Suietal. Microb Cell Fact (2020) 19:198
https://doi.org/10.1186/s12934-020-01450-w
RESEARCH
Engineering cofactor metabolism
forimproved protein andglucoamylase
production inAspergillus niger
Yu‑fei Sui1,2, Tabea Schütze2 , Li‑ming Ouyang1, Hongzhong Lu3, Peng Liu1, Xianzun Xiao1, Jie Qi1,
Ying‑Ping Zhuang1* and Vera Meyer2*
Abstract
Background: Nicotinamide adenine dinucleotide phosphate (NADPH) is an important cofactor ensuring intracel‑
lular redox balance, anabolism and cell growth in all living systems. Our recent multi‑omics analyses of glucoamylase
(GlaA) biosynthesis in the filamentous fungal cell factory Aspergillus niger indicated that low availability of NADPH
might be a limiting factor for GlaA overproduction.
Results: We thus employed the Design‑Build‑Test‑Learn cycle for metabolic engineering to identify and prioritize
effective cofactor engineering strategies for GlaA overproduction. Based on available metabolomics and 13C meta‑
bolic flux analysis data, we individually overexpressed seven predicted genes encoding NADPH generation enzymes
under the control of the Tet‑on gene switch in two A. niger recipient strains, one carrying a single and one carrying
seven glaA gene copies, respectively, to test their individual effects on GlaA and total protein overproduction. Both
strains were selected to understand if a strong pull towards glaA biosynthesis (seven gene copies) mandates a higher
NADPH supply compared to the native condition (one gene copy). Detailed analysis of all 14 strains cultivated in
shake flask cultures uncovered that overexpression of the gsdA gene (glucose 6‑phosphate dehydrogenase), gndA
gene (6‑phosphogluconate dehydrogenase) and maeA gene (NADP‑dependent malic enzyme) supported GlaA
production on a subtle (10%) but significant level in the background strain carrying seven glaA gene copies. We thus
performed maltose‑limited chemostat cultures combining metabolome analysis for these three isolates to charac‑
terize metabolic‑level fluctuations caused by cofactor engineering. In these cultures, overexpression of either the
gndA or maeA gene increased the intracellular NADPH pool by 45% and 66%, and the yield of GlaA by 65% and 30%,
respectively. In contrast, overexpression of the gsdA gene had a negative effect on both total protein and glucoamyl‑
ase production.
Conclusions: This data suggests for the first time that increased NADPH availability can indeed underpin protein
and especially GlaA production in strains where a strong pull towards GlaA biosynthesis exists. This data also indicates
that the highest impact on GlaA production can be engineered on a genetic level by increasing the flux through
the pentose phosphate pathway (gndA gene) followed by engineering the flux through the reverse TCA cycle (maeA
gene). We thus propose that NADPH cofactor engineering is indeed a valid strategy for metabolic engineering of A.
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Open Access
Microbial Cell Factories
*Correspondence: [email protected].cn; vera.meyer@tu‑berlin.de
1 State Key Laboratory of Bioreactor Engineering, East China University
of Science and Technology, Shanghai 200237, People’s Republic of China
2 Chair of Applied and Molecular Microbiology, Institute of Biotechnology,
Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin,
Germany
Full list of author information is available at the end of the article
Page 2 of 17
Suietal. Microb Cell Fact (2020) 19:198
Background
The filamentous fungus Aspergillus niger is one of the
main cell factories used nowadays in the industry for
homologous or heterologous protein production due
to its extraordinary ability for protein expression and
secretion [1–3]. The Design-Build-Test-Learn (DBTL)
cycle is an increasingly adopted systematic meta-
bolic engineering strategy to achieve the desired out-
come through reconstructing heterologous metabolic
pathways or rewiring native metabolic activities [4,
5]. Rational strain development of cell factories can
be improved by the iterative application of the DBTL
cycles, which not only contributes to the optimization of
biomanufacturing processes, it is also advantageous to
build a complete metabolic model of engineered cells to
deepen our understanding of cellular metabolism. Note-
worthy, the advance of genetic engineering has speeded
up the DBTL cycle of metabolic engineering [6]. For the
cell factory A. niger, several genetic approaches have
proven their potency to improve its enzyme producing
capability, including protein carrier approaches, tun-
able Tet-on driven gene expression, and morphology
engineering, to name but a few [1, 7–9]. However, the
impact of cofactor engineering, i.e., the rebalance of the
intracellular redox status, on protein production has not
been systematically studied in A. niger.
NADPH is a limiting factor for the biosynthesis of
amino acids that are the building blocks of proteins. For
instance, 3mol and 4mol of NADPH is required for pro-
ducing 1 mol of arginine and lysine, respectively [10].
Thus, adequate cytosolic NADPH supply is indispensa-
ble to maintain the intracellular redox balance and serves
as a driving force for efficient amino acid biosynthesis
[11]. NADPH also provides the main anabolic reducing
power for biomass growth, lipid formation, and also for
natural product biosynthesis [12]. Indeed, cofactor engi-
neering has been reported to improve productivities in
the bacterial cell factories Escherichia coli [13, 14], and
Corynebacterium glutamicum, as well as in the yeast cell
factory Yarrowia lipolytica [15]. Two common strategies
have mainly been employed to optimize the availabil-
ity of NADPH. One is to activate the enzyme activities
of NAD(H) kinases (EC 2.7.1.86, EC 2.7.1.23) which are
used to obtain NADPH or NADP + through phospho-
rylation of NADH and NAD + , respectively. The other is
to modulate the expression strength of typical NADPH
generating enzymes of the glycolytic pathway, the pen-
tose phosphate pathway or the citric acid cycle. These
include glucose-6-phosphate dehydrogenase (G6PDH),
6-phospho-gluconate dehydrogenase (6PGDH), NADP-
dependent isocitrate dehydrogenase (NADP-ICDH),
and NADP-dependent malic enzyme (NADP-ME) [16,
17]. Notably, heterologous protein expression in Pichia
pastoris and A. niger can be triggered through boosted
carbon flux to the pentose phosphate pathway (PPP), a
catabolic pathway also known to produce NADPH [18,
19]. This suggests that central carbon metabolism may
have evolved to ensure the production of cellular compo-
nents under the balance of energy production and con-
sumption [4]. In agreement, the metabolic flux through
the PPP increased by 15–26% compared to the parental
strains when GlaA was overproduced in A. niger [20] or
the enzyme amylase overproduced in A. oryzae [21].
In the past two decades, extensive studies have focused
on engineering a high flux through the PPP in E. coli,
C. glutamicum, A. nidulans, and A. niger [11, 22–25].
A block of the glycolytic pathway by down-regulating
the pgi gene encoding a phosphoglucose isomerase was
one successful strategy in C. glutamicum [11]. In order
to elevate the NADPH pool originating from the PPP
in A. niger, the gsdA gene (glucose 6-phosphate dehy-
drogenase), the gndA gene (6-phosphogluconate dehy-
drogenase) and the tktA gene (transketolase) were
individually overexpressed in A. niger. Strong overexpres-
sion of gndA led to a nine-fold increase in intracellular
NADPH concentration, while gsdA and tktA affected the
NADPH level only weakly [25]. However, any correlation
between the NADPH supply and enzyme overproduction
remained unclear.
