Transcriptome-guided identification of YALI0_F02013g and YALI0_A19910g as candidate NADPH-dependent oxidoreductases associated with enhanced erythritol production in Yarrowia lipolytica

NADPH competition by non-erythrose-reductase oxidoreductases limits erythritol yields in Yarrowia lipolytica , yet the specific contributors remain poorly defined. This study characterised two candidate genes, YALI0_F02013g (putative pyridoxine 4-dehydrogenase) and YALI0_A19910g (putative glycerol 2-dehydrogenase), using time-resolved transcriptomics, molecular docking and metabolic modelling. RNA-seq analysis across 96 h of fermentation revealed distinct temporal profiles: YALI0_F02013g was progressively induced 3.4-fold (peak 5040 FPKM at 72 h), while YALI0_A19910g was repressed 920-fold by 96 h (Table 2). Expression trends were validated by qRT-PCR (Pearson r > 0.94; Table 3). YALI0_A19910g expression correlated strongly negatively with erythritol titre (Pearson r = − 0.858), whereas YALI0_F02013g showed a weak positive correlation. Molecular docking predicted high NADPH binding affinities for both enzymes (− 9.8 and − 8.6 kcal mol⁻ 1 , respectively; Fig. 2) and identified conserved catalytic triads. An integrated prioritisation model ranked YALI0_F02013g as the higher-priority target (5.6/10 vs 5.0/10; Table 7). In silico flux estimates suggest that repressing YALI0_F02013g could conserve approximately 67% of the competing NADPH demand, potentially increasing erythritol yield by ~14%; these projections require experimental validation (Table 8). These findings identify YALI0_F02013g as a candidate metabolic bottleneck in the strain background examined, offering a specific target for engineering improved cofactor efficiency in industrial Yarrowia lipolytica strains.

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Journal
Biotechnology for Biofuels and Bioproducts
Published
2026-10-17
DOI
https://doi.org/10.1186/s13068-026-02827-6
Primary Topic
Microbial Metabolic Engineering and Bioproduction
Type
article
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article

Transcriptome-guided identification of YALI0_F02013g and YALI0_A19910g as candidate NADPH-dependent oxidoreductases associated with enhanced erythritol production in Yarrowia lipolytica

Wael A. Alsubhi, Yasir Anwar, Muhammad Sarfaraz Iqbal, Muhammad Hasnain Iqbal et al.
Biotechnology for Biofuels and Bioproducts
Microbial Metabolic Engineering and Bioproduction
article

Transcriptome-guided identification of YALI0_F02013g and YALI0_A19910g as candidate NADPH-dependent oxidoreductases associated with enhanced erythritol production in Yarrowia lipolytica

Wael A. Alsubhi, Yasir Anwar, Muhammad Sarfaraz Iqbal, Muhammad Hasnain Iqbal, Tariq Babakarkhil, Hairong Cheng, Abdulrahman Faisal Alkhanani
article en

Abstract

NADPH competition by non-erythrose-reductase oxidoreductases limits erythritol yields in Yarrowia lipolytica , yet the specific contributors remain poorly defined. This study characterised two candidate genes, YALI0_F02013g (putative pyridoxine 4-dehydrogenase) and YALI0_A19910g (putative glycerol 2-dehydrogenase), using time-resolved transcriptomics, molecular docking and metabolic modelling. RNA-seq analysis across 96 h of fermentation revealed distinct temporal profiles: YALI0_F02013g was progressively induced 3.4-fold (peak 5040 FPKM at 72 h), while YALI0_A19910g was repressed 920-fold by 96 h (Table 2). Expression trends were validated by qRT-PCR (Pearson r > 0.94; Table 3). YALI0_A19910g expression correlated strongly negatively with erythritol titre (Pearson r = − 0.858), whereas YALI0_F02013g showed a weak positive correlation. Molecular docking predicted high NADPH binding affinities for both enzymes (− 9.8 and − 8.6 kcal mol⁻ 1 , respectively; Fig. 2) and identified conserved catalytic triads. An integrated prioritisation model ranked YALI0_F02013g as the higher-priority target (5.6/10 vs 5.0/10; Table 7). In silico flux estimates suggest that repressing YALI0_F02013g could conserve approximately 67% of the competing NADPH demand, potentially increasing erythritol yield by ~14%; these projections require experimental validation (Table 8). These findings identify YALI0_F02013g as a candidate metabolic bottleneck in the strain background examined, offering a specific target for engineering improved cofactor efficiency in industrial Yarrowia lipolytica strains.

Biotechnology for Biofuels and Bioproducts
Shanghai Jiao Tong University (CN), King Abdulaziz University (SA), Government College University, Faisalabad (PK), Nangarhar University (AF), University of Hafr Al-Batin (SA), State Key Laboratory of Microbial Metabolism
Openalex Percentile: Top 24%
Microbial Metabolic Engineering and Bioproduction
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