SugarMALDI: An Application for oligosaccharides’ identification in MALDI-MS data
4 affiliations
- 1l’Analyse et la Protéomique, MSAP, Miniaturisation pour la Synthèse, Lille, France, F-59000
- 2CNRS Institut CARMeN UMR
- 3Shrieking sixties
- 4Institut Pasteur
Abstract
Rationale : High-throughput MALDI-MS analyses produce extensive datasets daily. Each spectrum obtained from a complex mixture of oligosaccharides, generated through the enzymatic digestion of polymeric carbohydrates, can contain a vast amount of information requiring processing. Therefore, the availability of specialized informatics tools to facilitate data interpretation is essential. Methods : SugarMALDI is introduced as a cloud-based platform designed to support MALDI-MS interpretation of oligosaccharides. It enables the identification of both labeled and unlabeled oligosaccharides in complex MALDI-MS spectra, facilitates molecular formula assignment, and assesses candidate matches according to mass accuracy. Users can select from nine elemental monosaccharides available in the database, as well as define ionization adducts and chemical modifications, and modify parameters, allowing the software to be flexibly tailored to specific analytical contexts. Results : Designed for high-throughput workflows, the platform accelerates data processing while ensuring reliable interpretation. It was successfully validated using enzymatically digested standard plant gums, including arabinogalactan and galactomannan, as well as authentic watercolor samples, confirming its robustness and practical relevance. The average execution time was approximately two minutes per file, increasing proportionally with the number of selected monosaccharides. These results highlight the software’s efficiency, adaptability, and suitability for diverse analytical applications. Conclusions : SugarMALDI provides assisted data interpretation tailored to the needs of glycobiologists and glycochemists. It supports structural and compositional characterization, enables polysaccharide identification, and delivers clear visual reporting of results, thereby streamlining analysis and enhancing the efficiency and reliability of glycomic investigations.
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BibTeX
@misc{ho2026sugarmaldi,
title = {{SugarMALDI: An Application for oligosaccharides’ identification in MALDI-MS data}},
author = {Pierre-Alexandre Ho and Christian Rolando and Marie Yammine},
howpublished = {ChemRxiv},
year = {2026},
month = sep,
doi = {10.26434/chemrxiv.15008457/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008457/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - SugarMALDI: An Application for oligosaccharides’ identification in MALDI-MS data
AU - Pierre-Alexandre Ho
AU - Christian Rolando
AU - Marie Yammine
PY - 2026
DA - 2026/09/07
PB - ChemRxiv
DO - 10.26434/chemrxiv.15008457/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008457/v1
AB - Rationale : High-throughput MALDI-MS analyses produce extensive datasets daily. Each spectrum obtained from a complex mixture of oligosaccharides, generated through the enzymatic digestion of polymeric carbohydrates, can contain a vast amount of information requiring processing. Therefore, the availability of specialized informatics tools to facilitate data interpretation is essential. Methods : SugarMALDI is introduced as a cloud-based platform designed to support MALDI-MS interpretation of oligosaccharides. It enables the identification of both labeled and unlabeled oligosaccharides in complex MALDI-MS spectra, facilitates molecular formula assignment, and assesses candidate matches according to mass accuracy. Users can select from nine elemental monosaccharides available in the database, as well as define ionization adducts and chemical modifications, and modify parameters, allowing the software to be flexibly tailored to specific analytical contexts. Results : Designed for high-throughput workflows, the platform accelerates data processing while ensuring reliable interpretation. It was successfully validated using enzymatically digested standard plant gums, including arabinogalactan and galactomannan, as well as authentic watercolor samples, confirming its robustness and practical relevance. The average execution time was approximately two minutes per file, increasing proportionally with the number of selected monosaccharides. These results highlight the software’s efficiency, adaptability, and suitability for diverse analytical applications. Conclusions : SugarMALDI provides assisted data interpretation tailored to the needs of glycobiologists and glycochemists. It supports structural and compositional characterization, enables polysaccharide identification, and delivers clear visual reporting of results, thereby streamlining analysis and enhancing the efficiency and reliability of glycomic investigations.
ER -