MetNetComp Database [1] / Minimal gene deletions Minimal gene deletions for simulation-based growth-coupled production. You can also see maximal gene deletions.

Model : STM_v1_0 [2].
Target metabolite : pg140_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (36 of 119: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 23
  Gene deletion: STM3646 STM0620 STM2792 STM2285 STM3526 STM4326 STM2952 STM4109 STM3709 STM1135 STM1448 STM3062 STM4184 STM4484 STM0399 STM3179 STM1480 STM4126 STM2338 STM2466 STM1124 STM0733 STM3708   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.101943 (mmol/gDw/h)
  Minimum Production Rate : 0.004246 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 10.047651
  EX_glc__D_e : 5.000000
  EX_nh4_e : 1.123424
  EX_pi_e : 0.094651
  EX_k_e : 0.018105
  EX_so4_e : 0.012435
  EX_mg2_e : 0.000805
  EX_fe2_e : 0.000747
  EX_ca2_e : 0.000483
  EX_cl_e : 0.000483
  EX_cobalt2_e : 0.000322
  EX_cu2_e : 0.000322
  EX_mn2_e : 0.000322
  EX_mobd_e : 0.000322
  EX_zn2_e : 0.000322

Product: (mmol/gDw/h)
  EX_h2o_e : 12.893781
  EX_co2_e : 10.074899
  EX_h_e : 8.778544
  EX_ac_e : 7.918557
  Auxiliary production reaction : 0.004246
  EX_glyald_e : 0.000071
  DM_hmfurn_c : 0.000045

Visualization
  1. Download JSON file.
  2. Go to Escher site [3].

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: 27-Sep-2023
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