Presentation Information
[P04-464]Development of a high-throughput analysis for metabolites in yeast culture medium using PESI-MS
○Takeo Taniguchi1, Nobuyuki Okahashi1, Prihardi Kahar2, Takanari Hattori3, Chiaki Ogino2, Hidenori Takahashi3, Fumio Matsuda1 (1. The University of Osaka (Japan), 2. Kobe University (Japan), 3. Shimadzu Corporation (Japan))
Keywords:
High Throughput analysis,yeast,metabolite,PESI-MS,mass spectrometry
[Introduction]
High-throughput metabolite profiling of culture supernatants facilitates the discovery of industrially valuable strains. Probe electrospray ionization-mass spectrometry (PESI-MS) is suitable for the rapid analysis as it requires no complex pretreatment or separation steps. In this study, we profiled metabolites in culture supernatants from 14 yeast strains under 3 culture conditions using PESI-MS.
[Materials and Methods]
S. cerevisiae and 13 non-conventional yeasts were cultured for 24 h in SD medium containing 2, 5, or 10% glucose. Equal volumes of ethanol were mixed with spent medium supernatant and served for PESI-qTOF/MS. 28 metabolites (amino acids, organic acids and sugar alcohols) were measured per sample in 15 seconds.
[Results]
To confirm the measurement stability of medium components, SD medium supplemented with 28 metabolites (100 μM each) was measured 10 times using PESI-MS. The relative standard deviation for peak intensities was less than 10% for 22 metabolites, confirming the stability of the analysis. For 23 metabolites, a standard error of < 5% was achieved within 6 s of acquisition, further reducing analysis time. The method was applied to the analysis of 126 medium supernatant samples (14 yeast strains × three glucose concentrations × biological triplicates). Each sample was analyzed in 15 seconds (6 seconds for both negative and positive modes, with 2.4 seconds for polarity switching). All 28 metabolites (amino acids, organic acids and sugar alcohols) were detected in yeast culture supernatant. Principal component analysis separated Komagataella phaffii from other yeast strains. These clusters were further classified into small groups depending on the medium glucose concentration. The loading plot showed that the separation of K. phaffii was primarily driven by α-ketoglutarate (αKG) and αKG-derived amino acids, whose secretion levels were markedly higher in K. phaffii, indicating its potential as a platform strain for bioproduction of αKG-derived compounds such as GABA through metabolic engineering. In parallel, glucose concentration-dependent clusters revealed common metabolic shifts. High-glucose cultures showed increased extracellular pyruvate levels, whereas low-glucose cultures exhibited enhanced secretion of amino acids such as valine and proline. These results demonstrated that strain and culture condition-dependent metabolic traits can be evaluated by PESI-MS for rapid phenotypic screening and rational strain selection in microbial bioproduction
High-throughput metabolite profiling of culture supernatants facilitates the discovery of industrially valuable strains. Probe electrospray ionization-mass spectrometry (PESI-MS) is suitable for the rapid analysis as it requires no complex pretreatment or separation steps. In this study, we profiled metabolites in culture supernatants from 14 yeast strains under 3 culture conditions using PESI-MS.
[Materials and Methods]
S. cerevisiae and 13 non-conventional yeasts were cultured for 24 h in SD medium containing 2, 5, or 10% glucose. Equal volumes of ethanol were mixed with spent medium supernatant and served for PESI-qTOF/MS. 28 metabolites (amino acids, organic acids and sugar alcohols) were measured per sample in 15 seconds.
[Results]
To confirm the measurement stability of medium components, SD medium supplemented with 28 metabolites (100 μM each) was measured 10 times using PESI-MS. The relative standard deviation for peak intensities was less than 10% for 22 metabolites, confirming the stability of the analysis. For 23 metabolites, a standard error of < 5% was achieved within 6 s of acquisition, further reducing analysis time. The method was applied to the analysis of 126 medium supernatant samples (14 yeast strains × three glucose concentrations × biological triplicates). Each sample was analyzed in 15 seconds (6 seconds for both negative and positive modes, with 2.4 seconds for polarity switching). All 28 metabolites (amino acids, organic acids and sugar alcohols) were detected in yeast culture supernatant. Principal component analysis separated Komagataella phaffii from other yeast strains. These clusters were further classified into small groups depending on the medium glucose concentration. The loading plot showed that the separation of K. phaffii was primarily driven by α-ketoglutarate (αKG) and αKG-derived amino acids, whose secretion levels were markedly higher in K. phaffii, indicating its potential as a platform strain for bioproduction of αKG-derived compounds such as GABA through metabolic engineering. In parallel, glucose concentration-dependent clusters revealed common metabolic shifts. High-glucose cultures showed increased extracellular pyruvate levels, whereas low-glucose cultures exhibited enhanced secretion of amino acids such as valine and proline. These results demonstrated that strain and culture condition-dependent metabolic traits can be evaluated by PESI-MS for rapid phenotypic screening and rational strain selection in microbial bioproduction
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