Comparative Fluxome and Metabolome Analysis of Formate as an Auxiliary Substrate for Penicillin Production in Glucose‐Limited Cultivation of Penicillium chrysogenum

Abstract

During glucose-limited growth, a substantial input of adenosine triphosphate (ATP) is required for the production of β-lactams by the filamentous fungus Penicillium chrysogenum. Formate dehydrogenase has been confirmed in P. chrysogenum for formate oxidation allowing an extra supply of ATP, and coassimilation of glucose and formate has the potential to increase penicillin production and biomass yield. In this study, the steady-state metabolite levels and fluxes in response to cofeeding of formate as an auxiliary substrate in glucose-limited chemostat cultures at the dilution rates (D) of both 0.03 h −1 and 0.05 h −1 are determined to evaluate the quantitative impact on the physiology of a high-yielding P. chrysogenum strain. It is observed that an equimolar addition of formate is conducive to an increase in both biomass yield and penicillin production at D = 0.03 h −1 , while this is not the case at D = 0.05 h −1 . In addition, a higher cytosolic redox status (NADH/NAD + ), a higher intracellular glucose level, and lower penicillin productivity are only observed upon formate addition at D = 0.05 h −1 , which are virtually absent at D = 0.03 h −1 . In conclusion, the results demonstrate that the effect of formate as an auxiliary substrate on penicillin productivity in the glucose-limited chemostat cultivations of P. chrysogenum is not only dependent on the formate/glucose ratio as published before but also on the specific growth rate. The results also imply that the overall process productivity and quality regarding the use of formate should be further explored in an actual industrial-scale scenario.

Changes in Oxygen Availability during Glucose-Limited Chemostat Cultivations of Penicillium chrysogenum Lead to Rapid Metabolite, Flux and Productivity Responses

“…An Agilent Zorbax SB-C 18 reversed-phase column (150 mm × 4.6 mm ID, 5 µm) was used to determine the concentrations of PAA, PenG, and byproducts in the penicillin biosynthetic pathway using equal gradient, reversed-phase high-performance liquid chromatography (HPLC). The mobile phase was 0.44 g/L potassium dihydrogen phosphate in acetonitrile/water (65/35, v/v); the injection volume was 5 µL, the detection wavelength was 214 nm, the flow rate was 1.5 mL/min and the column temperature was 25 • C [52].…”

“…For extracellular sampling, the cold steel-bead method, combined with liquid nitrogen, was used for the fast filtration and quenching of extracellular enzyme activities, as described previously [52]. For intracellular sampling, approximately 1.2 mL of broth was taken from the bioreactor into a tube containing the quenching solution (−27.5 • C, 40% v/v aqueous methanol).…”

Impact of Altered Trehalose Metabolism on Physiological Response of Penicillium chrysogenum Chemostat Cultures during Industrially Relevant Rapid Feast/Famine Conditions

“…For extracellular sampling, the cold steel-bead method combined with liquid nitrogen was used for the fast filtration and quenching of extracellular enzyme activities, as described previously [27]. For intracellular sampling, about 1 mL of broth was taken from the bioreactor into a tube containing the quenching solution (−27.5 • C, 40% V/V aqueous methanol).…”

“…The mobile phase consisted of 0.44 g KH 2 PO 4 per liter in the acetonitrile/water solution (65/35, V/V). The sample injection volume, the detection wave length, the flow rate and the column temperature were 5 µL, 214 nm, 1.5 mL/min and 25 • C, respectively [27].…”

Coupled metabolic‐hydrodynamic modeling enabling rational scale‐up of industrial bioprocesses

“…The functioning of the complex biological system can be understood by either top‐down (e.g., constraint‐based genome‐scale metabolic models) or bottom‐up approach (dynamic models based on differential equations; Kerkhoven, Lahtvee, & Nielsen, ). Targeted, quantitative metabolomics can yield significant insights into molecular mechanisms and metabolic regulation, which can be implemented to set up metabolic models describing intracellular activities (Cakir et al, ; Wang, Wang, et al, ). Strikingly, by combing metabolic flux analysis methods with other “omics” data sets (proteomics, transcriptomics), this new “omics” platform technology can help to provide a more complete understanding of a biological system (Buescher et al, ; Jang, Chen, & Rabinowitz, ; Matsuda et al, ; Toya & Shimizu, ; Wiechert & Noh, ; Zamboni, Saghatelian, & Patti, ).…”