Energy Charge as an Indicator of Pexophagy in Pichia pastoris

Reconstruction of a Cofactor Self-Sufficient Whole-Cell Biocatalyst System for Efficient Biosynthesis of Allitol from d-Glucose

The combined catalysis of glucose isomerase (GI), d-psicose 3-epimerase (DPEase), ribitol dehydrogenase (RDH), and formate dehydrogenase (FDH) provides a convenient route for the biosynthesis of allitol from d-glucose; however, the low catalytic efficiency restricts its industrial applications. Here, the supplementation of 0.32 g/L NAD⁺ significantly promoted the cell catalytic activity by 1.18-fold, suggesting that the insufficient intracellular NAD(H) content was a limiting factor in allitol production. Glucose dehydrogenase (GDH) with 18.13-fold higher activity than FDH was used for reconstructing a cofactor self-sufficient system, which was combined with the overexpression of the rate-limiting genes involved in NAD⁺ salvage metabolic flow to expand the available intracellular NAD(H) pool. Then, the multienzyme self-assembly system with SpyTag and SpyCatcher effectively channeled intermediates, leading to an 81.1% increase in allitol titer to 15.03 g/L from 25 g/L d-glucose. This study provided a facilitated strategy for large-scale and efficient biosynthesis of allitol from a low-cost substrate.

Improved Sample Preparation for Untargeted Metabolomics Profiling of Escherichia coli

Metabolomics is a powerful tool that can systematically describe global changes in the metabolome of microbes, thus improving our understanding of the mechanisms of action of antibiotics and facilitating the development of next-generation antibacterial therapies. However, current sample preparation methods are not efficient or reliable for studying the effects of antibiotics on microbes. In the present study, we reported a novel sample preparation approach using cold methanol/ethylene glycol for quenching Escherichia coli, thus overcoming the loss of intracellular metabolites caused by cell membrane damage. After evaluating the extraction efficiency of several extraction methods, we employed the optimized workflow to profile the metabolome of E. coli exposed to cephalexin. In doing so, we proved the utility of the proposed approach and provided insights into the comprehensive metabolic alterations associated with antibiotic treatment.

IMPORTANCE The emergence and global spread of multidrug-resistant bacteria and genes are a global problem. It is critical to understand the interactions between antibiotics and bacteria and find alternative treatments for infections when we are moving closer to a postantibiotic era. It has been demonstrated that the bacterial metabolic environment plays an important role in the modulation of antibiotic susceptibility and efficacy. In the present study, we proposed a novel metabolomic approach for intracellular metabolite profiling of E. coli, which can be used to investigate the metabolite alterations of bacteria caused by antibiotic treatment. Further understanding of antibiotic-induced perturbations of bacterial metabolism would facilitate the discovery of new therapeutic targets and pathways.