Based on the metabolic reconstruction, a stoichiometric model was set up that includes 284 metabolites and 335 reactions, of which 268 represent biochemical conversions and 67 represent
Trang 1Reconstruction of the central carbon metabolism
Helga David, Mats A˚kesson and Jens Nielsen
Center for Process Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs Lyngby, Denmark
The topology of central carbon metabolism of Aspergillus
nigerwas identified and the metabolic network
reconstruc-ted, by integrating genomic, biochemical and physiological
information available for this microorganism and other
related fungi The reconstructed network may serve as a
valuable database for annotation of genes identified in future
genome sequencing projects on aspergilli Based on the
metabolic reconstruction, a stoichiometric model was set up
that includes 284 metabolites and 335 reactions, of which 268
represent biochemical conversions and 67 represent
trans-port processes between the different intracellular
compart-ments and between the cell and the extracellular medium
The stoichiometry of the metabolic reactions was used in
combination with biosynthetic requirements for growth
and pseudo-steady state mass balances over intracellular metabolites for the quantification of metabolic fluxes using metabolite balancing This framework was employed to perform an in silico characterisation of the phenotypic behaviour of A niger grown on different carbon sources The effects on growth of single reaction deletions were assessed and essential biochemical reactions were identified for different carbon sources Furthermore, application of the stoichiometric model for assessing the metabolic capabilities
of A niger to produce metabolites was evaluated by using succinate production as a case study
Keywords: Aspergillus niger; metabolic reconstruction; flux balance analysis; functional genomics
Filamentous fungi are important organisms for the
pro-duction of industrial enzymes, speciality chemicals and
pharmaceuticals Moreover, they play a major role for
human welfare as agents of biodegradation, spoilage and
decay, and some filamentous fungi act as pathogens for
humans, animals and plants, being responsible for a large
number of deaths and substantial losses in the agricultural
sector annually For these reasons it has been decided
recently to sequence several species of filamentous fungi
(http://gene.genetics.uga.edu/white_papers/anidulans.html)
In order to identify possible targets for drugs that may treat
medical mycoses and to identify better fungicides that may
prevent biodeterioration and against plant pathogenicity in
agriculture, it will be of significant value to reconstruct the map of fungal metabolism, as this will give new insight into cellular function A metabolic map will also be very useful for the design of improved producing strains that may then
be constructed through metabolic engineering [1] The budding yeast, Saccharomyces cerevisiae, is probably the best understood fungus and the eukaryotic model organism par excellence Even though it represents a valuable starting point, yeast is not an adequate model for analysing overall cell function of filamentous fungi as the latter exhibit more genes and larger genomes, endowing them with more extensive metabolic capabilities
A key model system for filamentous fungi is Aspergillus nidulans, for which many specific mutants are available Furthermore, several species of aspergilli are of industrial importance, as producers of a wide array of products that range from metabolites, such as organic acids (e.g citric acid, A niger [2]) and polyketides (e.g statins, A terreus [3]),
to proteins, both homologous (e.g a-amylase, A oryzae [4]) and heterologous (e.g human interferon, A nidulans [5]) Besides their industrial relevance, some species of aspergilli can cause infections in humans and animals, namely allergic
or invasive bronchopulmonary aspergillosis (A fumigatus,
A terreus), pulmonary aspergilloma (A niger) and sinusitis (A flavus) ([6], http://www.Aspergillus.man.ac.uk) Further-more, powerful genetic, biochemical and molecular bio-logical techniques are available for analysis of cellular function in these organisms, and introduction of directed genetic modifications in aspergilli may hereby be used to design efficient cell factories through metabolic engineering for production of different industrially important products
in the future [1,7,8]
Correspondence to J Nielsen, Center for Process Biotechnology,
BioCentrum-DTU, Building 223, Technical University of Denmark,
DK-2800 Kgs Lyngby, Denmark.
Fax: + 45 4588 4148, Tel.: + 45 4525 2696,
E-mail: jn@biocentrum.dtu.dk
Enzymes: transketolase (EC 2.2.1.1); NADPH-dependent L -xylulose
reductase (EC 1.1.1.10); glutamine-fructose-6-phosphate transaminase
(isomerising; EC 2.6.1.16); and chitin synthase (EC 2.4.1.16);
gluco-samine-phosphate N-acetyltransferase (EC 2.3.1.4);
phosphoacetyl-glucosamine mutase (EC 5.4.2.3); UDP-N-acetylphosphoacetyl-glucosamine
pyrophosphorylase (EC 2.7.7.23); D -xylulose reductase (NADH- and
NADPH-dependent) (EC 1.1.1.9); mannitol-2-dehydrogenase
(NADP + -dependent) (EC 1.1.1.138); NADP + -dependent isocitrate
dehydrogenase (EC 1.1.1.42); pyruvate decarboxylase (EC 4.1.1.1);
ATP/citrate oxaloacetate-lyase (EC 4.1.3.8).
