MetNetComp Database [1] / Minimal gene deletions Minimal gene deletions for simulation-based growth-coupled production. You can also see maximal gene deletions.

Model : iML1515 [2].
Target metabolite : ps161_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (63 of 76: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4382 b0474 b2518 b4384 b2744 b4152 b2781 b1612 b1611 b4122 b1759 b4374 b4161 b0675 b4138 b4123 b0621 b2406 b2943 b2197 b2835 b3918 b1912 b0494 b1206   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.570486 (mmol/gDw/h)
  Minimum Production Rate : 0.301299 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 16.906969
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.271612
  EX_pi_e : 0.851593
  EX_so4_e : 0.143660
  EX_k_e : 0.111355
  EX_fe2_e : 0.009163
  EX_mg2_e : 0.004949
  EX_ca2_e : 0.002969
  EX_cl_e : 0.002969
  EX_cu2_e : 0.000404
  EX_mn2_e : 0.000394
  EX_zn2_e : 0.000195
  EX_ni2_e : 0.000184
  EX_cobalt2_e : 0.000014

Product: (mmol/gDw/h)
  EX_h2o_e : 40.627429
  EX_co2_e : 21.136998
  EX_h_e : 7.240762
  EX_succ_e : 0.594898
  EX_ura_e : 0.404559
  Auxiliary production reaction : 0.301299
  DM_5drib_c : 0.000128
  DM_4crsol_c : 0.000127

Visualization
  1. Download JSON file.
  2. Go to Escher site [3].
  3. Select "Data > Load reaction data" and apply the downloaded file.

References
[1] Tamura, T. MetNetComp: Database for minimal and maximal gene deletion strategies for growth-coupled production of genome-scale metabolic networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press.
[2] Norsigian, C. J., Pusarla, N., McConn, J. L., Yurkovich, J. T., Dräger, A., Palsson, B. O., & King, Z. (2020). BiGG Models 2020: multi-strain genome-scale models and expansion across the phylogenetic tree. Nucleic acids research, 48(D1), D402-D406.
[3] King, Z. A., Dräger, A., Ebrahim, A., Sonnenschein, N., Lewis, N. E., & Palsson, B. O. (2015). Escher: a web application for building, sharing, and embedding data-rich visualizations of biological pathways. PLoS computational biology, 11(8), e1004321.

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Last updated: 21-Sep-2023
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