. For
four genes (TRX2, cTPxII, mTPx and GPX1), the mRNA level
underwent a slight (?2-fold) increase immediately after the
rpb1-1 mutant cells were transferred to the non-permissive tem-
perature and, therefore, no mRNA decay rate could be accurately
determined (exemplified in Figure 7a by cTPxII and mTPx). In
contrast, the rest of the mRNAs decreased immediately after the
temperature upshift, and their half-lives were readily calculated
(Table 1).
The half-lives of mRNA determined in temperature-shifted
rpb1-1 cells were in good agreement with those of six mRNAs
(TRX1, TRX3, TRR2, nTPx, GPX3 and GSH2) previously ap-
proachedbythiolutininhibition.TheGLR1exceptionfurthersup-
ports the notion that the half-life value of mRNA calculated in
thiolutin-treated cells is most probably overestimated. Besides,
thehalf-livesoffive(TRR1,cTPxI,cTPxIII,GPX2andGSH1)out
of eight mRNAs that were up-regulated by thiolutin could be de-
termined by means of thermal inactivation of RNA polymerase II
in rpb1-1 mutant cells. Nevertheless, given that the increase in
temperature triggers in wild-type cells (Figure 6), a reduction
in the steady-state levels of GPX2 and GSH1 mRNAs, we cannot
completely rule out the possibility of some underestimation in the
decay rates of 4.8 and 9.6 min quantified for these transcripts in
rpb1-1 cells (Table 1).
Since S. cerevisiae displays the heat-shock response essentially
as actively growing cells [26], one further question was whether
yeast cells transiently arrested at the diauxic shift would show
the same rapid response to the temperature upshift as cells in the
exponential phase. We approached this question by following
the heat-shock response of wild-type cells grown to the onset
of the diauxic phase. Overall, the magnitude of the response of
cells in diauxic arrest (results not shown) was lower compared
with the response seen in rapidly growing cells (Figure 6). Hence,
theamountsofTRX2andGPX2mRNAsdidnotvarysignificantly
after shifting the wild-type cells to 37◦C, and the maximal up-
regulation of cTPxII, mTPx and GPX1 mRNAs was less than
2-fold. Only GSH1 mRNA was reduced in abundance to a similar
degree as seen in exponential cells.
Theslightincreasein cTPxII,mTPx andGPX1mRNAs quanti-
fiedinwild-typecellsafterthetemperatureshiftwasnotobserved
in the conditional rpb1-1 mutant cells (illustrated by cTPxII and
mTPx transcripts in Figure 7b); the mRNA levels decayed with
characteristic half-lives (Table 1). Nevertheless, given the slight
effect quantified in wild-type cells, the possibility of some bias in
the decay rates calculated for these transcripts in rpb1-1 mutant
cells cannot be ruled out completely. An interesting observation
is that the half-life of 11.1 min calculated for GPX1 mRNA is in
verygoodagreementwiththatpreviouslydeterminedinwild-type
by thiolutin inhibition. In any case, we have to keep in mind that
the half-life of individual mRNAs might change with the growth
phase, i.e. in response to change in the physiological demands
of cells. In this context, previous research [27] concluded that,
c ?2004 Biochemical Society

Page 7

Thioredoxin- and GSH-dependent redox systems in yeast
145
Figure 7
quantification
Examples of mRNA decay curves determined by absolute
rpb1-1 mutant cells were grown in YPD medium to reach an A6000.5 (exponentially growing,
expG)ortotheonsetofthediauxicarrest(0.1%glucose).Transcriptionwasshut-offasdetailed
inFigure6.ThepercentageofcTPxII ormTPx moleculesremainingafterthetemperatureupshift
was plotted against time. Earlier works [11,22] have shown that RNA polymerase II-dependent
transcription is reduced in rpb1-1 mutant cells to less than 10% within 2 min after the shift to
37◦C.
whereas nutrient limitation at diauxic shift does not affect the
stability of some mRNAs, others show accelerated turnover via
TOR (target of rapamycin) pathway inhibition.