(Received 4 June 2003, revised 14 August 2003,
accepted 20 August 2003)
Trang 2Several efforts have been made for the understanding and
the quantitative description of the metabolism of A niger
during citric acid producing conditions In concrete,
experimental techniques, such as 13C-NMR analysis [9],
and modelling strategies, namely metabolic flux analysis [10]
and other mass balance and energy balance techniques [11],
as well as biochemical system theory [12], have been applied
to quantitatively describe citric acid production and assist
in the design of improved producing strains However, no
comprehensive model is available for the analysis of the
central carbon metabolism of this microorganism, which is
essential for a rational optimisation approach
Lately, detailed metabolic models, largely based on
genomic sequence information, have been developed for
microorganisms whose genomes have been sequenced and
annotated The modelled organisms include the
prokary-otes Haemophilus influenzae [13], Escherichia coli [14],
Helicobacter pylori [15] and most recently the eukaryote,
Saccharomyces cerevisiae [16] In spite of, or rather
because of, its economic importance, there is currently
no publicly available genome sequence for A niger;
however, although scattered, there is a considerable
amount of biological knowledge in the literature In this
work, we present a comprehensive reconstruction of the
central carbon metabolism of A niger that served as a
basis for the development of a detailed stoichiometric
model consisting of 335 reactions and 284 metabolites
distributed over three intracellular compartments (cytosol,
mitochondria and glyoxysomes) and the extracellular
medium The metabolic model was used for the
quanti-fication of fluxes through the branches of the metabolic
network Herein, metabolite balancing was applied in
combination with linear optimisation methods to perform
an in silico characterisation of the phenotypic behaviour of
A niger, under different environmental and genetic
con-ditions, and to investigate its biochemical capabilities for
metabolite production
Materials and methods
Computational protocol
The quantification of metabolic fluxes was accomplished
using metabolite balancing Reactions from the metabolic
reconstruction were incorporated into a stoichiometric
model that consisted of a set of algebraic equations
representing material balances over intracellular metabolites
in the metabolic network, assuming pseudo-steady state in
the metabolite concentrations and negligible dilution effects
from growth [17–19] The stoichiometric model is
conveni-ently represented in matrix form as
S v ¼ 0 where, the matrix S contains the stoichiometric
coeffi-cients and the vector v represents the fluxes in the
metabolic reactions As the number of reactions is
typically greater than the number of intracellular
metabolites, the system of equations comprising the
stoichiometric model is underdetermined and an infinity
of feasible flux distributions exists In computational
studies, a particular flux distribution can be found by
formulating a suitable objective function and using
linear optimisation [20], often referred to as flux balance analysis [21] The linear programming problem was formulated as
max z¼ cTv s.t Sv ¼ 0
ai vi bi where, the vector c specifies the importance of the individual fluxes in the objective z The linear inequali-ties (ai,bi) are used to define additional constraints on the individual fluxes, including information on reversi-bility, measured substrate uptake or product formation rates, etc In what concerns reversibility, fluxes corres-ponding to reversible reactions are allowed to be positive
or negative, whereas fluxes corresponding to irreversible reactions can only have positive values
Unless otherwise stated, growth was simulated by opti-misation of flux to biomass for a specified uptake rate of a selected carbon source Other substrates, such as ammonia, sulphate, phosphate, oxygen, etc., could be taken up freely All major metabolic products (carbon dioxide, organic acids, alcohols, amino acids, etc.) were allowed to be excreted Linear programming calculations were performed using commercially available software,LINDO CALLABLE LIBRARY
(Lindo Systems, Inc., Chicago, IL, USA) andOPTIMIZATION TOOLBOXinMATLAB6.1 (The Mathworks, Inc.)
Results and discussion
Reconstruction process The metabolic reconstruction aims at depicting a detailed description of the central carbon metabolism of A niger, namely of the metabolism of carbohydrates, organic acids, polyols and other alcohols, and amino-sugars, as well as the oxidative phosphorylation in the electron transport chain Information was gathered through an extensive survey of literature, including scientific articles and biochemistry textbooks, and of on-line databases Integration of different types of information, namely genomic, biochemical and physiological, and of data referring to related microorgan-isms, was crucial to carry out the reconstruction, as publicly available systematised information for A niger is scarce Therefore, in the reconstruction process, whenever there was physiological evidence for the presence of a reaction or pathway in A niger, but no genomic nor biochemical data were available to support it, genomic or biochemical data referring to A nidulans, other species of aspergilli, or other filamentous fungi, such as Penicillium chrysogenum, were considered Moreover, some data were extrapolated from the recently developed genome-scale metabolic reconstruc-tion of S cerevisiae [16]
