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 : pg180_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (60 of 75: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b0474 b2518 b3831 b1278 b3752 b4152 b2781 b3844 b1612 b1611 b4122 b1759 b4161 b4138 b4123 b0621 b0153 b4381 b2406 b0452 b3035 b2197 b3918 b1206 b3546   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.539971 (mmol/gDw/h)
  Minimum Production Rate : 0.285096 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 16.935657
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.597476
  EX_pi_e : 0.805955
  EX_so4_e : 0.135975
  EX_k_e : 0.105398
  EX_fe2_e : 0.008672
  EX_mg2_e : 0.004684
  EX_ca2_e : 0.002811
  EX_cl_e : 0.002811
  EX_cu2_e : 0.000383
  EX_mn2_e : 0.000373
  EX_zn2_e : 0.000184
  EX_ni2_e : 0.000174
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_h2o_e : 39.385673
  EX_co2_e : 22.078676
  EX_h_e : 6.568363
  EX_succ_e : 0.563077
  EX_ura_e : 0.382919
  Auxiliary production reaction : 0.285096
  DM_5drib_c : 0.000121
  DM_4crsol_c : 0.000120

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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