Download Engineering primary metabolic pathways of industrial

Journal of Biotechnology 129 (2007) 6–29
Engineering primary metabolic pathways
of industrial micro-organisms
Alexander Kern a , Emma Tilley b , Iain S. Hunter b , Matic Legiša c , Anton Glieder a,∗
a Institute for Molecular Biotechnology, TU Graz, Petersgasse 14, 8010 Graz, Austria
Department of Bioscience, Strathclyde University, 204 George Street, G1 1XW Glasgow, Scotland
Department for Biotechnology and Industrial Mycology, National Institute of Chemistry, Hajdrihova 19, SI-1001 Ljubljana, Slovenia
b
c
Received 11 April 2005; received in revised form 4 July 2006; accepted 18 August 2006
Abstract
Metabolic engineering is a powerful tool for the optimisation and the introduction of new cellular processes. This is mostly
done by genetic engineering. Since the introduction of this multidisciplinary approach, the success stories keep accumulating.
The primary metabolism of industrial micro-organisms has been studied for long time and most biochemical pathways
and reaction networks have been elucidated. This large pool of biochemical information, together with data from proteomics,
metabolomics and genomics underpins the strategies for design of experiments and choice of targets for manipulation by
metabolic engineers. These targets are often located in the primary metabolic pathways, such as glycolysis, pentose phosphate
pathway, the TCA cycle and amino acid biosynthesis and mostly at major branch points within these pathways. This paper
describes approaches taken for metabolic engineering of these pathways in bacteria, yeast and filamentous fungi.
© 2006 Elsevier B.V. All rights reserved.
Keywords: Metabolic engineering; Metabolic models; Primary metabolism; Gene expression and disruption; Industrial micro-organisms
1. Introduction
In the past, improvement of microbial and cellular processes was achieved mainly by evolutionary
(classical) breeding methods or repeated rounds of
mutagenesis and selection of a desired phenotype.
These methods are still very useful (Sauer, 2001;
∗ Corresponding author. Tel.: +43 316 873 4074;
fax: +43 316 873 4071.
E-mail address: [email protected] (A. Glieder).
0168-1656/$ – see front matter © 2006 Elsevier B.V. All rights reserved.
doi:10.1016/j.jbiotec.2006.11.021
Sonderegger and Sauer, 2003; van Maris et al., 2004b),
but since the introduction of recombinant DNA technology a more rational approach for biotechnological
process development and optimisation became obvious. Bailey defined metabolic engineering as an
“Improvement of cellular activities by the manipulation of enzymatic, transport and regulatory functions
of the cell with use of recombinant DNA technology”
(Bailey, 1991), which was generalized to “purposeful modification of the intermediary metabolism using
recombinant DNA technology” (Cameron and Tong,
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
1993) or “genetic modification of cellular biochemistry to introduce new properties or to modify existing
ones” (Jacobsen and Khosla, 1998).
Today the main goals of metabolic engineering can
be summarized in the following four categories: (1)
improvement of yield, productivity and overall cellular physiology, (2) extension of the substrate range,
(3) deletion or reduction of by-product formation and
(4) introduction of pathways leading to new products.
Commonly these goals can be achieved by a three-step
procedure. Firstly, a genetic modification is proposed,
based on metabolic models. After genetic modification,
the recombinant strain is analysed and the results are
then used to identify the next target for genetic manipulation, if necessary. Thus, the construction of an optimal
strain involves a close interaction between synthesis
and analysis, usually for several consecutive rounds.
The rapid development and frequent success in this
field is demonstrated by the large number of reviews
about the theoretical and practical aspects of metabolic
engineering (Cameron and Chaplen, 1997; Cameron
and Tong, 1993; Nielsen, 1998, 2001; Ostergaard et al.,
2000; Stephanopoulos, 1994; Stephanopoulos, 1999;
Stephanopoulos and Sinskey, 1993; Stephanopoulos
and Vallino, 1991). Knowledge of cellular and microbial physiology (Nielsen and Olsson, 2002), as well
as the underlying metabolic networks or enzymes, is
an important prerequisite for successful engineering.
The need for readily available information on these
topics has been addressed by the creation of several
databases, such as KEGG (Kanehisa, 1997; Kanehisa
and Goto, 2000), BRENDA (Schomburg et al., 2002)
and MetaCyc (Krieger et al., 2004). Software tools,
e.g. FluxAnalyser (Klamt et al., 2002), MetaFluxNet
(Lee et al., 2003), OptKnock (Burgard et al., 2003;
Pharkya et al., 2003) and MetaboLogic (Zhu et al.,
2003) link experimental data with database knowledge.
Recently, a computational approach for the identification of every possible biochemical reaction from
a given set of enzyme reaction rules was reported
(Hatzimanikatis et al., 2005). This allows the de novo
synthesis of metabolic pathways composed of these
reactions and the evaluation of these novel pathways
with respect to their thermodynamic properties.
A new term, ‘Inverse Metabolic Engineering’ (IME)
has been coined to encompass the construction of
strains with a particularly desirable physiological phenotype, e.g. enhanced production of heterologous
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protein (Bailey et al., 2002; Gill, 2003; Nielsen, 1998,
2001). This is a challenging approach to identify the
genes that confer a prominent phenotype when the
responsible mutation(s) are anywhere on the genome,
but not at the place of the coding gene itself. For example, over-expression of certain sigma factors enhanced
protein production in stationary phase (Weikert et al.,
2000). Screening of libraries to detect such changes has
been substantially superseded by analysis of transcriptomic arrays to detect up- or down-regulation of genes,
if genome data were available. This is an interesting
alternative to the classic approach for detection of ratelimiting steps, where it is necessary to have extensive
knowledge about the pathway and the reaction kinetics
of the enzymes involved.
Metabolic engineers have access to a vast array of
genetic tools to design new intriguing strains. Existing
platforms include suitable and safe laboratory strains,
transformation systems, auxotrophic and dominant
markers and also constitutive as well as tightlyregulated promoters. Simultaneous over-expression of
several enzymes using only strong promoters might not
improve existing pathways but instead stress the organisms by increasing the metabolic burden (Mattanovich
et al., 2004). Furthermore, high levels of several or
all enzymes of a pathway may lead to undesirable
changes in metabolite levels and subsequent downregulation of some enzymes. The rigid control of the
fluxes in, especially, the central carbon metabolism has
been demonstrated already in yeast. The genes for eight
different enzymes were placed on multi-copy vectors.
Separately or pairwise overproduction of these glycolytic enzymes did not result in higher rate of ethanol
formation or modified levels of key metabolites, compared to a wild-type strain (Schaaff et al., 1989).
Balanced and coordinated expression of enzymes of
a metabolic pathway therefore requires sets of, possibly artificial, promoters (Alper et al., 2005; Jensen
and Hammer, 1998; Mijakovic et al., 2005; Solem and
Jensen, 2002). Synthetic promoters have been used to
study the control of the glycolytic flux in E. coli by
measuring the ATP demand (Koebmann et al., 2002).
Literature and database knowledge, combined with
experimental data and mathematical modelling, can
be used to identify metabolic networks (Pedersen et
al., 2000). Models for metabolic flux distribution are
needed to improve the production of a desired metabolite. Once the network is known, such models include
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A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
the respective fluxes and how they are controlled.
Metabolic flux analysis (MFA), metabolic control analysis (MCA) and the biochemical systems theory (BST)
are most commonly used techniques to create mathematical models.
Depending on the method, certain principles need
to be taken into account (Voit, 2003). Metabolic flux
quantification is a crucial prerequisite to direct as much
carbon as possible to the desired product. In the simplest concept of metabolite balancing or stoichiometric
MFA, material balances are set up for each metabolite
in the network. Assuming the metabolite concentrations are in steady state, a set of algebraic equations
relating the fluxes is obtained. Linear programming is
then used to calculate the fluxes through the branches
of the network (Ren et al., 2003; Stephanopoulos et
al., 1998). Further information is needed to complement the flux data to derive a more accurate model.
The use of 13 C-labelled glucose and measurement of
the labelling patterns of the intracellular metabolites
(e.g. proteinogenic amino acids) by NMR or MS techniques (GC–MS, LC–MS, MALDI-TOF-MS) provides
an additional set of data to augment the metabolite
balances (Wiechert, 2001). This additional information then allows MFA to be extended to other useful
applications: identification of branch points (nodes) in
cellular pathways or the existence of different pathways, calculation of non-measured extracellular fluxes
and most importantly the calculation of maximum theoretical yields. There are numerous recent examples for
the use of NMR or GC–MS techniques for metabolic
flux analysis, although in most cases GC–MS is the
preferred method because it is usually faster and more
sensitive (Blank et al., 2005; Christensen and Nielsen,
1999; Fredlund et al., 2004; Raghevendran et al., 2004;
Thykaer et al., 2002; Van Dien et al., 2003).