Irrespective of the importance of the PPP for NADPH
regeneration, an efficient carbon economy is only guaran-
teed when the carbon flux enters the glycolytic pathway
(Embden-Meyerhoff-Parnass pathway, EMP) instead of the
PPP because the PPP releases one carbon as CO2 when oxi-
dizing 1mol of hexose. Takeno etal. [26] thus substituted
the endogenous NAD-dependent glyceraldehyde-3-phos-
phate dehydrogenase (GAPDH) in the EMP in C. glu-
tamicum with a heterologous NADP-dependent GAPDH,
leading to 2mol of NADPH generation instead of 2mol
NADH from 1mol of hexose. This genetic modification
niger to improve GlaA production, a strategy which is certainly also applicable to the rational design of other microbial
cell factories.
Keywords: Aspergillus niger, NADPH, Genetic engineering, CRISPR/Cas9, Tet‑on, Metabolic engineering, Chemostat,
Glucoamylase
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Suietal. Microb Cell Fact (2020) 19:198
provoked a substantial improvement in the yield of L-lysine
production by 70–120%. Similar strategies also have been
followed to overproduce ethanol in the yeast Saccharomy-
ces cerevisiae [27] or lycopene and ε-caprolactone in the
bacterium Clostridium acetobutylicum [28]. Likewise, cyto-
solic NADP-ME has been shown to positively affect lipid
accumulation in oleaginous fungi [29, 30].
As summarized above, a wealth of metabolomic and
fluxomic data in A. niger demonstrated that strains
adapted to protein overproducing conditions channel a
higher carbon flux through the PPP. However, cofactor
engineering has not been considered yet or performed
in A. niger to guide enzyme overproduction. We thus
mined our recently published genome-scale metabolic
network model (GSMM) developed for the A. niger pro-
tein producing reference strain CBS 513.88 [31]. This
iHL1210 model identified the involvement of NADPH
in 173 intracellular redox reactions in A. niger, includ-
ing 49 NADPH generating reactions [31]. Notably, the
GSMM did not predict any NADPH/NADP + shuttle in
the mitochondrial membrane, and we thus concluded
that any mitochondrial NADPH is unlikely to become
directly consumed by cytosolic amino acid biosynthe-
sis. Overall, the GSMM predicted that seven potential
NADPH generating enzymes are of importance for GlaA
production in A. niger (Table1, Fig.1): two enzymes of
the cytosolic PPP (glucose-6-phosphate dehydrogenase,
G6PDH; 6-phosphogluconate dehydrogenase 6PGDH),
two cytosolic NADP-dependent enzymes (NADP-ICDH
and NADP-ME) and three uncharacterized open read-
ing frames (An12g04590, An14g00430, An16g02510).
An12g04590, An14g00430 show high homology to
NADP + oxidoreductases, and An16g02510 displays
homology to alcohol dehydrogenases. In order to evalu-
ate whether the model prediction is strain-dependent,
we individually overexpressed all seven candidate genes
in two A. niger host strains. Strain AB4.1 produces native
levels of GlaA as it carries one glaA gene copy, and strain
B36 is a derivative thereof, carrying seven glaA gene
copies and is thus a high-yield GlaA producing strain
[32]. All 14 strains were first investigated in shake flask-
level cultivations. Based on the data gained, three engi-
neered strains were selected for chemostat cultivations
to decipher the association among genetic perturbation,
NADPH availability, and GlaA production in A. niger.
Results
Strain generation using CRISPR/Cas9 technology
andthesynthetic Tet‑on gene switch
In order to compare the effect of the seven selected genes
on GlaA production in an A. niger strain carrying one
glaA (AB4.1) or seven glaA (B36) gene copies, we first
had to ensure that the introduced genetic modifications
would allow us to directly compare the observed phe-
notypes. This required that the introduced genes would
be under the same genetic control and furthermore
introduced at the same genomic locus in both recipient
strains. We thus decided to integrate an additional copy
of all candidate genes under the control of the strong
and tunable Tet-on gene switch into the pyrG locus of
A. niger. This gene switch is inducible by the addition of
doxycycline (DOX) to the culture medium, is tight in the
absence of DOX and metabolism-independent in A. niger
[33]. It has furthermore been shown to strongly induce
gene expression up to levels above the glucoamylase
gene, which is one of the highest expressed genes in A.
niger [33–35].
Strain AB4.1 is a uridine-auxotroph due to a defective
pyrG gene, a locus that is perfectly suited for gene tar-
geting and screening purposes. The introduction of an
Table 1 GSMM-predicted NADPH producing reactions inA. niger
[m] reactions in the mitochondrion; Rn, reaction. All reactions listed here were predicted in Lu etal. [31]
Rn
name Rn description Formula Gene
R25 Glucose 6‑phosphate‑dehydrogenase (gsdA) G6P + NADP = > D6PGL + NADPH + H An02g12140
R27 Phosphogluconate dehydrogenase (gndA) 6PGC + NADP = > Ru5P + CO2 + NADP An11g02040
R36 Isocitrate dehydrogenase (icdA) (NADP +) ICIT[m] + NADP[m] = > AKG[m] + CO2[m] + NADPH[m] An02g12430
R38 Isocitrate dehydrogenase (NADP +) ICIT + NADP = > AKG + CO2 + NADPH An02g12430
R55 Malic enzyme
(NADP‑specific) (maeA)MAL + NADP = > PYR + CO2 + NADPH An05g00930
R57 Malic enzyme
(NADP‑specific) MAL[m] + NADP [m] = > PYR
[m] + CO2[m] + NADPH [m] An05g00930
R110 (S)‑3‑Hydroxybutanoyl‑CoA: NADP + oxidoreductase 3HBCoA[m] + NADP [m] < = > AACCoA[m] + NADPH [m] +H[m] An14g00430
R125 dihydrofolate:NADP + oxidoreductase NADP [m] + DHF[m] < = > NADPH [m] + FOLATE[m] An12g04590
R190 Alcohol dehydrogenase ETH + NADP < = > ACAL + NADPH + H An16g02510
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Suietal. Microb Cell Fact (2020) 19:198
intact pyrG copy at this locus occurs efficiently and con-
fers uridine prototrophy in A. niger [36]. However, strain
B36 does carry an intact pyrG gene [37]. We thus first
mutated the pyrG locus in this strain in order to apply the
same gene targeting strategy for all seven genes in both
recipient strains. We edited the pyrG gene in B36 by fol-
lowing a CRISPR/Cas9 strategy that employed ribonu-
cleoprotein particles. This approach was first published
for the penicillin producer Penicillium chrysogenum [38]
and has later been successfully established in other fun-
gal cell factories [39]. As explained in detail in Additional
file1: Fig. S1, this approach enabled us to obtain a deriva-
tive of B36, strain YS20.2, which carries a 195bp deletion
within the pyrG ORF and is therefore unable to grow on
medium lacking uridine or uracil. Both recipient strains,
AB4.1 and YS20.2, were eventually used to integrate Tet-
on driven candidate genes at the pyrG locus (for details
see Materials and Methods and Additional file 1: Fig.