Figure 1 depicts the process of reconstruction of
A niger’s central carbon metabolism and Table 1 presents
a list of the on-line databases consulted
Presence of metabolic reactions The presence of each reaction comprised in the metabolic network of A niger was assessed based on genomic, biochemical or physiological data, with decreasing degrees of reliability The trustwor-thiness in the asserted metabolic reactions or pathways also
Trang 3decreases when reactions were included based on
informa-tion referring to other fungal species
The genome of A niger, being almost three times larger
than the baker’s yeast genome (35.9 Mb), has been
com-pletely sequenced by the Dutch company, DSM (Heerlen,
the Netherlands), and 14 400 genes have been identified
About 40% of the genes have been annotated and
classified into functional categories The categories
‘Meta-bolism’ and ‘Energy’ account for 3111 genes (21.6%) and
354 genes (2.5%), respectively, and about 209 genes are
involved in the metabolism of carbohydrates [21a]
How-ever, A niger’s genome sequence and annotation are not
available to the public and hence specific genomic data for
this fungus was collected from a survey in literature, yielding
about 20 reactions assigned to genes This gap of
informa-tion was to some degree supplemented with genomic data
for A nidulans, which is more abundant and systematised
(http://www.gla.ac.uk/Acad/IBLS/molgen/aspergillus/index
html)
The genomic data was complemented with reports on the
presence of specific enzyme activities For instance, the
enzy-matic step in the pentose metabolism of A niger catalysed by
the NADPH-dependentL-xylulose reductase (EC 1.1.1.10)
was included in the metabolic reconstruction, although the
corresponding gene has not been cloned, as there are reports
on the activity of this enzyme in A niger [22,23]
Based on the metabolic networks of other fungal species, additional reactions or pathways were included in the metabolic reconstruction whenever there was physiological evidence for the consumption of a given substrate or formation of a given metabolic product in A niger For example, chitin is known to be a major component of the cell wall of most filamentous fungi, and in particular of
A niger [24], but only some enzymatic steps in the biosynthetic pathway leading to this polymer have been characterised in this species, namely those catalysed
by the enzymes glutamine-fructose-6-phosphate transami-nase (isomerising; EC 2.6.1.16) [24a] and chitin syn-thase (EC 2.4.1.16) [25] The remaining steps included in the reconstruction were based on the metabolic path-way in S cerevisiae [PATHWAY (KEGG), Table 1] that involves the enzymes glucosamine-phosphate N-acetyl-transferase (EC 2.3.1.4), phosphoacetylglucosamine mutase (EC 5.4.2.3) and UDP-N-acetylglucosamine pyrophospho-rylase (EC 2.7.7.23)
Stoichiometry, cofactor requirement and reversibi-lity Once the presence of a reaction was confirmed, its stoichiometry was ascertained This task was straightfor-ward for those reactions that had EC numbers ascribed, as queries could here be made directly in enzyme databases, whereas the stoichiometry of reactions without EC numbers assigned was determined through meticulous investigation
in the literature and reaction or pathway databases Some enzymes may catalyse several reactions, an example being transketolase (EC 2.2.1.1) in the pentose phosphate pathway that catalyses the transfer of two carbon groups in the two conversions D -ribose-5-phos-phate +D-xylulose-5-phosphate« sedoheptulose-7-phos-phate +D-glyceraldehyde-3-phosphate and D -erythrose-4-phosphate +D-xylulose-5-phosphate« beta-D -fructose-6-phosphate +D-glyceraldehyde-3-phosphate In such cases, all asserted reactions for the enzyme in question were included in the metabolic reconstruction A related issue refers to enzymes that can use more than one cofactor For instance, D-xylulose reductase (EC 1.1.1.9) accepts both NADH and NADPH as cofactors However,
Fig 1 Schematic representation of the reconstruction process The
arrows indicate the order in which the survey was accomplished and
point towards decreasing reliability on the asserted reactions The
information provided by metabolic pathways databases (ERGO, WIT,
PATHWAY) and enzyme databases (BRENDA) can also rely on
genomic data During the reconstruction process, protein databases
were also consulted (not represented in the diagram) In ‘other fungi’
are included other species of aspergilli, P chrysogenum and S
cere-visiae.
Table 1 On-line databases consulted during the reconstruction process.
ERGO (http://wit.integratedgenomics.com/IGwit/) Metabolic pathways Emericella nidulansa WIT (http://wit.mcs.anl.gov/WIT2/) Metabolic pathways Aspergillus nidulans
PATHWAY (KEGG) (http://www.genome.ad.jp/kegg/metabolism.html) Metabolic pathways Saccharomyces cerevisiae and
other microorganisms BRENDA (http://www.brenda.uni-koeln.de/) Enzymes Aspergillus niger and other
microorganisms PDSBSTR (http://www.genome.ad.jp/dbget-bin/www_bfind?pdbstr-today) Proteins aspergilli
PIR (http://pir.georgetown.edu/) Proteins aspergilli
PRF (http://www.prf.or.jp/en/) Proteins aspergilli
SWISS-PROT (http://www.expasy.org/sprot/) Proteins aspergilli
A nidulans linkage map (http://www.gla.ac.uk/Acad/IBLS/molgen/
aspergillus/index.html)
Genes Aspergillus nidulans
a
Sexual phase of the fungal life cycle of Aspergillus nidulans.
