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 : dcdp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (21 of 84: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b4382 b4269 b0493 b3588 b3003 b3011 b1241 b0351 b4384 b2744 b0871 b3617 b0160 b1982 b0675 b2361 b2291 b0261 b4388 b0112 b0114 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.520961 (mmol/gDw/h)
  Minimum Production Rate : 1.693518 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 20.767784
  EX_nh4_e : 10.706883
  EX_glc__D_e : 10.000000
  EX_pi_e : 3.889558
  EX_so4_e : 0.131188
  EX_k_e : 0.101688
  EX_fe2_e : 0.008367
  EX_mg2_e : 0.004519
  EX_ca2_e : 0.002712
  EX_cl_e : 0.002712
  EX_cu2_e : 0.000369
  EX_mn2_e : 0.000360
  EX_zn2_e : 0.000178
  EX_ni2_e : 0.000168
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_h2o_e : 49.822515
  EX_co2_e : 20.823726
  EX_h_e : 8.173829
  Auxiliary production reaction : 1.693518
  EX_acald_e : 1.275207
  DM_5drib_c : 0.000350
  DM_4crsol_c : 0.000116

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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