S2). Respective genetic modifications were proven by
PCR and Southern blot analyses (Additional file1: Figs.
S3, S5, S6, S7). All 14 strains obtained are summarized in
Table3. We finally also decided to delete the native ORFs
of An14g00430 and An16g02510 in their respective Tet-
on driven overexpression strains in order to analyze their
deletion phenotypes.
The impact ofNADPH engineering onGlaA production
isstrain‑dependent
All 14 strains were subjected to batch cultivations
in shake-flask format, whereby a medium contain-
ing maltose as GlaA-inducing carbon source was
used. FW35.1 (a pyrG + derivative of AB4.1) and B36
were taken along as corresponding reference strains.
DOX-induced gene expression in all seven AB4.1
derivatives was about 1.5–2.7 times higher compared
to the reference strain FW35.1 as examined by qRT-
PCR (Additional file1: Fig. S8, TableS4). Although
this led to an elevated NADPH pool of about 30% in
Fig. 1 Pathway map highlighting all seven genes modified during this study in red. The cytosolic glycolytic pathway, the pentose phosphate
pathway and the mitochondrially located citric acid cycle are shown
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Suietal. Microb Cell Fact (2020) 19:198
the case of gndA, icdA or An16g02510, no significant
increase in GlaA enzyme activity was observed for all
of seven strains compared to the FW35.1 reference
(Additional file1: Fig. S8, TableS4). However, when
all seven candidate genes were overexpressed in the
YS20.2 background strain containing seven glaA gene
copies, increased transcript levels were similar as in
AB4.1, but for An16g02510 higher transcription levels
(fourfold) were observed (Fig.2b). Noteworthy, over-
expression of gndA displayed the highest effect on the
Fig. 2 Data for shake flask‑level cultivations of all engineered strains in the YS20.2 background in relation to the control strain B36. a Dry cell weight
(DCW); b Relative expression level of glaA and engineered genes; c Total secreted protein per gram biomass at 72 h after inoculation; d Enzyme
activity of GlaA per gram biomass at 72 h after inoculation; e Intracellular NADPH concentration in the exponential phase; f Comparison between
engineered strains in the AB4.1 and YS20.2 background, respectively. All experiments were conducted in biological quadruplicates. Significance
values were calculated with the two‑tailed t‑test with independent variables (*p < 0.05, **p < 0.01, ***p < 0.001)
Page 6 of 17
Suietal. Microb Cell Fact (2020) 19:198
transcription of glaA (2.4-fold) compared to B36. A
NADPH pool increase of about 30% was measured in
three other strains overexpressing maeA, gndA, gsdA,
respectively (Fig. 2e). With regard to Tet-on driven
gene expression of maeA, gndA, gsdA, about 10%
increase in secreted total protein, and about 10–18%
higher GlaA activity was observed for these engineered
strains (Fig.2c, d, Additional file1: TableS4). These
observations encouraged our hypothesis that NADPH
engineering might be a promising strategy to improve
GlaA production.They furthermore implied that the
success of such an approach is dependent on the glaA
gene copy number as the impact on protein produc-
tion is not linearly correlated with increased transcrip-
tion of NADPH producing enzymes. To shed further
light on these phenomena, we selected thethree most
promising YS20.2 background strains overexpressing
maeA, gndA, gsdA, respectively, cultivated them under
chemostat conditions, and compared their perfor-
mance with the reference strain B36.
Physiology andgene expression duringmaltose‑limited
chemostat cultivations
Strain B36 and the three strains overexpressing maeA,
gndA, and gsdA, respectively, were run in duplicate malt-
ose-limited chemostat cultures. To induce the expression
of these three candidate genes, 10µg/ml DOX was added
during the early exponential growth phase, when the bio-
mass reached 1–2 gDCW/kg. After about 22h, the cultiva-
tion process was switched to the chemostat mode with a
dilution rate D = 0.1h−1, as described in Kwon etal. [32]
and the Materials and Methods section. DOX was con-
tinuously added through the feed medium. During expo-
nential and steady state conditions, culture samples were
taken using an in-house developed fast-quenching sam-
pling device (unpublished) for biomass determination,
gene expression analyses (qRT-PCR), intracellular metab-
olite quantification (GC/LC–MS) and secreted protein
determination. Carbon was accounted for in carbon bal-
ances of the feed medium, effluent culture broth, and
exhaust gas. The carbon dioxide evolution rate (CER), the
oxygen uptake rate (OUR), and biomass concentrations
reached constant levels after about three-volume changes
(Fig.3a, c).
Interestingly, overexpression of gsdA or gndA increased
biomass accumulation, whereas overexpression of maeA
reduced it. This is also reflected by the final carbon-
recoveries (Table2). They were higher in both gsdA or
gndA overexpressing strains (110%, 104%), but lower in
maeA overexpressing strain (91%) compared to 99% of
the B36 strain. Similar to shake flask-level cultivations,
transcript levels of all three overexpressed genes were
about 1.3 (gsdA, gndA) or 2.7 (maeA) times above their
respective transcript levels in B36 during the exponential
phase. They considerably increased 3.3-fold (gsdA, gndA)
or 8.2-fold (maeA) during steady state conditions (Fig.3e,
f). This data might suggest that although all three genes
are under the same Tet-on driven transcriptional control
at the same locus (pyrG), other regulatory mechanisms,
e.g., mRNA turnover or metabolic feedback regulation,
might additionally control the activity of these three
genes. Notably, overexpression of gsdA increased biomass
accumulation (Table2) but inhibited the yield of total
secreted protein and GlaA by 40% (Fig.3d), suggesting a
competition between growth and protein production as
previously proposed [11]. In contrast, overexpression of
gndA and maeA positively impacted protein secretion by
60% and 30%, respectively (Table2). This data was con-
sistent with NADPH pool measurements during steady
state conditions: Overexpression of gndA and maeA
increased NADPH levels (46% and 66%, respectively),
whereas only wild-type NADPH levels were observed for
the strain overexpressing gsdA (Fig.3g).
