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 : fpram_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (14 of 51: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b4382 b1241 b0351 b4069 b4384 b2744 b2297 b2458 b2407 b3616 b3589 b1623 b3665 b0261 b2406 b0112 b3654 b3714 b3664 b0114 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.486934 (mmol/gDw/h)
  Minimum Production Rate : 1.867481 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 20.743925
  EX_nh4_e : 10.861285
  EX_glc__D_e : 10.000000
  EX_pi_e : 2.337180
  EX_so4_e : 0.122620
  EX_k_e : 0.095046
  EX_fe2_e : 0.007821
  EX_mg2_e : 0.004224
  EX_ca2_e : 0.002534
  EX_cl_e : 0.002534
  EX_cu2_e : 0.000345
  EX_mn2_e : 0.000336
  EX_zn2_e : 0.000166
  EX_ni2_e : 0.000157
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 43.979029
  EX_co2_e : 19.915571
  EX_h_e : 10.788198
  EX_ac_e : 2.579095
  Auxiliary production reaction : 1.867481
  DM_5drib_c : 0.000110
  DM_4crsol_c : 0.000109

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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