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

  • Schmidt, Matthias1, 2, 3
  • Pearson, Allison N1, 2, 4
  • Incha, Matthew R1, 2, 4
  • Thompson, Mitchell G1, 5
  • Baidoo, Edward E K1, 2
  • Kakumanu, Ramu1, 2
  • Mukhopadhyay, Aindrila1, 2
  • Shih, Patrick M1, 2, 4, 5
  • Deutschbauer, Adam M4, 5
  • Blank, Lars M3
  • Keasling, Jay D1, 2, 6, 7, 8, 9, 10
  • 1 Joint BioEnergy Institute, Emeryville, California, USA.
  • 2 Biological Systems & Engineering Division, Lawrence Berkeley National Laboratorygrid.184769.5, Berkeley, California, USA.
  • 3 Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, Aachen, Germany. , (Germany)
  • 4 Department of Plant and Microbial Biology, University of California, Berkeleygrid.47840.3f, California, USA.
  • 5 Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratorygrid.184769.5, Berkeley, California, USA.
  • 6 Joint Program in Bioengineering, University of California, Berkeleygrid.47840.3f, California, USA.
  • 7 Institute for Quantitative Biosciences, University of California, Berkeleygrid.47840.3f, California, USA.
  • 8 Department of Chemical and Biomolecular Engineering, University of California, Berkeleygrid.47840.3f, California, USA.
  • 9 The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark. , (Denmark)
  • 10 Center for Synthetic Biochemistry, Institute for Synthetic Biology, Shenzhen Institutes for Advanced Technologies, Shenzhen, China. , (China)
Published Article
Applied and Environmental Microbiology
American Society for Microbiology
Publication Date
Mar 14, 2022
DOI: 10.1128/aem.02430-21
PMID: 35285712


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.

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