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 : lipa_cold_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (21 of 128: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 35
  Gene deletion: STM3646 STM1749 STM2463 STM2285 STM3526 STM0322 STM3091 STM1290 STM4326 STM1511 STM1884 STM2947 STM3709 STM1135 STM0491 STM0369 STM1448 STM1326 STM4062 STM4184 STM4484 STM2317 STM3179 STM1480 STM4126 STM2338 STM2466 STM1933 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 : 0.022002 (mmol/gDw/h)
  Minimum Production Rate : 0.025355 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 9.275137
  EX_glc__D_e : 5.000000
  EX_nh4_e : 0.293170
  EX_pi_e : 0.070222
  EX_k_e : 0.003907
  EX_so4_e : 0.002684
  EX_mg2_e : 0.000174
  EX_fe2_e : 0.000161
  EX_cl_e : 0.000104
  EX_ca2_e : 0.000104
  EX_cobalt2_e : 0.000069
  EX_cu2_e : 0.000069
  EX_mn2_e : 0.000069
  EX_mobd_e : 0.000069
  EX_zn2_e : 0.000069

Product: (mmol/gDw/h)
  EX_h2o_e : 11.178055
  EX_co2_e : 10.165827
  EX_dha_e : 4.893384
  EX_h_e : 0.899525
  EX_ac_e : 0.611583
  EX_acald_e : 0.094632
  Auxiliary production reaction : 0.025355

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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