High-throughput Saccharomyces cerevisiae Cultivation Data for Untargeted Metabolomics

Supporting Information for a high-throughput yeast cultivation method includes credentialing results for untargeted metabolomics. The dataset, associated with Lorenzo Favilli at the University of Luxembourg, contains results from HILIC and RP-lipids chromatography, metabolite annotations, and statistical analyses. It is published under an Open Access license.

Use Cases

• Benchmarking metabolite annotation tools based on credentialing results and manual quality control described.
• Comparing metabolite recovery rates against public databases like YMDB and HMDB using InChKey-based analysis.
• Validating high-throughput cultivation protocols using physiological constraint measurements such as growth rate and glucose uptake.
• Reproducing statistical analyses from the associated publication using the provided R script and results.

Strengths

• Includes credentialing results from two complementary chromatography methods: HILIC and RP-lipids.
• Provides manual quality control checks and Level 1 compound identifications, suggesting curated annotations.
• Contains an R script for annotation, supporting computational reproducibility.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Luxembourg

Collection Method

High-throughput cultivation of Saccharomyces cerevisiae followed by untargeted metabolomics analysis.