Authors: Raheja Y, Singh V, Kumar N, Agrawal D, Sharma G, Di Falco M, Tsang A, Chadha BS
The current study is the first to describe the temporal and differential transcriptional expression of two lytic polysaccharide monooxygenase (LPMO) genes of Rasamsonia emersonii in response to various carbon sources. The mass spectrometry based secretome analysis of carbohydrate active enzymes (CAZymes) expression in response to different carbon sources showed varying levels of LPMOs (AA9), AA3, AA7, catalase, and superoxide dismutase enzymes pointing toward the redox-interplay between the LPMOs and auxiliary enzymes. Moreover, it was observed that cello-oligosaccharides have a negative impact on the expression of LPMOs, which has not been highlighted in previous reports. The LPMO1 (30 kDa) and LPMO2 (47 kDa), cloned and expressed in Pichia pastoris, were catalytically active with (kcat/Km) of 6.6×10-2 mg-1 ml min-1 and 1.8×10-2 mg-1 ml min-1 against Avicel, respectively. The mass spectrometry of hydrolysis products of Avicel/carboxy methyl cellulose (CMC) showed presence of C1/C4 oxidized oligosaccharides indicating them to be Type 3 LPMOs. The 3D structural analysis of LPMO1 and LPMO2 revealed distinct arrangements of conserved catalytic residues at their active site. The developed enzyme cocktails consisting of cellulase from R. emersonii mutant M36 supplemented with recombinant LPMO1/LPMO2 resulted in significantly enhanced saccharification of steam/acid pretreated unwashed rice straw slurry from PRAJ industries (Pune, India). The current work indicates that LPMO1 and LPMO2 are catalytically efficient and have a high degree of thermostability, emphasizing their usefulness in improving benchmark enzyme cocktail performance. KEY POINTS: • Mass spectrometry depicts subtle interactions between LPMOs and auxiliary enzymes. • Cello-oligosaccharides strongly downregulated the LPMO1 expression. • Developed LPMO cocktails showed superior hydrolysis in comparison to CellicCTec3.
Keywords: Rasamsonia emersonii; Hydrolysis; In silico modeling; LPMOs; Mass spectrometry;
PubMed: https://pubmed.ncbi.nlm.nih.gov/39167166/
DOI: 10.1007/s00253-024-13240-0