Metabolic differences revealed bymultivariate statistical
analysis
In total, 42 intracellular metabolites were identified
and quantified for all eight chemostat runs. These
included nine sugar phosphates, eight organic acids,
19 amino acids, and six currency metabolites (NAD,
NADH, NADP, NADPH, ADP, ATP). Principal Com-
ponent Analysis (PCA) uncovered that samples from
all four strains separated into four distinct groups as
shown in the score plot of Partial Least Squares Dis-
crimination Analysis (PLS-DA) (Fig.4a). Especially
the strain overexpressing maeA displayed the strong-
est metabolic changes, whereas the strains overex-
pressing gsdA and gndA, respectively, showed only
subtle differences when compared to the metabolic
profile of strain B36. The loading map uncovered
representative metabolites which mainly contributed
to the separation of these four strains. Variations
of relative abundances of pyruvate (PYR), succinate
(SUC), histidine (HIS), maltose (MAL), 6-phospho-
gluconate (6PG) mainly contributed to distinguish
both gsdA and gndA overexpressing strains, whereas
the majority of variables contributed to the separa-
tion of OE maeA strain (Fig.4a). A variable impor-
tance plot (VIP) displaying the relative contributions
of these representative metabolites demonstrated
that VIP values of 18 metabolites out of the 42
metabolites were above 1 (Fig.4b), suggesting that
these 18 metabolites could be considered as poten-
tial markers to discriminate all four strains. Path-
way enrichment analyses highlighted that the PPP,
the glyoxylate bypass, and dicarboxylate metabolism
Page 7 of 17
Suietal. Microb Cell Fact (2020) 19:198
had a significant impact in the strains overexpress-
ing gsdA and gndA, respectively. However, glycine,
serine, and threonine metabolism was enriched in
the strains overexpressing gsdA and maeA. The latter
in general showed overrepresentation of amino acid
metabolic pathways, including alanine, aspartate and
glutamate metabolism, arginine and proline metabo-
lism besides glycine, serine and threonine metabo-
lism (Fig.4c–e).
Metabolic profiling ofamino acid pools andcentral carbon
metabolism
Figure5 and Additional file1: TableS5 summarize the
amino acid pools in all three overexpression strains
compared to B36. In general, Ala, Glu, Gly, Leu, and Lys
are the top five amino acids in the biomass of A. niger,
whereas Ser, Thr, Ala, Leu, and Gly account for about
50% of the total amino acids in GlaA [40]. Our metabo-
lomics analyses uncovered that in all four strains, amino
acids from the glutamate family are most and aromatic
amino acids are least abundant, which is in general agree-
ment to previously reported amino acid pools in A. niger
[41]. Overall, the amino acid pool in the gndA overex-
pression strain was slightly reduced compared to B36
but was increased in strains overexpressing gsdA (22%)
or maeA (30%), respectively (Additional file1: TableS5).
A general observation was also that the histidine pool
dramatically increased when gsdA (increased by three
folds) or gndA (60%) were overexpressed. Two out of the
five amino acids dominating A. niger’s biomass (Glu, Lys)
accumulated in the strain overexpressing gsdA, while the
pool sizes of three top GlaA composing amino acids (Ser,
Thr, Gly) were less abundant compared to B36. This data
might explain the reduced GlaA production in this strain.
In the case of maeA overexpression, nearly all amino
acids where higher abundant when compared to strain
B36 (Additional file1: TableS5), especially the pools for
the GlaA dominating amino acids Thr, Ala, Leu, and Val,
suggesting that increased amino acid pools might cause
the extra driving force for GlaA formation in a maeA
overexpressing strain. In contrast, the overall amino acid
pools of the strain overexpressing gndA displayed only
moderate reduction compared to B36 (Additional file1:
TableS5).
As summarized in Fig.6 and Additional file1: TableS6,
overexpression of gsdA, gndA, and maeA, led to a signifi-
cant flux redistribution of the central carbon metabolism,
including PPP, EMP, and TCA. As expected, the glyco-
lytic pathway intermediates G6P and F6P were signifi-
cantly reduced in the two PPP engineered strains which
overexpressed gsdA and gndA, respectively. Diverting the
carbon flux towards the PPP at the branch node of G6P
after overexpression of gsdA and gndA has in fact low-
ered the flux towards the EMP. The 6PG and PEP pools
increased (due to gsdA overexpression), which in turn
inhibited the upper glycolytic pathway (feedback inhibi-
tion via 6PG [42] and PEP [43]). Another consequence is
a reducedcarbon uptaken rate, which is indeed the case
for the strain overexpressing gsdA (Table2). On the lower
glycolytic pathway, the accumulation of the intermediates
PEP and PYR, respectively, in OE gsdA and OE gndA led
to a reduced flux through 3PG (Additional file1: Fig. S9),
accompanied by a reduction of the serine family pool in
these two strains. This data could be well explained by
the close association between the abundance of metabo-
lite precursors on the central metabolic network and the
pool size of the correlated amino acid families as already
reported elsewhere [44]. Importantly, the PPP is not the
only key for NADPH regeneration but also provides two
important precursors for amino acid biosynthesis, i.e.,
ribose 5-phosphate (R5P) and erythrose 4-phosphate
(E4P), which in turn are required for His and aromatic
amino acid biosynthesis. Overproduction of gndA chan-
neled more carbon from 6PG to Ru5P, resulting in a
lower abundance of 6PG as expected. Surprisingly, the
R5P pools declined in both strains overexpressing gsdA
and gndA, respectively. However, taking into account
the increased biomass formation and higher His pools
in these two strains, the increased carbon flux towards
R5P was possibly channeled towards nucleotide biosyn-
thesis. In agreement with previous reports studying high
protein secretion in A. niger [18, 41] and our in silico
metabolic flux simulations (Additional file 1: Fig. S9),
the flux through the TCA cycle was also reduced during
overexpression of the PPP genes gsdA and gndA, respec-
tively. However, the picture for the TCA cycle intermedi-
ates was inhomogeneous. The TCA cycle intermediates
AKG, FUM, and OAA were less abundant, whereas MAL
Fig. 3 Physiological parameters for A. niger B36 and three overexpression strains during chemostat cultivation at a dilution rate of 0.1 h−1. a CO2
evolution rate (CER) in mmol/L/h; b Formation of the by‑product oxalic acid in µmol/g cell dry weight; c Dry cell weight in gDCW/kg; d Yield of
total secreted protein per gram biomass; e glaA relative gene expression level at the exponential growth phase and during steady state; f Relative
gene expression level of the overexpressed genes during exponential growth and steady state; g Intracellular NADPH level at steady state. Data
represent the mean ± SD from two independent cultures which were measured in technical triplicates. Significance values were calculated with
the two‑tailed t‑test with independent variables (*p < 0.05, **p < 0.01, ***p < 0.001). Straight lines in a‑d indicate the switch from batch to chemostat
cultivation. OE gsdA: strain overexpressing gene gsdA; OE gndA: strain overexpressing gene gndA; OE maeA: strain overexpressing gene maeA
(See figure on next page.)
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Suietal. Microb Cell Fact (2020) 19:198
Table 2 Physiology data inchemostat cultures
Data for strain B36 and three Tet-on driven overexpression strains derived thereof are shown for chemostat cultures with maltose as growth-limiting substrate.
