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J. Biol. Chem., Vol. 277, Issue 16, 13983-13988, April 19, 2002
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From the Departments of Biochemistry and
¶ Chemistry, Institute of Chemistry, University of São
Paulo, Avenida Prof. Lineu Prestes 748, São Paulo SP
05508-900, Brazil
Received for publication, August 9, 2001, and in revised form, November 15, 2001
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ABSTRACT |
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 TOP
 ABSTRACT
 INTRODUCTION
EXPERIMENTAL PROCEDURES
RESULTS
DISCUSSION
REFERENCES
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Despite the intense interest in the metabolic
regulation and evolution of the ATP-producing pathways, the long
standing question of why most multicellular microorganisms metabolize
glucose by respiration rather than fermentation remains unanswered. One
such microorganism is the cellulolytic fungus Trichoderma
reesei (Hypocrea jecorina). Using EST analysis and
cDNA microarrays, we find that in T. reesei expression
of the genes encoding the enzymes of the tricarboxylic acid
cycle and the proteins of the electron transport chain is programmed in
a way that favors the oxidation of pyruvate via the tricarboxylic acid
cycle rather than its reduction to ethanol by fermentation. Moreover,
the results indicate that acetaldehyde may be channeled into acetate
rather than ethanol, thus preventing the regeneration of
NAD+, a pivotal product required for anaerobic metabolism.
The studies also point out that the regulatory machinery controlled by
glucose was most probably the target of evolutionary pressure that
directed the flow of metabolites into respiratory metabolism rather
than fermentation. This finding has significant implications for the development of metabolically engineered cellulolytic microorganisms for
fuel production from cellulose biomass.
Evolution has produced a diverse array of metabolic pathways and
regulatory mechanisms that reflect the adaptation of an immense variety
of microorganisms to different environments and nutritional requirements. A prominent example is the metabolism of glucose, the
primary and preferred fuel for eukaryotic microorganisms. Although
glucose is metabolized by a highly conserved series of connected
enzymatic reactions, the mechanisms that regulate its fate and the
properties of the ATP-producing pathways have been subjected to
selection pressure during evolution. Aerobic (respiration) and
anaerobic (fermentation) pathways are used by microorganisms to obtain
energy from glucose, in the form of ATP. These pathways allow organisms
to produce ATP at different rates and with different efficiencies;
respiration proceeds at a lower rate and with a high yield, whereas
fermentation operates at higher rates but with lower yield. Selection
pressure imposed by energy limitation and the high ATP yield of
respiration has been implicated in facilitating the evolutionary
transition from unicellular to undifferentiated multicellular organisms
(1).
Unicellular microorganisms, such as the yeast Saccharomyces
cerevisiae, use both pathways depending on the metabolic state of
the cell, whereas multicellular microorganisms, such as filamentous fungi, preferentially use respiration (2). Mucor racemosus, a dimorphic fungus that can grow either in a unicellular (yeast-like) or a multicellular (mycelial) form, also uses both; the unicellular form exploits fermentation, whereas the multicellular form is capable
of respiration (3-5).
S. cerevisiae preferentially ferments glucose, even in the
presence of oxygen, producing ethanol and CO2 by anaerobic
metabolism. Only after exhaustion of the available glucose is
respiration activated, and the yeast cells then use the ethanol as a
carbon and energy source for aerobic metabolism. The switch from
anaerobic to aerobic metabolism, referred to as the diauxic shift, has
stimulated a profusion of research on metabolic regulation in S. cerevisiae and other eukaryotic microorganisms (6-9). However,
several basic questions remain unanswered. For example, why do
eukaryotic microorganisms other than S. cerevisiae
preferentially obtain energy from glucose by respiration and,
therefore, do not undergo a diauxic shift? What factor(s) determine(s)
this difference and at what molecular level has selection operated? The
answers to these questions will have a critical impact not only on our
basic knowledge of the metabolic regulation of glucose utilization and
its evolution but also on the potential use of eukaryotic
microorganisms for metabolic engineering and the production of useful compounds.