Recently, Wang et al. [23] have coupled the global trans-
criptionalshut-offassay,basedontherpb1-1mutation,withDNA
microarray analysis to determine half-lives of yeast mRNA on a
genomic scale. As shown in Table 1, our data are in reasonably
good agreement with data determined by DNA microarray in four
(TRR1,TRR2,GSH2andGLR1)outof16transcriptsinvestigated.
For most mRNAs, however, the half-lives reported in the present
study (based on refined absolute quantifications) were longer
(cTPxI) or shorter (e.g. cTPxIII) or impossible to determine in
exponentially growing cells (e.g. cTPxII; see Figure 7a).
DISCUSSION
The response to oxidants
Quantifications reported in the present study demonstrate that
the transcript levels of nine out of 16 genes investigated were in-
creasedinresponsetooxidativestress.Regardingthethioredoxin-
dependent redox system, up-regulated genes code for one (TRX2)
of the two cytoplasmic thioredoxins and the corresponding
reductase (TRR1) and for four (cTPxI, cTPxII, cTPxIII, mTPx)
of the five TPxs. Large amounts of transcripts, ranging from
>500 to approx. 50 copies/total RNA, were quantified under
oxidizing conditions, in agreement with the central role attributed
to this system in defence against oxidative stress [2]. Concerning
the GSH-dependent system, elevated transcripts code for one
(GPX2) of the three GPxs and for two (GSH1, GLR1) of the
three enzymes for the synthesis and reduction of glutathione. Up-
regulated levels of these transcripts were, in general, lower
(?50 copies/total RNA) compared with those quantified for the
thioredoxin system. Overall, the relative induction levels reported
inpreviousstudies[2]aremuchlowerthantherelativeincrements
calculated in the present study from absolute measurements, and
they were typically obtained under more stringent conditions, i.e.
higher oxidant dose and/or longer exposure time. For instance,
maximal increments of 7-fold were quantified for cTPxII under
oxidative conditions [5]. Regarding their regulation, our results
areconsistentwiththeideathattheseninetranscriptsareprimarily
up-regulated by Yap1p in response to mild ROS stress [2,18], and
our results also agree with the observation that this transcrip-
tional factor is constitutively activated in ?trx1?trx2 double-null
mutant [28].
The transcript levels of the remaining seven genes (TRX1,
TRX3,TRR2,nTPx,GPX1,GPX3andGSH2)werenotaffectedby
the oxidants; this result shows some discrepancies with previous
observations. For instance, up-regulation by H2O2of nTPx and
GSH2 expressions has been reported previously [29,30], even
though the increments were small in both cases (?2-fold) and
were generated under acute conditions (400 µM, ?30 min). On
the basis of the refined quantifications determined in the present
studyandthefactthattheywereobtainedatrelativelylowoxidant
concentrations and short exposure time to distinguish primary
fromputativesecondaryresponsestothegivendrug,weconclude
that these nine transcripts are actually not induced in response to
mild oxidative stress. Furthermore, our observation that GSH1
but not GSH2 is induced by oxidant challenge is consistent with
γ-glutamylcysteine synthetase being the bottleneck for de novo
synthesis of GSH and with the observation that GSH2 disruption
results in the accumulation of γ-glutamylcysteine, which is as
good a yeast antioxidant as GSH [3].
Crosstalk between heat-shock and oxidative stress responses
Mild heat shock causes expression to be induced in four cases
(TRX2, cTPxII, mTPx and GPX1) and to be repressed or lowered
in two cases (GPX2 and GSH1), the level of the remaining ten
transcripts being unaffected after shifting the cells from 24 to
37◦C.ExpressionofthegenesresponsibleforROSdetoxification
(suchascatalaseorsuperoxidedismutase)isinducedbymildheat
shock (see e.g. [31,32]), thus connecting both stress responses. In
the present study, we show that the transcript levels of TRX2,
cTPxII and mTPx increase also in response to oxidative stress.
