On‐line untargeted metabolomics monitoring of an Escherichia coli succinate fermentation process

Abstract

The real-time monitoring of metabolites (RTMet) is instrumental for the industrial production of biobased fermentation products. This study shows the first application of untargeted on-line metabolomics for the monitoring of undiluted fermentation broth samples taken automatically from a 5 L bioreactor every 5 min via flow injection mass spectrometry. The travel time from the bioreactor to the mass spectrometer was 30 s. Using mass spectrometry allows, on the one hand, the direct monitoring of targeted key process compounds of interest and, on the other hand, provides information on hundreds of additional untargeted compounds without requiring previous calibration data. In this study, this technology was applied in an Escherichia coli succinate fermentation process and 886 different m/z signals were monitored, including key process compounds (glucose, succinate, and pyruvate), potential biomarkers of biomass formation such as (R)-2,3-dihydroxy-isovalerate and (R)-2,3-dihydroxy-3-methylpentanoate and compounds from the pentose phosphate pathway and nucleotide metabolism, among others. The main advantage of the RTMet technology is that it allows the monitoring of hundreds of signals without the requirement of developing partial least squares regression models, making it a perfect tool for bioprocess monitoring and for testing many different strains and process conditions for bioprocess development.

Electrodeionization for the Bio-Succinic Acid Production Process

“…The bioconversion of succinic acid can be carried out using various strains of microorganisms, and the possibility of using various carbon sources as a fermentation medium (including waste sources) makes the process in line with the principles of sustainable development. In the upstream stage, fermentation broth is obtained and the required process conditions and the appropriate pH generate succinate as a product. , As a result, downstream processing requires not only purification from byproducts, biomass, and unreacted medium but also conversion of the carboxylate to the free acid form. Most of the methods possible to separate succinic acid and presented in Figure require preliminary treatment and acidification of the solution and do not provide direct separation of the carboxylate (sodium succinate).…”

“…In the upstream stage, fermentation broth is obtained and the required process conditions and the appropriate pH generate succinate as a product. 45,46 As a result, downstream processing requires not only purification from byproducts, biomass, and unreacted medium but also conversion of the carboxylate to the free acid form. Most of the methods possible to separate succinic acid and presented in Figure 14 require preliminary treatment and acidification of the solution and do not provide direct separation of the carboxylate (sodium succinate).…”

On‐line targeted metabolomics for real‐time monitoring of relevant compounds in fermentation processes

“…On-line metabolomics was conducted by connecting the fermenter to a TSQ Quantiva triple quadrupole (Thermo Scientific) mass spectrometer with the fluidics system previously described by Cortada-Garcia et al (2022) but the fermentation broth samples were subtracted from the bioreactor using a biomass filtration probe (TRACE Analytics GmbH) equipped with a polypropylene membrane.…”

“…However, this approach is limited to volatile molecules, whereas fermentation monitoring with MS directly from the liquid broth is a much less developed approach. The authors recently demonstrated the use of untargeted on‐line metabolomics (RTMet) directly sampling from the liquid phase as a bioprocess monitoring tool with an Escherichia coli fermentation process of succinate production (Cortada‐Garcia et al, 2022 ). In the study, the authors used a high‐resolution Orbitrap mass spectrometer, which allows the detection of metabolites with a mass tolerance of 5 ppm.…”

“…This way, a linear model was created to correlate RTMet MS data to metabolite concentration. Furthermore, the RTMet MS data of (R)-2,3-dihydroxy-isovalerate-a compound of BCAA metabolism previously identified as a biomass biomarker(Cortada-Garcia et al, 2022)-was correlated to the off-line WCW biomass data. This way, the on-line monitoring of this biomarker could be used as a proxy to monitor the biomass WCW concentration.…”