Efficient biotransformation of methanol to fatty alcohols

2023-03-14

Recently, our group engineered yeast Ogataea polymorpha for efficient productions of fatty alcohol from sole methanol by coupling peroxisomal metabolism.

Methanol is a potential feedstock for biomanufacturing because it could be easily obtained in an environment-friendly manner. But it is challenging to construct a microbial cell factory for methanol based bioproduction due to the toxicity of methanol and the complex cellular metabolism.

Fatty alcohols are widely used as detergents, emulsifiers, and emollients in personal care products, such as soaps, shampoos and creams. The global fatty alcohol market is expected to reach 7.0 billion USD by 2025 with a compound annual growth rate (CAGR) of 5.2%. Microbial production from methanol might provide an efficient and sustainable route for supplying fatty alcohol while preventing resource shortages and environmental pollution. However, due to the toxicity of methanol and formaldehyde (the oxidative intermediate of methanol), the overproduction of fatty alcohols in microbial cell factories is hindered. Therefore, engineering cellular metabolism to couple product biosynthesis with cell growth may reduce the toxicity and improve chemical production.

We observed a compromised fatty alcohol production when constructing the cytosolic biosynthesis pathway O. polymorpha. But peroxisomal compartmentalization significantly improved fatty alcohol production by coupling the cellular metabolism and product biosynthesis. Further enhancing the supply of precursor and cofactor in peroxisome improved the cellular fitness and enabled high-level production of fatty alcohol (up to 3.6 g/L).

This work provides a feasible engineering strategy to improve methanol biotransformation toward sustainable production of fatty alcohols and shows some insights of methanol metabolism. This study was published in PNAS on Mar. 13. The study was supported by the National Natural Science Foundation of China. (Text and image by Xiaoxin Zhai)

Link: https://www.pnas.org/doi/10.1073/pnas.2220816120


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