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 : nmn_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (74 of 79: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 34
  Gene deletion: b3831 b1278 b3614 b0910 b3752 b4152 b2779 b2925 b2097 b2781 b3617 b1612 b1611 b4122 b2690 b1759 b3962 b4267 b1415 b0411 b2799 b3945 b4388 b4138 b4123 b0621 b4381 b3821 b1380 b3918 b0508 b4266 b1206 b3924   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.428693 (mmol/gDw/h)
  Minimum Production Rate : 0.226412 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 30.490675
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.237859
  EX_pi_e : 0.639932
  EX_so4_e : 0.107953
  EX_k_e : 0.083678
  EX_fe2_e : 0.006885
  EX_mg2_e : 0.003719
  EX_ca2_e : 0.002231
  EX_cl_e : 0.002231
  EX_cu2_e : 0.000304
  EX_mn2_e : 0.000296
  EX_zn2_e : 0.000146
  EX_ni2_e : 0.000138
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 44.919153
  EX_co2_e : 30.952254
  EX_h_e : 8.645654
  EX_ac_e : 3.430690
  EX_succ_e : 0.447037
  Auxiliary production reaction : 0.226412
  EX_ura_e : 0.077595
  EX_dxylnt_e : 0.000287
  DM_5drib_c : 0.000096
  DM_4crsol_c : 0.000096

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.

Last updated: 21-Sep-2023
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