This study assessed the feasibility of using bleached cellulose pulp from Eucalyptus wood as a feedstock for the production of itaconic acid by fermentation. Additionally, different process strategies were tested with the aim of selecting suitable conditions for an efficient production of itaconic acid by the fungus Aspergillus terreus. The feasibility of using cellulose pulp was demonstrated through assays that revealed the preference of the strain in using glucose as carbon source instead of xylose, mannose, sucrose or glycerol. Additionally, the cellulose pulp was easily digested by enzymes without requiring a previous step of pretreatment, producing a glucose-rich hydrolysate with a very low level of inhibitor compounds, suitable for use as a fermentation medium. Fermentation assays revealed that the technique used for sterilization of the hydrolysate (membrane filtration or autoclaving) had an important effect in its composition, especially on the nitrogen content, consequently affecting the fermentation performance. The carbon-to-nitrogen ratio (C:N ratio), initial glucose concentration and oxygen availability, were also important variables affecting the performance of the strain to produce itaconic acid from cellulose pulp hydrolysate. By selecting appropriate process conditions (sterilization by membrane filtration, medium supplementation with 3 g/L (NH₄)₂SO₄, 60 g/L of initial glucose concentration, and oxygen availability of 7.33 (volume of air/volume of medium)), the production of itaconic acid was maximized resulting in a yield of 0.62 g/g glucose consumed, and productivity of 0.52 g/L·h.

Industrial-sized fermenters differ from the laboratory environment in which bioprocess development initially took place. One of the issues that can lead to reduced productivity on a large scale or even early termination of the process is the presence of bioreactor heterogeneities. This work proposes and adopts a design–build–test–learn-type workflow that estimates the substrate, oxygen, and resulting growth heterogeneities through a compartmental modelling approach and maps Yarrowia lipolytica-specific behavior in this relevant range of conditions. The results indicate that at a growth rate of 0.1 h⁻¹, the largest simulated volume (90 m³) reached partial oxygen limitation. Throughout the fed-batch, the cells experienced dissolved oxygen values from 0 to 75% and grew at rates of 0 to 0.2 h⁻¹. These simulated large-scale conditions were tested in small-scale cultivations, which elucidated a transcriptome with a strong downregulation of various transporter and central carbon metabolism genes during oxygen limitation. The relation between oxygen availability and differential gene expression was dynamic and did not show a simple on–off behavior. This indicates that Y. lipolytica can differentiate between different available oxygen concentrations and adjust its transcription accordingly. The workflow presented can be used for Y. lipolytica-based strain engineering, thereby accelerating bioprocess development.

The transcriptional regulatory network (TRN) in Yarrowia lipolytica coordinates its cellular processes, including the response to various stimuli. The TRN has been difficult to study due to its complex nature. In industrial-size fermenters, environments are often not homogenous, resulting in Yarrowia experiencing fluctuating conditions during a fermentation. Compared with homogenous laboratory conditions, these fluctuations result in altered cellular states and behaviors due to the action of the TRN. Here, a machine learning approach was deployed to modularize the transcriptome to enable meaningful description of its changing composition. To provide a sufficiently broad dataset, a wide range of relevant fermentation conditions (nutrient limitations, growth rates, pH values, oxygen availability and CO2 stresses) were run and samples obtained for RNA-Seq generation. We thus significantly increased the number of publicly available transcriptomic dataset on Y. lipolytica W29. In total, 23 independently modulated gene sets (termed iModulons) were identified of which 9 could be linked to corresponding regulons in S. cerevisiae. Strong responses were found in relation to oxygen limitation and elevated CO2 concentrations represented by (i) altered ribosomal protein synthesis, (ii) cell cycle disturbances, (iii) respiratory gene expression, and (iv) redox homeostasis. These results provide a fine-grained systems-level understanding of the Y. lipolytica TRN in response to industrially meaningful stresses, providing engineering targets to design more robust production strains. Moreover, this study provides a guide to perform similar work with poorly characterized single-cellular eukaryotic organisms. Highlights: - A large screening setup significantly expands the public RNA-Seq library on Y. lipolytica . - This work provides a systems-level understanding of the TRN in response to industrial stresses. - iModulon analysis can help accelerate bioprocess development. - Results can guide similar work on poorly characterized single-cellular eukaryotic organisms.