Standard deviations ( ±) are given for mean values of duplicate independent steady state results which were measured in technical triplicates. OE gsdA: strain
overexpressing gene gsdA; OE gndA: strain overexpressing gene gndA; OE maeA: strain overexpressing gene maeA. Cbiomass, biomass concentration (dry cell weight
(DCW)); qCO2, specific carbon dioxide evolution rate; qO2, specific oxygen uptake rate; RQ, respiratory quotient calculated as the ratio of CO2 production and O2
consumption rates; qprotein, specific production rate of extracellular protein; qs, specificsubstrate consumption rate; YGlaA/X, yield of total glucoamylase activity on
biomass; C-recovery, carbon recovery
B36 OE gsdA OE gndA OE maeA
µexponential phase (h−1) 0.21 ± 0.01 0.21 ± 0.02 0.21 ± 0.01 0.19 ± 0.01
Cbiomass (gDCW/kg) 5.66 ± 0.16 7.5 ± 0.36 6.46 ± 0.17 4.74 ± 0.29
qCO2 (mmol/gDCW·h) 1.33 ± 0.04 1.00 ± 0.03 1.1 ± 0.03 1.45 ± 0.09
qO2 (mmol/gDCW·h) 1.6 ± 0.18 1.19 ± 0.15 1.51 ± 0.11 1.79 ± 0.20
RQ 0.83 ± 0.09 0.81 ± 0.1 0.73 ± 0.06 0.81 ± 0.09
qProtein (mg/gDCW·h) 3.71 ± 0.41 2.27 ± 0.37 5.62 ± 1 4.94 ± 0.49
qs (mmolmaltose /gDCW·h) 0.39 ± 0.011 0.31 ± 0.009 0.35 ± 0.031 0.47 ± 0.011
YGlaA/X (U/gDCW) 23.84 ± 1.08 14.38 ± 0.82 38.88 ± 3.6 30.83 ± 0.1
C‑recovery 99% 110% 104% 91%
Fig. 4 Bioplot (combining the loading plot and score plot). Three biological replicates from each strain were denoted with the same color (a), VIP
score of 42 intracellular metabolites calculated using the PLS‑DA (b), and respective pathway impact analysis for metabolic profiling at steady state
(c–e)
Page 10 of 17
Suietal. Microb Cell Fact (2020) 19:198
accumulated when gsdA was overexpressed. In the case
for gndA overexpression, the experimental data showed
only weak differences for the pool sizes of TCA inter-
mediates when compared to strain B36 (Fig. 6, Addi-
tional file1: Fig. S9). Last but not least, overexpression
of maeA facilitated not only amino acid biosynthesis
but also improved the carbon flux towards the EMP and
TCA cycle (Fig.6) and elevated the pools of the key inter-
mediates F6P, G3P, PEP, OAA, and FUM but not PYR.
Worth mentioning in this context is oxalic acid, a major
by-product during A. niger cultivation which stems from
OAA [45]. Whereas the oxalic acid pool did not differ in
Fig. 5 The pool sizes of amino acids for the A. niger reference strain B36 and three overexpression strains at steady state. Blocks in the heat map
represent B36, OE gsdA (strain overexpressing gene gsdA), OE gndA (strain overexpressing gene gndA), and OE maeA (strain overexpressing
gene maeA) from left to right. Amino acids labeled in yellow are the top five amino acids present in GlaA. Red arrows indicate the enzymes
overexpressed. Quantified amino acid amounts and significance values are given in Additional file 1: Table S5
Page 11 of 17
Suietal. Microb Cell Fact (2020) 19:198
the strains overexpressing gsdA or gndA, respectively, it
was substantially increased by about 30% in OE maeA,
suggesting that the elevated pool size of OAA could be
responsible for the accumulation of this by-product
(Fig.3b).
Discussion
NADPH regeneration is a limiting step for amino acid
biosynthesis; hence NADPH availability and allocation
are essential for efficient protein production. This study
demonstrates that the NADPH pool can be increased by
Fig. 6 The pool sizes of a part of the metabolites on central carbon metabolism pathways for the A. niger reference strain B36 and three engineered
strains at steady state. Blocks in the heat map represent B36, OE gsdA (strain overexpressing gene gsdA), OE gndA (strain overexpressing gene gndA),
and OE maeA (strain overexpressing gene maeA) from left to right. Red arrows indicate the enzymes overexpressed. Quantified sugar and organic
acid amounts including significance values are given in Additional file 1: Table S6
Page 12 of 17
Suietal. Microb Cell Fact (2020) 19:198
30% in A. niger through genetic engineering by the gndA,
gsdA, and maeA genes, respectively. However, the physi-
ological consequences of this increased NADPH pool are
strain-dependent. For the native GlaA producing strain
AB4.1, which carries only one glaA copy, we assume that
the excess of NADPH might not be allocated to increased
amino acid biosynthesis but was channeled to other
NADPH consumption pathways, e.g., for the produc-
tion of steroids, lipids, and nucleotides and thus biomass
formation. In contrast, due to the higher glaA gene num-
ber in B36, it is tempting to speculate that the excess in
NADPH was indeed used for GlaA production because
of the higher intracellular pull towards GlaA production
and its amino acid precursors. Future 13C metabolic flux
analyses targeting sugars, amino acids, steroids, lipids,
and nucleotides in these strains will prove or disprove
this hypothesis. These analyses will also clarify whether
NADPH supply is a bottleneck for protein biosynthesis,
as previously proposed for the yeast Y. lipolytica [46].
Metabolic flux analysis is the most authoritative
method for measuring invivo fluxes [47]. In this study,
we used our previously updated A. niger GSMM iHL1210
[31] to predict the flux distribution of the central car-
bon metabolic network in silico during steady-state
conditions of three strains overexpressing gndA, gsdA,
and maeA, respectively. These simulation results indi-
cated that the relative flux of the EMP and TCA cycle
decreased after redirecting a higher flux through the
PPP when gndA or gsdA were overexpressed, a situation
which was reverse predicted when maeA was overex-
pressed. This predicted computational flux distribution
was congruent with the invivo metabolite pools meas-
ured by mass spectrometry: The upper glycolytic path-
way intermediates G6P and F6P were significantly lower
(p < 0.05) in the two strains overexpressing gndA or gsdA,
which both encode enzymes of the PPP. When compared
with other autonomously evolved metabolic networks
from forced protein overproduction [18, 41, 48], it illus-
trates a comparable flux pattern through the PPP and
TCA cycle as observed here, suggesting similarities of
core carbon metabolism in the central metabolic network
in diverse high-yield protein overproducing A. niger cell
factories.
Notably, overexpression of the gsdA gene improved bio-
mass accumulation and only slightly increased NADPH
production, which were paralleled by reduced protein
production capacity by about 40%. This observation is
generally consistent with previous reports for A. niger
and other filamentous fungal cell factories. For example,
a high specific protein production rate has been shown
to correlate with relatively low growth rates in Tricho-
derma reesei [49], due to a reduced proteome allocated
for central metabolism [12]. Also, a recent multi-omics
analysis from our group that integrated transcriptom-
ics, metabolomics and GSMM simulations proposed
that an increased GlaA production is probably achieved
through reduced growth, which likely is regulated at
several metabolic mechanisms: (i) an increased carbon
catabolism that generates more amino acid precursors
for protein production, (ii) a reduced fatty acid and ribo-
some biogenesis and, thus, reduced growth, and (iii) an
increased flux through the glyoxylate bypass to reduce
NADH formation from the citric acid cycle and to main-
tain the cellular redox balance [50]. In the current study,
at least for the two strains overexpressing gndA and gsdA,
respectively, we observed that both the PPP and the gly-
oxylate pathway changed considerably (Fig.4). The gen-
eral view might be that once growth is limited, more
reducing equivalents (NADH and NADPH), and pre-
cursors can be channeled into protein and glucoamylase
production. We have shown previously that A. niger ben-
efits from a very flexible transcriptional machinery that
ensures adaptation to the burden of high protein loads
[32]. When forced to overexpress glaA, A. niger increases
the transcription of secretory pathway genes involved in
translation, protein folding, and protein secretion. Under
this circumstance, the expression of genes less important
for growth and survival becomes decreased loads [32].