Nonetheless, they were superinduced by oxidants (Figure 1)
relativetotheresponsetomildheatshock(Figure6).Thisfinding
further supports the idea that these three components of the thio-
redoxin system are regulated by different transcription factors
depending on the specific stressful environmental condition, i.e.
throughYap1pinresponsetooxidantsandthroughMsn2p/Msn4p
inresponsetoheatshock[18].Incontrast,thethreecomponentsof
theGSH-dependentredoxsystem(GPX1,GPX2andGSH1)show
unique responses to the above-mentioned environmental changes
(Figures 1 and 6), a result that is mostly in disagreement with
c ?2004 Biochemical Society

Page 8

146
F. Monje-Casas, C. Mich´ an and C. Pueyo
previous studies [2]. For instance, contrary to the quantifications
given here, Northern blotting and lacZ transcriptional fusion
have indicated that the expression of GPX1 [7] and GSH1 [29]
is induced by both heat-shock and oxidative stress conditions.
Nonetheless,inourstudies,thesetwogenesappeartoplaydistinct
roles in both stress responses.
Growth phase-related gene expression
Datagiveninthepresentstudyshowthateachtranscriptexhibitsa
unique temporal expression profile in YPD as yeast cells proceed
from exponential to stationary growth phase. Nonetheless, some
general trends are observed, as follows.
Most mRNAs (TRX1, TRX2, TRR1, cTPxI, cTPxIII, nTPx,
GPX2,GPX3,GSH1,GSH2andGLR1)reachedmaximalornear-
maximal steady-state levels a few hours after the inoculum, when
glucose concentration is high and cells are actively growing.
After this early up-regulation, the mRNA levels decrease to reach
minimalornear-minimalexpressionlevelsinthestationaryphase.
This temporal expression profile contrasts with the following
ideas:(i)geneexpressionisbasicallystableduringtheexponential
growth phase in glucose-rich medium; (ii) changes in gene
expression are mostly associated with the metabolic shift from
fermentation to respiration; and (iii) the expression of genes
coding for antioxidant defences, especially if they can be induced
by ROS (e.g. TRX2 or cTPxIII) are largely up-regulated during
and after the diauxic shift and in the stationary phase (see e.g.
[5,19,20,30,33]fortheinvestigatedgenes).Incontrast,ourresults
as a whole are more in line with the following observations:
(i) outstanding transcriptional changes take place early after the
inoculation of cells into a complete fermentable growth medium
[17];(ii)theup-regulationofantioxidant-defensivefunctionsdoes
not depend on the post-diauxic onset of respiration [33]; and
(iii) the high overall transcriptional capacity of cells at the early
growth stage decreases progressively to be almost completely
blocked at the end of the exponential phase [34].
Exceptions to the most common temporal expression profile
were cTPxII, mTPx and GPX1. For these genes, the number of
transcript molecules was at the minimal level at highglucose con-
centrations, reaching maximal or near-maximal value during the
diauxic shift (Figure 4). This variation ranged from 81-fold
(cTPxII) to 17-fold (mTPx), depending on the transcript. These
outstandingincrementsintranscriptlevels,togetherwiththeirup-
regulationinresponsetomildheatshock(Figure6),agreewiththe
key role attributed to the transcription factors Msn2p and Msn4p
in mediating the transactivation of cTPxII and mTPx during the
diauxictransition[35–37]andalsoagreewiththeidentificationby
computer search of GPX1 among putative STRE (stress-response
element)-controlled genes [19,38,39].
