Adaptive Laboratory Evolution and Metabolic Engineering of Zymomonas mobilis for Bioethanol Production Using Molasses

Abstract

Molasses with abundant sugars is widely used for bioethanol production. Although the ethanologenic bacterium Zymomonas mobilis can use glucose, fructose, and sucrose for ethanol production, levan production from sucrose reduces the ethanol yield of molasses fermentation. To increase ethanol production from sucrose-rich molasses, Z. mobilis was adapted in molasses, sucrose, and fructose in parallel. Adaptation in fructose is the most effective route to generate an evolved strain F74 with improved molasses utilization, which is majorly due to a G99S mutation in Glf for enhanced fructose import. Subsequent sacB deletion and sacC overexpression in F74 to divert sucrose metabolism from levan production to ethanol production further enhanced ethanol productivity 28.6% to 1.35 g/L/h. The efficient utilization of molasses by diverting sucrose metabolic flux through adaptation and genome engineering not only generated an excellent ethanol producer using molasses but also provided the strategy for developing microbial cell factories.

Enhanced Enzymatic Hydrolysis of High-Solids Content Corncobs by a Lytic Polysaccharide Monooxygenase from Podospora anserina S Mat+ for Valuable Monosaccharides

“…Corncob hydrolysate has typically been used for ethanol production using yeast or Zymomonas mobilis . However, little research has been conducted on converting it into monosaccharides, which may be due to challenges in downstream separation or the effects of acetic acid during enzymatic conversion . In our attempt to produce d -allulose through an enzymatic process using glucose isomerase (GI) and d -allulose 3-epimerase (DAE) in a one-pot system, we compared the control group with the hydrolysate of 25% corncob with the same initial glucose concentration (Figure d).…”

Systemic metabolic engineering of Enterobacter aerogenes for efficient 2,3-butanediol production

“…A dynamic tolerance engineering strategy was designed by introducing the deinococcal response regulator DR1558 to improve microbial productivity and relieve metabolic burden. Engineering strategies to improve cellular stress resistance such as adaptive evolution (Huang et al 2023 ; Zhou et al 2023 ), regulatory factor introduction (Wu et al 2021 ), tolerance target screening (Li et al 2023 ; Cámara et al 2022 ), and transport engineering (Mutanda et al 2022 ) are now widely developed. Among them, the introduction of regulatory factors is a useful strategy to improve tolerance to target compounds even in the face of unknown toxicity mechanisms.…”

Reconstruction of the genome-scale metabolic network model of Sinorhizobium fredii CCBAU45436 for free-living and symbiotic states

“…At present, the GSMMs of model organisms such as Saccharomyces cerevisiae (Heavner and Price, 2015) and Escherichia coli (Weaver et al, 2014) are relatively comprehensive, but there are still many blanks for non-model organisms, which results in significant limitation for their utilization. There are some GSMMs of none-model organisms like iZM516 (Wu et al, 2023), iQY1018 (Yuan et al, 2023), and iZDZ767 (Zhang et al, 2023) which reveal potentially efficient ways to produce substances with economic benefits by microorganisms (Huang et al, 2023). In 2020, Contador and others developed iCC541, the first generation of the metabolic network model of S. fredii CCBAU45436 (Contador et al, 2020).…”