Metabolic flux analysis is a valuable tool to study
pathway interactions and the quantification of flux distribution around branch points, but it does not provide
insight in flux control, which describes the relationship between the flux in a pathway and the activity of
its enzymes. This relation is defined by MCA (Heinrich
and Rapoport, 1974; Kacser and Burns, 1973) in terms
of the flux control coefficient (FCC), which represents
the percentage change in flux divided by the percentage
change in activity of an enzyme that was responsible for that flux change. According to this concept, an
enzyme with a flux control coefficient close to 1 could
be defined as “rate-limiting”. However, quantitative
measurements of flux control coefficients showed that
such values are unusual (Fell, 1992, 1998) and that flux
control is distributed over all steps in a pathway, with
some steps having a higher flux control than others. The
fact, that metabolic fluxes exert control at several levels,
e.g. transcriptional control (Zaslaver et al., 2004), translational control, activation-inactivation or allosteric
control of enzymes, makes it especially challenging to
predict the consequences of genetic modifications. An
alternative modelling approach, that does not require
the vast amounts of information needed for MCA was
presented by (Visser et al., 2000). Their approach,
termed “tendency modelling”, minimises the number
of model parameters and the mathematical effort, but
only aims to predict flux tendencies.
Biochemical systems theory (Savageau, 1969),
which is based on kinetic models and accounts for
regulatory signals, e.g. feedback inhibition allows new
kinetic models to be set up to quantify fluxes through
pathways, not only at steady state but also under transient conditions.
The so-called ‘–omics’ technologies, mainly
functional genomics, proteomics and metabolomics
contribute significantly towards metabolic engineering
as large amounts of data are produced, which can be
used to gain a better understanding of flux control and
consequently lead to improved models of metabolic
pathways. DNA microarrays (Dharmadi and Gonzalez,
2004) are used to study the transcriptional responses
of an organism to genetic and environmental changes
(Boer et al., 2003; Featherstone and Broadie, 2002;
Giaever et al., 2002; Oh and Liao, 2000a, 2000b). This
genomic approach has allowed the identification of regulatory networks. A reduction of the levels of negative
regulators or increase of positive regulators of gene
expression then should enable a uniform and balanced
increase of enzyme activities of the target metabolic
pathway. Processing and normalization of the microarray data obtained is still challenging. In an attempt to
reduce this problem, (Hyduke et al., 2003) developed a
software package to estimate gene-specific confidence
intervals for each gene in a cDNA microarray data set.
Proteome analysis allows profiling of a large number of proteins on a two-dimensional polyacrylamide
gel by systematic separation, identification and quantification (Han et al., 2001; Kim et al., 2004b).
Thereby, changes in the levels of protein expression
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
of different mutants or under different environmental conditions can be determined and used to define
target enzymes/proteins for further manipulation (Han
and Lee, 2003). Clearly, proteome analysis is not limited to 2D PAGE and protein quantification but also
allows the identification of post-translational modifications (Kirkpatrick et al., 2005; Peng et al., 2003) which
are potent regulators of protein function (Mesojednik
and Legisa, 2005).
Metabolomics covers the quantification of intracellular and extracellular metabolite concentrations using
analytical devices in appropriate time scales (Buchholz
et al., 2002; Burja et al., 2003). Metabolome data can
also be used to identify a silent phenotype in terms of
growth rate or other fluxes by quantification of changes
in certain metabolite concentrations relative to the concentration of a selected metabolite. These “metabolic
snapshots” allow identification of functions of deleted
genes (Raamsdonk et al., 2001).
1.1. Yeast
Although there are numerous technological applications for non-conventional yeasts, e.g. Pichia
pastoris, Schizosaccharomyces pombe or Hansenula
polymorpha (Pichia angusta) (Spencer et al., 2002),
metabolic engineering has been performed was almost
exclusively with Saccharomyces cerevisiae. Nevertheless, considerable metabolic information about
non-conventional yeasts has been gathered lately
(Blank et al., 2005; Ren et al., 2003). The physiological
properties of non-conventional yeasts are interesting
and presumably more applications in metabolic engineering will follow (Branduardi et al., 2004). Metabolic
flux profiles of the yeasts P. stipitis (Fiaux et al.,
2003) and P. pastoris (Sola et al., 2004) have recently
been determined using NMR spectroscopy. However,
the most notable progress in engineering of central
metabolism has been reported for S. cerevisiae.
The extension of substrate range for fermentation
is one of the most active fields, because this is an
important prerequisite to make the production of bulk
products, mainly ethanol, economically feasible. Cellulosic biomass is an attractive feedstock since it is
available as a waste product in large amounts. The
hydrolysates of these complex carbohydrate polymers
contain different hexoses and pentoses, including glucose, galactose, mannose, arabinose and xylose, the last
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being the most abundant hemicellulose sugar. This fact
lead to an huge amount of research devoted to fermentation of xylose and other pentoses (Jeffries and Jin,
2004).
Wild-type strains of S. cerevisiae, while basically
capable of growing on xylose are not capable of fermenting this compound anaerobically. As the costs
of aerating bioreactors for ethanol production is significant, this presents a major obstacle for industrial
application.
The introduction of the XYL1 and XYL2 genes from
the xylose-metabolizing yeast P. stipitis, encoding the
NAD(P)H dependent xylose reductase (XR) and the
NADH dependent xylitol dehydrogenase (XDH), as
well as over-expression of the endogenous XKS1 gene,
encoding a xylulokinase (XKS), allowed anaerobic
growth and ethanol fermentation in the S. cerevisiae
strain TMB3001 (Eliasson et al., 2000; Toivari et
al., 2001) Over-expression of the XKS1 gene leads
to increased xylose utilisation and lowered ATP/ADP
ratios (Toivari et al., 2001). Inclusion of glucose in
the media was still necessary and xylose consumption and ethanol production were low. Nevertheless,
this approach showed potential for further improvement, despite the restrictive effects of the anaerobic
redox imbalance and extensive by-product formation
(e.g. xylitol). Expression of the xylose utilisation
pathway described above in combination with evolutionary engineering, improved the xylose catabolism
of TMB3001 and resulted in the TMB3001C1 strain
(Sonderegger and Sauer, 2003). This was the first
report of a strain capable of growing on xylose as
sole carbon source under strictly anaerobic conditions.
This strain produced 19% more ethanol than the parent strain, but still was hampered by slow growth
(0.119 h−1 ) and high xylitol production. Expression
of redox metabolism genes was altered in a way that
more NADH was reoxidized and more NADPH was
formed, allowing faster conversion of xylose to xylulose. Nevertheless, the imbalance of cofactors was still
growth limiting, as addition of acetoin, an NADH
oxidizing compound, increased anaerobic growth rate
(Sonderegger et al., 2004a). Cofactor balances calculated from flux analysis revealed a constant specific
NADPH production rate in the cytosol and increased
production of ATP. Whether higher NADPH production could improve the growth rate further is still an
open question. However, the results from the evolved
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strain demonstrated that xylose metabolism is not
linked to respiration. The authors concluded, that the
rate of ATP production is the actual limiting factor for
anaerobic growth on xylose, and not the redox balance
as such, which still limits the ATP production rate.
Several approaches to alleviate this imbalance to
improve ethanol production were reported, leading to
the conclusion that the branch point between glycolysis
and PPP is a hot spot for engineering. Jeppsson et al.
(2002) reduced the flux through the NADPH-producing
pentose phosphate pathway (PPP) by disruption of
either the GND1 gene, coding for an isoform of 6phosphogluconate dehydrogenase, or the ZWF1 gene,
encoding glucose 6-phosphate dehydrogenase. Disruption of the GND1 gene prevented conversion of
6-phosphogluconate to ribulose 5-phosphate. Consequently both strains showed increased ethanol yields
and lower xylitol production. Disruption of the ZWF1
gene resulted in the highest ethanol and lowest xylitol yield (0.41 and 0.05 g g−1 , respectively) among
the tested strains. Acetate production was increased
and the rate of xylose consumption was lowered by
84% due to reduced NADPH-dependent reduction of
xylose to xylitol. Over-expression of the xylose reductase (XR), which is responsible for this conversion,
significantly elevated the xylose consumption rate,
but with the drawback of increased glycerol yields.
This is due to DHAP conversion by XR. The depletion of this precursor for glycerol production limited
the usefulness of increased XR activity (Jeppsson et
al., 2003). Over-expression of a NADP+ -dependent
glyceraldehyde-3-phosphate dehydrogenase (NADPGAPDH) from Kluyveromyces lactis, whose function
is not coupled to wasteful CO2 formation, in a zwf1 S.
cerevisiae strain also increased rate and yield of ethanol
production and decreased xylitol production. This strategy allowed the reduction of the CO2 /ethanol ratio of
2.5 (mol/mol) in the control strain to 1.3 in the recombinant strain, thereby improving the ethanol yield (Verho
et al., 2003).