Trang 4the exact cofactor requirements are often unknown, and in
such cases both reactions involving NADH and NADPH
were considered
By default, all the reactions were considered to be
reversible, unless specific information indicating
unidirec-tionality was available [e.g hexokinase (EC 2.7.1.1)] In the
stoichiometric model, some reactions were subsequently
assumed to be irreversible in the forward or the backward
direction, in order to avoid artificial transhydrogenation
cycles converting NADH into NADPH without net
con-version of metabolites (refer to section Removing artificial
transhydrogenation cycles)
Compartmentation and localisation of reactions In the
metabolic reconstruction, intracellular compartmentation is
considered and consequently reactions and metabolites are
distributed among the extracellular medium and three
intracellular compartments, namely cytosol, mitochondria
and glyoxysomes Thus, besides biochemical conversions,
the metabolic network also includes transport processes
between the different compartments and between the cell
and the environment By default, all the reactions were
considered to occur in the cytosol, unless specific
informa-tion on their localisainforma-tion was available
In the reactions denoting transport processes across the
cytoplasmic, mitochondrial and glyoxysomal membranes,
neither protons nor ATP were considered, due to lack of
specific information for aspergilli and for A niger in
particular This assumption might have a profound effect
when balancing protons or ATP for the calculation of fluxes
using the stoichiometric model and this matter is further
discussed in the section Energetic parameters
Reaction statistics
Table 2 presents information on the number of biochemical
transformations and metabolites that occur extracellularly
and intracellularly, in the different compartments, as well as
information on the number of transport processes, which
are defined across the cytoplasmic, mitochondrial and
glyoxysomal membranes, both for the reconstructed
net-work and for the metabolic model subsequently developed
(section Stoichiometric model for A niger)
The biochemical conversions comprising the metabolic reconstruction (both with and without EC numbers assigned) were classified into the six main classes of enzymes, according to the type of transformation implica-ted The involvement of each class of enzymes in the carbohydrate metabolism, as well as energy metabolism proposed for A niger, was assessed and compared to those
in the metabolic reconstructions of S cerevisiae [16] and of
E coli[14]
As shown in Fig 2, the oxidoreduction reactions that are catalysed by oxidoreductases (class 1), represent the pre-dominant group of biochemical transformations (39%), being followed by reactions catalysed by transferases (class 2), which account for 26% of the total number of reactions in the part of A niger’s metabolism under investigation Hydrolases (class 3) and lyases (class 4) have lower contributions, corresponding to 15 and 11% of the total number of reactions considered, respectively Iso-merases (class 5) and ligases (class 6) are involved to an even lesser extent, comprising 7% and 2% of the reactions under study, respectively
The relative contributions of the different classes of enzymes in the reconstructed carbohydrate and energy metabolisms in A niger seem to follow the same trend of those in S cerevisiae and a reasonable quantitative agree-ment is also observed The same scenario does not apply for
E coli, where isomerases occupy the third position in abundance, in the reconstructed carbohydrate and energy metabolisms, and are followed by lyases, hydrolases and ligases (Fig 2)
Furthermore, the substrate specificity of the different groups of enzymes included in the metabolic reconstruction
of A niger was evaluated based on the ratio of the number
of reactions to the number of enzymes in each category Transferases appear to be the less substrate specific enzymes, followed by oxidoreductases, isomerases and lyases, whereas hydrolases and ligases seem to have high substrate speci-ficities, each of them catalysing only one reaction
Stoichiometric model forA niger Following the phase of compilation of information con-cerning the structure of the central carbon metabolism of
Table 2 Number of reactions and metabolites included in the metabolic reconstruction and in the stoichiometric model, and their localisation Additionally to the reactions comprised in the metabolic reconstruction, the metabolic model also includes merged biochemical conversions.
Processes
Intracellular [number of reactions (%)] Extracellular
[number of reactions (%)]
Total [number of reactions (%)] Cytosol Mitochondria Glyoxysomes
Metabolites 181 (63.7) 43 (15.1) 11 (3.9) 49 (17.3) 284 (100) Reactions
Biochemical conversions
Transport processes
46 (68.7) a 14 (20.9) a 7 (10.4) a – 67 (20)
a
Cytoplasmic, mitochondrial and glyoxysomal membrane.