This phenomenon is called ’Repression under secretion
stress’ (RESS) and was first discovered in T. reesei [51].
A. niger can, thus, fall back on a very efficient gene regu-
latory and metabolic machinery that balances cellular
capacities with the intracellular burden. However, it is
currently impossible to predict nor to understand all reg-
ulatory mechanisms and their correlations behind these
phenomena. Additionally, 13C-flux analysis detected
that the two NADPH generating reactions, i.e., NADP-
ICDH and G6PDH, contributed only negligibly (below
5%) to the total NADPH production [52]. This could be
an alternative reason for the minor changes in NADPH
when comparing the strain overexpressing gsdA to the
reference strain B36. Moreover, more NADPH might
have been consumed for growth in this strain. Yet, this
observation is opposite to the critical role of G6PDH in
the production of NADPH in Saccharomyces cerevisiae
[53]. Our study clearly uncovered that overexpression
of the gndA or maeA gene, respectively, enhanced total
protein production and specifically GlaA production in
A. niger. Whereas the gndA gene encodes one enzyme of
the PPP, the maeA encoded enzyme is part of the cyto-
solic reverse TCA cycle. Overexpression of both genes
gave rise to both the NADPH pool (46%, 66%, respec-
tively) and protein production rates (65%, 30%, respec-
tively) compared to B36, thus implying that our in silico
predicted cofactor engineering approach is a biological
valid and thus successful approach to improve protein
Page 13 of 17
Suietal. Microb Cell Fact (2020) 19:198
production capacities of A. niger. Notably, overexpression
of maeA provoked the most complex metabolic changes
(Fig.5 and 6). NADP-ME is critical not only for pyruvate
supply but also enhanced the flux through glycolysis and
TCA cycle to provide sufficient precursors for amino acid
production. Based on our previous multi-omics analysis
and exogenous amino acid addition experiments [50],
Ala, Glu, Gly, and Asp were confirmed as four amino acid
limiting GlaA production in A. niger. This was further
corroborated by our recent study reporting that remov-
ing the amino acid limitation is supporting GlaA produc-
tion [54]. Hence, enriched pools of amino acids, carbon
precursors and NADPH due to increased maeA tran-
scription could altogether boost GlaA production. How-
ever, increased maeA transcription was paralleled by the
accumulation of the by-product oxalic acid, which could
in turn be targeted in the next DBTL cycle to even fur-
ther increase GlaA production.
Conclusions
In this study, we followed a DBTL approach to system-
atically understand and optimize GlaA production in
A. niger. Our previous multi-omics integration analyses
predicted that NADPH regeneration could be one so
far unstudied bottleneck for enzyme production in A.
niger. To test this hypothesis, we genetically engineered
strains with improved NADPH biosynthetic capacities.
Metabolic profiling and multivariate statistical analy-
sis revealed that three NADPH regeneration enzymes
encoded by the gsdA, gndA, and maeA genes play the
most significant decisive role during batch and continu-
ous cultivations, whereby overexpression of the gndA
and maeA genes provoked the highest flux redistribu-
tions towards protein biosynthesis. Future studies will
examine whether combined overexpression of these can-
didate genes, e.g., by polycistronic gene expression [55],
will further improve protein production capacities of A.
niger and thus evaluate whether combinatorial cofactor
engineering is a further successful approach for strain
engineering.
Materials andmethods
Plasmids construction
Integrative plasmids used for overexpressing NADPH
generating genes in the A. niger strains were cloned by
Gibson assembly or AQUA cloning [56]. The backbone
vector was obtained by digesting pFW22.1 with PmeI,
and then the 8.1kb fragment was purified by gel extrac-
tion. Plasmid pFW22.1 carries the Tet-on inducible gene
expression system, and an unfunctional pyrG, which was
used as a selective marker for transformant screening
[35]. Open reading frames (ORF) of NADPH generating
enzymes (6PGDH (gsdA), G6PDG (gndA), NADP-ICDH
(icdA), NADP-ME (maeA), An14g00430, An15g04590,
and An16g02510) were amplified by PCR, using genomic
DNA from the A. niger B36 strain as a template. PCR
products were integrated into pFW22.1 at the PmeI site
(Additional file1: Fig. S2). Primers carrying overlapping
regions to the backbone vector and plasmids constructed
in this study are listed in Additional file1: Tables S7 and
S8, respectively.
Strains
A. niger strains used in this study are listed in Table3.
AB4.1 is a lab strain with only one glaA copy and uridine
auxotrophic [36]. B36 is an engineered strain with multi-
ple copies of glaA and derived from N402 [37]. YS20.2 is
a uridine auxotrophic derivative of B36, which was engi-
neered using CRISPR/Cas9 (see below). Overexpression
strains of NADPH generating genes were constructed in
the background of AB4.1 or YS20.2, and transformants
were screened based on uridine prototrophy. Gene dele-
tions were obtained using the split marker method [57].
PCR products containing either ~ 1.5kb 5′ or 3′ flanking
regions of the corresponding gene and a part of the selec-
tive marker hygromycin were used for transformation
(for details please refer to Additional file1: Fig. S4 and
TableS7). To avoid a lethal phenotype, all deletion strains
were built in their corresponding overexpression strains.
A. niger transformation, genomic DNA extraction, and
Southern hybridization were performed as previously
described in Arentshorstet etal. [58] with the follow-
ing exceptions: strain YS20.2 was cultivated at 80rpm to
obtain young mycelium for protoplastation. PEG medi-
ated transformation was done using 60% PEG 4000 as
described in Pohl etal. [38]. This improved the transfor-
mation rate from 1CFU/µgDNA to 4–5CFU/µgDNA.
All overexpression and deletion strains were generated
without CRISPR. Positive transformants were confirmed
by diagnostic PCR and Southern analysis (Fig. S3, S5, S6,
and S7).
Medium
Strains were grown at 30°C using a complete or minimal
medium supplemented with 1mM uridine when neces-
sary [58]. Shake flask medium (g/L): 3% Maltose·H2O,
10 g tryptone, 5 g Yeast extract, 1 g KH2PO4, 0.5 g
MgSO4·7H2O, 0.03 g ZnCl2, 0.02 g CaCl2, 0.0076 g
MnSO4·H2O, 0.3g FeSO4·7H2O, 3ml Tween 80, pH was
adjusted to 5.5 by 1M HCl. Maltose-limited chemostat
medium was as described in Kwon etal. [32] with the
following slight modification: the medium contained 1%
(w/v) of maltose in batch cultures and 0.8% (w/v) during
chemostat cultivations. Germination was induced by the
addition of 0.003% (w/w) yeast extract. Media used for
CRISPR/Cas9 gene editing: 200µg/ml hygromycin and
Page 14 of 17
Suietal. Microb Cell Fact (2020) 19:198
500µg/ml caffeine were supplied into MM transforma-
tion media. Filtered-sterilized 0.75g/L 5-FOA, 10mM
proline and 10mM uridine were added to MM medium
when subcultivating uridine auxotrophic transformants.
