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 : prlp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (37 of 71: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b4069 b2502 b4384 b2744 b2297 b2458 b3617 b0030 b2883 b1982 b1623 b4374 b2361 b2291 b0261 b0411 b0112 b0114 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.515800 (mmol/gDw/h)
  Minimum Production Rate : 0.988516 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 21.884569
  EX_nh4_e : 10.513172
  EX_glc__D_e : 10.000000
  EX_pi_e : 2.474576
  EX_so4_e : 0.129889
  EX_k_e : 0.100680
  EX_fe2_e : 0.008284
  EX_mg2_e : 0.004475
  EX_cl_e : 0.002685
  EX_ca2_e : 0.002685
  EX_cu2_e : 0.000366
  EX_mn2_e : 0.000356
  EX_zn2_e : 0.000176
  EX_ni2_e : 0.000167
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_h2o_e : 46.985670
  EX_co2_e : 20.514121
  EX_h_e : 11.424845
  EX_ac_e : 1.742893
  Auxiliary production reaction : 0.988516
  DM_5drib_c : 0.000346
  DM_4crsol_c : 0.000115

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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