Trang 5A niger, a stoichiometric model was developed and
subse-quently used to simulate growth and metabolite production
as described in the section Model predictions A list of the
reactions that comprise the stoichiometric model is available
as supplementary material
Anabolic reactions To describe growth, biomass
produc-tion was regarded as a drain of macromolecules and
building blocks required to produce cellular components
The demands on each of these compounds were estimated
based on the biomass composition No drain of free
metabolites or dilution of the metabolite pool due to
biomass growth was considered [17] The cellular
compo-sition considered for A niger was based on the contents of
the main biomass components of A oryzae determined in
[26] (Table 3) The pathways considered for amino acid
synthesis were based on a metabolic reconstruction of
amino acid biosynthesis of A nidulans from sequenced
expressed sequence tag data (http://wit.mcs.anl.gov/WIT2),
whereas the reactions for the anabolism of lipids, nucleic
acids and other macromolecules were taken from a
simplified model developed by Pedersen et al [26] for the
central carbon metabolism of A oryzae
Within the scope of this study, a single overall equation
denoting formation of biomass was included in the model,
even though the cellular composition varies with the specific growth rate [26] The sensitivity of the biomass yield to perturbations in the biosynthetic demands has been assessed
in different studies and some authors concluded that the biomass yield was not overly sensitive to changes in biosynthetic requirements [27], whereas others emphasised the importance of incorporating changes in biomass com-position with growth rate in flux estimation [28]
Removing artificial transhydrogenation cycles As men-tioned previously, due to the lack of information, many reactions were, by default, represented as being reversible and/or accepting both NADH and NADPH as cofactors When simulating the model, this would result in artificial transhydrogenation cycles converting NADH into NADPH without net formation of other metabolites Such cycles may arise between pairs of reactions involving the same metabolites but different cofactors As these cycles are not likely to be present under physiological conditions, one of the reactions involved was either constrained to be irrevers-ible or removed from the reaction set
As an example, we can refer to the potential cycle between the reactions catalysed by the enzymesD-xylulose reductase (NADH- and NADPH-dependent) and manni-tol-2-dehydrogenase (NADP+-dependent) (EC 1.1.1.138), interconverting D-xylulose and D-arabitol (Fig 3) In this case, the transhydrogenation cycle was avoided by removing from the metabolic reconstruction the NADH-dependent reaction catalysed byD-xylulose reductase, which is equi-valent in assuming that the reduction ofD-xylulose involves only the cofactor NADPH A summary of the constraints considered to avoid artificial transhydrogenation cycles in the metabolic model proposed for A niger is presented in Table 4
Energetic parameters An advantage of using stoichiomet-ric models is that only a small number of parameters need to
be determined In addition to the biomass composition, the only parameters that had to be estimated were key energetic parameters: ATP requirement for nongrowth associated purposes (mATP), ATP yield on biomass (YXATP) and operational P/O ratios These parameters cannot be
Fig 2 Comparison of relative contributions of different enzyme classes
in the reconstructed carbohydrate and energy metabolisms of A niger
(210 reactions), S cerevisiae (143 reactions) and E coli (119 reactions).
Table 3 Cellular composition considered for determination of stoichiometric coefficients in biomass equation in the metabolic model of A niger.
Biomass component
Molecular mass (g per mol
of monomer in polymer)
Content a
(g per 100 g dry weight) Normalised b
Stoichiometric coefficient c
(mmol per g dry weight)
a For growth on glucose, using ammonia as the nitrogen source and for a specific growth rate of 0.1 h)1[26] b Without considering ash.
c
In the equation representing biomass formation (units: mmol of monomers in polymer per g dry weight).
Trang 6determined independently, but if one of the parameters is
known the others can be estimated from experimental data
[17]
ATP and protons were in general not accounted for in the
transport processes over the cellular membranes (refer to
section Compartmentation and localisation of reactions)
The only cases in which protons were explicitly considered
were the reactions involved in the oxidative phosphorylation
and electron transport chain, driving the proton motive
force and generating ATP In eukaryotes, many compounds
are transported across the mitochondrial membrane by
proton symport, resulting in an influx of protons into the
mitochondrion that contributes to the incomplete coupling
between the oxidation and phosphorylation processes in the oxidative phosphorylation, and consequently gives rise to lower P/O ratios than the theoretical values [17] In order to account for this phenomenon in the model, the proton’s stoichiometric coefficient in the reaction catalysed by the enzyme H+-transporting ATP synthase (EC 3.6.1.34) was based on the operational P/O ratios observed in A niger [29,30] (Table 5)
The parameters mATP and YXATP (or rather the ATP requirements in the reaction denoting growth) were adjus-ted, so that the computed growth-yield matched experi-mentally observed biomass yields of A niger, for different growth rates in glucose-limited continuous cultures [31] The estimated values for the energetic parameters of A niger are shown in Table 6, together with values found in the literature for the related filamentous fungus P chrysogenum [29] and for S cerevisiae [32] The ATP requirement for nongrowth associated purposes calculated for A niger is within the values presented for P chrysogenum and S cere-visiae, whereas the ATP yield on biomass is slightly lower than for P chrysogenum and falls in the experimental range found in the literature for yeast The former parameter was estimated to be 3.7 mmol ATP per g dry weight per h for
A niger, under citric acid production conditions [10] Model predictions
Once all relevant metabolic pathways of the central carbon metabolism of A niger were identified and the model was further refined, the analysis of the system pursued with the
Fig 3 Representation of the artificial transhydrogenation cycle between
the reactions catalysed by the enzymes D -xylulose reductase
(NADH-dependent) and mannitol-2-dehydrogenase (NADP+-dependent),
inter-converting D -xylulose and D -arabitol.
Table 4 Potential artificial transhydrogenation cycles arising when simulating the metabolic model for A niger and actions taken to avoid them.
R, reversible reaction; I, irreversible reaction.