Engineering of ammonium assimilation has been
shown to be another good method to overcome the
obstacle of redox cofactor imbalance. The GDH1 gene
encodes an NADPH-dependent glutamate dehydrogenase, which catalyses the assimilation of ammonium to
glutamate by reaction with 2-oxoglutarate. Its deletion
renders S. cerevisiae unable to assimilate ammonium
in a NADPH-dependent manner. Instead, NADH was
redirected for ammonia assimilation at the cost of
glycerol production. Increased ethanol and decreased
glycerol yields were achieved, although the overall ethanol productivity was severely affected since
growth was reduced. Alternative reactions for ammonia
assimilation were provided by over-expression of the
GDH2 gene (NADH-dependent glutamate dehydrogenase) or the GS-GOGAT system (cooperative action of
glutamate synthase (GLT1) and glutamine synthetase
(GLN1)) in the gdh1 strain to successfully overcome
the growth problem (Nissen et al., 2000). After this
proof of principle, the same strategy was used in a
xylose consuming strain, resulting in reduced xylitol
excretion in combination with a 15% higher xylose fermentation rate and an increased yield of ethanol (Roca
et al., 2003). Under aerobic conditions these modifications reduced flux through the pentose phosphate
pathway and increased flux through the TCA cycle
(Moreira dos Santos et al., 2003). Unfortunately, the
applicability of this strategy for NADH reoxidation
by reduction of xylitol excretion is limited, due to the
coupled requirement for anabolic ammonium.
Sonderegger et al. (2004b) introduced the phosphoketolase pathway in their mutant strain, TMB3001C1,
thereby engineering the redox metabolism rationally. Addition of a functional phosphoketolase
Fig. 1. Overview of primary metabolic pathways. ACDH, acetaldehyde dehydrogenase; ACK, acetate kinase ACN, aconitase; ADH, alcohol dehydrogenase; ALD, aldehyde dehydrogenase; CS, citrate synthase; ENO, enolase; FBA, fructose-bisphosphate aldolase; FUM, fumarase;
GAP-DH, glyceraldehyde 3-phosphate dehydrogenase; GDH, glutamate dehydrogenase; GND, 6-phosphogluconate-dehydrogenase; GPD, glycerol 3-phosphate dehydrogenase; GPP, glycerol phosphatase; G6P-DH, glucose 6-phosphate dehydrogenase; GS, glutamine synthetase; ICD,
isocitrate dehydrogenase; LDH, lactate dehydrogenase; MAE, malic enzyme; MDH, malate dehydrogenase; OAA-DC, oxaloacetate decarboxylase; ODH, 2-oxoglutarate dehydrogenase; PDC, pyruvate decarboxylase; PDH, pyruvate dehydrogenase; PEP-CK, phosphoenolpyruvate
carboxykinase; PEP-CL, phosphoenol-pyruvate carboxylase; PFK, phosphofructokinase; PGA, 2-keto-3-deoxy-6-phosphogluconate aldolase;
PG-DH, phosphogluconate dehydratase; PGI, phosphoclucose-isomerase; PGL, 6-phosphogluconolactonase; PGM, phosphoglycerate mutase;
PK, phosphoketolase; PKS, pyruvate kinase; PPS, phosphoenolpyruvate synthetase; PTA, phosphotransacetylase; PYC, pyruvate carboxylase;
SDH, succinate dehydrogenase; SUC, succinyl synthetase; TAL, transaldolase; TK, transketolase; TPI, triosephosphate isomerase; XDH, xylitol
dehydrogenase; XI, xylose isomerase; XKS, xylulose kinase; XR, xylose reductase.
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
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A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
pathway, consisting of a phosphoketolase (PK),
phosphotransacetylase (PTA) and an acetaldehyde
dehydrogenase (ACDH), theoretically leads to a net
reoxidation of one NADH per xylose converted to
ethanol. PK’s convert xylulose-5-P to glyceraldehyde3-P and acetyl-P, PTAs catalyse the formation
of acetyl-CoA from acetyl-P followed by ACDHcatalysed formation of acetaldehyde (see Fig. 1). This
engineering strategy improved the yield of ethanol by
about 25% without affecting the anaerobic fermentation rate. The authors also identified acetate as a strong
inhibitor of xylose fermentation and disruption of the
ALD6 gene, encoding the NADPH-dependent aldehyde
dehydrogenase, increased the xylose fermentation rate
by 50%. The next logical step, namely combination
of reduced acetate formation with the phosphoketolase pathway, further improved the fermentation and
production features of the resulting strain in comparison to the control. This alternative route of carbon to
ethanol obviously did not interfere with other metabolic
reactions, which is a great advantage over other strategies, which usually resulted in increased ethanol yield
at the cost of the fermentation rate or vice versa. Further improvements of this strategy, by either rational or
evolutionary methods, seem possible.
Fermentation of xylose under anaerobic conditions
is made feasible by a completely different approach by
expression of a heterologous xylose isomerase (XI),
which directly converts xylose into xylulose in a redoxneutral manner. This strategy circumvents the problem
of cofactor imbalance. However, most attempts were
unsuccessful because the introduced xylose isomerases
were not expressed well, an exception being the xylose
isomerase from the anaerobic fungus Piromyces sp.
(Kuyper et al., 2003, 2004). Expression of this enzyme
resulted in anaerobic growth on xylose with a specific
growth rate of 0.005 h−1 , which was improved significantly by evolutionary breeding methods to 0.03 h−1 ,
accompanied by an ethanol yield of 0.42 g g(xylose)−1
(Kuyper et al., 2004). Most recently, over-expression of
all structural enzymes involved in conversion of xylose
further enhanced the growth rate to 0.09 h−1 (Kuyper
et al., 2005).
All of these improvements were achieved in laboratory strains, as industrial strains of S. cerevisiae
are usually diploid or polyploid and lack auxotrophic
markers. (Wang et al., 2004) have introduced the xylose
utilisation pathway (XR, XDH and XKS) in an indus-
trial strain. Ethanol yield was increased in conjunction
with high xylitol excretion due to the redox imbalance
described above. This demonstrated that the results
from laboratory strains can be extrapolated to industrial
strains, as expected.
Arabinose is another widespread pentose for ethanol
production. Early attempts to express either the
bacterial (Sedlak and Ho, 2001) or fungal arabinoseutilisation pathway (Richard et al., 2002, 2003) in
S. cerevisiae were not extremely successful due to
problems with arabinose uptake. In addition, a redox
cofactor imbalance resulted in minimal production of
ethanol. Recently an NADH-dependent reductase was
identified from the yeast Ambrosiozyma monospora
(Verho et al., 2004). This enzyme converts l-xylulose,
which is an intermediate of arabinose-utilisation,
and may help to circumvent, at least partially, the
imbalance. Over-expression of enzymes assembling a
bacterial arabinose-utilisation pathway, consisting of
Bacillus subtilis AraA, E. coli AraB and AraD as well
as over-expression of the arabinose-transporting galactose permease from yeast, allowed the development of
an arabinose-utilising strain. A B. subtilis gene was
chosen because the corresponding E. coli enzyme was
not expressed well. However, the doubling time of
the transformants was very low and strains could not
grow on arabinose as sole carbon source. To improve
the growth rate, transformants were subjected to serial
transfer under restrictive conditions to apply selective pressure and a doubling time of about 7,9 h was
reached for anaerobic growth on arabinose with an
ethanol yield of 0.08 g g(cell dry mass)−1 (Becker and
Boles, 2003). Analysis by DNA microarrays revealed
that the main reasons for improved growth were a
low l-ribulokinase activity and increased transaldolase
activities. Both results are consistent with earlier data.
Pathways with an initial ATP-requiring reaction, such
as the l-ribulokinase reaction, which finally produce
a surplus of ATP, need tight control of the respective
enzyme. Under conditions for which ATP consumption and production are equal, accumulation of pathway
intermediates may continue because the ATP level does
not change. Therefore, the initial reaction is not limited by the failure of the remaining pathway reactions
(Teusink et al., 1998). A few years earlier Walfridsson
et al. (1995) showed that the endogenous transaldolase
activity of S. cerevisiae was too low for efficient utilisation of PPP metabolites, because over-expression
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
of the gene encoding transaldose enhanced growth on
d-xylose significantly.
Redirection of carbon fluxes through alternative
pathways also seems to be a suitable application for
wine production. Depending on the strain and the
composition of must, higher levels of acetic acid are
sometimes produced, affecting the quality of product.
The concentration of acetic acid in fermented products,
such as wine and beer, must remain low. (Remize et al.,
2000) investigated the effects of reduced excretion of
acetate by S. cerevisiae via engineering of the “pyruvate dehydrogenase bypass”. Pyruvate decarboxylase
(encoded by three structural genes: PDC1, PDC5
and PDC6), acetaldehyde dehydrogenase, encoded by
the ALD gene family and acetoacetyl-CoA synthetase
(ACS) are responsible for this bypass. Reduction
of pyruvate decarboxylase activity did not result in
reduced levels of acetate, whereas ALD6 disruptants,
exhibiting 60 and 30% of wild-type acetaldehyde
dehydrogenase activity, showed a substantial reduction in yield of acetate (75 and 40%, respectively).
