# Real-time metabolomics on E. coli cell cultures

Nina Lager-lachaud, Maud Heuillet, Rochelle Kouakou, Margot Hernandez, Esther Boiron, Christophe Ellero, Xavier Cameleyre, Floriant Bellvert

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## To cite this version:

Nina Lager-lachaud, Maud Heuillet, Rochelle Kouakou, Margot Hernandez, Esther Boiron, et al. Real-time metabolomics on E. coli cell cultures. 17èmes journées scientifiques du Réseau Francophone de Métabolomique et Fluxomique, Jun 2025, Paris, France. 2025. [hal-05095581](https://hal.science/hal-05095581v1)

HAL Id: hal-05095581

https://hal.science/hal-05095581v1

Submitted on 3 Jun 2025

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# Real-time metabolomics on *E. coli* cell cultures

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Nina Lager-Lachaud*<fnref n="1" />,<fnref n="2" />, Maud Heuillet<fnref n="1" />,<fnref n="2" />, Rochelle Kouakou<fnref n="1" />,<fnref n="2" />, Margot Hernandez<fnref n="3" />, Esther Boiron<fnref n="3" />, Christophe Ellero<fnref n="1" />, Xavier Cameleyre<fnref n="1" />, and Floriant Bellvert†<fnref n="1" />,<fnref n="2" />

## Introduction

Fermentation monitoring is a powerful tool for bioprocess development, optimisation and control. Several parameters can be tracked including temperature, dissolved oxygen, pH, metabolites, etc... As metabolites represent the final step of biological regulation, they are key indicators. Metabolic changes can occur very rapidly, and traditional metabolic analyses are time-consuming. Therefore, online high-resolution time course analysis is required. To achieve this, we adapt a real-time metabolomic workflow from instrumental development (Cortada-Garcia, et al., 2022) to automated reprocessing, enabling feedback to the fermenter in real time to optimise bioprocesses.

## Instrumental development

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## Software development

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### One tool controls all modules

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* Source code driving and synchronizing all modules

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* Intuitive graphical interface

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* User guide (GitHub)

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* Modular and adaptable to different designs

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### Real-time processing workflow

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## Results & Discussion

<figure><img src="image_12.png" /><figcaption>¹³C: 24/33 compounds labeled
(no normalization by DO)</figcaption></figure>

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### ☐ Metabolome coverage :

* Improve metabolome coverage : FIA parameters optimization

* Validate metabolites identification with offline points (IC-HRMS & NMR)

### ☐ Metabolome quantification :

* Relative quantification in progress : addition of non-metabolised internal standard in cell culture -> MOPS

* Next step : Absolute quantification with NMR benchtop in series or external calibration curve...

### ☐ Other applications :

* Transpose to other types of cell cultures, such as adherent cells (cf. HepatOtwins project)

<figure><img src="image_14.png" /></figure>

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## References

[1] On-line targeted metabolomics for real-time monitoring of relevant compounds in fermentation processes. *Cortada-Garcia et al.* 2023

[2] On-line untargeted metabolomics monitoring of an *Escherichia coli* succinate fermentation process. *Cortada-Garcia et al.* 2022

## Acknowledgments

MetaboHUB ANR-11-INBS-0010;

MetEx+ ANR-21-ESRE-0035;

MetaboHUB (JVCE) ANR-24-INBS-0012

<footnote n="1">¹Toulouse Biotechnology Institute (TBI), Université de Toulouse, CNRS, INRAE, INSA, 31077 Toulouse, France - INSA - Institut National des Sciences Appliquées - France</footnote>

<footnote n="2">²MetaboHUB-MetaToul, National Infrastructure of Metabolomics Fluxomics (ANR-11-INBS-0010), 31077 Toulouse, France - INSA - Institut National des Sciences Appliquées - France</footnote>

<footnote n="3">³Institut National des Sciences Appliquées - Toulouse - Institut National des Sciences Appliquées, Université de Toulouse - France</footnote>