Transhydrogenation cycle
(NADH fi NADPH) Metabolites involved Added constraint
NAD(H)-dependent D -Xylulose/xylitol NADP(H)-dependent reaction Xylitol dehydrogenase (R), considered to be irreversible in the
L -Arabitol dehydrogenase (R), direction of reduction
D -Xylulose reductase (EC 1.1.1.9) (R)
NADP(H)-dependent
D -Xylulose reductase (EC 1.1.1.9) (R)
NAD(H)-dependent D -Xylulose/ D -arabitol NAD(H) not considered to act as
D -Xylulose reductase (EC 1.1.1.9) (R) cofactor in the reaction catalysed by
D -Xylulose reductase (EC 1.1.1.9) (R),
Mannitol 2-dehydrogenase (EC 1.1.1.138) (R)
NAD(H)-dependent Glycerone/glycerol NADP(H) and NAD(H)-dependent Glycerol dehydrogenase (EC 1.1.1.6) (R) reactions considered to be
Glycerol dehydrogenase I and II (EC 1.1.1.72) (R) reduction and oxidation, respectively NAD(H)-dependent
2-Hydroxy-3-oxopropionate reductase (R)
2-Hydroxy-3-oxopropionate/glycerol Both NADP(H) and
NAD(H)-dependent reactions
2-Hydroxy-3-oxopropionate reductase (R) direction of reduction
NAD(H)-dependent Acetaldehyde/ethanol NADP(H)-dependent reactions Alcohol dehydrogenase I (EC 1.1.1.1) (R) considered to be irreversible in the NADP(H)-dependent
D -Lactaldehyde dehydrogenase II (EC 1.1.1.78) (R),
Glycerol dehydrogenase II (EC 1.1.1.72) (R)
direction of reduction
Trang 7quantification of metabolic fluxes, using the framework of
metabolite balancing in combination with linear
program-ming algorithms Flux distributions corresponding to
opti-mal growth were calculated by maximising the flux of the
reaction denoting biomass formation, while setting the
substrate uptake rate to an appropriate value (Materials and
methods)
When simulating growth on glucose, it was observed that
the model predicted zero flux through the pentose
phos-phate pathway that is believed to be the major pathway for
generation of NADPH Using 13C-labelling experiments,
the pentose phosphate flux in a glucoamylase-producing
recombinant strain of A niger was estimated to be 58% and
72% of the glucose uptake rate, during batch (0.19 h)1)
[33] and chemostat cultures (0.10 h)1) [34], respectively For
an a-amylase-producing strain and a wild-type strain of
A oryzae grown in chemostats at specific growth rates
of approximately 0.10 h)1, metabolite balancing was
employed to calculate pentose phosphate pathway fluxes of
35% and 40%, respectively [26] Carbon labelling analysis of
glucose-limited continuous cultures of A nidulans indicated
that about 20 and 40% of the glucose is metabolised through
this pathway, at low and high growth rates, respectively [7]
Besides the pentose phosphate pathway, other mechanisms
have been proposed for the generation of NADPH in
aspergilli, such as the mannitol cycle, the glycerol cycle and
pyruvate/malate cycle, which involve transhydrogenation at
the expense of ATP However, these cycles seem to operate
discontinuously and the studies accomplished provide no
support for a significant contribution of these cycles in
NADPH generation [7]
In the model simulations, NADPH is formed
preferen-tially in the reaction catalysed by the cytosolic enzyme
NADP+-dependent isocitrate dehydrogenase (EC 1.1.1.42)
There is biochemical evidence for the presence of a
NADP+-dependent isocitrate dehydrogenase in the
cyto-plasm of A niger [35,36], however, the activity of this
enzyme seems to be very low, compared to the activity of the
mitochondrial isoenzyme, when glucose is used as carbon
source [37] If the flux through this enzyme is constrained to
zero in the model simulations, the pentose phosphate
pathway becomes active (about 29% of the glucose is metabolised through this pathway for a growth rate of 0.09 h)1), and the computed biomass yield on glucose drops slightly [from 0.521 to 0.512 g (dry weight) per g glucose] All flux distributions obtained using the model for simulation of growth involve secretion of fumarate in a rate that corresponds to 1–2% of the substrate uptake rate, and about to 3% of the specific growth rate on a carbon atom basis However, there are no reports on the produc-tion of this organic acid by A niger Through investigaproduc-tion
of the metabolic reconstruction for A niger, it can be observed that fumarate is formed in the cytosol in reactions involved in the biosynthesis of amino acids and nucleotides, but there is no reaction for its consumption in this compartment Unless a reaction in which cytosolic fumarate can be used as substrate or a transport process from the cytosol into the mitochondrion, where it can be consumed, are included in the metabolic network, secretion of fumarate
to the extracellular medium is inevitable, as this compound
is considered to be balanced in the stoichiometric model The lack of evidence for a cytosolic fumarate dehydratase or
a carrier for fumarate over the mitochondrial membrane, associated with a low predicted secretion rate of fumarate to the extracellular medium, seem to be reasonable reasons for accepting the simulated results
Similar effects on the computed flux distributions result from balancing of metabolites, such as CoA, NAD(P)+, FAD as well as one carbon compounds, for which there is
no net formation and consumption
The proposed model predicts optimal metabolic beha-viour based on the stoichiometry of the reactions in the metabolic network and on the biomass composition con-sidered However, there are other factors, such as kinetic or genetic regulation, that govern the metabolism and which are not accounted for in the model and therefore can explain the differences verified between simulated and experimental results, in some cases, such as the wrongly predicted flux through the pentose phosphate pathway discussed above The example of fumarate secretion is indicative that the model needs to be further validated in order to predict reliable results and illustrates how the model can be used to guide experimental work, e.g to identify the possible fate of fumarate produced in the cytosol
Biomass yields on different carbon sources.The maximum theoretical growth yield on different carbon sources was calculated for A niger and compared to experimentally observed yields for A oryzae for which a range of substrates have been investigated [4] In order to account for the relative effect of maintenance for nongrowth associated purposes, all computations were performed considering the corresponding experimental substrate uptake rates
Table 5 P/O ratios considered for the computations and experimental
range observed for A niger.
