Effect of increasing cell density on metabolic dynamics
Our previous study showed that increasing the initial cell density ofS. cerevisiae resulted in an improved glucose uptake rate and
enhanced lactic acid accumulation
(Pangestu et al., 2022).
The present findings align with our previous observations and are even
further confirmed with more evidence. As depicted in Figure 2b, the
augmentation of cell density expedited the rate of glucose consumption
in both strains, with a more pronounced effect observed in the BTCC3L
strain (red vs. yellow straight lines) than in the F118L strain (blue
vs. green straight lines). Consistent with the screening results, the
accumulation of lactic acid in the F118L strain also vastly surpassed
that in the BTCC3L strain during cultivation (Figure 2a). However,
increasing cell density in the BTCC3L strain led to an 18-fold increase
in lactic acid yield (from 0.004 ± 0.002 to 0.07 ± 0.00 g·g
glucose-1), which was still lower than the values
observed in the F118L strain across both low- and high-density cell
cultures (0.23 ± 0.05 g·g glucose-1 and 0.27 ± 0.03
g·g glucose-1, respectively). Notably, in comparison
to our prior research, this BTCC3L strain
(LDH +, CYB2 -)
displayed slightly higher lactic acid accumulation than the BTCC3LX5
strain (LDH +, PDC5 -),
though at a 2-fold lower level than that of the BTCC3LX1 strain
(LDH +, PDC1 -)
(Pangestu et al., 2022),
thus revealing the order of how effective the disruption of those genes
is in improving L-lactic acid production. In addition to lactic acid,
the accumulation of other major metabolites, namely, ethanol and
glycerol, also exhibited elevation in the BTCC3L strain when cultivated
at a higher cell density. To provide stronger evidence, we also
attempted to perform an identical genetic modification strategy in the
BY4741 strain, a common laboratory strain exhibiting no flocculation
behavior, and observed a similar trend, i.e., enhanced accumulation of
major metabolites as a result of amplifying the cell density (Figure
S1d). In contrast, the concentration of lactic acid in the F118L strain
experienced a relatively negligible change, albeit a slight improvement,
in response to altering the initial cell concentration, implying a
lesser cell-density dependence in lactic acid accumulation by the
flocculant yeast.
Gene expression analysis revealed significant changes as the cell
density increased (L vs. H ). Specifically, in the BTCC3L
strain, 31 genes were upregulated, with the expression of theHSP26 gene being the highest, and 1 gene, ACS1 , was
downregulated (|LFC| ≥ 2, -log10adjusted p -value ≥ 1.30) (Figure 3a). Figure 3b illustrates the
interaction network of DEGs in the BTCC3L strain. Notably, the majority
of DEGs are related to glycolysis and pyruvate metabolism, represented
by gray nodes. Additionally, six glycolytic genes (FBA1 ,PFK1 , PGK1 , PGM2 , TDH3 , and TPI1 )
connect the gray group with other clusters associated with the ETC
(yellow nodes), cell growth (blue nodes), and stress response (red
nodes). This observation supports the interconnectedness of metabolic
turbulence in glycolysis with other pathways. While the PTK2 gene
does not appear to have direct connections with other clusters, a deeper
exploration of interactions at the second shell of the network reveals
its connection to the TPK1 gene (not measured in this study),
which is directly linked to the HXK1 , PGM2 , RAS2 ,
and SOL4 genes (Figure S2).
The dramatic upregulation of the HSP26 gene, the most upregulated
DEG in the BTCC3L strain (shown in Figure 3c), was likely due to the
higher lactic acid accumulation, as its transcription is known to be
repressed under less acidic conditions
(Carmelo & Sá-Correia,
1997). The other top five genes with the highest LFC (PGK1 ,SPI1 , TDH1 , and TDH3 ) are associated with
glycolysis, highlighting the strong impact of increasing cell density on
this pathway. Along with glycolysis, as shown in Figure 3d, other DEGs
are also involved in amino acid biosynthesis (10 genes) and PPP (6
genes), with predominant expression in the cytosol (7 genes),
mitochondria (7 genes), or both compartments (11 genes) according to the
functional enrichment analysis
(Raudvere et al., 2019).
The results also indicate that altering the cell density affected proton
transmembrane transport, ATP and pyruvate metabolism, NAD and NADP
binding, and GAPDH (NAD+ and
NAD(P)+) phosphorylation.
Figure 4 provides an overview of the impact of increasing cell density
on the metabolic profile of the BTCC3L strain. The treatment resulted in
the upregulation of genes associated with hexose transport (i.e.,HXT7 ), glycolysis (i.e., HXK1 , PGM2 , PFK1 ,FBA1 , TPI1 , TDH1, TDH2, TDH3, PGK1 , GPM2 andENO1 ), PPP (i.e., ZWF1 , SOL4 and TKL2 ) and
ethanol metabolism (PDC5 and ADH3 ). These upregulations
led to an increased glucose consumption rate and the generation of
fermentation products. For comparison, a separate study employed a
combined global metabolic engineering strategy and CRISPR-δ integration
(GMES/CRISPR) approach to randomly introduce 12 glycolysis-related
genes, complemented with the LDH gene, into the genome, aiming to
amplify the activity of the pathway
(Mitsui et al., 2020). In
this study, we attained a similar outcome by only performing a
higher-density cell cultivation without the need for extensive genetic
modifications.
