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 : ocdca_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (74 of 75: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: b2242 b3553 b3831 b2744 b3614 b0910 b3752 b2781 b1004 b3713 b1109 b0046 b1612 b1611 b4122 b1759 b2210 b1033 b4374 b2361 b2291 b1415 b4138 b4123 b0621 b2406 b0452 b2492 b0904 b2197 b3028 b3918 b4042 b1206 b0221 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.508783 (mmol/gDw/h)
  Minimum Production Rate : 0.268711 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 993.265496
  EX_o2_e : 278.283535
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.216423
  EX_pi_e : 0.490776
  EX_so4_e : 0.128122
  EX_k_e : 0.099311
  EX_mg2_e : 0.004414
  EX_ca2_e : 0.002648
  EX_cl_e : 0.002648
  EX_cu2_e : 0.000361
  EX_mn2_e : 0.000352
  EX_zn2_e : 0.000173
  EX_ni2_e : 0.000164
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_fe3_e : 999.991828
  EX_h2o_e : 546.480587
  EX_co2_e : 30.714541
  EX_succ_e : 0.530555
  EX_ura_e : 0.360803
  Auxiliary production reaction : 0.268711
  DM_5drib_c : 0.000114
  DM_4crsol_c : 0.000113

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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