Thesis by Ian Ramtanon: « Exploration de la diversité chimique et des tendances de réactivité enzymatique dans des échantillons complexes de biomasse : approche combinée spectrométrie de masse haute résolution/résonance magnétique nucléaire » (Exploring chemical diversity and enzymatic reactivity trands in complex biomass samples: a combined high resolution mass spectrometry and nuclear magnetic resonance approach).
Lignocellulosic biomass is a renewable resource for which conversion into bioethanol is a promising avenue for producing alternative, low-carbon fuels. Converting this biomass requires a pretreatment step to break it down. However, this process generates compounds that can inhibit the action of enzymes used to hydrolyze cellulose into glucose, thereby reducing the efficiency of this reaction. In order to improve the profitability of such processes, these inhibitors need to be identified, but their presence in a highly complex environment composed of several hundred products is a real challenge.
The PhD project addressed this issue from the perspective of an innovative multi-technique analytical strategy making it possible to map the chemical diversity of hydrolysates and subsequently propose a methodology for establishing links between the constituents and the observed enzyme inhibition. This strategy is based on a fractionation approach using successive liquid-liquid extraction steps via CPC1, to simplify the hydrolysates studied, followed by characterization of each fraction by LC-HRMS/MS2 [1] and NMR3. This generates complementary datasets due to the universality of the response of the principal compounds by NMR and the sensitivity of mass spectrometry. The inhibiting properties of the fractions and hydrolysates were then evaluated using enzymatic hydrolysis reactivity tests before the application of chemometric [2] and chemoinformatic methods to analyze these multidimensional data (CPC-LC-HRMS/MS, CPC-NMR, reactivity response).
1 Liquid-liquid extraction by centrifugal partition chromatography
2 Liquid chromatography coupled with high-resolution tandem mass spectrometry
3 Nuclear Magnetic Resonance
Considerable chemical diversity was demonstrated, as illustrated in Figure 1 for a hydrolysate. The illustration provided offers a summary overview of the complexity of the sample (each point representing a detected compound) and the main chemical families. The approach also facilitates identification through information propagation, since the identification of a single compound per cluster enables proposals to be made for points in the same cluster (belonging to the same chemical family) and increases the confidence level of groupings through the use of color coding.
Analyses carried out on 22 hydrolysates from a variety of biomass types revealed the combined presence of sugars, organic acids, and phenolic compounds, some of which play a decisive role in enzyme inhibition. Finally, advanced processing of this complex data made it possible to propose candidates with inhibiting propensities concerning enzymatic hydrolysis.
These advances pave the way for new methodological approaches aimed at gaining a better understanding of inhibition mechanisms and optimizing strategies for converting biomass into bioethanol.
References:
- I. Ramtanon, A. Berlioz-Barbier, S. Remy, JH. Renault, A. Le Masle. A combined liquid chromatography – trapped ion mobility – tandem high-resolution mass spectrometry and multivariate analysis approach for the determination of enzymatic reactivity descriptors in biomass hydrolysates, Journal of Chromatography A, vol. 1706, (2023),
>> DOI : https://doi.org/10.1016/j.chroma.2023.464277
- I. Ramtanon, M. Lacoue-Nègre, A. Berlioz-Barbier, A. Le Masle, JH. Renault, A selective genetic algorithm - PLS-DA approach based on untargeted LC-HRMS: Application to complex biomass samples, Chemometrics and Intelligent Laboratory Systems, vol. 261, (2025),
>> DOI : https://doi.org/10.1016/j.chemolab.2025.105381
Scientific contact: Agnès Le Masle