Dataset Information

Massively parallel fitness profiling reveals multiple novel enzymes in Pseudomonas putida lysine metabolism

ABSTRACT: The lysine metabolism of Pseudomonas putida can produce multiple important commodity chemicals and is implicated in rhizosphere colonization. However, despite intensive study, the biochemical and genetic links between lysine metabolism and central metabolism remains unresolved in P. putida. Here, we leverage Random Barcode Transposon Sequencing (RB-TnSeq), a genome-wide assay measuring the fitness of thousands of genes in parallel, to identify multiple novel enzymes and regulators in both L- and D-lysine metabolism. We first describe three pathway enzymes that catabolize 2-aminoadipate (2AA) to 2-ketoglutarate (2KG) connecting D-lysine to the TCA cycle. One of these enzymes, PP_5260, contains a DUF1338 domain, a family without previously described biological function. We demonstrate PP_5260 converts 2-oxoadipate (2OA) to 2-hydroxyglutarate (2HG), a novel biochemical reaction. We expand on recent work showing that the glutarate hydroxylase CsiD can co-utilize 2OA and 2KG. We further show glutarate metabolism is locally regulated by two independent glutarate responsive transcription factors, and that cellular abundance of D- and L-lysine pathway proteins are highly sensitive to pathway specific substrates. This work demonstrates the utility of RB-TnSeq of discovering novel metabolic pathways in even well-studied bacterial species.

ORGANISM(S): Pseudomonas Putida Kt2440

SUBMITTER: Chris Petzold

PROVIDER: PXD011350 | panorama | Fri May 17 00:00:00 BST 2019

REPOSITORIES: PanoramaPublic

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Massively Parallel Fitness Profiling Reveals Multiple Novel Enzymes in Pseudomonas putida Lysine Metabolism.

Thompson Mitchell G MG Blake-Hedges Jacquelyn M JM Cruz-Morales Pablo P Barajas Jesus F JF Curran Samuel C SC Eiben Christopher B CB Harris Nicholas C NC Benites Veronica T VT Gin Jennifer W JW Sharpless William A WA Twigg Frederick F FF Skyrud Will W Krishna Rohith N RN Pereira Jose Henrique JH Baidoo Edward E K EEK Petzold Christopher J CJ Adams Paul D PD Arkin Adam P AP Deutschbauer Adam M AM Keasling Jay D JD

mBio 20190507 3

Despite intensive study for 50 years, the biochemical and genetic links between lysine metabolism and central metabolism in Pseudomonas putida remain unresolved. To establish these biochemical links, we leveraged random barcode transposon sequencing (RB-TnSeq), a genome-wide assay measuring the fitness of thousands of genes in parallel, to identify multiple novel enzymes in both l- and d-lysine metabolism. We first describe three pathway enzymes that cat ...[more]

