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 : nadp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (63 of 74: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 42
  Gene deletion: b4467 b3399 b4269 b0493 b3588 b3003 b3011 b1241 b0351 b2502 b2744 b0871 b2779 b3617 b3844 b1238 b1004 b3713 b1109 b0046 b3236 b1982 b0675 b2361 b0261 b3945 b1602 b0507 b4381 b3915 b1727 b2975 b0114 b3603 b0529 b2492 b0904 b1380 b2660 b0606 b2285 b1010   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.352190 (mmol/gDw/h)
  Minimum Production Rate : 0.402115 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 33.710846
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.642356
  EX_pi_e : 1.546070
  EX_so4_e : 0.088688
  EX_k_e : 0.068745
  EX_fe3_e : 0.005657
  EX_mg2_e : 0.003055
  EX_ca2_e : 0.001833
  EX_cl_e : 0.001833
  EX_cu2_e : 0.000250
  EX_mn2_e : 0.000243
  EX_zn2_e : 0.000120
  EX_ni2_e : 0.000114

Product: (mmol/gDw/h)
  EX_h2o_e : 53.107856
  EX_co2_e : 33.628335
  EX_h_e : 5.874107
  EX_etoh_e : 0.712402
  Auxiliary production reaction : 0.402115
  EX_his__L_e : 0.340654
  EX_ade_e : 0.000394
  DM_5drib_c : 0.000236
  DM_4crsol_c : 0.000079

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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