P/O ratios
Considered value
Experimental range for A nigera
a Values taken from [29,30].
Table 6 Energetic parameters estimated for A niger and comparison values found in the literature for other fungi.
Energetic parameters
Considered value
Experimental value
P chrysogenum a S cerevisiae b
m ATP (mmol ATP per g dry weight per h) 1.9 2.9 < 1
a
For an operational P/O ratio of 1.5 and Y ¼ 0.5 gÆg)1[29].bValues taken from [32].
Trang 8The predicted optimal growth yields are generally in
good agreement with the experimentally observed values
(Fig 4) First of all, it can be seen that the biomass yield
on glucose for A oryzae is slightly lower than that of
A niger against which the model was calibrated When
fructose is used as the sole carbon source, the simulated
flux distribution is as expected, very similar to that
obtained for growth on glucose (results not shown)
leading to an identical predicted biomass yield The largest deviations between predicted and experimental result are observed for glycerol and acetate, which may
be explained by a less optimised metabolic network for these uncommon substrates, i.e futile cycles may operate
in vivo, but they are not predicted by the model Interestingly, the predicted growth yield on mannitol is higher than that the one for growth on glucose, a trend that is also observed experimentally Theoretically, this is due to the fact that compared to glucose, each mole of mannitol converted to fructose-6-phosphate generates an additional mole of NADPH that can be used for biosynthesis
Essential reactions.In order to study the importance of the biochemical reactions in the metabolic reconstruction, each individual reaction was deleted from the metabolic network and optimal growth for the corresponding mutant was simulated for different carbon sources, namely glucose, xylose, glycerol and acetate Table 7 shows that only a small
Fig 4 Computed and experimental growth yields, during growth on
different carbon sources Experimental data refers to A oryzae [4].
Table 7 Essential and growth-retarding reactions for growth of A niger on different carbon sources and pathways in which they take part mit, Mitochondrial reaction; gly, glyoxysomal reaction (the remaining reactions are cytosolic).
Trang 9number of biochemical reactions are essential for growth on
the carbon sources under study, reflecting the flexibility of
the metabolic network to meet the biosynthetic
require-ments, as well as the fact that many of the reactions are not
involved during growth on these carbon sources The
removal from the metabolic network of reactions that are
essential for growth on some carbon sources may have a
retardant or have no effect on growth on other carbon
sources The reactions that are essential for growth on the
different carbon sources studied are mainly involved in the
major catabolic pathways, namely tricarboxylic acid cycle
(all carbon sources), pentose phosphate pathway (pentose),
gluconeogenesis (glycerol and acetate) and glyoxylate shunt
(acetate), as well as in the oxidative phosphorylation (all
carbon sources) Furthermore, the model predicts that the
elimination of certain reactions in the pathways of synthesis
of biomass components (chitin, glucan, glycogen and
mannitol) has a lethal effect on A niger, for all the carbon
sources investigated
Metabolite yields A nigeris an important organism for
metabolite production, in particular for organic acids By
maximising the excretion flux of a desired product instead of
the biomass flux, the stoichiometric model can be used to
assess the maximum theoretical yield for a given pair of
substrate and product The optimisation also results in one
possible optimal flux distribution corresponding to the
optimal yield, although it does not necessarily give
information on how it could be achieved An efficient
process would typically require optimisation of both
environmental conditions and microorganism, e.g using
genetic manipulations Some of these considerations can,
however, also be investigated using the described modelling
framework as will be seen in the example below
Considering the production of succinate from glucose,
the maximum theoretical yield for A niger is 1.5 mol
succinate per mol glucose (0.98g per 1 g glucose)
corres-ponding to 100% carbon yield Unless the cells are forced to
produce succinate, this outcome is not immediately
physio-logically meaningful Normally, succinate is observed as a
by-product in fermentation, and although A niger is a
strictly aerobic organism one could imagine a production
phase under microaerobic conditions In the simulations,
this could then be mimicked by constraining the specific
oxygen uptake to be below a certain value
Figure 5 shows how the maximum and minimum
succinate yields vary with the biomass yield on glucose,
under fully aerobic conditions and ‘microaerobic’
condi-tions The lighter shaded area of the figure represents the
possible combinations of yields of biomass and succinate
on glucose for fully aerobic conditions (unconstrained
oxygen uptake rate), whereas the darker shaded area was
obtained by constraining the specific oxygen uptake rate to
be below 0.5 mmol O2per g dry weight per h
(‘microaer-obic’ conditions) The highlighted points indicate the cases
optimal growth and optimal succinate production, under
fully aerobic conditions, as well as optimal growth, at
‘microaerobic’ conditions These results suggest that a
restricted oxygen supply does not necessarily imply
pro-duction of succinate, and, at growth rates close to the
optimal, the main fermentation by-product predicted is
ethanol
Thus, to enforce production of succinate, one might have
