Literature DB >> 35285712

Nitrogen Metabolism in Pseudomonas putida: Functional Analysis Using Random Barcode Transposon Sequencing.

Matthias Schmidt1,2,3, Allison N Pearson1,2,4, Matthew R Incha1,2,4, Mitchell G Thompson1,5, Edward E K Baidoo1,2, Ramu Kakumanu1,2, Aindrila Mukhopadhyay1,2, Patrick M Shih1,2,4,5, Adam M Deutschbauer4,5, Lars M Blank3, Jay D Keasling1,2,6,7,8,9,10.   

Abstract

Pseudomonas putida KT2440 has long been studied for its diverse and robust metabolisms, yet many genes and proteins imparting these growth capacities remain uncharacterized. Using pooled mutant fitness assays, we identified genes and proteins involved in the assimilation of 52 different nitrogen containing compounds. To assay amino acid biosynthesis, 19 amino acid drop-out conditions were also tested. From these 71 conditions, significant fitness phenotypes were elicited in 672 different genes including 100 transcriptional regulators and 112 transport-related proteins. We divide these conditions into 6 classes, and propose assimilatory pathways for the compounds based on this wealth of genetic data. To complement these data, we characterize the substrate range of three promiscuous aminotransferases relevant to metabolic engineering efforts in vitro. Furthermore, we examine the specificity of five transcriptional regulators, explaining some fitness data results and exploring their potential to be developed into useful synthetic biology tools. In addition, we use manifold learning to create an interactive visualization tool for interpreting our BarSeq data, which will improve the accessibility and utility of this work to other researchers. IMPORTANCE Understanding the genetic basis of P. putida's diverse metabolism is imperative for us to reach its full potential as a host for metabolic engineering. Many target molecules of the bioeconomy and their precursors contain nitrogen. This study provides functional evidence linking hundreds of genes to their roles in the metabolism of nitrogenous compounds, and provides an interactive tool for visualizing these data. We further characterize several aminotransferases, lactamases, and regulators, which are of particular interest for metabolic engineering.

Entities:  

Keywords:  BarSeq; Pseudomonas putida; RB-TnSeq; amino acid; aminotransferase; aminotransferases; biosensor; biosensors; lactam; metabolism; nitrate; nitrite; nitrogen; nitrogen metabolism; nucleotide; polyamine; t-SNE; transposon

Mesh:

Substances:

Year:  2022        PMID: 35285712      PMCID: PMC9004399          DOI: 10.1128/aem.02430-21

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   5.005


  148 in total

1.  Identification of the initial steps in D-lysine catabolism in Pseudomonas putida.

Authors:  Olga Revelles; Rolf-Michael Wittich; Juan L Ramos
Journal:  J Bacteriol       Date:  2007-01-26       Impact factor: 3.490

2.  An adenosine triphosphate-dependent, avidin-sensitive enzymatic cleavage of urea in yeast and green algae.

Authors:  R J Roon; B Levenberg
Journal:  J Biol Chem       Date:  1968-10-10       Impact factor: 5.157

3.  COG database update: focus on microbial diversity, model organisms, and widespread pathogens.

Authors:  Michael Y Galperin; Yuri I Wolf; Kira S Makarova; Roberto Vera Alvarez; David Landsman; Eugene V Koonin
Journal:  Nucleic Acids Res       Date:  2020-11-09       Impact factor: 16.971

4.  Ethanolamine utilization in Salmonella typhimurium.

Authors:  D M Roof; J R Roth
Journal:  J Bacteriol       Date:  1988-09       Impact factor: 3.490

5.  New yeast recombineering tools for bacteria.

Authors:  Robert M Q Shanks; Daniel E Kadouri; Daniel P MacEachran; George A O'Toole
Journal:  Plasmid       Date:  2009-05-27       Impact factor: 3.466

Review 6.  Nitrogen control in bacteria.

Authors:  M J Merrick; R A Edwards
Journal:  Microbiol Rev       Date:  1995-12

7.  The davDT operon of Pseudomonas putida, involved in lysine catabolism, is induced in response to the pathway intermediate delta-aminovaleric acid.

Authors:  Olga Revelles; Manuel Espinosa-Urgel; Soeren Molin; Juan L Ramos
Journal:  J Bacteriol       Date:  2004-06       Impact factor: 3.490

8.  Homologs of the Acinetobacter baumannii AceI transporter represent a new family of bacterial multidrug efflux systems.

Authors:  Karl A Hassan; Qi Liu; Peter J F Henderson; Ian T Paulsen
Journal:  mBio       Date:  2015-02-10       Impact factor: 7.867

9.  Transcriptional Regulation of Carnitine Catabolism in Pseudomonas aeruginosa by CdhR.

Authors:  Jamie A Meadows; Matthew J Wargo
Journal:  mSphere       Date:  2018-02-07       Impact factor: 4.389

10.  Omics-driven identification and elimination of valerolactam catabolism in Pseudomonas putida KT2440 for increased product titer.

Authors:  Mitchell G Thompson; Luis E Valencia; Jacquelyn M Blake-Hedges; Pablo Cruz-Morales; Alexandria E Velasquez; Allison N Pearson; Lauren N Sermeno; William A Sharpless; Veronica T Benites; Yan Chen; Edward E K Baidoo; Christopher J Petzold; Adam M Deutschbauer; Jay D Keasling
Journal:  Metab Eng Commun       Date:  2019-08-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.