MassIVE MSV000098800

Partial Public PXD067246

Quantitative Decoding of Pathway Fluxes that Couple Carbon and Energy Metabolism in Lignin Carbon Utilization

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Description

Soil Pseudomonas species, which thrive on lignin derivatives, are widely explored for biotechnology applications in lignin valorization. However, how the native metabolism coordinates phenolic carbon processing with required cofactor generation remains poorly understood. Here, we achieve quantitative understanding of this metabolic balance through a detailed multi-omics investigation of Pseudomonas putida KT2440 grown on four common phenolic acid substrates: ferulate, p-coumarate, vanillate, and 4-hydroxybenzoate. Relative to succinate, proteomics reveals >140-fold increase in transport and catabolic proteins for aromatics, but metabolomics identifies bottlenecks in initial catabolism to maintain favorable cellular energy charge, which is compromised in mutants with resolved bottlenecks. Up to 30-fold increase in pyruvate carboxylase and glyoxylate shunt proteins implies a metabolic remodeling confirmed by kinetic 13C-metabolomics. Quantitative analysis by 13C-fluxomics demonstrates coupling of this remodeling with cofactor production. Specifically, anaplerotic carbon recycling through pyruvate carboxylase promotes tricarboxylic acid cycle fluxes to generate 50-60% NADPH yield and 60-80% NADH yield, resulting in up to 6-fold greater ATP surplus than with succinate metabolism; the glyoxylate shunt sustains cataplerotic flux through malic enzyme for the remaining NADPH yield. This quantitative blueprint affords cofactor imbalance predictions in proposed engineering of key metabolic nodes in lignin valorization pathways. The cells were digested for proteomics analysis following the E4 protocol published recently. E4 filters (CDS Analytical, Oxford, PA) were used. For LCMS, Ultimate 3000 nanoLC coupled to Orbitrap Eclipse and FAIMS PRO interface were used. Data-independent acquisition data were collected, and processed using Spectronaut (version 19.5). [doi:10.25345/C5HM52Z2M] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Quantitative proteomics ; In-cell digestion ; On-filter digestion ; E3technology ; Pseudomonas putida ; DatasetType:Proteomics

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Principal Investigators:
(in alphabetical order) 		Ludmilla Aristilde, McCormick School of Engineering and Applied Science, Northwestern University, USA
Submitting User: yayu
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