Genes (TRX3 and TRR2) encoding mitochondrial thioredoxin
anditsspecificreductaseshowothernoteworthyexceptions,since
theirmRNAswereatconsiderablyhighlevelsatbothhighandlow
glucoseconcentrationsinthegrowthmedium.Nonetheless,when
compared with the rest of the investigated transcripts, basal
amounts of TRX3 and TRR2 mRNAs were quite constant; the ra-
thersmallvariationsofapprox.3.5-foldobservedalongthegrowth
curvewasmostprobablyconnectedtomitochondrialdevelopment
[4]. It is also noteworthy that, although none of the investigated
mRNAs were specifically up-regulated or maintained at maximal
amounts in stationary-phase cells, the transcripts (TRX3, TRR2
and mTPx) encoding the three mitochondrial proteins together
with the transcript encoding Gpx1p exceptionally showed, in
stationary phase, levels that were higher than or similar to those
quantified in actively proliferating cells. This finding suggests
that these four proteins might offer a first line of defence against
endogenous ROS generated during the stationary-phase arrest
under non-stressed physiological conditions.
mRNA decay in yeast
In S. cerevisiae, transcription is commonly inhibited by specific
drugs, such as thiolutin, or by thermal inactivation of a tem-
perature-sensitive RNA polymerase II [22,23]. In the present
study, we report that these procedures bring the oxidative stress
and heat-shock responses into play. We have also evaluated how
these methods interfere with the analysis of the decay rate of indi-
vidual mRNAs, and we have emphasized the difficulties in
precisely measuring the half-lives of those yeast mRNAs that are
particularly sensitive to environmental changes. Keeping these
experimentaluncertaintiesinmind,asawholeourresultssatisfied
the criterion that the decay rates of individual yeast mRNAs are
related to the physiological function of the proteins they encoded
[23]. Hence, the half-lives of the investigated mRNAs were
distributedwithinanarrowerrange(fromapprox.70to ?10 min)
andweresignificantlylonger(withameanof31 minandamedian
of 33 min) when compared with previously reported global
mRNAhalf-lives[23].Thismayunderlietheneedforaprolonged
translational window to reach high levels of expression, which
seems to be a property of the mRNAs involved in central phy-
siological functions and working in the same biological process
[23].
Moreover, in agreement with previous results in mouse liver
[10], we find that (i) transcripts (TRX1 and TRX2) encoding cyto-
plasmic thioredoxins persist ?3-fold longer than the trans-
cripts (TRR1) encoding the reductase that, in turn, control the
redox state and activity of these molecules; (ii) the transcript
(TRR2) for mitochondrial reductase turns over more slowly than
the transcript (TRR1) for the cytosolic isoenzyme; and (iii) the
transcript (GLR1) encoding the enzyme for recycling GSH dis-
plays a decay rate approx. 2-fold higher than that of the transcript
(TRR1) encoding the enzyme for recycling reduced thioredoxins.
Although a positive significant correlation was found between
the decay rates of liver mRNAs and their steady-state amounts
[10], no simple correlation could be appreciated in yeast. This
lackofcorrespondencehighlightstheimportanceoftheregulation
of transcriptional initiation rates in modulating the significant
alterations that most yeast mRNAs exhibit in their steady-state
levels throughout the different stages of growth.
Rates of transcriptional initiation
Given that the steady-state levels of any mRNA depend on its rate
ofdegradationaswellasitsrateofinitiation,ourmeasurementsof
mRNA decayrates (Table1)andthenumberofmRNA molecules
(Figure 4) make it possible to estimate the rates of transcriptional
initiation[40].Asawhole,thesecalculations(notshown)indicate
that, in S. cerevisiae, the rate of in vivo transcriptional initiation
forindividualgenesmayvaryoverarangeofatleasttwoordersof
magnitude.Forinstance,wefoundthat,whereascTPxI transcripts
would be initiated every 47 s at early exponential phase in YPD
medium, the rate of GPX1 transcriptional initiation would be one
transcript every 77 min. Remarkably, however, this latter trans-
cript would be much more frequently initiated at diauxic phase,
for which an initiation rate of one GPX1 transcript every 68 s
could be estimated.