To carry out a comprehensive investigation aimed at understanding these
differences, we have established an EST data base for the filamentous
fungus Trichoderma reesei. Using the complementary DNA
microarray technology we analyzed the gene expression profile during
glucose exhaustion and compared it to the temporal program of gene
expression accompanying the metabolic shift from fermentation to
respiration in S. cerevisiae (6). The fungus T. reesei was chosen for this study because its natural habitats and
nutritional requirements are very different from those of S. cerevisiae. Although relatively high concentrations of sugars
prevail in the natural habitats of S. cerevisiae, the
ubiquitous soil inhabitant T. reesei (10) has adapted to a
nutrient-poor environment in which it exploits extracellular
hydrolases, such as cellulase, to obtain glucose from polysaccharides
(11). In addition, the genus Trichoderma includes species of
economic importance. Enzymes produced by Trichoderma are
used in the textile, food, and paper industries (12-14). Moreover, strains of Trichoderma that produce chitinolytic enzymes are
mycoparasitic and can be used as biocontrol agents against
plant-pathogenic fungi (15).
This report is based on the sequences of the 5' ends of 2835 randomly
selected cDNA clones that corresponded to 1151 unique transcripts.
The complete sequence of the mitochondrial genome of T. reesei is also presented. Putative functions were assigned to
36.0% of these transcripts, unknown proteins represent 3.0%, whereas
61% of the ESTs showed no significant similarity to any other sequence
in the data base, indicating that these sequences are specific to
filamentous fungi and/or T. reesei. We also show that
patterns of glucose-dependent regulation of gene
transcription in S. cerevisiae and T. reesei
differ in regard to critical genes whose products control the direction
of flow of primary metabolites. Although the expression of genes for
products involved in the tricarboxylic acid cycle and in mitochondrial
respiration is repressed strongly in S. cerevisiae in the
presence of glucose, in T. reesei these genes remain active
under these conditions. Thus, in T. reesei, in contrast to
S. cerevisiae, aerobic metabolism prevails in the presence
of high levels of glucose.
Media, Growth Conditions, and Metabolite Analysis--
T.
reesei, strain QM 9414, was obtained from the American Type
Culture Collection (ATCC 26921). A 0.5-liter inoculum (containing 107 spores/ml) was added to a 14-liter fermentation vessel
containing 10 liters of culture medium (16) supplemented with glucose
at a final concentration of 100 mM. The culture was
maintained at 28 °C with constant agitation and aeration. Aliquots
of the culture were withdrawn, as indicated, and mycelium was collected
by filtration and frozen in liquid nitrogen.
Glucose concentration in the culture supernatants was measured using a
SERA-PAK kit (Bayer). Ethanol in the culture supernatants and acetate
were measured enzymatically using the TC acetic acid and TC ethanol
kits obtained from Roche Molecular Biochemicals.
cDNA Library--
Total cellular RNA was extracted from
glycerol-grown T. reesei cultures by the guanidium
isothiocyanate procedure (17), and poly(A)+ RNA was
purified using oligo(dT) chromatography. A unidirectional cDNA
library was constructed in the Uni-ZAP XR vector. In vivo excision of pBluescript plasmids was performed in Escherichia coli SOLR (Stratagene). To assess the quality of the library, the
ratio of recombinants to non-recombinants and the average size of the
cDNA inserts were determined by PCR analysis of the DNA from 96 individual clones.
DNA Sequencing--
Mitochondrial DNA was isolated by cesium
chloride/bisbenzimide density gradient centrifugation (18). Shotgun
libraries were constructed from sheared mitochondrial DNA cloned into
pUC18. Plasmid DNA from individual colonies was prepared with the
Concert rapid plasmid miniprep system (Invitrogen), and DNA sequencing reactions were performed using the BigDye terminator cycle sequencing kit (PerkinElmer Life Sciences) and the M13 reverse and M13 ( Computational Analysis--
Sequences were edited for each EST
using the program phred+phrap+consed (19-21). Only ESTs with a minimum
length of 150 bases and a phred quality value of at least 20 were considered for further analysis. Edited sequences were translated
and used as query sequences to search the GenBankTM
non-redundant protein data base by using the program BLASTX (22) at the
National Center for Biotechnology Information (NCBI). Scores Microarray Analysis--
Inserts were amplified by PCR in a
96-well format using M13 reverse and M13 ( cDNA Library Analysis--
A unidirectional cDNA library
was constructed from mycelia of T. reesei, grown on glycerol
as the sole carbon source as described under "Experimental
Procedures." The library was named TrEST-A, and we randomly selected
4320 clones for sequencing. PCR analysis of 96 individual clones
revealed that 99% produced an amplification product with an average
size of 1.2 kb. We obtained 2835 ESTs with a minimum length of 150 bases and a Phred quality value of at least 20. Of the 2835 ESTs, 808 sequences remained as singletons, and 2027 sequences formed 343 clusters. Therefore, this analysis shows that we obtained the partial
sequences of 1151 expressed genes of T. reesei. The clusters
ranged in size from 2 (177 clusters) to 90 (1 cluster) sequences.
