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

Model : iML1515 [2].
Target metabolite : sbt6p_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (49 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 37
  Gene deletion: b4467 b1478 b4382 b1241 b0351 b4384 b2930 b4232 b3697 b3925 b0871 b2926 b0030 b2407 b3844 b1004 b3713 b1109 b0046 b3236 b2690 b0937 b1982 b0411 b2799 b3945 b1602 b2913 b0529 b2492 b0904 b3927 b1380 b1517 b0606 b2285 b1011   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.442616 (mmol/gDw/h)
  Minimum Production Rate : 0.051641 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 33.937417
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.781702
  EX_pi_e : 0.478591
  EX_so4_e : 0.111460
  EX_k_e : 0.086396
  EX_fe2_e : 0.007109
  EX_mg2_e : 0.003840
  EX_ca2_e : 0.002304
  EX_cl_e : 0.002304
  EX_cu2_e : 0.000314
  EX_mn2_e : 0.000306
  EX_zn2_e : 0.000151
  EX_ni2_e : 0.000143
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 44.393854
  EX_co2_e : 32.702616
  EX_h_e : 8.477275
  EX_glyclt_e : 4.408855
  Auxiliary production reaction : 0.051641
  EX_ade_e : 0.000298
  DM_mththf_c : 0.000198
  DM_5drib_c : 0.000100
  DM_4crsol_c : 0.000099

Visualization
  1. Download JSON file.
  2. Go to Escher site [3].
  3. Select "Data > Load reaction data" and apply the downloaded file.

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: 21-Sep-2023
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