CRISPR/Cas9 genetic modification
CRISPR/Cas9 modifications were done using the ribonu-
cleoprotein (RNP) approach [38]. The Cas9 protein was
expressed from the pET28aCas9cys vector (Addgene:
53,261) and purified by AKTA FPLC (Fast protein liq-
uid chromatography, GE, USA). The sgRNA was selected
online using the Cas-Designer website (https ://www.
rgeno me.net/cas-desig ner/). Two sgRNAs were designed
to test the gene targeting efficiency, which located at
205bp and 393bp after the start codon of pyrG. DNA
templates for invitro sgRNA synthesis (MegaScript T7
Transcription Kit, Thermo Fisher Scientific, USA) were
constructed as DNA oligos incorporating a T7-promoter
sequence, 20 bp protospacer and a 77 bp sgRNA tail
(Primers are listed in Additional file1: TableS9). During
transformation, 5µl purified Cas9 protein, 1µl or 2µl
sgRNA, and 2µg pMA171.1 plasmid carrying hygromy-
cin as a selective marker [59] were used. Transformants
were subcultivated on MM plates containing uridine,
proline, and 5-FOA (details on concentrations are above).
Consequently, the ORF region of pyrG from sporulating
single colonies on 5-FOA medium was amplified to con-
firm mutations by sequencing (Additional file1: Fig. S1).
Shake flask‑level cultivation
To evaluate the performance of engineered strains as GlaA
producers, 106 spores/ml of reference strains FW35.1 [35]
or B36 [32] and engineered strains were inoculated into
50ml shake flask liquid medium and cultivated at 30°C
and 250rpm. After 18h of cultivation, 20µg/mL doxy-
cycline (DOX) was used to induce gene expression. In
order to ensure gene overexpression, the same amount
of DOX was added every 12h after the initial induction.
Samples were taken at 24, 48, and 72h after inoculation.
Physiological parameters (dry weight, total secreted pro-
tein, residual glucose, and enzyme activity of GlaA in the
broth) were measured. Samples for NADPH measure-
ment and qRT-PCR were taken in the exponential phase.
Experiments were performed in biological quadruplicates.
Chemostat cultivation
Submerged cultivations were carried out in 5 L bioreac-
tors (NCBIO, Shanghai, China). Batch cultivations were
adapted from Kwon et al. [32]. Chemostat cultivations
were initiated in the late exponential growth phase when
OUR (Oxygen Uptake Rate) or CER (Carbon-dioxide Evo-
lution Rate) started to decrease and DO (Dissolved Oxy-
gen) started to increase. The dilution rate (D) was set at
0.1h−1. The steady-state was reached after approximately
three residence times (≈ 30h) and indicated by constant
CO2, O2, and biomass concentrations. Samples were taken
regularly (6–8h) to monitor growth and to determine if a
Table 3 Aspergillus niger strains used inthis study
Strain name Background strain Relevant genotype/description References
AB4.1 N402 cspA1‑, pyrG − [36]
FW35.1 AB4.1 cspA1‑, pyrG + [35]
B36 N402 Multi copies of glaA, amdS + [37]
YS20.2 B36 pyrG‑, with 195 bp deletion at 101 bp ~ 295 bp after pyrG start codon This study
YS7.4 AB4.1 Overexpression of An02g12140 (gsdA) via Tet‑on, pyrG + This study
YS23.20 YS20.2 Overexpression of An02g12140 (gsdA) via Tet‑on, pyrG + This study
YS9.9 AB4.1 Overexpression of An11g02040 (gndA) via Tet‑on, pyrG + This study
YS22.17 YS20.2 Overexpression of An11g02040 (gndA) via Tet‑on, pyrG + This study
YS10.6 AB4.1 Overexpression of An02g12430 (icdA) via Tet‑on, pyrG + This study
YS37.10 YS20.2 Overexpression of An02g12430 (icdA) via Tet‑on, pyrG + This study
YS12.16 AB4.1 Overexpression of An05g00930 (maeA) via Tet‑on, pyrG + This study
YS21.14 YS20.2 Overexpression of An05g00930 (maeA) via Tet‑on, pyrG + This study
YS11.8 AB4.1 Overexpression of An14g00430 via Tet‑on, pyrG +
Overexpression of An14g00430 via Tet‑on, pyrG + This study
YS24.9 YS20.2
YS16.1 YS11.8 An14g00430::hygB This study
YS26.3 YS24.9 An14g00430::hygB This study
YS14.4 AB4.1 Overexpression of An16g02510 via Tet‑on, pyrG + This study
YS38.2 YS20.2 Overexpression of An16g02510 via Tet‑on, pyrG + This study
YS15.7 YS14.4 An16g02510::hygB This study
YS35.9 YS38.2 An16g02510::hygB This study
Page 15 of 17
Suietal. Microb Cell Fact (2020) 19:198
steady-state had been reached. All samples were quickly
frozen in liquid nitrogen. 10µg/ml DOX was added when
the biomass reached 1–2g/kg. To ensure induction, 10µg/
mL DOX was also applied to the feed medium. Samples
used for extracting intracellular metabolites were taken
during steady-state and intracellular metabolites were
quantified by GC/LC–MS. Samples for NADPH measure-
ment and qRT-PCR were taken both in the mid-exponen-
tial phase (4h after DOX induction) and at steady-state.
Determination ofdry weight, total secreted protein,
residual glucose andenzyme activity ofglucoamylase
4mL of samples were taken at the indicated time points
from shake flask or bioreactor cultures. Biomass was har-
vested through vacuum filtration, washed 3 times with
deionized water, then frozen at − 80°C and finally freeze-
dried overnight to determine dry weight. Total extracel-
lular protein in the culture supernatant was determined
via the Bradford assay (BioRad, California, USA) accord-
ing to the manufacturer’s protocols, and absorbance
(600nm) was measured using a GloMax®-Multi Detec-
tion System (Promega, Madison, USA). Quantifica-
tion of residual glucose in the cultivation medium was
performed with the Glucose GOD/PAP Liqui-color kit
(Human, Wiesbaden, Germany) according to the manu-
facturer’s manual. The enzyme activity of GlaA was
measured as described in Lu etal. [50].
Quantification ofextracellular organic acid
By-products such as extracellular acetic acid, citric acid,
oxalic acid, pyruvic acid, and succinic acid were deter-
mined by HPLC (Shimadzu, Kyoto, Japan) using a VAR-
IAN Metacarb H plus column and 5mM H2SO4 as a
mobile phase at a flow rate of 0.4ml/min and 50 °C.
Acids were detected at a wavelength of 210nm.