Using BLASTX (22) and a stringency score Gene Expression Analysis during Glucose Exhaustion--
Homology
searches using the sequenced cDNAs against the
GenBankTM data base revealed that sufficient coverage had
been achieved to allow a comprehensive study of the gene expression
profile during glucose exhaustion. Using complementary DNA microarray technology we analyzed the expression of the available set of T. reesei genes after attachment to glass slides. We compared transcript populations from cells harvested when glucose reached 83 mM to those expressed at various times as the glucose level declined (Fig. 2). Fluorescently labeled
cDNA was prepared from mRNA isolated from cells at 83 mM glucose in the presence of Cy3 (green)-labeled dUTP and
from mRNA obtained at 46, 11, 1, and 0 mM glucose in
the presence of Cy5 (red)-labeled dUTP. The labeled cDNAs were
mixed and hybridized, in duplicate, to the microarrays.
The first striking finding was that many genes coding for enzymes of
the tricarboxylic acid cycle were not repressed in glucose-rich medium,
and those that were, citrate synthase and
The abundances of transcripts encoding enzymes of the glycolytic
pathway in T. reesei were either unaffected or, in some
cases, decreased slightly upon glucose exhaustion. The gene encoding enolase, however, is highly expressed in the presence of glucose-rich medium and is markedly repressed on depletion of the sugar. Thus, as in
S. cerevisiae, up-regulation of the glycolytic transcripts in the presence of glucose will increase the flow of metabolites through the glycolytic pathway to yield pyruvate. The flow of metabolites in this direction is facilitated by the fact that two
enzymes involved in the first steps of the pentose phosphate pathway,
glucose-6-phosphate dehydrogenase and 6-phosphogluconate dehydrogenase,
are expressed only at relatively low levels in the presence of glucose
(Fig. 3).
However, a striking difference between the two microorganisms concerns
the fate of pyruvate, as is evident from the pattern of expression of
the transcripts of the genes for tricarboxylic acid cycle enzymes seen
upon depletion of glucose. Whereas high concentrations of glucose
strongly repress genes encoding enzymes of the tricarboxylic acid cycle
cycle in S. cerevisiae, the corresponding transcripts in
T. reesei behave quite differently. We have identified the
genes for 5 of the 8 successive reaction steps in the tricarboxylic acid cycle. Glucose partially represses expression of the genes for
citrate synthase and
A second difference between the two species concerns the
fate of the acetaldehyde formed by the decarboxylation of pyruvate by
pyruvate decarboxylase, which is up-regulated in both microorganisms in
the presence of glucose. In S. cerevisiae, the acetaldehyde formed is reduced to ethanol by NADH in a reaction catalyzed by alcohol
dehydrogenase and is not converted to acetate due to the strong
repression of aldehyde dehydrogenase by glucose. This step is essential
for anaerobic metabolism because it generates the NAD+ that
is required for glycolysis to continue. In T. reesei we have
identified two paralogous genes for aldehyde dehydrogenase, the ALD2
transcript is strongly repressed by glucose, but ALD1 is not affected.
If both enzymes have comparable specificity, then acetaldehyde will be
converted to acetate in T. reesei even in the presence of
glucose. To address this question, we measured the concentration of
ethanol and acetate after the addition of a high concentration of
glucose to T. reesei culture grown in the presence of
glycerol. The results show that, in contrast to S. cerevisiae, ethanol concentration did not change, whereas the concentration of acetate increased upon the addition of glucose (Fig.
5). This result indicates that, although
one of the two paralogous genes for aldehyde dehydrogenase is repressed
by glucose, acetate will be produced in the presence of a high
concentration of glucose.
Upon exhaustion of glucose, the activation of the gene encoding
acetyl-coenzyme A synthase will allow the entry of acetate, produced
via the pyruvate bypass route, to replenish the tricarboxylic acid
cycle. Under these conditions, the genes encoding phosphoenolpyruvate carboxykinase will also be activated, allowing the tricarboxylic acid
cycle intermediates to flow via oxalacetate to fuel the gluconeogenic pathway (Fig. 4).
We validated the expression of selected genes involved in the metabolic
pathways controlling the utilization of glucose by Northern analysis.
The results are presented in Fig. 6 and
were found to be in agreement with the results obtained from the
microarrays.