Additionally, the relative gene expression of the exogenous LDHgene was still low due to the intact PDC and ADH genes.
However, we observed an increase in lactic acid accumulation (Figure 2a)
and a noticeable enhancement of LDH gene expression (LFC = 5.83,
Figure S3a) upon increasing cell density. Notably, the gene was not
included as one of the DEGs in Figure 3c due to its relatively high
variance among the three measured biological replicates, resulting in
the -log10 adjusted p-value of 0.71 (lower than the
predefined significance threshold of 1.30), yet this increased
expression might be adequate to explain the observations. It is
noteworthy that L-lactate can also be produced from methylglyoxal
(Takatsume et al., 2006), a
minor byproduct of glycolysis, as indicated by the upregulation of theGRE2 gene (Figure 4). However, further investigation is required
to determine the significance of this pathway considering that the
compound is not typically generated in large quantities inside the cell.
Nevertheless, in high-cell density cultures, there is a possibility that
the generation of methylglyoxal and lactaldehyde, its conversion product
by the GRE gene, is substantial. If so, it presents a promising
strategy to rewire glucose conversion to lactate via a nonpyruvate
route, since the pyruvate-to-lactate route competes with several
reactions, such as alcohol metabolism and the TCA pathway. It is
important to note that cultivating the wild-type BTCC3 strain (without
the introduction of the LDH gene) in high-cell density culture
did not lead to an increase in lactic acid accumulation
(Pangestu et al., 2022),
which suggests that the increase in lactic acid production observed in
this study was likely attributed to the genetic engineering strategies
employed in the BTCC3 strain rather than solely the effect of high-cell
density culture. It is also important to further study the affinity of
the lactate dehydrogenase enzyme to methylglyoxal and lactaldehyde, as
these compounds share chemical structure similarities with pyruvate.
The increased glycolytic activity resulted in an enhancement of the
energy production capacity, as indicated by the significant upregulation
of genes associated with the ETC, specifically the NDI1 ,CYC1 and CYT1 genes, which are located in the inner
mitochondrial membrane and are responsible for facilitating the movement
of electrons from respiratory complex I to IV (Figure 4). As electrons
pass through these complexes, protons (H+) are pumped
from the mitochondrial matrix to the intermembrane space, generating a
concentration gradient
(Mitchell, 1961). The
intermembrane space becomes more positively charged compared to the
mitochondrial matrix, and subsequently, the protons flow back to the
mitochondrial matrix through the F0 domain, driving the
rotation of a rotor within ATP synthase, which induces conformational
changes in the F1 domain, leading to the conversion of
ADP and inorganic phosphate to ATP. The synthesized ATP is then
transported to supply energy for various processes, including numerous
key metabolic pathways and cellular adaptation to changing environments.
For instance, elevated lactic acid generation can lead to a depletion in
intracellular pH. Vacuolar H+-ATPase (V-ATPase),
consisting of multiple subunits, including VMA2 and VMA4 ,
plays a crucial role in acidifying the vacuole by pumping protons
(H+) into the vacuolar lumen
(Forgac, 2007) and
maintaining the proper cytosolic pH for optimum enzymatic activities.
The upregulation of RAS2 in high-density cell culture, on the
other hand, may be attributed to the increased accumulation of
fructose-1,6-bisphosphate (F1,6BP)
(Peeters et al., 2017) and
the response to nutrient-limited conditions
(Bhattacharya et al.,
1995; Pothoulakis & Ellis, 2018) caused by the high cell-density
conditioning. These changes then stimulate adenylate cyclase, an enzyme
that converts ATP into cyclic adenosine monophosphate (cAMP), which then
activates protein kinase A (PKA), which phosphorylates and regulates the
activity of various downstream targets, including transcription factors
that control the expression of ACT1 , a gene encoding actin
involved in multiple cellular processes such as cell division, cell
motility, intracellular transport, cell shape and structure, and signal
transduction
(Hubberstey &
Mottillo, 2002; Pardee, 2010). Additionally, PKA activation influences
the expression of the cell wall protein gene YGP1(Arnthong et al.,
2022; Howard et al., 2001) and various stress-response genes, such asHSP26 , HSP150 , and SPI1 , via the RIM101 pathway,
HOG pathway, Msn2/4 transcription factor regulation, or other possible
routes
(Ferguson
et al., 2005; Ma & Liu, 2010; Martínez-Pastor et al., 1996; Mira et
al., 2009; Schüller et al., 1994). HSP26 functions as a
molecular chaperone
(Haslbeck & Vierling,
2015), aiding in protein folding and stability, whereas HSP150acts as a cell wall stabilizer
(Kapteyn et al., 1999).
Meanwhile, SPI1 is involved in cell wall biogenesis, contributing
to cell wall strength and protection
(Simões et al., 2006).
Therefore, these interactions provide a rational explanation for the
correlations observed between glycolytic rate, cell cycle and growth,
and stress tolerance, as these processes are regulated by PKA-mediated
signaling pathways.
Surprisingly, in the F118L strain, none of the examined genes showed
significant differential expression (Figure 3a). This finding suggests
that the observed metabolic dynamics described earlier occurred in the
F118L strain without the need for high-cell density conditioning.
However, to corroborate this hypothesis, further analysis comparing the
gene expression patterns in both strains at different cell densities is
needed, as will be detailed in the subsequent cross-strain analysis.