Similarly, on the basis of the number of mRNA molecules
quantified in H2O2-stressed cells (Figure 1) and assuming that the
decay rate is not affected by the treatment (only a few examples
of regulated mRNA decay in response to external cues have been
described in yeast), we now calculate that, for instance, the rate of
c ?2004 Biochemical Society

Page 9

Thioredoxin- and GSH-dependent redox systems in yeast
147
TRR1 transcriptional initiation would be one transcript every 4 s
in the presence of the oxidant. It is noteworthy that this value is in
excellent agreement with the maximal transcriptional initiation
in vivo calculated for yeast his3 mRNA (one transcript every 6–
8 s) [40] and with the maximal initiation rate of E. coli RNA
polymerase in vivo (one transcript every 2–3 s) [41].
This work was supported by Ministerio de Ciencia y Tecnolog´ ıa (grants PB98-1627 and
BMC2002-00179). F.M.-C. was a recipient of a predoctoral fellowship from Junta de
Andaluc´ ıa and C.M. was supported by a postdoctoral contract from Junta de Andaluc´ ıa.
We thank J. Madrid-R´ ısquez for technical support and P.O. Brown (Department of
Biochemistry,StanfordUniversitySchoolofMedicine,Stanford,CA,U.S.A.)forproviding
Y262 strain.
REFERENCES
1 Hohmann, S. and Mager, W. H. (1997) Yeast Stress Responses, Springer-Verlag,
Heidelberg
2 Grant, C. M. (2001) Role of the glutathione/glutaredoxin and thioredoxin systems in yeast
growth and response to stress conditions. Mol. Microbiol. 39, 533–541
3 Grant, C. M., MacIver, F. H. and Dawes, I. W. (1997) Glutathione synthetase is
dispensable for growth under both normal and oxidative stress conditions in the yeast
Saccharomyces cerevisiae due to an accumulation of the dipeptide γ-glutamylcysteine.
Mol. Biol. Cell 8, 1699–1707
4 Pedrajas, J. R., Kosmidou, E., Miranda-Vizuete, A., Gustafsson, J. A., Wright, A. P. and
Spyrou, G. (1999) Identification and functional characterization of a novel mitochondrial
thioredoxin system in Saccharomyces cerevisiae. J. Biol. Chem. 274, 6366–6373
5 Park, S. G., Cha, M. K., Jeong, W. and Kim, I. H. (2000) Distinct physiological functions
of thiol peroxidase isoenzymes in Saccharomyces cerevisiae. J. Biol. Chem. 275,
5723–5732
6 Pedrajas, J. R., Miranda-Vizuete, A., Javanmardy, N., Gustafsson, J. A. and Spyrou, G.
(2000) Mitochondria of Saccharomyces cerevisiae contain one-conserved cysteine
type peroxiredoxin with thioredoxin peroxidase activity. J. Biol. Chem. 275,
16296–16301
7 Inoue, Y., Matsuda, T., Sugiyama, K., Izawa, S. and Kimura, A. (1999) Genetic analysis of
glutathione peroxidase in oxidative stress response of Saccharomyces cerevisiae.
J. Biol. Chem. 274, 27002–27009
8 Avery, A. M. and Avery, S. V. (2001) Saccharomyces cerevisiae expresses three
phospholipid hydroperoxide glutathione peroxidases. J. Biol. Chem. 276, 33730–33735
9 Delaunay, A., Pflieger, D., Barrault, M. B., Vinh, J. and Toledano, M. B. (2002) A thiol
peroxidase is an H2O2receptor and redox-transducer in gene activation.
Cell (Cambridge, Mass.) 111, 471–481
10 Jurado, J., Prieto-Alamo, M. J., Madrid-R´ ısquez, J. and Pueyo, C. (2003) Absolute gene
expression patterns of thioredoxin and glutaredoxin redox systems in mouse.
