involved in alcohol catabolism, and the thiamine repressible thiA promoter, controlling
expression of thiamine thiazole synthase
involved in thiamine synthesis. This type of
promoters can typically also be expected to
function in other species, such as the PthiA of
A. oryzae shown to also be functional in A.
nidulans (Shoji et al. 2005) and the A. nidulans
PalcA applied in A. fumigatus (Romero et al.
2003). Some very strong inducible promoters
depend on degradation of the feedstock, e.g.,
the starch-inducible promoter of A. niger glaA,
controlling expression of a secreted glucoamylase/1,4-alpha-glucosidase for starch hydrolysis. Similarly, a favorite promoter from T.
reesei is the cel7a promoter controlling expression of secreted cellobiohydrolase I, which is
induced on media containing cellulose or lactose. For promoters that normally drive expression of secreted biomass-degrading enzymes,
the conditions inducing the gene expression
typically involve co-induction of other endogenous genes of secreted biomass-degrading
enzymes. Thereby, this may lead to production
of these enzymes as undesired side-products.
The activation mechanisms of such promoters
are more specialized than for genes of the central metabolism and may not be directly transferrable from species to species. For example,
activation of T. reesei Pcel7a involves recruitment of a general transcription factor of
cellulase-encoding genes, Xyr1 (Castro et al.
2016), in complex with a non-coding RNA,
HAX1 (Till et al. 2018; Table 10.2).
a) Approaches for Identification of Natural
Promoters
Classical promoters may often be chosen due to
their availability and history rather than due to
considerations on whether their expression
profile and strength fit the heterologous production process. Hence, in many cases the
default choice is to employ the strongest promoter available as a basis for heterologous production. However, in some cases, maximum
transcription levels are not desirable. For example, if the goal is to produce a complex secondary metabolite, the set of genes required to
synthesize this compound may need to be
expressed at different levels to achieve a balanced biosynthetic pathway. Expanding the
library of fungal promoters to include members displaying a wide range of different
expression strengths and other properties is
therefore desirable. Fortunately, their discovery
is accelerated by the availability of fully or partially sequenced fungal genomes. For example,
by analyzing genome-wide transcription profiles obtained at different growth stages on different relevant growth media, it is possible to
identify promoters with properties that are tailored to fit a given process. In the simplest
scheme, one may apply small-scale targeted
transcriptomic approaches, like RT-qPCR to
determine the promoter strength under certain
conditions (Li et al. 2012). Alternatively, large
publically available datasets can be applied,
such as the A. niger transcriptome microarrays
covering several different growth conditions
(Andersen et al. 2008; Breakspear and Momany
2007). Currently, transcriptomic microarray
datasets covering 155 different cultivation conditions are available for A. niger (Scha ¨pe et al.
2019). Using this approach to their advantage,
Blumhoff and co-workers identified six novel
constitutive A. niger promoters with varying
expression strength (Blumhoff et al. 2013).
The library contains promoters that are stronger and weaker than A. niger PgpdA displaying
ten-fold differences in expression levels of
native genes, and when applied to produce the
b-glucuronidase (uidA) from E. coli, 1000-fold
in specific activity yields were obtained. A similar set of T. reesei promoters displaying varying expression strengths has been derived from
its glycolytic genes (Li et al. 2012), and in Penicillium chrysogenum both homologous and heterologous promoters have been evaluated for
expression efficiency (Polli et al. 2016). It is
important to note that although genome-wide
transcription profiles provide mRNA levels for
specific genes, they do not define the exact
promoter sequences that control these genes.
To this end, a global map of transcription initiation sites in A. nidulans was generated based
on full-scale RNA-sequencing of gene tran240
J. K. H. Rendsvig et al.
expression of thiamine thiazole synthase
involved in thiamine synthesis. This type of
promoters can typically also be expected to
function in other species, such as the PthiA of
A. oryzae shown to also be functional in A.
nidulans (Shoji et al. 2005) and the A. nidulans
PalcA applied in A. fumigatus (Romero et al.
2003). Some very strong inducible promoters
depend on degradation of the feedstock, e.g.,
the starch-inducible promoter of A. niger glaA,
controlling expression of a secreted glucoamylase/1,4-alpha-glucosidase for starch hydrolysis. Similarly, a favorite promoter from T.
reesei is the cel7a promoter controlling expression of secreted cellobiohydrolase I, which is
induced on media containing cellulose or lactose. For promoters that normally drive expression of secreted biomass-degrading enzymes,
the conditions inducing the gene expression
typically involve co-induction of other endogenous genes of secreted biomass-degrading
enzymes. Thereby, this may lead to production
of these enzymes as undesired side-products.
The activation mechanisms of such promoters
are more specialized than for genes of the central metabolism and may not be directly transferrable from species to species. For example,
activation of T. reesei Pcel7a involves recruitment of a general transcription factor of
cellulase-encoding genes, Xyr1 (Castro et al.
2016), in complex with a non-coding RNA,
HAX1 (Till et al. 2018; Table 10.2).
a) Approaches for Identification of Natural
Promoters
Classical promoters may often be chosen due to
their availability and history rather than due to
considerations on whether their expression
profile and strength fit the heterologous production process. Hence, in many cases the
default choice is to employ the strongest promoter available as a basis for heterologous production. However, in some cases, maximum
transcription levels are not desirable. For example, if the goal is to produce a complex secondary metabolite, the set of genes required to
synthesize this compound may need to be
expressed at different levels to achieve a balanced biosynthetic pathway. Expanding the
library of fungal promoters to include members displaying a wide range of different
expression strengths and other properties is
therefore desirable. Fortunately, their discovery
is accelerated by the availability of fully or partially sequenced fungal genomes. For example,
by analyzing genome-wide transcription profiles obtained at different growth stages on different relevant growth media, it is possible to
identify promoters with properties that are tailored to fit a given process. In the simplest
scheme, one may apply small-scale targeted
transcriptomic approaches, like RT-qPCR to
determine the promoter strength under certain
conditions (Li et al. 2012). Alternatively, large
publically available datasets can be applied,
such as the A. niger transcriptome microarrays
covering several different growth conditions
(Andersen et al. 2008; Breakspear and Momany
2007). Currently, transcriptomic microarray
datasets covering 155 different cultivation conditions are available for A. niger (Scha ¨pe et al.
2019). Using this approach to their advantage,
Blumhoff and co-workers identified six novel
constitutive A. niger promoters with varying
expression strength (Blumhoff et al. 2013).
The library contains promoters that are stronger and weaker than A. niger PgpdA displaying
ten-fold differences in expression levels of
native genes, and when applied to produce the
b-glucuronidase (uidA) from E. coli, 1000-fold
in specific activity yields were obtained. A similar set of T. reesei promoters displaying varying expression strengths has been derived from
its glycolytic genes (Li et al. 2012), and in Penicillium chrysogenum both homologous and heterologous promoters have been evaluated for
expression efficiency (Polli et al. 2016). It is
important to note that although genome-wide
transcription profiles provide mRNA levels for
specific genes, they do not define the exact
promoter sequences that control these genes.
To this end, a global map of transcription initiation sites in A. nidulans was generated based
on full-scale RNA-sequencing of gene tran240
J. K. H. Rendsvig et al.