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 : ocdca_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (11 of 105: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: STM3646 STM1749 STM2463 STM2285 STM3526 STM4326 STM1511 STM1885 STM0517 STM2947 STM3709 STM3068 STM2141 STM1135 STM4183 STM0491 STM0368 STM0974 STM1448 STM3069 STM4484 STM2317 STM3179 STM1480 STM4126 STM2338 STM2466 STM1933 STM1124 STM3063 STM4467 STM2196 STM3240 STM3708 STM2971 STM1826   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.040006 (mmol/gDw/h)
  Minimum Production Rate : 0.002891 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 8.870676
  EX_glc__D_e : 5.000000
  EX_nh4_e : 0.533082
  EX_pi_e : 0.127687
  EX_k_e : 0.007105
  EX_so4_e : 0.004880
  EX_mg2_e : 0.000316
  EX_fe2_e : 0.000293
  EX_ca2_e : 0.000190
  EX_cl_e : 0.000190
  EX_cobalt2_e : 0.000126
  EX_cu2_e : 0.000126
  EX_mn2_e : 0.000126
  EX_mobd_e : 0.000126
  EX_zn2_e : 0.000126

Product: (mmol/gDw/h)
  EX_h2o_e : 11.603334
  EX_co2_e : 9.901074
  EX_dha_e : 4.806136
  EX_h_e : 0.528467
  EX_acald_e : 0.102065
  EX_kdo2lipid4_e : 0.046105
  Auxiliary production reaction : 0.002892
  EX_glyclt_e : 0.002000
  DM_hmfurn_c : 0.000018

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.

Last updated: 27-Sep-2023
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