This effect was associated with a rerouting of carbon
flux towards succinate, butanediol and glycerol. The
regulatory capability of the ALD6 disruptant was further used for the overproduction of glycerol, which is
employed for synthesis of many different products, e.g.
cosmetics. In S. cerevisiae, glycerol is synthesised from
DHAP, a glycolytic intermediate, in a two-step reaction: reduction by glycerol 3-phosphate dehydrogenase
(GPD) and consecutive dephosphorylation by glycerol
3-phosphatase (GPP). Over-expression of a glycerol
3-phosphate dehydrogenase isoenzyme, encoded by
GPD2, is known to increase production of glycerol and
lower production of ethanol, but this is accompanied by
increased levels of acetic acid.
The combination of over-expression of the GPD2
gene (glycerol 3-phosphate dehydrogenase) and ALD6
disruption (Eglinton et al., 2002) reduced production of
acetic acid four-fold, while raising the concentration of
glycerol in the medium from 13.4 to 16.3 g/l compared
with control strain that did not have the ALD6 gene
disrupted.
High glycerol yields have also been achieved
in tpi1 mutants, lacking the glycolytic enzyme
triose phosphate isomerase. Apparently accumulation of DHAP is prevented by its conversion to
glycerol. These mutants are not capable of growth
on glucose as sole carbon source. A quadruple
13
mutant (tpi1nde1nde2gut2) was constructed by
Overkamp et al. (2002) to show that the growth defect
was due to mitochondrial reoxidation of cytosolic
NADH, thus rendering it unavailable for reduction of
DHAP. NDE1 and NDE2 encode isoenzymes of extramitochondrial NADH dehydrogenase, while GUT2
encodes an enzyme of the glycerol 3-phosphate shuttle.
The mutant strain grew on glucose, although rates were
dependent on concentration of glucose in the medium.
As conversion of glucose into glycerol and pyruvate
is neutral in terms of ATP production, growth of the
quadruple mutant on glucose seemingly depends on
respiration for production of ATP. Expression of many
enzymes involved in the respiratory dissimilation of
pyruvate is subject to catabolite repression, explaining
the sensitivity to glucose by the mutant strain. Serial
transfer in batch cultures was performed and the growth
rate was improved, but remained quite low, a fact that
interestingly may contribute to the high yield of glycerol of over 200 g l−1 (Overkamp et al., 2002).
Production of lactic acid has received a lot of
attention due to its numerous applications in food, pharmaceutical and cosmetic industry as well as in the
synthesis of biodegradable polymers. Although lactate
is classically produced using bacterial cells, engineered
yeast cells offer solutions for problems, such as low
pH, inhibitory effects of the produced acid and purification procedures. The first attempts to produce lactate
in yeasts by expression of a lactate dehydrogenase
(LDH) (Adachi et al., 1998; Dequin and Barre, 1994;
Porro et al., 1995; Skory, 2003) resulted in low yields
and production of ethanol. Reduction of the pyruvate decarboxylase or alcohol dehydrogenase activity
(Skory, 2003) did not improve the lactate production in
a satisfactory manner. Alcoholic fermentation can be
completely eliminated by deletion of the three genes
for pyruvate decarboxylase (Hohmann, 1991), but is
known to be associated with severe impairment of
cellular growth (Flikweert et al., 1996; Pronk et al.,
1996). Kluyveromyces lactis, which only possesses one
PDC gene, was used as an alternative for S. cerevisiae
(Porro et al., 1999). Deletion of the PDC1 gene and
expression of a bovine LDH resulted in a total replacement of ethanol for lactic acid fermentation, without
hindering growth, thereby increasing the lactic acid
yield 2.7-fold in comparison with the heterolactic control strain. Despite the high LDH activity, the highest
obtained yield of 1.19 is still below the maximum
14
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
theoretical value of 2 mmol of lactate per mmol glucose. van Maris et al. (2004a) attempted to elucidate the
role of oxygen in metabolically engineered homofermentative lactate producing S. cerevisae and analysed
its behaviour under various areation conditions. The
authors concluded that the conversion of glucose to
extracellular lactate does not yield ATP, most probably
due to the need of energy for the product export, thereby
also providing an explanation for the low lactate production rates under anaerobic conditions. Transgenic
strains in which LDH genes were integrated into the
S. cerevisiae genome under control of the ADH1 promoter (Colombie et al., 2003) or the PDC1 promoter
(Ishida et al., 2005) brought no improvements. Increasing the copy number of integrated LDH genes yielded
122 g l−1 lactate with a high optical purity (>99.9%) on
a cheap, cane-juice based medium (Saitoh et al., 2005),
but the fundamental problems of lactate production in
S. cerevisiae, such as growth depletion under anaerobic
conditions or alcoholic fermentation have not yet been
solved despite the efforts of numerous research groups.
1.2. Filamentous fungi
Filamentous fungi are an extremely diverse group of
heterotrophic micro-organisms that are exploited for
various biotechnological applications: they are used
in the production of foods, beverages, organic acids,
enzymes, polysaccharides, antibiotics and other pharmaceuticals. Fungi produce a vast array of secondary
metabolites and some species have highly efficient
protein secretion mechanisms that can be exploited
to express homologous or heterologous gene products (O’Donnell and Peterson, 1992). Although there
are several model organisms among filamentous fungi,
such as Neurospora crassa and Aspergillus nidulans,
they were mostly used for studying fungal physiology and genetics but not for metabolic engineering.
In spite of the industrial importance of this group of
micro-organisms, reports on the use of different techniques of metabolic engineering were published mostly
by academic institutions. The papers deal predominately with the application of different mathematical
models, such as: metabolic flux, metabolic control and
metabolic networks analysis, to identify the strategic
steps that could be improved by genetic manipulation
in order to increase the productivity and/or yields. On
the other hand, it seems that improvements of the fluxes
by recombinant DNA techniques conducted by various
industrial laboratories have remained largely unpublished. Therefore, papers dealing with the so-called
constructive type of metabolic engineering (Bailey et
al., 2002) are numerous while reports using the inverse
metabolic engineering technique are infrequent.
As the filamentous fungi are obligate aerobes, no
fermentative products are accumulated that would originate from the intermediates of glycolytic flux, but they
may excrete some acids that are intermediates of the
tricarboxylic acid cycle. Citric acid can be transported
out of the cells of Aspergillus niger. This organism
was therefore used for detailed studies of primary
metabolite production (Ruijter et al., 2002). Information from the measurements of different metabolite
levels was used by Torres (Torres, 1994a, 1994b) to
prepare mathematical models that simulated production of citric acid. The authors used the BST method
to propose a process optimisation solution. Data taken
from batch fermentation were transposed to a metabolic
model of carbohydrate metabolism, and the mechanistic model was translated subsequently in mathematical
terms adopting the expression of an S-system representation within the framework of BST (Savageau, 1976).
It showed that, as the steady state was stable, sensitivity theory could be applied (Torres, 1994a). The flux
and metabolite concentration control structure of the
system that was derived indicated that substrate uptake
was the main-rate-limiting step of the process (Torres,
1994b). Using this model, it was possible to use the linear programming to optimise the process. Maintaining
the metabolite pools within narrow physiological limits
and allowing the enzyme concentrations to vary within
a 0.1- to 50-fold range of their basal values, would
allow up to three-fold increase of the glycolytic flux and
result in nearly 100% transformation of substrate into
product (citric acid). To achieve these improvements, it
would be necessary to modulate seven or more enzymes
simultaneously (Torres et al., 1996). To test the model
and to increase the glycolytic flux in A. niger, two genes
coding for key regulatory enzymes have been overexpressed. However, no increase in glycolytic flux or
citric acid accumulation was observed. It appeared that
the fungus adapted to over-expression by decreasing
the specific activity of the enzymes through reduction
of the level of fructose-2,6-biphosphate, a potent effector of 6-phosphofructokinase (Ruijter et al., 1997). On
the other hand, the metabolic control model of carbo-
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
hydrate metabolism proposed by Torres et al. (1996)
was constructed using data obtained during the growth
of A. niger in medium containing low concentrations of
glucose. Today, it is accepted that this procedure leads
to metabolic alterations and slower rate of accumulation of citric acid (Xu et al., 1989) At the concentrations
higher then 400 mM, glucose enters the fungal cells
on the basis of a simple diffusion model (Wayman
and Mattey, 2000). Later, in another study 13 C-NMR
analysis revealed that the control of glycolysis during the cultivation of fungi in a medium containing a
high concentration of sugar was shifted from the level
of fructose-6-phosphate to that of glyceraldehyde-3phosphate (Peksel et al., 2002). This puts a new light
on further efforts for the optimisation of the process,
either by traditional or recombinant techniques.
