Search

Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards., (© 2023. Battelle Memorial Institute and the Author(s).)

High titer, rate, yield (TRY), and scalability are challenging metrics to achieve due to trade-offs between carbon use for growth and production. To achieve these metrics, we take the minimal cut set (MCS) approach that predicts metabolic reactions for elimination to couple metabolite production strongly with growth. We compute MCS solution-sets for a non-native product indigoidine, a sustainable pigment, in Pseudomonas putida KT2440, an emerging industrial microbe. From the 63 solution-sets, our omics guided process identifies one experimentally feasible solution requiring 14 simultaneous reaction interventions. We implement a total of 14 genes knockdowns using multiplex-CRISPRi. MCS-based solution shifts production from stationary to exponential phase. We achieve 25.6 g/L, 0.22 g/l/h, and ~50% maximum theoretical yield (0.33 g indigoidine/g glucose). These phenotypes are maintained from batch to fed-batch mode, and across scales (100-ml shake flasks, 250-ml ambr®, and 2-L bioreactors).

Microbial production of fuels and commodity chemicals has been performed primarily using natural or slightly modified enzymes, which inherently limits the types of molecules that can be produced. Type I modular polyketide synthases (PKSs) are multi-domain enzymes that can produce unique and diverse molecular structures by combining particular types of catalytic domains in a specific order. This catalytic mechanism offers a wealth of engineering opportunities. Here we report engineered microbes that produce various short-chain (C5-C7) ketones using hybrid PKSs. Introduction of the genes into the chromosome of Streptomyces albus enables it to produce >1 g · l -1 of C6 and C7 ethyl ketones and several hundred mg · l -1 of C5 and C6 methyl ketones from plant biomass hydrolysates. Engine tests indicate these short-chain ketones can be added to gasoline as oxygenates to increase the octane of gasoline. Together, it demonstrates the efficient and renewable microbial production of biogasolines by hybrid enzymes.