Mitochondrial Activity--
Aerobic metabolism
requires the expression of proteins involved in mitochondrial activity
and the flow of electrons and protons through the complex of
respiratory chain proteins that are encoded by mitochondrial and
nuclear genes. Therefore, to determine whether transcripts encoded by
the mitochondrial genome of T. reesei are subject to strong
repression by glucose, as in S. cerevisiae, the complete
sequence of the mitochondrial genome of the filamentous fungus was
determined. The 42,130-bp circular mitochondrial DNA encodes 15 polypeptides, 2 rRNAs, and 25 tRNAs, all of which are transcribed from
the same DNA strand (Fig. 7A).
We have measured the abundance of several RNAs transcribed from
different parts of the mitochondrial genome. The probes used are
indicated in Fig. 7A and included three synthetic
oligonucleotides complementary to gene sequences for cytochrome
c oxidase polypeptide III (COX III) and for subunits 2 and 5 of NADH ubiquinone oxidoreductase (ND2, ND5). The transcripts are
abundant in the presence of glucose (Fig. 7B), and levels
increase only slightly upon glucose depletion, indicating that
glucose-rich medium does not strongly repress mitochondrial gene
expression in T. reesei, unlike the case in S. cerevisiae (26, 27). We were also interested in determining whether the transcripts of the nuclear genes encoding the mitochondrial polypeptides V and VI of cytochrome c oxidase (COX V and COX
VI), which are also repressed strongly by glucose in S. cerevisiae, would respond to glucose similarly to the transcripts
of the mitochondrially encoded genes. The results presented in Fig.
7C show that, indeed, the COX V and VI transcripts are
expressed at a level comparable to the mitochondrially encoded COX III,
ND2, and ND5 RNAs (Fig. 7, B and C). Together,
these data indicate that, in contrast to the case in S. cerevisiae, respiration in T. reesei is repressed only
partially, if at all, in the presence of high concentrations of
glucose. In other words, T. reesei will respire in the
presence of glucose-rich medium, whereas the respiratory pathway in
S. cerevisiae is repressed under the same metabolic
conditions.
The transcript profiles of T. reesei during glucose
exhaustion presented in this report provide a description of the
molecular basis of the shunting of the end product of the glycolytic
pathway, pyruvate, into aerobic rather than anaerobic metabolism. They have obvious implications for the long standing question of why some
eukaryotic microorganisms, such as T. reesei, utilize
glucose by aerobic metabolism. First, in the presence of glucose-rich medium, the expression of the genes encoding the enzymes of the tricarboxylic acid cycle will allow the available pyruvate to fuel the
tricarboxylic acid cycle. In addition, pyruvate can be converted to
acetaldehyde and then to acetate via the pyruvate bypass route.
Furthermore, the conversion of acetaldehyde to acetate and not to
ethanol as in S. cerevisiae precludes the generation of the
NAD+ required for anaerobic metabolism. Second, analysis of
the expression of several mitochondrial and nuclear gene-encoding
proteins involved in mitochondrial respiration confirms that T. reesei is able to carry out respiration in glucose-rich medium.
Regulation of gene transcription by glucose in S. cerevisiae
and T. reesei therefore differs with respect to critical
genes, the products of which control the direction of the flow of
metabolites. Although the expression of genes involved in the
tricarboxylic acid cycle and in mitochondrial respiration is repressed
strongly in S. cerevisiae in the presence of glucose, in
T. reesei these genes remain active under these conditions.
Thus, aerobic metabolism will prevail in T. reesei in the
presence of glucose-rich medium. The gene expression profile described
for T. reesei in this work is most probably also used by
other multicellular microorganisms to obtain energy by respiration,
rather than fermentation, in the presence of high levels of glucose.
The fact that, in Aspergillus nidulans, the cytochrome
c gene (cycA) is also not repressed by glucose (28) supports this contention.
In S. cerevisiae and Kluyveromyces lactis, the
main regulatory effect of glucose occurs at the transcriptional level
(8, 29). This also seems to be the case in T. reesei because
the primary effect is on the level of mRNA of critical steps
directing the flow of metabolites to aerobic rather than anaerobic
metabolism, corresponding well with the fact that T. reesei
is a preferentially respiratory micoorganism. Future analysis of
metabolic flux using 13C should be of great value to
accompany the metabolic gene expression studies reported in our work.
