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 : dtmp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (17 of 70: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 20
  Gene deletion: b2744 b3614 b0910 b4152 b2781 b1612 b1611 b4122 b1759 b4374 b0675 b4138 b4123 b0621 b4381 b2406 b0452 b3918 b4042 b1206   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.724399 (mmol/gDw/h)
  Minimum Production Rate : 0.382471 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 990.794086
  EX_o2_e : 272.112485
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.850864
  EX_pi_e : 1.081231
  EX_so4_e : 0.182418
  EX_k_e : 0.141398
  EX_mg2_e : 0.006284
  EX_ca2_e : 0.003770
  EX_cl_e : 0.003770
  EX_cu2_e : 0.000514
  EX_mn2_e : 0.000501
  EX_zn2_e : 0.000247
  EX_ni2_e : 0.000234
  EX_cobalt2_e : 0.000018

Product: (mmol/gDw/h)
  EX_fe3_e : 999.988365
  EX_h2o_e : 546.107929
  EX_co2_e : 22.895489
  EX_succ_e : 0.755398
  Auxiliary production reaction : 0.382471
  EX_ura_e : 0.131235
  DM_5drib_c : 0.000163
  DM_4crsol_c : 0.000162

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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