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 : 12dgr140_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (31 of 105: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: STM3646 STM4108 STM2285 STM3526 STM0322 STM4326 STM1511 STM1884 STM2952 STM3529 STM1135 STM0369 STM1448 STM4184 STM4484 STM2317 STM3179 STM4569 STM1480 STM4126 STM0977 STM2196 STM3240 STM2971 STM1826   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.255816 (mmol/gDw/h)
  Minimum Production Rate : 0.038482 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 18.500000
  EX_glc__D_e : 5.000000
  EX_nh4_e : 2.819121
  EX_pi_e : 0.226863
  EX_k_e : 0.045433
  EX_so4_e : 0.031205
  EX_mg2_e : 0.002020
  EX_fe2_e : 0.001875
  EX_ca2_e : 0.001212
  EX_cl_e : 0.001212
  EX_cobalt2_e : 0.000808
  EX_cu2_e : 0.000808
  EX_mn2_e : 0.000808
  EX_mobd_e : 0.000808
  EX_zn2_e : 0.000808

Product: (mmol/gDw/h)
  EX_h2o_e : 26.001778
  EX_co2_e : 18.910897
  EX_h_e : 2.168707
  Auxiliary production reaction : 0.038482
  EX_glyald_e : 0.000177
  DM_hmfurn_c : 0.000114

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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