Metabolic engineering of eukaryotic cells for the production of useful
compounds represents a formidable challenge. However, the power of this
approach is evident from the recent report that an obligate
photosynthetic microalga can be converted into a heterotrophic organism
by introducing a human gene that encodes a glucose transporter (30).
T. reesei is capable of hydrolyzing cellulose to glucose (11). The gene expression profile described in this report provides valuable information for the metabolic engineering necessary to turn
this preferentially respiratory microorganism into a fermenter, a step
that will be required if T. reesei is to be used for the efficient production of ethanol fuel from cellulose biomass.
Finally, it is believed that multicellular organisms capable of
respiration arose from unicellular fermenters early in the course of
evolution, after the concentration of oxygen in the atmosphere began to
rise and following the engulfment of aerobic bacteria that evolved into
mitochondria (31). It is not surprising, therefore, that the molecular
alterations in response to glucose, which determined the switch from
fermentation to respiration, are observed in both nuclear and
mitochondrial genes coding for mitochondrial enzymes and proteins.
Because effectors specific for glucose repression are conserved in
yeast and filamentous fungi (32), the crucial alterations most probably
occurred in the target sequences for the glucose repressor in the
promoters of the relevant genes, which prevented the binding of repressor.
INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
EXPERIMENTAL PROCEDURES
RESULTS
DISCUSSION
REFERENCES
EXPERIMENTAL PROCEDURES
TOP
ABSTRACT
INTRODUCTION
EXPERIMENTAL PROCEDURES
RESULTS
DISCUSSION
REFERENCES
20) primers (Stratagene). For
ESTs,1 single-pass sequences
of the 5' ends of cDNAs were performed. Samples were loaded on an
ABI 377 DNA sequencer (PerkinElmer Life Sciences) for automated
sequence analysis.
80 were
considered to be significant, and the top-scoring genes were used to
group the transcripts by their putative function. For computational and
graphical analysis of the microarrays data we employed the Cluster and
TreeView programs (23). Mitochondrial DNA consensus was generated by
phred+phrap+consed (19-21). ORFs were predicted by ORF finder (NCBI)
and searched against the GenBankTM non-redundant protein
data base using the program BLASTP (22). tRNAs and rRNAs were located
using tRNAscan-S.E. v.1.11 program (24) and BLASTN, respectively
(22).
20) primers (Stratagene).
PCR products were then purified in a 96-well filtration plate using the
Millipore MultiScreen Assay System. Each PCR product was verified by
agarose gel electrophoresis and was considered correct if the amplified product resulted in a single band. These DNAs were spotted on glass
slides and hybridized with fluorescently labeled cDNA prepared by
reverse transcription in the presence of Cy3 or Cy5-labeled deoxyuridine triphosphate (Glass fluorescent kit;
CLONTECH). cDNA prepared from cells harvested
at 83 mM glucose was labeled with Cy3 (reference
sample), and those prepared at each later time were
labeled with the Cy5 fluor. Hybridization, image analysis, and
integration were performed with a GeneTac hybridization station, GeneTac biochip analyzer, and GeneTac integrator 3.0.1 (Genomic Solutions, www.genomicsolutions.com)
RESULTS
TOP
ABSTRACT
INTRODUCTION
EXPERIMENTAL PROCEDURES
RESULTS
DISCUSSION
REFERENCES
80, the total number of ESTs
that could be assigned a cellular role on the basis of sequence
similarity to proteins with known function was 348. The remaining ESTs
are either unclassified (52 sequences), show similarity to sequences of
unknown function (19 sequences), or have no significant similarity to
any protein sequences in the data bases (no matches, 732 sequences).
Those ESTs that encode putative protein sequences that show similarity
to products in the NCBI non-redundant data base were classified into
functional groups (Fig. 1). The
functional groups presented in Fig. 1 are principally based on the
classification developed at the Institute for Genomic Research
(TIGR, Rockville, MD; available at
www.tigr.org/docs/tiger-scripts/ egad_scripts/role_report.spl)
(25). The complete list of ESTs classified into functional groups
is available through the Internet (trichoderma.iq.usp.br/TrEST.html).
Most of the known transcripts belong to groups related to housekeeping
genes such as those involved in metabolism (14%), protein synthesis
(9%), and RNA synthesis (2%). The high percentage of the ESTs that
showed no hits (61%) most probably reflect the absence in the data
base of a completely sequenced genome related to filamentous fungi. In
fact the data base contains just 98 sequences from T. reesei. Therefore, our data represent an increase of more than
10-fold in the number of T. reesei expressed genes in the
data base.
