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 : dadp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (88 of 95: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: b3553 b3399 b1241 b0351 b4384 b2744 b0871 b0030 b1004 b3713 b1109 b0046 b3236 b1982 b1033 b1623 b2799 b3945 b1602 b4381 b3915 b0452 b1727 b0755 b3612 b0529 b2492 b0904 b3927 b1380 b2660 b1518 b0606 b2285 b1007 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.501904 (mmol/gDw/h)
  Minimum Production Rate : 0.023046 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 995.234177
  EX_o2_e : 288.106887
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.589634
  EX_pi_e : 0.530232
  EX_so4_e : 0.126389
  EX_k_e : 0.097968
  EX_mg2_e : 0.004354
  EX_cl_e : 0.002612
  EX_ca2_e : 0.002612
  EX_cu2_e : 0.000356
  EX_mn2_e : 0.000347
  EX_zn2_e : 0.000171
  EX_ni2_e : 0.000162
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_fe3_e : 999.991939
  EX_h2o_e : 552.770910
  EX_co2_e : 39.100207
  Auxiliary production reaction : 0.023046
  EX_hxan_e : 0.013471
  DM_mththf_c : 0.000225
  DM_5drib_c : 0.000113
  DM_4crsol_c : 0.000112

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.

Last updated: 21-Sep-2023
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