J. Biol. Chem. 278, 45546–45554
11 Nonet, M., Scafe, C., Sexton, J. and Young, R. (1987) Eucaryotic RNA polymerase
conditional mutant that rapidly ceases mRNA synthesis. Mol. Cell. Biol. 7,
1602–1611
12 Burke, D., Dawson, D. and Stearns, T. (2000) Methods in Yeast Genetics, Cold Spring
Harbor Laboratory Press, Plainview, NY
13 Collart, M. A. and Oliviero, S. (1993) Saccharomyces cerevisiae. Preparation of yeast
RNA. In Current Protocols in Molecular Biology, vol. 2 (Ausubel, F. M., Brent, R.,
Kingston, R. E., Moore, D. D., Seidman, J. G., Smith, J. A. and Struhl, K., eds.),
pp. 13.12.1–13.12.2, John Wiley & Sons, Indianapolis, IN
14 Prieto-´Alamo, M. J., Cabrera-Luque, J. M. and Pueyo, C. (2003) Absolute quantitation of
normal and ROS-induced patterns of gene expression: an in vivo real-time PCR study in
mice. Gene Expr. 11, 23–34
15 Pueyo, C., Jurado, J., Prieto-´Alamo, M. J., Monje-Casas, F. and L´ opez-Barea, J. (2002)
Multiplex reverse transcription-polymerase chain reaction for determining transcriptional
regulation of thioredoxin and glutaredoxin pathways. Methods Enzymol. 347, 441–451
16 Wenzel, T. J., Teunissen, A. W. and de Steensma, H. Y. (1995) PDA1 mRNA: a standard for
quantitation of mRNA in Saccharomyces cerevisiae superior to ACT1 mRNA.
Nucleic Acids Res. 23, 883–884
17 Brejning, J., Jespersen, L. and Arneborg, N. (2003) Genome-wide transcriptional changes
during the lag phase of Saccharomyces cerevisiae. Arch. Microbiol. 179, 278–294
18 Gasch, A. P., Spellman, P. T., Kao, C. M., Carmel-Harel, O., Eisen, M. B., Storz, G.,
Botstein, D. and Brown, P. O. (2000) Genomic expression programs in the response of
yeast cells to environmental changes. Mol. Biol. Cell 11, 4241–4257
19 DeRisi, J. L., Iyer, V. R. and Brown, P. O. (1997) Exploring the metabolic and genetic
control of gene expression on a genomic scale. Science 278, 680–686
20 Garrido, E. O. and Grant, C. M. (2002) Role of thioredoxins in the response of
Saccharomyces cerevisiae to oxidative stress induced by hydroperoxides.
Mol. Microbiol. 43, 993–1003
21 Kim, I. H., Kim, K. and Rhee, S. G. (1989) Induction of an antioxidant protein of
Saccharomyces cerevisiae by O2, Fe3+, or 2-mercaptoethanol. Proc. Natl.
Acad. Sci. U.S.A. 86, 6018–6022
22 Parker, R., Herrick, D., Peltz, S. W. and Jacobson, A. (1991) Measurement of mRNA
decay rates in Saccharomyces cerevisiae. Methods Enzymol. 194, 415–423
23 Wang, Y., Liu, C. L., Storey, J. D., Tibshirani, R. J., Herschlag, D. and Brown, P. O. (2002)
Precision and functional specificity in mRNA decay. Proc. Natl. Acad. Sci. U.S.A. 99,
5860–5865
24 Tipper, D. J. (1973) Inhibition of yeast ribonucleic acid polymerases by thiolutin.
J. Bacteriol. 116, 245–256
25 Jimenez, A., Tipper, D. J. and Davies, J. (1973) Mode of action of thiolutin, an inhibitor of
macromolecular synthesis in Saccharomyces cerevisiae. Antimicrob. Agents Chemother.
3, 729–738
26 Kirk, N. and Piper, P. W. (1991) The determinants of heat-shock element-directed lacZ
expression in Saccharomyces cerevisiae. Yeast 7, 539–546
27 Albig, A. R. and Decker, C. J. (2001) The target of rapamycin signaling pathway regulates
mRNA turnover in the yeast Saccharomyces cerevisiae. Mol. Biol. Cell 12, 3428–3438
28 Izawa, S., Maeda, K., Sugiyama, K., Mano, J., Inoue, Y. and Kimura, A. (1999)
Thioredoxin deficiency causes the constitutive activation of Yap1, an AP-1-like
transcription factor in Saccharomyces cerevisiae. J. Biol. Chem. 274, 28459–28465
29 Sugiyama, K., Izawa, S. and Inoue, Y. (2000) The Yap1p-dependent induction of
glutathione synthesis in heat shock response of Saccharomyces cerevisiae.
