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The Multidimensional Chromatography (MDC) Workshop
The Multidimensional Chromatography (MDC) Workshop
The Multidimensional Chromatography (MDC) Workshop draws experts in this exciting field to share and discuss their research.
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Untargeted determination of cycling yeast metabolites by GCxGC-TOF MS (Lina Mikaliunaite, MDCW 2023)

Tu, 21.11.2023
| Original article from: The Multidimensional Chromatography (MDC) Workshop
A computational method for the untargeted determination of cycling yeast metabolites using a comprehensive GC×GC-TOFMS dataset was developed.
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  • Photo: Untargeted determination of cycling yeast metabolites by GCxGC-TOF MS (Lina Mikaliunaite, MDCW 2023)
  • Video: LabRulez: Lina Mikaliunaite: Untargeted determination of cycling yeast metabolites by GCxGC-TOF MS (MDCW 2023)
  • 🎤 Presenter: Lina Mikaliunaite, Robert Synovec (University of Washington, Seattle, USA)

💡 Book in your calendar: 15th Multidimensional Chromatography Workshop (MDCW) January 2024

15th Multidimensional Chromatography (MDC) Workshop 2024

Abstract

A computational method for the untargeted determination of cycling yeast metabolites using a comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) dataset was developed.

The yeast metabolomic cycle for the diploid yeast strain CEN. PK with a 5 hr cycle period relative to the O₂ concentration level is comprehensively examined to determine the metabolites that exhibit cycling. Samples were collected over only two cycles (10 hr with a total of 24 time-point sampling intervals at 25 min each) as an experimental constraint. Due to the limited number of cycles expressed in the dataset, a computational method was devised to determine with statistical significance whether or not a given metabolite exhibited a temporal signal pattern that constituted cycling in the context of the 5 hr cycle period. The computational method we report compares the experimentally obtained 24 time-point metabolite signal sequences to randomly generated signal sequences coupled with statistically based confidence level LOF metrics to determine whether or not a given metabolite expresses cycling, and if so, what is the phase of the cycling.

Initially the GC×GC-TOFMS dataset was analyzed using tile-based Fisher ratio (F-ratio) analysis. Since there were 24 time-point intervals, this constituted 24 sample classes in the F-ratio calculation which produced 672 metabolite hits. Next, application of the computational method determined that there were 210 of the 672 metabolites exhibiting cycling: 55 identified metabolites and 155 unknown metabolites. Furthermore, the 210 cycling metabolites were categorized into four groups, and where applicable, a phase was determined.

The Multidimensional Chromatography (MDC) Workshop
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