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 : 1odec11eg3p_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (103 of 133: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: STM3646 STM1463 STM1749 STM2463 STM2285 STM3526 STM4567 STM4326 STM1511 STM2952 STM1299 STM0517 STM2947 STM3709 STM1135 STM0141 STM4183 STM0369 STM1448 STM1326 STM4062 STM4484 STM2317 STM3179 STM1480 STM4126 STM4578 STM2338 STM2466 STM1124 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 : 0.271132 (mmol/gDw/h)
  Minimum Production Rate : 0.012878 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 17.298279
  EX_glc__D_e : 5.000000
  EX_nh4_e : 2.987914
  EX_pi_e : 0.253324
  EX_k_e : 0.048153
  EX_so4_e : 0.033073
  EX_mg2_e : 0.002141
  EX_fe3_e : 0.001987
  EX_cl_e : 0.001284
  EX_ca2_e : 0.001284
  EX_cobalt2_e : 0.000856
  EX_cu2_e : 0.000856
  EX_mn2_e : 0.000856
  EX_mobd_e : 0.000856
  EX_zn2_e : 0.000856

Product: (mmol/gDw/h)
  EX_h2o_e : 25.166837
  EX_co2_e : 17.667420
  EX_h_e : 2.394969
  EX_acald_e : 0.691721
  EX_ac_e : 0.080434
  EX_glyclt_e : 0.013557
  Auxiliary production reaction : 0.012878
  EX_hxa_e : 0.000435
  DM_hmfurn_c : 0.000121

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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