Dataset Information

Mass Spectrometry Proteomics of Engineered Yarrowia lipolytica Strains for Enhanced Carotenoid and Lipid Production Across Two Growth Phases.

ABSTRACT: This submission contains the mass spectrometry proteomics dataset collected from the oleaginous yeast Yarrowia lipolytica. The data was collected from three strains grown in glycerol mineral medium: a parental control strain (PAR), a genetically modified carotenoid-producing strain (CAR), and a genetically modified lipid-producing strain (OBE). Samples were taken during two distinct physiological states: the initial exponential growth phase and the subsequent nitrogen-limited (Nlim) phase. The proteomics data was primarily used to constrain a newly reconstructed enzyme-constrained genome-scale model (ecGEM) of Y. lipolytica. The analysis provides insights into the physiological states of the engineered strains across the different phases and helped to assess the impact of genetic modifications on the production of target molecules. An average of 4,329 unique proteins were detected. The mass spectrometry acquisition utilized a Data Independent Analysis (DIA) method , and the raw data was processed using Dia-NN software.

INSTRUMENT(S):

ORGANISM(S): Yarrowia Lipolytica (candida Lipolytica)

SUBMITTER: Juliano Sabedotti De Biaggi

LAB HEAD: Petri-Jaan Lahtvee

PROVIDER: PXD072100 | Pride | 2026-03-30

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	220901_02_Orbi3_SK_SER_G60_T85_TTY_Lahtvee_DIA_250ng_Yarrowia_F19-S7_.raw	Raw
	220901_04_Orbi3_SK_SER_G60_T85_TTY_Lahtvee_DIA_250ng_Yarrowia_P25.raw	Raw
	220901_06_Orbi3_SK_SER_G60_T85_TTY_Lahtvee_DIA_250ng_Yarrowia_P51.raw	Raw
	220901_08_Orbi3_SK_SER_G60_T85_TTY_Lahtvee_DIA_250ng_Yarrowia_F10-S7.raw	Raw
	220901_14_Orbi3_SK_SER_G60_T85_TTY_Lahtvee_DIA_250ng_Yarrowia_F07-S9.raw	Raw

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Publications

Enzyme-constrained genome-scale model of Yarrowia lipolytica predicts growth-phase specific metabolic engineering targets.

De Biaggi Juliano Sabedotti JS Park Young-Kyoung YK Kerkhoven Eduard J EJ Ledesma-Amaro Rodrigo R Lahtvee Petri-Jaan PJ

Applied microbiology and biotechnology 20260324 1

The oleaginous yeast Yarrowia lipolytica has been gaining increasing importance as an industrial biotech platform, supported by several available metabolic engineering tools. Genome-scale models (GEMs) are relevant to the iterative improvement of this yeast, and their predictive ability is enhanced by enzymatic activity constraints (ecGEMs). Although the newest tools for ecGEM reconstruction use deep learning to expand the coverage of these constraints, this approach has not yet been applied to ...[more]

PMID: 41876849

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