Glycerol metabolism in E. coli have been described in the literature. However, cell changes are carried out as response to stress situations. In this study, two conditions were tested for transcription response in E. coli for further integration to metabolic network modeling. Gene expression-wide analyses reveal how cell have the ability to avoid glycerol toxicity increasing the consumption. The most striking response to glycerol consumption and the possible mechanism to optimize succinic acid production from glycerol was revealed by the combination of transcriptome, metabolic modeling, and machine learning analyses.
After glycerol incorporation in the cell mediated by GlpF, glycerol can be metabolized through two pathways. The first is mediated by the glycerol kinase GlpK through phosphorylation of glycerol to Gly-3-P, followed by GlpD activity under aerobic conditions, leading to dihydroxyacetone phosphate -DHAP- (Fig. 1). The alternative pathway consists of an oxidation step by glycerol dehydrogenase (GldA) to yield dihydroxyacetone (DHA), followed by phosphorylation by DHA kinase (DhaK) to give DHAP, as well. In this study, over expression of glpK was observed in both conditions, with a difference of around 20%. This result is not surprising since the GlpK-mediated reaction is the rate-limiting step in glycerol utilization . However, it has been observed that under the optimized culture conditions the glycerol utilization rate is higher than the evolved conditions, suggesting that should exits other mechanism in the cell to enhance glycerol utilization. Gly-3-P is the first intermediate between the glycerol pathway and the TCA cycle, as well as the biosynthesis and catabolism of lipids; however, accumulation of Gly-3-P can become toxic. Thus, it is carefully regulated . The export of Gly-3-P could be mediated by phoE and ompF membrane porins; however, down-regulation of phoE (–8.67 and − 9.04 Log2 FC for the optimized culture and the evolved strain, respectively) and up-regulation of ompF (Log2 FC 2.43) in the optimized culture suggest that it could play an essential role in E. coli ATCC 8739 glycerol metabolism at high uptake rates avoiding toxicity.
The marked up-regulation of glpQ (5.351 and 5.597 Log2 FC for the optimized culture and evolved strain, respectively), which catalyzes the hydrolysis of glycerol-phosphodiesters to an alcohol plus Gly-3-P together with ompF could explain the partially higher transcript abundance of glpT since the externally generated (or supplied) Gly-3-P activates GlpT [59, 60]. This protein exchanges Gly-3-P for phosphate, avoiding the toxicity of both Gly-3-P and the inorganic phosphates . As result, and considering that phosphate is necessary to increase glycerol utilization, autoregulation of the PhoB/PhoR two-component regulatory system need to be down expressed. Down regulation of PhoB/PhoR was observed in this study which could explain the achievement of optimal density , as well as contribute to the regulation of glycerol phosphate metabolism .
The transcriptional analysis also identified the differential expression of both flavin oxidases, glpD and glpABC. Once Gly-3-P is in the cytoplasm, it is oxidized to dihydroxyacetone phosphate by one of two flavin-dependent oxidases encoded by glpD or glpABC genes under aerobic or anaerobic conditions, respectively [40, 46]. In the presence of oxygen or nitrates, GlpD transfers electrons to the respective terminal oxidizes. In contrast, under anaerobic conditions the GlpABC system transfers the electrons to fumarate or nitrates . GlpD up-regulation was expected since culture conditions were under aerobic conditions, but higher expression of the glpABC system was surprising. Over expression of glpABC under aerobic conditions could be elucidated because of the activation of fumarate reductase enzymes (Table 1) in the evolved strain as results of high cell densities during the ALE process. However, in glycerol fermentation studies, the ΔfrdA mutant has been shown to be beneficial for glycerol fermentation because it prevents the negative impact of hydrogen by maintaining suitable redox conditions . Moreover, its activity could be supported by sdhABCD since they are structurally and functionally homologous . Therefore, we hypothesized that frdABCD up-regulation could be the reason why enhancement in the glycerol utilization was not observed in the evolved strain, even when an optimized culture medium was employed.
The insights on the molecular adaptive responses of E. coli to glycerol consumption revealed by the transcriptional datasets identified a marked hdeAB up-regulation only in the evolved strain. This is attractive since HdeAB are periplasmic proteins that play a role in optimal protection at low pH [66, 67]. Therefore, differences in hdeAB up-regulation in the evolved strain and the optimized culture medium probably occur because acetate is the main product in glycerol utilization and under ALE conditions the pH was not controlled. Moreover, the addition of a phosphate buffer system using the salts Na2HPO4 and KH2PO4 provides the culture medium used directly for the optimized condition with a buffering capacity (Ng, 2018).