An A. niger mutant with a silenced aoh gene encoding oxaloacetate hydrolase was also evaluated by MFA
(Pedersen et al., 2000). Oxalic acid is a toxic substance
produced as a by-product by Aspergilli, which are used
for the production of a variety of primary and secondary metabolites. Almost identical metabolic fluxes
were recorded when the parental strain was compared
with the mutant. This indicated that disruption of the
aoh gene had no pleiotropic consequences.
Xylose catabolism in Aspergillus species was studied by MCA (Prathumpai et al., 2003). In two A.
nidulans and in one A. niger strain, catabolic flux
exerted the main control at the level of polyol dehydrogenase, whereas when another strain was modelled, the
conclusion was that the main control of flux control is
at the first enzyme of the pathway, xylose reductase.
The primary metabolism of P. chrysogenum was
analysed by 2D(13 C,1 H) COSY NMR measurements.
Thus, the NADPH requirements for penicillin production were evaluated during growth in a chemostat
with either ammonia or nitrate as the nitrogen source
(van Winden et al., 2003). This advanced NMR
method enabled the authors to measure a number
of components of biomass. The data were used for
new metabolic flux analyses in which the cofactor
balances could be used or removed. The traditional non-oxidative pentose phosphate pathway was
enhanced with additional transketolase and transaldolase genes. Glycolysis was enhanced with the
fructose-6-phosphate aldolase/dihydroxyacetone gene
or by adding the phosphoenolpyruvate carboxykinase
gene. The results with the enhanced non-oxidative
15
pentose phosphate pathway model showed that the
transketolase and transaldolase reactions need not be as
reversible to obtain a good fit of the 13 C-labelling data.
13 C-NMR tracer experiments and NMR analysis
have been used for metabolic flux analysis of A.
oryzae producing ␣-amylase (Schmidt et al., 1998).
By growing this fungus on various nitrogen sources
the authors showed that flux analysis can be performed
on the basis of only well established stoichiometric
equations and measurements of the labelling state of
intracellular metabolites. There was no need for including NADH/NADPH balancing, nor assumptions for
energy yield to determine intracellular fluxes of primary metabolism by NMR analysis.
A more advanced technique for metabolic flux analysis using NMR spectrometry for the detection of
13 C-labelled isotopomers was employed for the construction of tentative model of central metabolism in
Ashbya gossypii (de Graaf et al., 2000). The authors
used 1 H-NMR spectroscopy which enabled them to
determine the complete isotopomer distribution in
metabolites having a backbone consisting of up to at
least four carbons. Thus, the isotopomer distribution
of aspartate isolated from (1-13 C) ethanol grown A.
gossypii was determined.
Pentose phosphate fluxes of Penicillium chrysogenum during production of ␤-lactam antibiotics were
described in two other studies. In the first stoichiometric model of P. chrysogenum, 61 internal fluxes were
determined and 49 intracellular metabolite levels were
measured. In addition, the uptakes of 21 amino acids,
glucose, lactate and ␥-aminobutyrate were taken into
consideration and production of penicillin measured.
The calculations showed that formation of penicillin
is accompanied by a large flux through the pentose
phosphate pathway due to an increased requirement for
NADPH, which was needed for formation of cysteine.
If cysteine was added to the media, the flux through the
PPP was reduced (Jorgensen et al., 1995). In the second
study of P. chrysogenum metabolism, different biosynthetic routes for generating cytosolic acetyl-CoA were
shown to influence the theoretical values of ATP and
NADPH requirements for cell biosynthesis (Henriksen
et al., 1996). The importance of formation of cysteine
in the cells of P. chrysogenum during production of
penicillin was also confirmed by other authors (van
Gulik et al., 2000). They analysed metabolic fluxes in
high and low producing mycelium and compared the
16
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
stoichiometric models. It appeared that production of
penicillin required significant changes in flux through
primary metabolism. Four principal nodes of primary
metabolism showed significant changes in flux partitioning and could be regarded as potential bottlenecks
for increased productivity.
By feeding 13 C-labelled glucose to a penicillinoverproducing strain, two novel pathways were
discovered that might have an impact on product formation. First of all, degradation of phenoxyacetic acid
(a side-chain precursor of penicillin) to acetyl-CoA
by citrate lyase was proposed. Further experimental
data suggested that the main activities of homocitrate
synthase and ␣-isopropylmalate synthase were located
in the cytosol (Christensen and Nielsen, 2000)., The
degradation of another side-chain precursor, adipate,
was evaluated using metabolic network analysis in a
recombinant strain of P. chrysogenum. Chemostat cultures with and without adipate, showed that degradation of the precursor caused undesired consumption of
adipate at the expense of formation of adipoyl-7-aminodeacetoxycephalosporanic acid (Thykaer et al.,
2002).
Another approach was used for engineering
of lovastatin producing Aspergillus terreus strains
(Askenazi et al., 2003). The method referred to as association analysis served to reduce the complexity of
profiling data sets to identify those genes whose expression was most tightly linked to secondary metabolite
production. Transcriptional profiles were generated by
genomic fragment microarrays from strains engineered
to produce varying amounts of lovastatin. Metabolite detection methods were employed to quantify
the production of secondary metabolites, lovastatine
and (+)-geodine. Association analysis of combined
metabolic and transcriptional data provided insight
into the genetic and physiological control of product
formation. This provided a tool for the improvement of lovastatin production. Also promoters for a
reporter-based selection system that was employed
after classical mutagenesis were included.
A complex stoichiometric model of the central
carbon metabolism was described recently, using information available on A. niger metabolism (David et
al., 2003). The metabolic network was reconstructed
by integrating genomic, biochemical and physiological information available for A. niger as well as
other related fungi. In the model, 284 metabolites and
335 reactions were included of which 268 represent
biochemical conversion. In addition, 67 transport processes between different intracellular compartments,
the interior of the cell and surrounding medium were
considered. The rationale of this work was to perform an in silico characterisation of the behaviour of
A. niger grown on different carbon sources. Thus, the
metabolic capacities of A. niger under different genetic
and environmental conditions were determined using
the framework of metabolite balancing in combination
with linear programming methods. This model predicts
the optimal metabolic behaviour and upper limits for
experimental data. However, the model requires further
validation and optimisation using experimental data.
Nevertheless, it can be used as a tool for the analysis,
interpretation and prediction of metabolic behaviour
and hence guide the design of improved production
strains through metabolic engineering. Furthermore,
this model could play a role in functional genomics.
Metabolites or reactions for which there is no interconnectivity in the metabolic network imply that these
metabolic reactions remain to be characterised.
2. Bacteria
2.1. Escherichia coli
Intense studies on Escherichia coli over the last
50 years have resulted in it becoming the prime
prokaryotic genetic model. Work with this species was
confined substantially to laboratory investigations until
the advent of foreign protein production whereupon the
utility of cloning methodologies for E. coli made it the
pre-eminent host for ‘protein factories’. It was at this
point that a troublesome characteristic of growth of E.
coli, the production of acetate when grown on (cheap)
glucose-based media (observed earlier (Bennett and
Holms, 1975), ceased to become a curiosity and
required a process optimisation solution. The problem
is still being observed today (Rozkov et al., 2004).
Unwanted production of acetate was a waste of carbon (up to 1/3 of the glucose used could appear as
acetate), caused pH control problems in the fermentation and the weak acetate anion could also interfere with
bacterial energetics by dissipating the pH component of
the membrane potential. A facile solution was to grow
the cells on glycerol, which was much more expen-
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
sive, but this could also result in unwanted formation of
product. Understanding how to grow E. coli efficiently,
to high cell density, with good levels of production of
foreign protein required a better understanding of the
flux of primary metabolites.
As well as flux from the central pathways to acetate,
there are other important factors: uptake of glucose,
division of carbon flow at the level of glucose 6phosphate (either to the EMP or to the PP pathway)
and the interplay between phosphenolpyruvate (PEP),
pyruvate and intermediates of the TCA cycle (including
the anaplerotic sequences that replenish TCA intermediates removed for growth or product formation).
Glucose uptake is normally by the phosphotransferase
system (PTS) that obligatorily consumes PEP and converts it to pyruvate while transferring the phosphate
group to glucose so that the product of the transport
process is glucose 6-phosphate – thus uptake and the
end steps of glycolysis are usually linked.
The connection between glucose uptake and PEP
utilisation has been broken in an ingenious way. Strains
that are defective in the glucose PTS are still capable
of slow growth on glucose, via one of the galactose transporters (GalP), which uses a proton symport
mechanism, after which the glucose is phosphorylated
internally using ATP. Glucose does not act as an inducer
of galP; therefore a constitutive mutant was needed.
Selection in a chemostat gave further up-regulation of
the transport activity and the eventual strain benefited
from up-regulation of the glucose kinase (whose activity is normally redundant when the PTS is operating).
