A Multiomics Approach Using Metabolomics and Lipidomics

Importance of Topic

Industrial fermentation processes rely on microorganisms such as Escherichia coli to produce valuable compounds for food, biotechnology, and energy sectors. Monitoring metabolic profiles through combined metabolomics and lipidomics enables detailed insights into cellular pathways, facilitating strain optimization, process control, and enhanced yield of high-value products like ergothioneine.

Study Objectives and Overview

This work investigates metabolic dynamics in E. coli engineered to produce ergothioneine when cultured with either thiosulfate or sulfate as sulfur sources. A multiomics strategy integrates hydrophilic metabolite profiling and lipid analysis to compare changes across cultivation stages and to assess how different sulfur substrates influence sulfur-containing metabolites and membrane lipid composition.

Methodology and Instrumentation

• Culture conditions: E. coli grown in minimal medium with 50 mM thiosulfate or 100 mM sulfate, sampled at 0, 24, 48, 72, 96, 120, 168, 216 hours.
• Sample preparation: Cell density normalized to OD = 2, rapid rinse, and extraction by Bligh–Dyer protocol separating aqueous (metabolites) and organic (phospholipids) phases.
• Chromatography–Mass Spectrometry: Simultaneous LC–MS/MS analysis on Shimadzu LCMS-8060 triple quadrupole system.
• Primary metabolite profiling: PFPP column (2.1 × 150 mm, 3 µm) with formic acid–water/acetonitrile gradient.
• Phospholipid profiling: C8 column (2.1 × 150 mm, 2.6 µm) with ammonium formate–water and acetonitrile/2-propanol gradient.

Key Findings and Discussion

• A total of 49 polar metabolites and 56 phospholipid species were quantified, revealing significant temporal shifts related to sulfur metabolism and membrane lipid composition.
• Cultures supplied with thiosulfate displayed a pronounced increase in cysteine, γ-Glu-Cys, and downstream sulfur metabolites (homocysteine, methionine, SAH, SAM) after the 72-hour transition to stationary phase.
• Lipidomics data showed early enrichment of phosphatidylethanolamine (PE) relative to phosphatidylserine (PS), indicating preferential membrane lipid biosynthesis linked to serine and cysteine availability.
• Overlaying metabolite and lipid profiles elucidates how sulfur source selection modulates both cytosolic pathways and membrane architecture, with implications for optimizing ergothioneine synthesis.

Benefits and Practical Applications

• Multiomics-driven monitoring supports real-time quality control and metabolic engineering by pinpointing bottlenecks in sulfur assimilation and lipid formation.
• Insights into phospholipid–metabolite interplay can guide fermentation medium design and genetic modifications to boost target compound yields.
• Approach is broadly applicable across microbial production platforms for pharmaceuticals, nutraceuticals, and biofuels.

Future Trends and Opportunities

• Integration with transcriptomics and proteomics for a systems-level understanding of regulatory networks controlling sulfur metabolism.
• High-throughput automation and machine learning models to predict optimal culture conditions and genetic targets.
• Dynamic flux analysis to map real-time metabolite flow and identify rate-limiting steps in ergothioneine biosynthesis.
• Expansion to other industrial microbes and metabolite classes to generalize multiomics workflows.

Conclusion

Combining metabolomics and lipidomics on a triple quadrupole LC–MS platform offers a powerful framework to unravel complex metabolic shifts driven by sulfur source selection. This multiomics approach enhances understanding of ergothioneine production in E. coli and lays the groundwork for targeted process improvements and strain engineering.

References

• Sample provided by Iwao Ohtsu and Yusuke Kawano, University of Tsukuba, Japan.
• Supported by the Science and Technology Research Promotion Program for Agriculture, Forestry, Fisheries and Food Industry, Ministry of Agriculture, Forestry and Fisheries, Japan.