Engineering topics

Bentley, Gayle J.

Publications and source records attributed to Bentley, Gayle J..

4 records

DOE OSTI2023

Initiation of fatty acid biosynthesis in Pseudomonas putida $\mathrm{KT2440}$

Deciphering the mechanisms of bacterial fatty acid biosynthesis is crucial for both the engineering of bacterial hosts to produce fatty acid-derived molecules and the development of new antibiotics. However, gaps in our understanding of the initiation of fatty acid biosynthesis remain. Here, we demonstrate that the industrially relevant microbe Pseudomonas putida KT2440 contains three distinct pathways to initiate fatty acid biosynthesis. The first two routes employ conventional β-ketoacyl-ACP synthase III enzymes, FabH1 and FabH2, that accept short- and medium-chain-length acyl-CoAs, respectively. The third route utilizes a malonyl-ACP decarboxylase enzyme, MadB. A combination of exhaustive in vivo alanine-scanning mutagenesis, in vitro biochemical characterization, X-ray crystallography, and computational modeling elucidate the presumptive mechanism of malonyl-ACP decarboxylation via MadB. Given that functional homologs of MadB are widespread throughout domain Bacteria, this ubiquitous alternative fatty acid initiation pathway provides new opportunities to target a range of biotechnology and biomedical applications.

09 BIOMASS FUELS↗

DOE OSTI2022

Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network

Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.

09 BIOMASS FUELS↗

DOE OSTI2022

Corrigendum to "Engineering glucose metabolism for enhanced muconic acid production in Pseudomonas putida KT2440" [Metab. Eng. 59 (2020) 64-75]

The plasmid used to delete hexR, pGB022, in our Pseudomonas putida KT2440 strain engineered to produce cis,cis-muconic acid from glucose, GB062, inadvertently introduced two mutations: a point mutation in the zwf-1, encoding the glucose-6-phosphate 1-dehydrogenase, that results in a conservative, V157I replacement and a deletion of the last 8 bp of the glucose-6-phosphate 1-epimerase gene, yeaD, leading to a frame shift in this gene and, consequently, the replacement of the last two amino acids of the C-terminus (LS) with 56 amino acids (RGPWVCPWVGKTAGCVSSRLFARSSIVLSVRLTYHLSVTLVCNVVVFTTLSLENRV).

BIOMASS FUELS↗

DOE OSTI2020

High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas putida KT2440

Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in Pseudomonas putida KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM.

59 BASIC BIOLOGICAL SCIENCES↗