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 : nadhx__S_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (69 of 81: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 41
  Gene deletion: b2836 b1478 b4382 b1241 b4384 b3708 b3008 b0871 b2925 b2097 b2926 b0030 b2407 b0583 b2690 b2920 b2797 b3117 b1814 b4471 b3665 b0675 b0822 b2406 b0112 b3654 b3714 b3664 b0114 b0728 b0886 b2366 b0529 b2492 b0904 b2578 b1533 b3927 b4042 b3662 b1517   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.588278 (mmol/gDw/h)
  Minimum Production Rate : 0.238670 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 26.663119
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.024043
  EX_pi_e : 1.044796
  EX_so4_e : 0.148140
  EX_k_e : 0.114828
  EX_fe2_e : 0.009448
  EX_mg2_e : 0.005103
  EX_cl_e : 0.003062
  EX_ca2_e : 0.003062
  EX_cu2_e : 0.000417
  EX_mn2_e : 0.000407
  EX_zn2_e : 0.000201
  EX_ni2_e : 0.000190
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_h2o_e : 48.095100
  EX_co2_e : 26.618110
  EX_h_e : 8.006147
  EX_pyr_e : 1.407463
  Auxiliary production reaction : 0.238670
  DM_mththf_c : 0.000264
  DM_5drib_c : 0.000132
  DM_4crsol_c : 0.000131

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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