Lipid production by Rhodosporidium toruloides from biodiesel-derived glycerol in shake flasks and bioreactor: Impact of initial C/N molar ratio and added onion-peel extract

Filippousi, Rosanina; Diamantopoulou, Panagiota; Stavropoulou, Margarita; Makris, Dimitris P.; Papanikolaou, Séraphim

doi:10.1016/j.procbio.2022.10.008

Cited by 15 publications

(10 citation statements)

References 77 publications

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“…All instances have been uploaded to a database for training ML models. Moreover, Rhodosporidium toruloides is a novel yeast that has recently gained research attention for its high lipid content , and native carotenoid production. , However, the literature on Rhodosporidium is sparse . Here, we demonstrate that transfer learning can use knowledge from well-studied domains (Yarrowia-trained model) to understand less-studied scenarios and speed up the learning process. , In summary, for the first time, this study integrated the GPT with knowledge engineering and ML for predicting microbial cell factories.…”

Section: Introductionmentioning

confidence: 78%

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Generative Artificial Intelligence GPT-4 Accelerates Knowledge Mining and Machine Learning for Synthetic Biology

Xiao,

Li,

Moon

et al. 2023

ACS Synth. Biol.

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Knowledge mining from synthetic biology journal articles for machine learning (ML) applications is a labor-intensive process. The development of natural language processing (NLP) tools, such as GPT-4, can accelerate the extraction of published information related to microbial performance under complex strain engineering and bioreactor conditions. As a proof of concept, we proposed prompt engineering for a GPT-4 workflow pipeline to extract knowledge from 176 publications on two oleaginous yeasts (Yarrowia lipolytica and Rhodosporidium toruloides). After human intervention, the pipeline obtained a total of 2037 data instances. The structured data sets and feature selections enabled ML approaches (e.g., a random forest model) to predict Yarrowia fermentation titers with decent accuracy (R 2 of 0.86 for unseen test data). Via transfer learning, the trained model could assess the production potential of the engineered nonconventional yeast, R. toruloides, for which there are fewer published reports. This work demonstrated the potential of generative artificial intelligence to streamline information extraction from research articles, thereby facilitating fermentation predictions and biomanufacturing development.

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Section: Introductionmentioning

confidence: 78%

Section: ■ Introductionmentioning

confidence: 99%

Generative Artificial Intelligence GPT-4 Accelerates Knowledge Mining and Machine Learning for Synthetic Biology

Xiao,

Li,

Moon

et al. 2023

ACS Synth. Biol.

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show abstract

“…This interesting trait has also been reported in other yeast such as Rhodosporidium toruloides, Cryptococcus curvatus and Lipomyces starkeyi. These endo-polysaccharides can be therefor considered as advantageous co-products increasing the economic viability and sustainability of the SCO bioprocess [25][26][27].…”

Section: Microbial Oil Production: Process Overview and Cultivation S...mentioning

confidence: 99%

Challenges and prospects of yeast-based microbial oil production within a biorefinery concept

Gallego-García,

Susmozas,

Negro

et al. 2023

Microb Cell Fact

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Biodiesel, unlike to its fossil-based homologue (diesel), is renewable. Its use contributes to greater sustainability in the energy sector, mainly by reducing greenhouse gas emissions. Current biodiesel production relies on plant- and animal-related feedstocks, resulting in high final costs to the prices of those raw materials. In addition, the production of those materials competes for arable land and has provoked a heated debate involving their use food vs. fuel. As an alternative, single-cell oils (SCOs) obtained from oleaginous microorganisms are attractive sources as a biofuel precursor due to their high lipid content, and composition similar to vegetable oils and animal fats. To make SCOs competitive from an economic point of view, the use of readily available low-cost substrates becomes essential. This work reviews the most recent advances in microbial oil production from non-synthetic sugar-rich media, particularly sugars from lignocellulosic wastes, highlighting the main challenges and prospects for deploying this technology fully in the framework of a Biorefinery concept.

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“…The yeast can accumulate up to 70% lipids of its dry weight [ 4 , 5 , 6 , 7 ]. Additionally, the yeast has the capability to utilize a wide range of carbohydrates as a carbon source present in low-cost biomass waste streams, including monosaccharides such as hexose and pentose, oligosaccharides such as cellobiose, sucrose, and maltose, and alcohols such as glycerol and ethanol [ 1 , 8 , 9 ]. These features are promising for future industrial applications [ 4 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Adaptation of Proteome and Metabolism in Different Haplotypes of Rhodosporidium toruloides during Cu(I) and Cu(II) Stress

et al. 2023

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Rhodosporidium toruloides is a carotenogenic, oleogenic yeast that is able to grow in diverse environments. In this study, the proteomic and metabolic responses to copper stress in the two haplotypes IFO0559 and IFO0880 were assessed. 0.5 mM Cu(I) extended the lag phase of both strains significantly, while only a small effect was observed for Cu(II) treatment. Other carotenogenic yeasts such as Rhodotorula mucilaginosa are known to accumulate high amounts of carotenoids as a response to oxidative stress, posed by excess copper ion activity. However, no significant increase in carotenoid accumulation for both haplotypes of R. toruloides after 144 h of 0.5 mM Cu(I) or Cu(II) stress was observed. Yet, an increase in lipid production was detected, when exposed to Cu(II), additionally, proteins related to fatty acid biosynthesis were detected in increased amounts under stress conditions. Proteomic analysis revealed that besides the activation of the enzymatic oxidative stress response, excess copper affected iron–sulfur and zinc-containing proteins and caused proteomic adaptation indicative of copper ion accumulation in the vacuole, mitochondria, and Golgi apparatus.

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Lipid production by Rhodosporidium toruloides from biodiesel-derived glycerol in shake flasks and bioreactor: Impact of initial C/N molar ratio and added onion-peel extract

Cited by 15 publications

References 77 publications

Generative Artificial Intelligence GPT-4 Accelerates Knowledge Mining and Machine Learning for Synthetic Biology

Generative Artificial Intelligence GPT-4 Accelerates Knowledge Mining and Machine Learning for Synthetic Biology

Challenges and prospects of yeast-based microbial oil production within a biorefinery concept

Adaptation of Proteome and Metabolism in Different Haplotypes of Rhodosporidium toruloides during Cu(I) and Cu(II) Stress

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