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Fig. 1.
Classification of the 1151 unique transcripts
of T. reesei. ESTs with BLASTX scores greater
than 80 are presented according to the classification developed at the
Institute for Genomic Research (TIGR, Rockville, MD) (25).
UNCLASSIFIED are those ESTs that show similarity to a
sequence with known function but do not fall into any of the
classification schemes utilized; UNKNOWN refers to those
sequences that show similarity to protein or DNA sequences to which no
cellular role has yet been assigned; NO MATCHES indicates
new sequences with no significant similarity to protein or DNA
sequences in the data bases.
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Fig. 2.
Glucose concentration and cell density
profiles during growth of T. reesei in glucose-rich
medium. An inoculum containing 0.5 × 1010 spores
was poured into a fermentation vessel containing 10 liters of culture
medium (see "Experimental Procedures" for details). Aliquots of the
culture were withdrawn at different glucose concentrations as indicated
by the vertical arrows. Cell density ( 
) was measured
after filtration of culture aliquots through Whatman paper (No. 3 MM
Chr) and drying overnight at 80 °C. Glucose concentrations (
)
were measured using a SERA-PAK kit (Bayer).
-ketoglutarate dehydrogenase, were only partially repressed. We identified 14 genes
that are expressed at 2-fold higher levels as glucose is depleted
from the growth medium (Fig. 3). An
overall view of the changes in the expression of genes involved in the
metabolic pathways controlling the utilization of glucose in T. reesei is shown in Fig. 4. For
purposes of comparison we also present the same portions of the
metabolic pathways of S. cerevisiae as reported previously by DeRisi et al. (6).
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Fig. 3.
Expression profile of genes repressed by
glucose. Clustered expression profiles for the 14 genes
that are expressed at >2-fold higher levels as glucose is depleted
from the growth medium. The Cluster and TreeView programs were employed
for data analysis (23).
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Fig. 4.
Comparison of the expression profiles of
genes for enzymes that participate in key metabolic processes involved
in the utilization of metabolites during glucose exhaustion in T. reesei and S. cerevisiae. To
facilitate comparison between the two microorganisms we present the
same portions of the metabolic pathways of S. cerevisiae,
and the behavior of genes encoding the enzymes that catalyze each step
as presented by DeRisi et al. (6). Red and
green boxes represent those genes whose expression increases
and decreases, respectively, upon glucose exhaustion. White
boxes indicate those genes that are unaffected. Yellow
boxes represent genes that have yet been not isolated from
T. reesei. The ADH gene has not been isolated; however,
activities of alcohol dehydrogenase in both directions were detected
and measured in T. reesei extracts (33).
-ketoglutarate dehydrogenase, whereas those for
isocitrate dehydrogenase, succinate dehydrogenase, and malate
dehydrogenase are unaffected (Fig. 4). If expression of these enzymes
are controlled mainly at the transcriptional level, then pyruvate will
be oxidized because of the higher level of expression of the
tricarboxylic acid cycle mRNAs when glucose concentration is high.
In contrast, in S. cerevisiae, pyruvate is channeled to
acetaldehyde under these conditions, as a result of the strong
repression of transcription of the genes for enzymes of the
tricarboxylic acid cycle by glucose.
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Fig. 5.
Production of ethanol and acetate in T. reesei after the addition of glucose. T. reesei cells were grown in a culture medium (16) containing
glycerol as a sole carbon source. The mycelia were centrifuged, washed,
and suspended in a culture medium lacking carbon sources. Glucose was
added (time 0 min) to a final concentration of 2%, and the culture was
incubated on a rotary shaker (200 rpm) at 28 °C. Aliquots were
withdrawn at the indicated time, and the concentrations of ethanol
( ) and acetate (
) were measured. For comparison, we also measured
the production of ethanol () by S. cerevisiae upon
addition of glucose to a final concentration of 2%. For details see
"Experimental Procedures."
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Fig. 6.
Effect of glucose on the expression of the
transcripts of critical genes involved in glucose metabolism.
Aliquots containing 10 µg of RNA were isolated from cells harvested
when glucose concentration reached 83 and 0 mM during
growth of T. reesei in glucose-rich medium (refer to Fig.
2). RNAs were fractionated electrophoretically on a 1.2% agarose gel,
transferred to Hybond-N membranes, and hybridized with labeled probes
as indicated. The actin transcript (ACT) is included as a
control (34).