Using such a strain, the conversion efficiency of glucose to 3-deoxy-d-arabinoheptulosonate 7-phosphate
(DAHP), the first dedicated intermediate in aromatic
amino acid biosynthesis was raised to 0.71 mol mol−1 ,
compared to 0.43 mol mol−1 when the PTS was operational (Baez et al., 2001). By following the fate of
13 C-labelled glucose, flux distributions have been confirmed (Flores et al., 2002). By over-expression of a
combination of genes in a PTS-minus strain, (BaezViveros et al., 2004) were able to increase the YPhe/Gluc
(the yield of phenylalanine per glucose consumed)
nearly 57% compared to the PTS+ strain.
The aromatic amino acid pathway has received
attention due to renewed interest in the microbial production of shikimic acid. This intermediate of the
aromatic pathway is a synthon for the neuramidase
inhibitor GS4104 (Tamiflu), an orally-active antiviral
17
compound for prevention and treatment of influenza.
Blocking the pathway, after the shikimate step, knocking out the shikimate importer to prevent re-absorbance
of the product, and using a non-PTS uptake system
resulted in a titre of 70 g/L and conversion efficiency
from glucose of 0.24 (Kramer et al., 2003).
As with streptomycetes, the PP pathway in E. coli
provides reducing power (NADPH) and carbon skeletons that are incorporated into nucleotides and aromatic
amino acids, but carbon flux is diverted from the
mainstream glycolytic pathway. Mutants in glucose 6phosphate dehydrogenase (zwf) have a non-operational
PP pathway but an increased TCA activity – consistent with the need to generate the ‘missing’ reducing
equivalents by this route (Zhao et al., 2004). In another
study, a zwf mutant showed little change in overall physiology (glucose uptake, metabolite production)
under glucose-limited conditions (flux was rerouted
via the EMP pathway and the non-oxidative part of
the PP pathway) whereas ammonia limitation resulted
in extensive overflow metabolism accompanied by
extremely low tricarboxylic acid cycle fluxes (Hua et
al., 2003). This indicates that the environmental conditions can have a profound effect on the overall result.
In the same study, a phosphoglucose isomerase (pgi)
mutant was studied. This enzyme converts glucose 6phosphate to fructose-6-phosphate and is effectively
the first dedicated step of the EMP pathway. The pgi
mutant used the PP pathway as the primary route of
glucose catabolism, which was to be expected. Surprisingly, the glyoxylate shunt was active in this mutant,
while the Entner-Doudoroff pathway played a minor
role in glucose catabolism (Hua et al., 2003). Synthesis of plasmid-encoded proteins and plasmid-DNA
replication often places a heavy metabolic burden on
producing cells and usually lowers the growth rate.
In contrast to studies where the glucose 6-phosphate
dehydrogenase gene was disrupted in order to force
more carbon down the glycolytic pathway, Flores et al.
(2004) over-expressed zwf to overcome the problem of
reduced growth rates.
The terminal stages of glycolysis involve complex
interplays. PEP may give rise to pyruvate, either by
pyruvate kinase (PK) or operation of the PTS, or it
may give rise to oxalacetate via the anaplerotic reaction PEP carboxylase (ppc). Pyruvate may be converted
in three ways: to lactate (oxidizing NADH), eventually
to ethanol, or decarboxylated to form acetyl-CoA in
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preparation for incorporation to the TCA cycle. There
are two PK isoforms (pykA and pykF), so a double
mutant had to be constructed (Emmerling et al., 2002).
This mutant diverted carbon flux via Ppc and malic
enzyme, which might be expected. Of course, pyruvate can also be produced in this PK-minus background
by uptake of glucose and concomitant formation of
pyruvate from PEP. The flux through Ppc was now
greater than that previously through the PK step, indicating that glucose utilisation was increased. Flux
through the PP pathway was reduced in concert during
glucose-limitation but increased under ammonia limitation – further emphasising the role of environmental
conditions on the outcome. These observations were
substantially verified by GC–MS analysis of metabolite
profiles (Fischer and Sauer, 2003)
The production of acetate can be substantially
alleviated by mutation of acetate kinase and phosphotransacetylase, which catalyse formation of acetate
from acetyl-CoA. However, this does decrease the cellular growth rate and often results in excretion of lactate
and some TCA cycle intermediates (El-Mansi, 2004).
Therefore, the problems associated with acetate excretion may be resolved, but at a metabolic cost.
E. coli has shown a remarkable tolerance to drastic changes in metabolic flux implying a considerable
elasticity in permitted pool size for key intermediates,
such as pyruvate and acetyl-CoA (Causey et al., 2004).
The construction of the strain TC44 for pyruvate excretion during oxidative metabolism of glucose required
mutations that would reduce the utilisation of pyruvate for cell growth and the elimination of all major
non-essential pathways. By combining mutations to
minimise ATP yield, cell growth, and CO2 production
(atpFH adhE sucA) with mutations that eliminate acetate production [poxB::FRT (FLP recognition
target) ackA] and fermentation products (focA-pflB
frdBC IdhA adhE), TC44 converted glucose to
pyruvate at a yield of 0.75 g pyruvate per g of glucose (77.9% of theoretical yield; 1.2 g of pyruvate
litres−1 h−1 ) in mineral salts medium with glucose as
the sole carbon source. A maximum of 749 mM pyruvate was produced in excess glucose, correlated with an
increased glycolytic flux of >50% compared with the
unmodified strain. The significant rate of pyruvate production and consequent yield in mineral salts medium
is an exciting economical result considering that other
biocatalysts for pyruvate production (yeast and bacteria
(Li et al., 2001; Yokota et al., 1994)) require complex
vitamin feeding strategies and complex nutrients.
Succinate formation occurs primarily through the
reductive branch of the TCA cycle, known as the fermentative pathway during anaerobic conditions and the
glyoxylate shunt. However, one major obstacle to high
succinate yield through the fermentation pathway is
due to NADH limitation: 1 mole of glucose can provide only 2 moles of NADH through the glycolytic
pathway; however, the formation of 1 mole of succinate requires 2 moles of NADH. While the amount of
NADH availability remains, any redirection of carbon
flux to OAA will yield limited succinate production.
Deactivating adhE, ldhA and ack-pta from the central
metabolic pathway, and activating the glyoxylate shunt
through the inactivation of iclR, which encodes a transcriptional repressor protein of the glyoxylate shunt,
has provided a novel in vivo method for increased succinate yield from glucose (Sanchez et al., 2005). The
deletion of the lactate and ethanol pathways (ldhA
adhE) both conserved NADH for further succinate
formation through the native fermentative pathway and
carbon atoms to help channel carbon to the acetylCoA pool and the glyoxylate shunt. Similarly, the
deletion of the ackA-pta pathway helped to channel
the carbon to acetyl-CoA. Together, these mutations
allowed for an increased yield of succinate from glucose to about 1.6 mol/mol with an average anaerobic
productivity rate of 10 mM/h (∼0.64 mM/h-OD600 ).
Interestingly, further de-repression of the glyoxylate
shunt by the deletion of the arcA (phosphorylated ArcA
is a dual transcriptional regulator of aerobic respiration
control and represses transcription of the glyoxylate
shunt operon (Spiro and Guest, 1991) did not significantly increase the succinate yield but did decrease
the glucose consumption by 80%. Further, analysis
of a adhEldhAack-pta strain over-expressing a
Bacillus subtilis NADH-insensitive citrate synthase
gene increased succinate production to that seen in the
adhE ldhA ack-pta iclR strain.
The capacity of metabolic networks to compensate for mutations is referred to as genetic robustness
(Wagner, 2000). With redundancy ensured by gene
duplication, the knockout of one gene is readily
compensated either by one or more isoenzymes, or
alternative pathways or genes with unrelated function becoming active and compensating for the loss
of function. Recent transcript analysis of acetate-
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
grown E. coli compared with that grown on glucose
highlighted the possible gene utilisation and the
roles of converging pathways (Oh et al., 2002). For
example, the recently characterised class I type of
fructose-bisphosphate aldolase (dhnA; (Thomson et
al., 1998)) was shown to be up-regulated compared
with the known fructose-bisphosphate aldolase (fba)
and the revelation of differentially regulated open
reading frames that were poorly characterised consequently providing important information to predict
their function in the future. The surprising induction
of phosphoenolpyruvate synthase (ppsA), thought to
be non-essential for gluconeogenesis during growth
on acetate (Holms, 1996), together with both NADdependent (sfcA) and NADP-dependent (maeB) malic
enzymes also highlights the dependability on genetic
robustness. Further mutational investigation of these
genes, as well as phosphoenolpyruvate carboxylase
(pckA), showed that both enzymes served to provide
the phosphoenolpyruvate pool. While single knock
out mutations of pckA and ppsA still yielded growth
on acetate, a double mutation did not, implying that
PpsA, together with the malic enzymes, acts as an
alternative pathway to PckA by delivering metabolites from the TCA cycle to the Embden-Meyerhoff
pathway. Precision is the obvious key to successful metabolic engineering. The utility to predict gene
function by microarray allows for the improvement
of pathway information and the focus for future
manipulation.
