C. Dynamic Pathway Control and Biosensors
The metabolic engineering of yeast to produce a
desired compound can result in an imbalanced
metabolism due to the disruption of a tightly
regulated, complex biological system, which
has evolved for growth and survival. However,
inherent control components of this system,
such as promoters, transcription factors, or
gene copy number, can be utilized for a
dynamic pathway control, thereby minimizing
metabolic imbalances and increasing product
titers (Michener et al. 2012; Schallmey et al.
2014; Shi et al. 2018).
1. Altering Gene Expression Level and Timing
The level and timing of pathway gene expression is crucial in metabolic engineering and can
be adjusted, for instance, by using constitutive
promoters of different strengths or promoters
that are inducible/repressible (Da Silva and
Srikrishnan 2012). This strategy was applied
successfully, for example, to increase 1-alkene
production and secretion in S. cerevisiae. By
replacing the strong eTDH3 promoter for
expression of the membrane-bound enzyme
PfUndB with the GAL7 promoter, which is activated upon glucose depletion, 1-alkene production was decoupled from growth (Zhou et al.
2018). The same strategy, i.e., to separate
growth from production by expressing pathway
genes under the control of carbon sourcedependent promoters, was also effective in
increasing docosanol production (Yu et al.
2017). A similar approach was applied for S.
cerevisiae short- and medium-chain FA production, again with a glucose-repressed promoter. Here, FAS1 and FAS2 were expressed
on a low copy plasmid under control of the
alcohol dehydrogenase II promoter of S. cerevisiae, pADH2, leading to increased short- and
medium-chain FA titers (Gajewski et al. 2017).
In another approach, several promoters of different strengths were tested for downregulating
the expression of IDH2 (carbon flux redistribution into free FA) and PGI1 (increasing NADPH
supply), respectively, as the deletion of either
gene led to growth defects. The expression of
the genes was reduced by using weaker promoters, leading to increased long-chain FA production in S. cerevisiae (Yu et al. 2018). These
examples underpin the importance of an
appropriate control of gene expression and
have much potential to be further exploited
for increasing short- and medium-chain FA
production—especially as promoters and terminators of different strengths have been
described in great detail in recent years (Alper
et al. 2005; Da Silva and Srikrishnan 2012; Curran et al. 2013; Lee et al. 2015).
2. Biosensors
Currently, the analysis of short- and mediumchain FA titers is time-consuming and laborious and is usually achieved through
chromatography-based methods. A more
rapid and convenient alternative are biosensors. They detect the concentration of a molecule—ideally over a wide range of
concentrations—and transform it into an easily
detectable, quantifiable output, such as growth
rate or fluorescence, eventually enabling highthroughput screenings, as depicted in Fig. 14.2
(Michener et al. 2012; Schallmey et al. 2014; Shi
et al. 2018). One example of in vivo biosensors
is transcription factors, which, in nature, are
inevitable for the dynamic control of gene
expression. Once their inducing molecules and
target promoters are known, transcription factors can be used in metabolic engineering to
regulate production pathway expression or
even live-monitor titers. Several bacterial transcription factor-based systems have been
adapted to yeast (Teo et al. 2013; Li et al. 2015;
Skjoedt et al. 2016; Wang et al. 2016), especially
dynamic sensor-regulator systems of the FA
intermediate MalCoA (Johnson et al. 2017).
The prokaryotic transcription factor-based
FapR-fapO system has been engineered in S.
cerevisiae and enabled the sensing of intracellular MalCoA levels (Li et al. 2015; David et al.
2016). This system has been expanded to dynamically control production by coupling the
expression of 3-hydroxypropionic acid path354
L. Baumann et al.
The metabolic engineering of yeast to produce a
desired compound can result in an imbalanced
metabolism due to the disruption of a tightly
regulated, complex biological system, which
has evolved for growth and survival. However,
inherent control components of this system,
such as promoters, transcription factors, or
gene copy number, can be utilized for a
dynamic pathway control, thereby minimizing
metabolic imbalances and increasing product
titers (Michener et al. 2012; Schallmey et al.
2014; Shi et al. 2018).
1. Altering Gene Expression Level and Timing
The level and timing of pathway gene expression is crucial in metabolic engineering and can
be adjusted, for instance, by using constitutive
promoters of different strengths or promoters
that are inducible/repressible (Da Silva and
Srikrishnan 2012). This strategy was applied
successfully, for example, to increase 1-alkene
production and secretion in S. cerevisiae. By
replacing the strong eTDH3 promoter for
expression of the membrane-bound enzyme
PfUndB with the GAL7 promoter, which is activated upon glucose depletion, 1-alkene production was decoupled from growth (Zhou et al.
2018). The same strategy, i.e., to separate
growth from production by expressing pathway
genes under the control of carbon sourcedependent promoters, was also effective in
increasing docosanol production (Yu et al.
2017). A similar approach was applied for S.
cerevisiae short- and medium-chain FA production, again with a glucose-repressed promoter. Here, FAS1 and FAS2 were expressed
on a low copy plasmid under control of the
alcohol dehydrogenase II promoter of S. cerevisiae, pADH2, leading to increased short- and
medium-chain FA titers (Gajewski et al. 2017).
In another approach, several promoters of different strengths were tested for downregulating
the expression of IDH2 (carbon flux redistribution into free FA) and PGI1 (increasing NADPH
supply), respectively, as the deletion of either
gene led to growth defects. The expression of
the genes was reduced by using weaker promoters, leading to increased long-chain FA production in S. cerevisiae (Yu et al. 2018). These
examples underpin the importance of an
appropriate control of gene expression and
have much potential to be further exploited
for increasing short- and medium-chain FA
production—especially as promoters and terminators of different strengths have been
described in great detail in recent years (Alper
et al. 2005; Da Silva and Srikrishnan 2012; Curran et al. 2013; Lee et al. 2015).
2. Biosensors
Currently, the analysis of short- and mediumchain FA titers is time-consuming and laborious and is usually achieved through
chromatography-based methods. A more
rapid and convenient alternative are biosensors. They detect the concentration of a molecule—ideally over a wide range of
concentrations—and transform it into an easily
detectable, quantifiable output, such as growth
rate or fluorescence, eventually enabling highthroughput screenings, as depicted in Fig. 14.2
(Michener et al. 2012; Schallmey et al. 2014; Shi
et al. 2018). One example of in vivo biosensors
is transcription factors, which, in nature, are
inevitable for the dynamic control of gene
expression. Once their inducing molecules and
target promoters are known, transcription factors can be used in metabolic engineering to
regulate production pathway expression or
even live-monitor titers. Several bacterial transcription factor-based systems have been
adapted to yeast (Teo et al. 2013; Li et al. 2015;
Skjoedt et al. 2016; Wang et al. 2016), especially
dynamic sensor-regulator systems of the FA
intermediate MalCoA (Johnson et al. 2017).
The prokaryotic transcription factor-based
FapR-fapO system has been engineered in S.
cerevisiae and enabled the sensing of intracellular MalCoA levels (Li et al. 2015; David et al.
2016). This system has been expanded to dynamically control production by coupling the
expression of 3-hydroxypropionic acid path354
L. Baumann et al.