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Construction of a minimal nif gene cluster and computational modeling to optimize nitrogen fixation

By: Andrea Balassy2, Carlos Barba2, Ray Henson2, Cheryl Immethun2, Young Je Lee2, Thomas Mueller4, Yi Xiao2, Blake Actkinson1, David Ayeke1, Laura Beebe3, Charlotte Bourg1, Jessica O’Callaghan3, Michael Toomey1, Tae Seok Moon2, Fuzhong Zhang2, and Costas Maranas4, iGEM, Washington University in St. Louis1 Dept. of Energy, Environmental and Chemical Engineering, Washington University in St. Louis2 iGEM, Pennsylvania State University3 Dept. of Chemical Engineering, Pennsylvania State University4

                          

Background

Broader Context

  • Plants cannot fix their own nitrogen
  • Some cyanobacteria natively fix nitrogen
  • Those bacteria could help development of diazotrophic plants
  • Team will engineer synthetic diazotrophic cyanobacteria first

Nitrogen-Fixing E. coli

  • Grows faster than cyanobacteria
  • Easier to manipulate genetically
  • Useful to characterize nitrogen-fixing genes
  • Useful for engineering a diazotrophic cyanobacteria
Nitrogen Project overview and E. coli’s role

Figure 1: Nitrogen Project overview and E. coli’s role

Images courtesy of cfb.unh.edu, landcareresearch.com, geneticliteracyproject.org, edenbrothers.com

 

Objectives

  • Determine minimal set of genes needed for nitrogen fixation
  • Identify ideal conditions for nitrogen fixation

Acknowledgements

Acknowledgements Logos



Methods

Creating a Minimal nif Cluster
Choosing Genes Choosing RBSs
  • Examine gene function
  • Compare to homologies in E. coli genome
  • Review other minimal nif clusters in literature1,2,3
  • Examine relative translation
  • Create synthetic RBSs using Salis RBS calculator4
Further nif Cluster Characterization
  • Individual gene CRISPR/dCas9 knockdown plasmids
  • Hypothetical protein overexpression plasmids

 

Minimal nif cluster; the two plasmids are shown; strong RBSs in gold, weak in blue; genes colored by function

Figure 2: Minimal nif cluster; the two plasmids are shown; strong RBSs in gold, weak in blue; genes colored by function.

 

Computational Modeling

Genome-Scale Model Parts

  • Relationships between genes, proteins, and reactions
  • Reaction directionality
  • Scaled biomass equation

Flux Balance Analysis

  • Method for predicting fluxes through metabolic networks
  • Logarithmic growth phase
  • Pseudo steady-state
Overview of genome scale modeling

Figure 3: Overview of genome scale modeling

 

Constraint-based modeling used in FBA

Figure 4: Constraint-based modeling used in FBA5

 

Results

Changes in Pyruvate Metabolism

  • POR5 produces reduced flavodoxin, a nitrogenase electron donor
  • Pyruvate dehydrogenase (PDH) knockout means increased flux through POR5, and a buildup of pyruvate in the cells6
  • Recommend experimental PDH knockout, combined with POR5 overexpression
  • Flux variability analysis: higher flux ranges in pyruvate synthase (POR5) for N2 fixing cells (compared with WT)
Flux redistributions after PDH KO Images adapted from Voet, Biochemistry 4th ed

Figure 5: Flux redistributions after PDH KO Images adapted from Voet, Biochemistry 4th ed., and from mcb.berkely.edu

 

Results cont.

Media Supplementation

Scatter plot relating max ATP to max biomass; reasonable additions shown in green; cost prohibitive additions shown in blue

Figure 6: Scatter plot relating max ATP to max biomass; reasonable additions shown in green; cost prohibitive additions shown in blue.

 

  • Supplemented glucose with additional substrate equal to

  • 15 metabolites gave greater increases in max ATP production per increase in max biomass than glucose
  • Six disaccharides are reasonable additions; remaining 9 metabolites are cost prohibitive

In Silico Gene Knockouts

  • Knockouts tested for coupling between reduced flavodoxin and biomass production
  • No coupling found
  • Tested half of all potential double knockouts
  • 1112 nonessential genes used to identify synthetically lethal pairs
Table 1. Single Gene Knockouts Double Gene Knockouts
(50% of total)
No effect on biomass 1073 573070
Some effect on biomass 39 42383
Lethal 255 40

Table 1: Number of gene knockouts with and without effects on biomass

 

Minimal Cluster RBS Design

  • Relative RBS strengths calculated for each gene
  • RFP expression correlates well with the calculated translation initiation rates
Activity of RBSs used in minimized nif cluster

Figure 7: Activity of RBSs used in minimized nif cluster

 

Conclusions

  • Recommend experimental PDH knockout
  • Recommend overexpression of POR5
  • Media supplements identified to increase ATP levels

Future Directions

  • Transform completed minimal cluster into E. coli
  • Test for nitrogenase activity using acetylene reduction assay
  • Co-transform knockdown and overexpression plasmids with nif plasmids
  • Test for knockdown and overexpression effects on activity
  • Based on results, create optimized nif cluster with maximized expression and minimal number of genes
  • Extend analysis from simple metabolites to more extensive media alterations

References

  1. Smanski et al. Nature Biotechnology, 2014
  2. Temme et al. PNAS, 2012
  3. Wang et al. PLOS Genetics, 2013
  4. Salis et al. Nature Biotechnology, 2009
  5. Orth et al. Nature Biotechnology, 2010