J. Biol. Chem. 275, 15535–15540
30 Cha, M. K., Choi, Y. S., Hong, S. K., Kim, W. C., No, K. T. and Kim, I. H. (2003) Nuclear
thiol peroxidase as a functional alkyl-hydroperoxide reductase necessary for stationary
phase growth of Saccharomyces cerevisiae. J. Biol. Chem. 278, 24636–24643
31 Sakaki, K., Tashiro, K., Kuhara, S. and Mihara, K. (2003) Response of genes associated
with mitochondrial function to mild heat stress in yeast Saccharomyces cerevisiae.
J. Biochem. (Tokyo) 134, 373–384
32 Boy-Marcotte, E., Lagniel, G., Perrot, M., Bussereau, F., Boudsocq, A., Jacquet, M. and
Labarre, J. (1999) The heat shock response in yeast: differential regulations and
contributions of the Msn2p/Msn4p and Hsf1p regulons. Mol. Microbiol. 33, 274–283
33 Maris, A. F., Assumpc ¸˜ ao, A. L., Bonatto, D., Brendel, M. and Henriques, J. A. (2001)
Diauxic shift-induced stress resistance against hydroperoxides in Saccharomyces
cerevisiae is not an adaptive stress response and does not depend on functional
mitochondria. Curr. Genet. 39, 137–149
34 Jona, G., Choder, M. and Gileadi, O. (2000) Glucose starvation induces a drastic
reduction in the rates of both transcription and degradation of mRNA in yeast.
Biochim. Biophys. Acta 1491, 37–48
35 Hong, S. K., Cha, M. K., Choi, Y. S., Kim, W. C. and Kim, I. H. (2002) Msn2p/Msn4p act
as a key transcriptional activator of yeast cytoplasmic thiol peroxidase II. J. Biol. Chem.
277, 12109–12117
36 Monteiro, G., Pereira, G. A. and Netto, L. E. (2002) Regulation of mitochondrial
thioredoxin peroxidase I expression by two different pathways: one dependent on cAMP
and the other on heme. Free Radical Biol. Med. 32, 278–288
37 Wong, C. M., Ching, Y. P., Zhou, Y., Kung, H. F. and Jin, D. Y. (2003) Transcriptional
regulation of yeast peroxiredoxin gene TSA2 through Hap1p, Rox1p, and Hap2/3/5p.
Free Radical Biol. Med. 34, 585–597
38 Treger, J. M., Schmitt, A. P., Simon, J. R. and McEntee, K. (1998) Transcriptional factor
mutations reveal regulatory complexities of heat shock and newly identified stress genes
in Saccharomyces cerevisiae. J. Biol. Chem. 273, 26875–26879
39 Moskvina, E., Schuller, C., Maurer, C. T., Mager, W. H. and Ruis, H. (1998) A search in the
genome of Saccharomyces cerevisiae for genes regulated via stress response elements.
Yeast 14, 1041–1050
40 Iyer, V. and Struhl, K. (1996) Absolute mRNA levels and transcriptional initiation rates in
Saccharomyces cerevisiae. Proc. Natl. Acad. Sci. U.S.A. 93, 5208–5212
41 Kennell, D. and Riezman, H. (1977) Transcription and translation initiation frequencies of
the Escherichia coli lac operon. J. Mol. Biol. 114, 1–21
Received 21 May 2004/18 June 2004; accepted 29 June 2004
Published as BJ Immediate Publication 29 June 2004, DOI 10.1042/BJ20040851
c ?2004 Biochemical Society