2.2. Bacillus sp.
Bacillus sp. are widely used for the production
of vitamins and other products, including industrial
enzymes, such as amylases, proteases and lipases.
Bacillus subtilis has historically been an attractive host
for the expression of protein on an industrial scale due
to its ability to secrete foreign proteins directly into the
culture medium (Doi and Wang, 1986; Priest, 1977).
This therefore, e.g. minimises the need for extensive
purification as seen for protein extracts from E. coli.
Anaplerotic reactions contribute to the flux through
the TCA cycle, the main provider for metabolic precursor molecules, therefore the reactions at the interface
between the lower part of glycolysis and the TCA cycle
are an important metabolic subsystem (Blencke et al.,
2003).
19
Pyruvate kinase mutants of B. subtilis showed a
higher production of CO2 from glucose in the TCA
cycle than could be accounted to the remaining conversion of PEP to pyruvate by the phosphotransferase
system. Zamboni et al. (2004) exposed the activity
of the, normally gluconeogenic PEP carboxykinase
as the reason for the increased flux towards the TCA
cycle upon disruption of the actual anaplerotic reaction
of pyruvate carboxylase. Interestingly, the mutations
led to impaired growth in an industrial, riboflavinproducing strain, whereas the wild-type strain could
not grow at all, most probably due to the unfavourable
kinetics of ATP synthesis in this background.
An intrinsic property and a critical process variable
in fed-batch fermentations with slow-growing cells is
the non-growth associated maintenance energy coefficient (Russell and Cook, 1995; Zamboni et al., 2003).
Alternating environmental conditions and by redirection of electron flow to more efficient proton pumping
branches within respiratory chains, it is possible to
optimise this maintenance metabolism – where the
organism remains in a viable state without growth but
with optimised energy generation. B. subtilis possesses
a branched respiratory chain consisting of both quinol
(cyd, qox, yth operons) and cytochrome c (ctaCDEF)
terminal oxidases (Calhoun et al., 1993; Neijssel and
Teixeira de Mattos, 1994; Richardson, 2000). By
increasing the efficiency of energy generation using
a cytochrome bd oxidase mutation, the rate of maintenance metabolism was reduced by 40% (Zamboni
et al., 2003). The possible route for improvement
was the translocation of two protons per transported
electron via the remaining cytochrome aa3 oxidase,
instead of only one proton via the bd oxidase, increasing riboflavin production. Zamboni and Sauer (2003)
added to this by indicating that efficient ATP generation is not necessary for exponential growth in batch
culture. There was no apparent phenotypic difference in
the bd oxidase mutation, and although the aa3 oxidase
mutation caused severe disruption to the TCA flux with
increased metabolic flow, no change in the productcorrected biomass yields was observed between the
mutant and the parental strain.
2.3. Streptomycetes
The order Actinomycetales comprises a plethora
of remarkable prokaryotic organisms. Genetically
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A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
diverse, they have a profound influence on our
daily lives. While some cause disease, e.g. tuberculosis (Mycobacterium tuberculosis) and leprosy
(Mycobacterium leprae), others are of great industrial
importance, such as Corynebacterium glutamicum,
which is a significant producer of amino acids (Ikeda,
2003). However, it is the dual industrial and therapeutic
importance of the genus Streptomyces that makes them
renowned.
Two streptomycete genomes have been sequenced
recently: the industrial-important Streptomyces avermitilis (Omura et al., 2001) and the genetically
well-characterised Streptomyces coelicolor A3(2)
(Bentley et al., 2002). At more than 8.66 Mb, the S.
coelicolor genome encodes pathways for the production of over 20 natural secondary metabolites.
Secondary metabolic pathways have been the obvious choice for investigation of strain manipulation and
yield improvement in Streptomyces. Until recently,
the enzymes controlling the pathways of primary
metabolism have been substantially ignored. Manipulation would allow greater harnessing of energy and
reducing power that in turn could be used to synthesise cellular building blocks and those for the valuable
metabolites.
Relatively little is known about the intermediary
metabolic pathways of most streptomycetes. An extensive review on primary metabolism by Hodgson (2000)
reported that the Embden-Meyerhof-Parnas (EMP), the
pentose phosphate (PP) and TCA cycle pathways were
present in a number of Streptomyces species. About
60% of the proteins identified in an early study of
the S. coelicolor proteome were associated with primary metabolism (Hesketh et al., 2002). Interestingly,
the genome sequence has identified many enzyme isoforms for some of the metabolic steps, which differ in
temporal expression. Till date, this observation has not
been exploited fully by manipulating the genes for such
enzymes.
The precursors for polyketide secondary metabolites are derived primarily from the intermediates,
acetyl-CoA and malonyl-CoA, peptide antibiotics are
derived from amino acids, sugars, shikimate and
nucleotides (Hodgson, 2000). Flux distributions calculated for production of actinorhodin (ACT, polyketide)
and ‘calcium-dependent antibiotic’ (CDA, oligopeptide) in S. coelicolor (Kim et al., 2004a; Naeimpoor
and Mavituna, 2000), demonstrated the scope for
re-programming. Precursor-directed biosynthesis with
mutated strains, by metabolic flux rebalancing,
provided novel products with improved properties
(Wohlleben and Pelzer, 2002). Fluxes associated
with prephenate and oxoglutarate, succinate, nitrogen
assimilation and flavin adenine dinucleotide (FAD)
production were fundamental for CDA production, and
correlated with direction of glucose flux to the oxidative
PP pathway (Kim et al., 2004a).
Distribution of carbon flux distribution in chemostat
cultures of S. lividans grown on glucose or gluconate
showed increased carbon flux through glycolysis and
the PP pathway with increased growth rate, whilst
the synthesis of both ACT and the pigmented antibiotic undecylprodigiosin (RED) was inverse to flux
through the PP pathway (Avignone Rossa et al., 2002).
Deletions of either of two genes (zwf1 and zwf2)
encoding the isozymes of glucose-6-phosphate dehydrogenase, which is the initial enzyme of the PP
pathway, resulted in enhanced production of the antibiotics ACT and RED (Butler et al., 2002). Interestingly,
glucose was utilised more efficiently via glycolysis,
with no decrease in concentration of NADPH. Similar
results were achieved with the devB strain, mutated in
6-phosphogluconolactonase, the next enzyme of the PP
pathway. However, a zwf1zwf2devB triple mutant
produced reduced levels of ACT and RED, suggesting
that NADPH is essential, either directly or indirectly,
in antibiotic production.
Metabolic flux analysis, through following the distribution of labelling in precursor pools, is fundamental
for the determination of influential pathways. Li et al.
(2004) established that crotonyl-CoA reductase (CCR)
had a significant role in provision of methylmalonylCoA for monensin biosynthesis in oil-based, 10-day
fermentations of S. cinnamonensis. Labelling of the
coenzyme A pools, and analysis of intracellular acylCoAs in high-titre production strains, demonstrated
that ccr mutants had lower levels of the monensin
precursor methymalonyl-CoA, while expression of a
heterologous ccr gene from S. collinus fully restored
production of monensin. Extended oil-based fermentation with S. cinnamonensis C730.1 determined that
ethyl [3,4-13C2]acetoacetate was incorporated intact
into both the ethylmalonyl-CoA- and methylmalonylCoA-derived positions of monensin, whereas no
labelling of the malonyl-CoA-derived positions was
observed. A ccr strain had reversed carbon
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
flux from an acetoacetyl-CoA intermediate – a
result contrasted in fermentations on glucose-soybean
medium, which provided ethylmalonyl-CoA but not
methylmalonyl-CoA. Production of precursors for secondary metabolites is therefore influenced substantially
by fermentation conditions.
Engineering of unusual precursor pathways can
result in increased polyketide production (Rodriguez
et al., 2004). A tylosin-overproducer of S. fradiae
was chosen as it made high levels of malonyl-CoA,
methylmalonyl-CoA, and ethylmalonyl-CoA precursors. When a fourth pathway, for methoxymalonylACP synthesis from S. hygroscopicus, was introduced
into a strain mutated in the tylosin polyketide synthases
(PKS) genes, the resultant recombinant produced
at least 1 g/l of a midecamycin analog. Such an
approach could also be used for creating novel
products.
In silico studies of metabolic flux distribution,
linked to sensitivity analyses during various phases
of the batch culture, is a fundamental tool in
the re-engineering of pathways involved in primary
metabolism. Whereas genetic amplifications create a
wide range of flux values, deletion of a gene results
in zero flux at that step. Specific routes should be
investigated with care so that pathways fundamental to
cellular biosynthesis or productivity are not impinged,
i.e. as seen with the S. coelicolor mutant for citrate synthase, citA. This enzyme, which acts at the junction
of the glycolytic and TCA pathway, is ideally situated
to maintain physiological balance by decreasing glycolytic flux or increasing TCA cycle flux. However, the
citA strain was unable to produce aerial mycelium
or the antibiotics ACT and RED. Although it consumed glucose at a higher rate, it was unable to oxidize
glycolytic products via the TCA cycle – a defect suppressed by the removal of glucose from the medium
or genetic manipulations of glucose kinase, preventing the utilisation of glucose (Viollier et al., 2001a).