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Fig. 7.
Map of T. reesei mtDNA and
effect of glucose on the expression of mitochondrial and nuclear
transcripts coding for mitochondrial proteins. A, the
unique direction of transcription is indicated by the arrow
above the map; exons are presented as filled boxes and
introns as open boxes. Genes that were used for Northern
analysis are marked in red. B, Northern blot
showing the effect of glucose concentration on the level of the
transcripts (marked in red in A) of the genes for
cytochrome c oxidase subunit III (COX III) and subunits 2 and 5 of NADH-ubiquinone oxidoreductase (ND2, ND5). Synthetic
oligonucleotides complementary to these genes were used as probes.
C, Northern blot showing the effect of glucose concentration
on the level of transcripts of the nuclear genes coding for COX V and
COX VI. The actin transcript (ACT) is included as a control
(34).
DISCUSSION
TOP
ABSTRACT
INTRODUCTION
EXPERIMENTAL PROCEDURES
RESULTS
DISCUSSION
REFERENCES
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ACKNOWLEDGEMENT |
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We thank Boris Stambuk for valuable discussions.
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FOOTNOTES |
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* This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo Grants Genoma-FAPESP 97/13461-1, FAPESP 97/5267-0, and PADCT-CNPq 62.0533/98-6.The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
The nucleotide sequence(s) reported in this paper has been submitted to the GenBankTM/EBI Data Bank with accession number(s) BM076169-BM077297 (EST) and AF447590 (mtDNA).
This work is dedicated to Professor Metry Bacila on his 80th birthday.
§ Present address: Dept. of Biochemical and Pharmaceutical Technology, Pharmaceutical Sciences School, University of São Paulo, São Paulo SP 05508-900, Brazil.
To whom correspondence should be addressed. Tel.:
55-11-3091-3848; Fax: 55-11-3091-3848; E-mail address:
dorry@iq.usp.br.
Published, JBC Papers in Press, February 1, 2002, DOI 10.1074/jbc.M107651200
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ABBREVIATIONS |
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The abbreviation used is: EST, expressed sequence tag.
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REFERENCES |
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TOP
ABSTRACT
INTRODUCTION
EXPERIMENTAL PROCEDURES
RESULTS
DISCUSSION
REFERENCES
|
|---|
| 1. |
Pfeiffer, T.,
Schuster, S.,
and Bonhoeffer, S.
(2001)
Science
292,
504-507 |
| 2. |
Kelly, J. M.,
Drysdale, M. R.,
Sealy-Lewis, H. M.,
Jones, I. G.,
and Lockington, R. A.
(1990)
Mol. Gen. Genet.
222,
323-328[CrossRef][Medline]
[Order article via Infotrieve] |
| 3. |
Schulz, B. E.,
Kraepelin, G.,
and Hinkelmann, W.
(1974)
J. Gen. Microbiol.
82,
1-13[Medline]
[Order article via Infotrieve] |
| 4. |
Rogers, P. J.,
Clark-Walker, G. D.,
and Stewart, P. R.
(1974)
J. Bacteriol.
119,
282-293 |
| 5. |
Inderlied, C. B.,
and Sypherd, P. S.
(1978)
J. Bacteriol.
133,
1282-1286 |
| 6. |
DeRisi, J. L.,
Iyer, V. R.,
and Brown, P. O.
(1997)
Science
278,
680-686 |
| 7. |
Kuhn, K. M.,
DeRisi, J. L.,
Brown, P. O.,
and Sarnow, P.
(2001)
Mol. Cell. Biol.
21,
916-927 |
| 8. |
Zeeman, A. M.,
Kuyper, M.,
Pronk, J. T.,
van Dijken, J. P.,
and Steensma, H. Y.
(2000)
Yeast
16,
611-620[CrossRef][Medline]
[Order article via Infotrieve] |
| 9. |
Flores, C. L.,
Rodriguez, C.,
Petit, T.,
and Gancedo, C.
(2000)
FEMS Microbiol. Rev.
24,
507-529[Medline]
[Order article via Infotrieve] |
| 10. | Eveleigh, D. E. (1985) in The Biology of Industrial Organisms (Demain, A. L. , and Solomon, N., eds) , p. 487, Benjamin/Cummings Co., Menlo Park, CA |
| 11. |
Beguin, P.
(1990)
Annu. Rev. Microbiol.
