Adaptive evolution of Methylotuvimicrobium alcaliphilum to grow in the presence of rhamnolipids improves fatty acid and rhamnolipid production from CH4.
Deepika AwasthiYung-Hsu TangBashar AmerEdward E K BaidooJennifer GinYan ChenChristopher J PetzoldMarina KalyuzhnayaSteven W SingerPublished in: Journal of industrial microbiology & biotechnology (2022)
Rhamnolipids (RLs) are well-studied biosurfactants naturally produced by pathogenic strains of Pseudomonas aeruginosa. Current methods to produce RLs in native and heterologous hosts have focused on carbohydrates as production substrate; however, methane (CH4) provides an intriguing alternative as a substrate for RL production because it is low cost and may mitigate greenhouse gas emissions. Here, we demonstrate RL production from CH4 by Methylotuvimicrobium alcaliphilum DSM19304. RLs are inhibitory to M. alcaliphilum growth (<0.05 g/l). Adaptive laboratory evolution was performed by growing M. alcaliphilum in increasing concentrations of RLs, producing a strain that grew in the presence of 5 g/l of RLs. Metabolomics and proteomics of the adapted strain grown on CH4 in the absence of RLs revealed metabolic changes, increase in fatty acid production and secretion, alterations in gluconeogenesis, and increased secretion of lactate and osmolyte products compared with the parent strain. Expression of plasmid-borne RL production genes in the parent M. alcaliphilum strain resulted in cessation of growth and cell death. In contrast, the adapted strain transformed with the RL production genes showed no growth inhibition and produced up to 1 μM of RLs, a 600-fold increase compared with the parent strain, solely from CH4. This work has promise for developing technologies to produce fatty acid-derived bioproducts, including biosurfactants, from CH4.
Keyphrases
- fatty acid
- room temperature
- cell death
- pseudomonas aeruginosa
- low cost
- escherichia coli
- mass spectrometry
- genome wide
- magnetic resonance
- poor prognosis
- cystic fibrosis
- risk assessment
- magnetic resonance imaging
- computed tomography
- machine learning
- crispr cas
- cell proliferation
- big data
- single cell
- staphylococcus aureus
- gene expression
- acinetobacter baumannii
- drug resistant
- heavy metals
- multidrug resistant
- ionic liquid
- bioinformatics analysis
- solid state