It was observed that the main and preferable route for glycerol consumption is the pathway mediated by GlpK since this gene was highly overexpressed in high glycerol consumption cultures. Moreover, glpK deletion has also been observed to be essential for glycerol utilization as the sole carbon source . Then, deletion of this gene could result in a non-effective bioconversion process. As a result, this gene should not be taken into account for engineered E. coli strains using glycerol as the carbon source even when the GLYK reaction was repeatedly predicted to be knocked by OptKnock in ECC2 and iTA821 since two pathways for glycerol utilization in E. coli exist.
Based on OptKnock and random forest model predictions, four critical control points, glycolysis, pyruvate metabolism, the pentose phosphate pathway, and the TCA cycle, are associated with the overproduction of succinic acid. FUM and SUCDi appear to be the most significant keys in the TCA cycle for succinate overexpression. Results of this study suggest that they are mutually exclusive. Parallelly, the knockout of by-products such as acetate, formate, and lactate by deleting POX, ACKr, PTAr, PFL, and LDH_D were highly predicted to be knocked out. Those results are interesting since one of the bottlenecks for industrial production of bio-based products is the elimination of by-products, which could facilitate the recovery and purification process. This results and those obtained in the transcriptional responses suggest that deletion of the pta need to be, almost as mandatory, carried out since acetate production become a competitive pathway in glycerol metabolism for succinic acid production .
The pyruvate dehydrogenase complex is a critical connection point between glycolysis and the TCA cycle, both of which function during aerobic respiration through catalyzing the conversion of pyruvate to acetyl coenzyme A (acetyl-CoA) . PDH deactivation results in PFL carrying the flux from pyruvate to acetyl-CoA . Simple reaction knockouts show that PDH deletion results in a growth rate reduction of ~ 5%. Additionally, 5 reactions (FUM, GAPD, PGK, PGM, and TPI) were predicted to have the most significant reduction (8–10%) in the growth rate during glycerol utilization. Of those reactions, only FUM has a significant positive effect over the succinate production when this deletion is carried out alone. These results indicate that those mutants predicted by OptKnock where FUM and PDH are predicted are potential mutants to be tested in the lab because it have been observed that a low growth rate could negatively affect the profitability of industrial bio-based production products [2, 70].. However, in mutants in which both FUM and PDH were predicted (59.45%), TPI appeared in around 12.60% (Fig. 5). Then, the deletion of genes associated with TPI in addition to FUM and PDH reactions could negatively affect the growth rate. This because in the absence of TpiA, DHAP is converted to methylglyoxal, which, even at sub-millimolar concentrations, is a toxic compound . DHAP is the results of the alternative pathway on glycerol metabolization consistent of an oxidation step by glycerol dehydrogenase (GldA). DHAP must be transformed into the general glycolytic pathway through isomerization by triosephosphate isomerase (TpiA) as glyceraldehyde-3-phosphate (GA3P). Therefore, deletion of tpiA could result in growth inhibition and cell death in the presence of glycerol as the only carbon source . However, since FBA is not able to capture regulation, this situation could not be predicted by OptKnock.
Finally, computational models suggest that deletions of just 6–7 reaction knockouts are beneficial for industrial production since the growth rate does not decrease extremely. It is important to consider that a similar succinate production could be achieved if 6–8 reactions are knocked for all models. An assumption using optimization methods to predict cell capabilities is that the cell could quickly adjust the metabolism to maximize growth under certain conditions. This affirmation could be true for WT strains because FBA predicts an optimal condition. However, in metabolically engineered strains, the cell attempts to compensate the genetic changes carried out by the fewest changes in gene regulation until it achieves an optimal state that could be predicted using FBA . Then, FBA in engineered strains predicts a long-term evolved state. Thus, an alternative to evaluate unevolved mutants is the MOMA method . MOMA solves this problem by finding the solution that is most similar to the WT state (maximization of WT growth rate). Figure 7 shows a jump in the Euclidian distance between the WT and mutant strains when succinate production increases. This result could imply that after genetic manipulation microbial cell factories requires to be evolutionary engineered. ALE studies have shown to provide the cell with the ability to growth under selection pressure to go up from a sub-optimal state to the optimal growth rate predicted using in silico models . Moreover, since OptKnock seeks to maximize the flux of a target chemical while maximizing the growth rate, our predictions could be beneficial for further ALE experiments because microbial cell factories have naturally evolved to maximize the growth rate. Thus, the succinic acid production rate would increase as biomass formation increases  by using ALE rounds after metabolically engineering cells .