Quantification ofintracellular metabolites
Quantification of intracellular metabolites was based on
Lu etal. [41], and slight modifications were made. This
study adopted the Isotope Dilution Mass Spectrom-
etry (IDMS) method to accurately quantify intracellular
metabolites [60]. 1–2ml broth was rapidly taken from
bioreactors by fast-sampling equipment to tubes with
10 ml precooled quench solution (− 27.6 °C 60% v/v
methanol solution) at steady-state. To precisely deter-
mine the amount of broth taken, the tubes were weighed
before and after sampling. In order to remove the extra-
cellular metabolites promptly, the mixture was filtered
with a vacuum pump. Then, 20 ml precooled quench
solution was used to rinse the filter cake. The washed fil-
ter cake and 100µl 13C internal standard solution were
added to prewarmed 25ml 75% (v/v) ethanol solution
and extracted 3 min at 95 °C. The tubes were cooled
down on the ice to room temperature. The filtrate was
collected after vacuum filtration and concentrated to
600µl by rotary evaporation. Subsequently, the metabo-
lite pools were quantified with the LC–MS/MS (Thermo
Fisher Scientific Corporation, USA) and GC–MS (Agi-
lent, Santa Clara, CA, USA).
Quantification ofintracellular NADPH
1ml broth was quickly taken from the shake flask or bio-
reactor and frozen immediately in liquid nitrogen. Samples
were thawed before measurement, diluted 2 or 5 times
with 1 × PBS, and centrifuged at 12,000rpm for 5min to
remove the supernatant. Intracellular NADPH was quanti-
fied by the EnzyFluo™ Assay Kit (BioAssay Systems Cor-
poration, USA) according to the manufacturer’s manual.
Quantitative real‑time PCR
Mycelium harvested for RNA extraction was ground in
liquid nitrogen and then extracted by the Fungal Total
RNA Isolation Kit (Sangon, Shanghai, China). About 1μg
of total RNA was used for cDNA synthesis using the Pri-
meScript™ RT reagent Kit with gDNA Eraser (Takara,
Shiga, Japan) according to the manufacturer’s instruc-
tions. The real-time PCR reaction system was prepared
with TB Green™ Premix Ex Taq™ II (Takara, Shiga,
Japan) in a volume of 25μl with diluted cDNA (about
1 µg) as a template. Diluted cDNA was used to keep
mean Ct (threshold cycles) values between 20 and 30.
Each reaction was carried out in triplicates. Oligonucleo-
tide primers used for qPCR are listed in Additional file1:
TableS7. The 28S rRNA and 18S rRNA were used as the
internal standard. PCR conditions were as follows: 95°C
for 3min, followed by subsequent 40 cycles of the three-
steps: 95°C for 30s, 58°C for 30s and 72°C for 30s.
Multivariate statistical analysis ofintracellular metabolites
Hierarchy clustering analysis of metabolomics data at
steady state was plotted using the R package pheatmap.
Principal component analysis and partial least squares
discriminant analysis (PLS-DA) were then performed
by the R package ggbiplot. Pathway enrichment analysis
was performed by the online metabolomics analysis web-
site MetaboAnalyst 4.0 (https ://www.metab oanal yst.ca/
Metab oAnal yst/faces /home.xhtml ).
Simulation ofrelative metabolic flux byA. niger GSMM
Relative metabolic fluxes were predicted as described in
Lu etal. [50] through A. niger GSMM iHL1210, which
was updated recently by our lab [31]. Maximization of
cell growth was set as the objective function, and malt-
ose was the sole carbon source. qS, qP, qO2, qCO2 from the
chemostat fermentations were set as constraints during
the simulation.
Page 16 of 17
Suietal. Microb Cell Fact (2020) 19:198
Supplementary information
Supplementary information accompanies this paper at https ://doi.
org/10.1186/s1293 4‑020‑01450 ‑w.
Additional file1: Fig. S1−S8, Tables S1–S9.
Abbreviations
PPP: Pentose phosphate pathway; EMP: Embden‑Meyerhof‑Parnas pathway;
TCA : Tricarboxylic acid cycle; CER: Carbon dioxide evolution rate; OUR: Oxygen
uptake rate; DO: Dissolved oxygen; PLS‑DA: Partial least squares discrimination
analysis; G6PDH: Glucose 6‑phosphate dehydrogenase; 6PGDH: Phosphoglu‑
conate dehydrogenase; NADP‑ICDH: NADP + dependent isocitrate dehydro‑
genase; NADP‑ME: NADP + dependent malic enzyme; 3PG: 3‑Phosphoglycer‑
ate; 3HBCoA: (S)‑3‑Hydroxybutanoyl‑CoA; AACCoA: Acetoacetyl‑CoA; AC:
Acetate; ACCoA: Acetyl‑CoA; ACAL: Acetaldehyde; AKG: α‑Ketoglutaric acid;
Ala: Alanine; Arg: Arginine; Asn: Asparagine; CIT: Citrate; DHAP: Dihydroxy‑
acetone‑phosphate; DHF: 7:8‑Dihydrofolate; E4P: Erythrose‑4‑phosphate;
ETH: Ethanol; F6P: Fructose‑6‑phosphate; FBP: 1,6 Fructose diphosphate;
FUM: Fumarate; GLC: Glucose; G1P: Glucose‑1‑phosphate; G6P: Glucose‑
6‑phosphate; GlaA: Glucoamylase; GLCNT: Gluconate; G3P: Glyceraldehyde‑
3‑phosphate; Gln: Glutamine; Glu: Glutamate; His: Histidine; ICT: Isocitrate;
Ile: Isoleucine; Leu: Leucine; Lys: Lysine; Mal: Malate; Met: Methionine; OA:
Oxalate; OAA: Cytosolic oxaloacetate; Orn: Ornithine; PEP: Phosphoenolpyru‑
vate; Phe: Phenylalanine; Pro: Proline; PYR: Pyruvate; R5P: Ribose‑5‑phosphate;
Ru5P: Ribulose‑5‑phosphate; S7P: Sedoheptulose‑7‑phosphate; Ser: Serine;
SUC: Succinate; Thr: Threonine; Trp: Tryptophan; Tyr: Tyrosine; Val: Valine; X5P:
D‑xylulose‑5‑phosphate.
Acknowledgements
Not applicable.
Authors’ contributions
YFS constructed all strains, characterized them, and performed shake flask
cultivations under the supervision of TS. YFS, XZX, and JQ carried out the
chemostat runs and analyzed the metabolome data. YFS and PL performed
metabolite quantification by GC/LC–MS detection and GSMM simulations.
YPZ and VM initiated this study and coordinated the project. YFS, LMQ, TS,
HZL, and VM co‑wrote the final text. All authors read and approved the final
manuscript.
Funding
Open Access funding enabled and organized by Projekt DEAL. The work of YFS
has been funded by the Chinese scholarship council.
Availability of data and materials
All data generated or analysed during this study are included in this published
article.
Ethical approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 State Key Laboratory of Bioreactor Engineering, East China University of Sci‑
ence and Technology, Shanghai 200237, People’s Republic of China. 2 Chair
of Applied and Molecular Microbiology, Institute of Biotechnology, Technische
Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany. 3 Depart‑
ment of Biology and Biological Engineering, Chalmers University of Technol‑
ogy, Kemivägen 10, 412 96 Gothenburg, Sweden.
Received: 8 July 2020 Accepted: 7 October 2020
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