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. 2025 Feb 8:26:102269.
doi: 10.1016/j.fochx.2025.102269. eCollection 2025 Feb.

Effect of different killing methods during curing on the phytochemical and bacterial composition of Vanilla planifolia using multi-omic approaches

Tiffany A Cuan-Escobar  1   2 , Alma Cuellar-Sánchez  2 , Haiku D J Gómez-Velázquez  3 , Juan L Monribot-Villanueva  4 , José A Guerrero-Analco  4 , Isabel Gutiérrez-Díaz  5 , Diego A Luna-Vital  1   2
Affiliations

Effect of different killing methods during curing on the phytochemical and bacterial composition of Vanilla planifolia using multi-omic approaches

Tiffany A Cuan-Escobar et al. Food Chem X. .

Abstract

Vanilla planifolia Jacks. ex Andrews, is cultivated for its aromatic pods, obtaining the primary source of vanillin, a molecule valued for its flavor and bioactivity. Mexico ranks among the top five global producers, and Papantla, Veracruz, contributes 70 % of national production. Developing vanilla's characteristic aroma involves a curing process composed of killing, sweating, drying, and conditioning, which enzymatic reactions and microbial activity play essential roles. This study assessed the impact of four killing treatments: microwave, hot water immersion, sonication, and freezing on the phenolic composition and bacterial communities in vanilla curing through metabolomic and 16S sequencing approaches. Freezing treatment resulted in the most substantial changes in phenolic profiles, including higher vanillin concentrations. Bacillus was the dominant bacterial genus, with hot water immersion and sonication showing the greatest α-diversity. These findings underscore the value of omic sciences in refining curing processes, enabling producers to achieve higher-quality vanilla through more efficient and technical methods.

Keywords: 16S sequencing; Curing process; Killing process; Metabolomics; Phenolic compounds; Vanilla planifolia.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Unlabelled Image
Graphical abstract
Fig. 1
Fig. 1
a) Hierarchical clustering heatmap of both ionization modes (ESI + and ESI -) found in untargeted metabolomic analysis as a result of different killing treatments in V. planifolia pods. The heatmap was generated using Euclidean and Ward for distance measure and clustering algorithm. Hot water immersion 80 °C (80 W), Freezing (FREE), Microwave (MIC) and Sonication (SON) as treatments. High correlated peak intensities are in MIC treatment. b) Principal Component Analysis (PCA) respecting peak intensities in both ionization modes (ESI + and ESI -) as a result of different killing treatments in V. planifolia pods. c) Tentative metabolic pathways found in four killing treatments in V. planifolia pods. It was determined by Mummichog algorithm and KEGG database in Functional Analysis module of MetaboAnalyst software. The statistical analysis was made with FDR.
Fig. 2
Fig. 2
a) Heatmap representing the identified metabolites in targeted metabolomic analysis. High content of phenolic compounds are found in the FREE treatment. b) Principal Component Analysis (PCA) respecting to the metabolites obtained in the targeted analysis because of different killing treatments in V. planifolia pods. c) Biplot graph showing the main contributions of the 4 killing treatments in the found metabolites. Glucovanillin in MIC, luteolin in 80 W, protocatechuic acid and caffeic acid in FREE and trans-cinnamic acid in SON.
Fig. 3
Fig. 3
Relative abundances of bacterial populations in the 3 study groups of V. planifolia pods: Control (Ctrl), Killed pods (K), Cured pods (C). A high displacement of bacterial populations is obtained in Cured group.
Fig. 4
Fig. 4
β-diversity PCoA Bray Curtis analysis. Thermal treatments like Microwave (CMIC), Hot water immersion 80 °C (C80 W) and Freezing (CFREE) are separated and dispersed in this plot, meaning differences in bacterial populations. CSON was clustered with the killed (K) treatments and the control, assuming similarity in their microorganisms.
Fig. 5
Fig. 5
Interaction network of metabolomic and 16S Sequencing features for V. planifolia. Green squares represent metabolites found in targeted metabolomics; red circles represent bacteria; red and blue lines represent positive and negative correlations respectively. Those correlations were selected by p < 0.01. The interactions were visualized by Cytoscape software. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
See this image and copyright information in PMC

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