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 : hxan_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (44 of 74: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b3831 b4069 b2744 b2297 b2458 b3617 b0160 b2883 b2498 b2361 b2291 b0261 b3654 b2868 b3714 b3664 b4064 b4464 b0114 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.649371 (mmol/gDw/h)
  Minimum Production Rate : 1.245229 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 24.458997
  EX_nh4_e : 11.994067
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.626387
  EX_so4_e : 0.163525
  EX_k_e : 0.126753
  EX_fe2_e : 0.010430
  EX_mg2_e : 0.005633
  EX_ca2_e : 0.003380
  EX_cl_e : 0.003380
  EX_cu2_e : 0.000460
  EX_mn2_e : 0.000449
  EX_zn2_e : 0.000221
  EX_ni2_e : 0.000210
  EX_cobalt2_e : 0.000016

Product: (mmol/gDw/h)
  EX_h2o_e : 51.086848
  EX_co2_e : 22.731696
  EX_h_e : 13.141827
  EX_ac_e : 2.194232
  Auxiliary production reaction : 1.245229
  DM_5drib_c : 0.000146
  DM_4crsol_c : 0.000145

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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