PMID: 31064836

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Project description:Among multiple interconnected pathways for L-Lysine (L-Lys) catabolism in pseudomonads, Pseudomonas aeruginosa PAO1 employed the decarboxylase and the transaminase pathways. However, up till now several genes involved in the operation and regulation of these pathways were still missing. Transcriptome analyses coupled with promoter activity measurements and mutant growth phenotype analysis lead us to identify several new members of the L-Lys and D-Lys catabolic pathways and their regulatory elements, including argR to trigger lysine decarboxylation into cadaverine, PauR for the Î³-glutamylation pathway of polyamine catabolism into 5-aminovalerate, gcdR-gcdHG for glutarate utilization, dpkA, amaR-amaAB and PA2035 for D-Lys catabolism, lysR-lysXE for L-Lys efflux, and lysP for L-Lys uptake. Gene expression microarray, including probe preparation, hybridization, fluidics run and chip scan, was performed by Georgia State University DNA/Protein Core Facility. P. aeruginosa PAO1 was grown aerobically in minimal medium P with 350 rpm shaking at 37C, in the presence of 10mM L-glutamate supplemented with 10 mM L-lysine, cadaverine, 5-amino valerate, glutaric acid, D-lysine or 5mM L-pipecolate. Cells were harvested when the optical density at 600 nm reached 0.5~0.6 by centrifugation for 5 minutes at 4C. Total RNA samples were isolated by RNeasy purification kit following instructions of the manufacturer (Qiagen). Reverse transcription for cDNA synthesis, fragmentation by DNase I treatment, cDNA probe labeling and hybridization were performed according to the instructions of GeneChip manufacturer (Affymetrix). Data were processed by Microarray Suite 5.0 software normalizing the absolute expression signal values of all chips to a target intensity of 500. GeneSpring software (Silicon Genetics) was used for expression pattern analysis and comparison. Data collection was carried out using GCOS 1.4 software (Affymetrix). Probe intensity values were normalized to a target value of 500 with normalization factor equal to 1. Data analysis was performed using GeneSpring GX 11 Software (Aglient, Palo Alto,CA). Related Research Papers: 1. Indurthi SM, Chou HT, Lu CD. Molecular Characterization of lysR-lysXE, gcdR-gcdHG, and amaR-amaAB Operons for Lysine Export and Catabolism: A Comprehensive Lysine Catabolic Network in Pseudomonas aeruginosa PAO1. Microbiology. 2015 Submitted [EMID:04803de65c782] 2. Chou HT, Li J, and Lu CD. Functional Characterization of the agtABCD and agtSR Operons for Î³-Aminobutyrate and Î´-Aminovalerate Uptake and Regulation in Pseudomonas aeruginosa PAO1. Curr. Microbiology. 2014 Jan;68(1):59-63. 3. Chou HT, Li JY, Peng YC, Lu CD. Molecular characterization of PauR and its role in control of putrescine and cadaverine catabolism through the Î³-glutamylation pathway in Pseudomonas aeruginosa PAO1. J Bacteriol. 2013 Sep; 195(17):3906-13. 4. Chou HT, Hegazy M, Lu CD. L-lysine Catabolism is Controlled by Arginine/ArgR in Pseudomonas aeruginosa PAO1. J Bacteriol. 2010 Nov;192(22):5874-80

Project description:This proposal is aimed at providing transcriptome data to underpin a long-term joint research programme of Steve Smith and Alison Smith. We are jointly studying starch synthesis and breakdown in Arabidopsis leaves, and individually studying other enzymes of carbohydrate metabolism (eg. sucrose synthases, invertases, sugar transporters). Collectively these enzymes are encoded by up to 100 known genes, but there are many others of relevance to our studies. For several years we have employed a defined set of growth conditions for this work (resulting in numerous publications). We have extensive data for changes in the amounts of starch, malto-oligosaccharides and sugars throughout the diurnal cycle in these plants, and we intend to quantitate numerous key enzymes. We now wish to profile changes in transcripts in these plants, so that this information can be correlated with changes in the amounts of key enzymes and metabolites. Analysis of the data sets will help us to relate the synthesis of certain enzymes to particular metabolic functions, and also to help identify genes encoding novel proteins involved in carbohydrate metabolism. Current research is aimed at discovering such novel proteins using proteomics approaches (BBSRC Grant: _Discovery and Functional Analysis of the Starch Proteome_). While the growth conditions (12h photoperiod, 150 umol/m2/s, 20C) and ecotype (Col-0) are specifically tailored to our experiments, they will be of value to the wider community, and could form the basis for collaborative studies with other groups. The experiment has involved sampling leaves at eleven different time points as follows: 0, 1, 2, 4, 8, 12, 13, 14, 16, 20, and 24 h (where time 0 is the onset of dark and 12 h is the onset of light). The 24 h time point is a repeat of 0 h. This sequence provides relatively more samples immediately after the light-dark transitions, when changes in metabolism are most pronounced. Plants were grown in a controlled environment chamber under defined conditions, and selected for harvest according to a random number generator. Three fully expanded leaves were harvested from each of 20 plants for each sample. Leaves were frozen at -80 C and a portion saved for metabolite and enzyme assays while RNA was isolated from the remainder. The RNA has been purified and is ready to send to Nottingham. Experiment Overall Design: Number of plants pooled:20 Experiment Overall Design: Biological replicates: 2

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Dataset Information

Massively parallel fitness profiling reveals multiple novel enzymes in Pseudomonas putida lysine metabolism

Publications

Massively Parallel Fitness Profiling Reveals Multiple Novel Enzymes in <i>Pseudomonas putida</i> Lysine Metabolism.

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