44,
219-248[CrossRef][Medline]
[Order article via Infotrieve] |
| 12. | Godfrey, T. (1996) in Industrial Enzymology (Dodfrey, T. , and West, S., eds), 2nd Ed. , pp. 361-371, Macmillan, Basingstoke, United Kingdom |
| 13. | Oksanen, J., Ahvenainen, J., and Home, S. (1985) Proc. Eur. Brew. Chem. 419-425 |
| 14. | Bailey, M., Buchert, J., and Viikari, L. (1993) in Proceedings of the 2nd TRICEL Symposium (Suominen, P., and Reinikainen, P., eds) (1993) Vol. 8, pp. 255-262, Foundation for Biotechnical and Industrial Fermentation Research, Espoo, Finland |
| 15. | Chet, I. (1987) in Innovative Approaches to Plant Disease Control (Chet, I., ed) , pp. 137-160, Wiley, New York |
| 16. |
El-Gogary, S.,
Leite, A.,
Crivellaro, O.,
Eveleigh, D. E.,
and El-Dorry, H.
(1989)
Proc. Natl. Acad. Sci. (U. S. A.)
86,
6138-6141 |
| 17. |
Chirgwin, J. M.,
Przybyla, A. E.,
MacDonald, R. J.,
and Rutter, W. J.
(1979)
Biochemistry
18,
5294-5299[CrossRef][Medline]
[Order article via Infotrieve] |
| 18. |
Garber, R. C.,
and Yoder, O. C.
(1983)
Anal. Biochem.
135,
416-422[Medline]
[Order article via Infotrieve] |
| 19. |
Ewing, B.,
Hillier, L.,
Wendl, M. C.,
and Green, P.
(1998)
Genome Res.
8,
175-185 |
| 20. |
Ewing, B.,
and Green, P.
(1998)
Genome Res.
8,
186-194 |
| 21. |
Gordon, D.,
Abajian, C.,
and Green, P.
(1998)
Genome Res.
8,
195-202 |
| 22. |
Altschul, S. F.,
Gish, W.,
Miller, W.,
Myers, E. W.,
and Lipman, D. J.
(1990)
J. Mol. Biol.
215,
403-410[CrossRef][Medline]
[Order article via Infotrieve] |
| 23. |
Eisen, M. B.,
Spellman, P. T.,
Brown, P. O.,
and Botstein, D.
(1998)
Proc. Natl. Acad. Sci. (U. S. A.)
95,
14863-14868 |
| 24. |
Lowe, T. M.,
and Eddy, S. R.
(1997)
Nucleic Acids Res.
25,
955-964 |
| 25. |
White, O.,
and Kerlavage, A. R.
(1996)
Methods Enzymol.
266,
27-40[Medline]
[Order article via Infotrieve] |
| 26. |
Ulery, T. L.,
Jang, S. H.,
and Jaehning, J. A.
(1994)
Mol. Cell. Biol.
14,
1160-1170 |
| 27. |
Costanzo, M. C.,
and Fox, T. D.
(1990)
Annu. Rev. Genet.
24,
91-113[CrossRef][Medline]
[Order article via Infotrieve] |
| 28. |
Raitt, D. C.,
Bradshaw, R. E.,
and Pillar, T. M.
(1994)
Mol. Gen. Genet.
242,
17-22[CrossRef][Medline]
[Order article via Infotrieve] |
| 29. |
Gancedo, J. M.
(1998)
Microbiol. Mol. Biol. Rev.
62,
334-361 |
| 30. |
Zaslavskaia, L. A.,
Lippmeier, J. C.,
Shih, C.,
Ehrhardt, D.,
Grossman, A. R.,
and Apt, K. E.
(2001)
Science
292,
2073-2075 |
| 31. | Margulis, L. (1981) Symbiosis in Cell Evolution , Freeman, San Francisco |
| 32. |
Ronne, H.
(1995)
Trends Genet.
11,
12-17[CrossRef][Medline]
[Order article via Infotrieve] |
| 33. | Beutler, H. O. (1984) in Methods of Enzymatic Analysis (Bergmeyer, H. U., ed), 3rd Ed., Vol. 4 , pp. 598-606, Verlag Chemie, Deerfield Beach, FL |
| 34. |
Matheucci, E., Jr.,
Henrique-Silva, F., El-,
Gogary, S.,
Rossini, C. H.,
Leite, A.,
Vera, J. E.,
Urioste, J. C.,
Crivellaro, O.,
and El-Dorry, H.
(1995)
Gene
161,
103-106[Medline]
[Order article via Infotrieve] |
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