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 : mal__L_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (12 of 29: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 32
  Gene deletion: b3553 b1478 b3942 b1732 b1241 b0351 b3844 b1004 b3713 b1109 b0046 b3236 b1779 b2463 b2210 b1033 b3551 b3945 b1602 b0153 b4219 b1832 b1778 b0584 b0529 b1380 b1710 b2480 b1206 b0606 b2285 b1010   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.588805 (mmol/gDw/h)
  Minimum Production Rate : 0.207086 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 33.954491
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.359041
  EX_pi_e : 0.567965
  EX_so4_e : 0.148273
  EX_k_e : 0.114931
  EX_fe2_e : 0.009457
  EX_mg2_e : 0.005108
  EX_ca2_e : 0.003065
  EX_cl_e : 0.003065
  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 : 50.759717
  EX_co2_e : 35.003927
  EX_h_e : 5.824345
  Auxiliary production reaction : 0.207086
  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.

Last updated: 21-Sep-2023
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