Similarly, aconitase mutants had fundamental physiological defects (Schwartz et al., 1999; Viollier et al.,
2001b).
The development of microarray technology based
on the S. coelicolor genome enables strain comparison based on the characterisation of expression
of thousands of genes, which provides information for future manipulation for strain improvement.
An approach for ‘reverse engineering’ of improved
21
erythromycin producing strains of Aeromicrobium erythreum by tagged-mutagenesis, identified two genes,
mutB and cobA, in the primary metabolic branch for
methylmalonyl-CoA utilisation. Knockouts of these
genes resulted in a permanent metabolic switch in the
flow of methylmalonyl-CoA, from the primary branch
into a secondary metabolic branch, enhancing erythromycin overproduction (Reeves et al., 2004).
2.4. Corynebacteria
Corynebacteria, mainly C. glutamicum, have been
used for industrial amino acid production for several decades and extensive studies about physiology,
genetics, a considerable number of patents and
metabolic engineering approaches emphasise the commercial importance of these micro-organisms (Bott and
Niebisch, 2003; Eggeling et al., 2005; Jetten et al.,
1994; Jetten and Sinskey, 1995; Kirchner and Tauch,
2003; Patek et al., 2003; Sahm et al., 1996; Wendisch,
2003).
Knowledge of the genome sequence (Kalinowski
et al., 2003) and development of robust microarray
procedures (Loos et al., 2001) facilitated research
on biotechnological applications (Hermann, 2003). In
2003, l-lysine production exceeded 600,000 tons per
year (Pfefferle et al., 2003), all of which were produced
by fermentation.
C. glutamicum exhibits high gluconeogenic activity in vivo via phosphoenolpyruvate carboxykinase
(PEPCk), which is responsible for phosphoenolpyruvate formation from anaplerotically synthesised
oxaloacetate during growth on glucose, thereby contributing to an apparently futile substrate cycling
between oxaloacetate, phosphoenolpyruvate and pyruvate (Petersen et al., 2000). Deletion of the respective
pck gene in l-lysine producing strain MH20-22B
resulted in increased intracellular concentrations of
l-aspartate, l-lysine, pyruvate, oxaloacetate and in
a 60% enhanced flux towards l-lysine biosynthesis,
whereas over-expression of pck led to a 20% decrease,
without significant changes in growth or substrate
uptake rate (Petersen et al., 2001). Increased CO2 production in the pck over-expressing strain was found
and further indicates elevated energy demand with
increasing PEPCk activity versus reduced CO2 production and energy demand in a pck mutant. The
counterproductive effect of PEPCk activity, which is
22
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
essential for gluconeogensis in C. glutamicum, has also
been shown for glutamate production. PEPCk deficient
mutants showed four-fold higher glutamate production,
whereas pck over-expression lowered production about
three-fold (Riedel et al., 2001).
Over-expression
of
pyruvate
carboxylase,
catalysing the formation of oxaloacetate from
pyruvate, therefore should have a similar effect on
lysine production. However, Koffas et al. (2003)
showed that over-expression of the pyc gene enhanced
growth but reduced specific lysine productivity.
Simultaneous expression of aspartate kinase, a key
enzyme of the lysine production pathway, abolished
this deficiency and yielded more than 250% increase
of the specific productivity. Over-expression of pyc
in a strain with different regulatory characteristics
resulted in seven-fold higher glutamate production and
increased lysine accumulation (Peters-Wendisch et
al., 2001), a clear indication of the importance of this
gene for strain improvement. “Genome–based strain
reconstruction” confirmed the importance of pyc in
lysine production (Ohnishi et al., 2002). Mutations in
genes of interest, in this case the genes of the lysine
biosynthesis pathway, were identified by comparative
genomic analysis in a classically developed production
strain. Beneficial mutations are then reassembled in a
wild-type background. Point mutations in three genes,
the homoserine dehydrogenase gene (homV59A ), the
aspartokinase gene (lysCT311I ) and the pyruvate carboxylase gene (pycP458S ) were identified. Introduction
of one mutation at a time into a wild-type strain led to
increased accumulation of lysine and the combination
of all three mutations showed a synergistic effect on
the production in the resulting AHP-3 strain. Recently,
the authors turned their attention to the PPP and
identified a mutation in the 6-phosphogluconate dehydrogenase gene (gnd) as useful for lysine production
(Ohnishi et al., 2005). Introduction of this mutation,
which resulted in lower sensitivity towards allosteric
inhibition by intracellular metabolites, into the AHP-3
strain led to 15% increased lysine production and
8% higher carbon flux through the PPP. A thorough
investigation of the influence of point mutations
in several genes of the central metabolism and of
amino acid production pathways on different carbon
sources was published recently (Georgi et al., 2005).
The effects of the mutations were miscellaneous
with respect to lysine yields on the carbon sources
but clearly certified positive effects of homV59A and
pycP458S . Fructose-1,6-bisphosphatase activity was
revealed as a limiting factor if sucrose was the sole
carbon source while over-expression of malE had no
effect on the lysine production with the tested carbon
sources.
Two intermediates of the PPP, ribose 5-phosphate
and erythrose 4-phosphate, are important precursors for
biosynthesis of nucleotides and aromatic amino acids,
highlighting the importance of this pathway for efficient production of desired metabolites. Transketolase,
an enzyme of the non-oxidative branch of the PPP, was
investigated as a possible target for metabolic engineering to increase the availability of ribose 5-phosphate
in C. ammoniagenes for production of inosine and
5 -xanthylic acid. A 10-fold increase of transketolase
activity resulted in about 80% product yield, compared
to the parental strain. Disruption of the tkt gene on the
other hand, resulted in up to 30% more accumulation
of product, proving that interception of the ribose 5phosphate shunt back to glycolysis by transketolase
allows the cells to redirect the carbon flow through
the oxidative PPP towards the purine-nucleotide pathway (Kamada et al., 2001). Disruption of the glucose
6-phosphate dehydrogenase gene (zwf) resulted in a
decrease in product yield of about 50%, indicating the
importance of the oxidative branch of the PPP for precursor supply, although non-oxidative synthesis was
possible, albeit at an insufficient level (Kamada et al.,
2003).
As l-lysine production correlates with intracellular NADPH supply, Marx et al. (2003) constructed
a phosphoglucose isomerase (pgi) null mutant of C.
glutamicum to redirect the carbon flux through the
PPP. l-Lysine production increased with simultaneous decrease of by-product formation and growth rate,
a common feature of pgi mutants due to disturbed
metabolism of NADPH. Redirection of the carbon
flux towards PPP may also have a general applicability for metabolic engineering of biosynthesis of
metabolites for which NADPH supply is necessary.
Another possibility is the engineering of the cofactor specificity of the enzymes involved (Banta et al.,
2002).
l-Phenylalanine, one of the essential amino acids
for humans, is synthesised from chorismate in three
steps, catalysed by enzymes which are subject to feedback inhibition. Liu et al. (2004) blocked the branch
A. Kern et al. / Journal of Biotechnology 129 (2007) 6–29
pathway of l-tyrosine biosynthesis by disruption of the
tyrA gene and integration of aroG and pheA from E.
coli, key genes in l-phenylalanine biosynthesis in E.
coli. Improved enzyme activity in the desired pathway
and disruption of the pathway competing for precursors resulted in the expected outcome, namely 30%
increased yield.
Recently, an attempt to enable C. glutamicum to
utilise whey, as a substrate, has been made. The
determinants for lactose (␤-galactosidase and lactose
permease) and galactose (galactose operon) utilisation
were heterologously expressed in the lysine production
strain C. glutamicum ATCC 21253.
The engineered strain was capable of slow growth
on whey-based medium and produced 2 mg/ml lysine,
a 10-fold increase compared to the parent strain.
Another interesting finding was that the engineered
strain retained its viability after extended incubation,
whereas the viability of the parental strain dropped
about 90% after 225 h (Barrett et al., 2004).
3. Conclusion
Many different pathways and regulatory features
have been targets for metabolic engineers, be it
increased yield of product or elimination of product,
which in the end serves the same purpose. As has been
discussed in the introduction, engineering the often
metabolism often has unexpected results and can cause
new problems, most often reduced growth rates. Evolutionary breeding has been shown to be an excellent
method to overcome these obstacles, when rational
solutions were not available or extremely complex
technically – if at all possible.
On the other hand, metabolic analysis of mutant
strains has provided invaluable insights into the underlying changes in metabolism, providing data for the
next round of metabolic engineering.
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