to consider inactivation (or addition) of specific metabolic reactions, for instance using genetic manipulations or starvation for important ‘cofactors’ The effects of such actions can also be investigated using the described frame-work simply by restricting the flux of the chosen reaction to zero or by adding a new reaction to the model It is, for example, possible to search for optimal deletions that give high product formation at optimal growth This can be elegantly formulated as a bi-level optimisation problem for any number of deletions [37a], but for the purpose of this study it is enough to consider direct search of optimal single and double deletions
Figure 6 shows the simulated results for the wild-type (darker shaded area), together with the theoretically optimal single (intermediate shaded area) and double (lighter shaded area) deletion mutants at ‘microaerobic’ conditions The optimal single deletion found was the disruption of pyruvate decarboxylase (EC 4.1.1.1), preventing extensive channel-ling of pyruvate towards ethanol and acetate For this mutant, several optimal flux distributions exist At specific growth rates close to the optimal, the succinate yield on glucose is at least 0.47 mol succinate per mol glucose (0.31 g per 1 g glucose), and the other fermentation prod-ucts are either glycerol orL-arabitol and ethanol When two disruptions are allowed, the highest succinate production is achieved by combining deletion of pyruvate decarboxylase with deletion of ATP:citrate oxaloacetate-lyase (EC 4.1.3.8), corresponding to a yield of at least 1.12 mol succinate per mol glucose (0.74 g per 1 g glucose), at optimal growth, being also produced as by-products glycerol and either ethanol or oxalate
These results suggest that the gene(s) encoding the mentioned enzyme(s) may be potential targets for metabolic
Fig 5 Computed succinate production limits of wild-type A niger, under different conditions Fully aerobic conditions (unconstrained
qO 2 ) (lighter shaded area) and ‘microaerobic conditions’ (qO 2 con-strained to be below 0.5 mmol O 2 per g dry weight per h) (darker shaded area) The highlighted points indicate: (j) optimal growth yield and (r) optimal succinate yield on glucose, under fully aerobic conditions, and (m) optimal growth yield on glucose, under ‘micro-aerobic’ conditions.
Trang 10engineering, however, mutant strains do not necessarily
grow optimally [38] Recent results suggest however, that it
is possible to evolve microorganisms exhibiting suboptimal
growth to the theoretically predicted properties [39]
Conclusions
The reconstruction of the central carbon metabolism of
A nigerpresented here provides the first detailed
descrip-tion of the central carbon metabolism of this
microorgan-ism, namely in what concerns carbohydrates, organic acids,
alcohols, and amino-sugars, and thereby covers the wide
variety of carbon compounds that can be used by this
fungus as a single carbon source for growth
As A niger’s genomic sequence and annotation are not
publicly available, the reconstruction process involved
compilation and integration of different types of
informa-tion concerning A niger as well as data regarding other
species of aspergilli and other fungi Thus, the metabolic
reconstruction presented here embodies a comprehensive
database of reactions, resulting from a multitude of
information sources, and accordingly may be used as a
platform for reconstructing the metabolism of other related
microorganisms
Although detailed to some extent, the metabolic
recons-truction does not intend to provide a complete description
of A niger’s metabolism of carbohydrates, organic acids,
alcohols, and amino-sugars; it represents instead an
endeavour to provide systematic information in order to
understand fungal metabolism
A thorough stoichiometric model was developed, based
on the reconstructed metabolic network, and used to
determine the metabolic capabilities of A niger, under
different genetic and environmental conditions, by
employ-ing the framework of metabolite balancemploy-ing in combination
with linear programming methods The model predicts
optimal metabolic behaviour, and hence upper limits to the
experimental data, and in some cases close agreement between experimental and simulated results can only be achieved by incorporating additional constraints related to the regulatory mechanisms governing the metabolism On the other hand, the model requires further validation and here the availability of experimental data plays an important role Once validated, the model can be used as a tool for the analysis, interpretation and prediction of metabolic beha-viour and hence guide the design of improved producing strains through metabolic engineering Furthermore, the model can play a role in functional genomics, through identification of metabolites or reactions for which there is
no interconnectivity in the metabolic network, and thereby suggesting missing metabolic reactions
Acknowledgements
The authors thank Jochen Fo¨rster for extending his experience in reconstructing and analysing metabolic networks to this project, Marlene Leong for software development and George Ruijter for sharing his knowledge of A niger’s metabolism.
Financial support was provided in part by Fundac¸a˜o para a Cieˆncia
e a Tecnologia, Portugal, through a research fellowship for H D M A˚ acknowledges Alf A˚kerman foundation, Sweden, and the Danish Biotechnology Instrument Center, Denmark The research work on metabolite production by Aspergillus was financed by Vinnova, Sweden, and Erhvervsfremmestyrelsen, Denmark, via the Øresund Center Contract ETIF.
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Fig 6 Computed succinate production limits of A niger, under
‘microaerobic’ conditions (qO 2 constrained to be below 0.5 mmol O 2
per g dry weight per h) Wild-type (darker shaded area); single deletion
mutant DEC 4.1.1.1 (intermediate shaded area); and double deletion
mutant DEC 4.1.1.1 + DEC 4.1.3.8(lighter shaded area).