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 : udp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (67 of 76: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b0474 b2518 b3831 b3614 b0910 b3752 b4152 b2925 b2097 b2781 b1612 b1611 b4122 b1779 b2690 b1759 b0411 b3945 b4138 b4123 b0621 b4381 b0114 b3918 b1206 b2285 b3893 b1474   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.406533 (mmol/gDw/h)
  Minimum Production Rate : 0.214708 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 991.760820
  EX_o2_e : 282.592929
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.967102
  EX_pi_e : 0.821560
  EX_so4_e : 0.102373
  EX_k_e : 0.079352
  EX_mg2_e : 0.003527
  EX_ca2_e : 0.002116
  EX_cl_e : 0.002116
  EX_cu2_e : 0.000288
  EX_mn2_e : 0.000281
  EX_zn2_e : 0.000139
  EX_ni2_e : 0.000131
  EX_cobalt2_e : 0.000010

Product: (mmol/gDw/h)
  EX_fe3_e : 999.993471
  EX_h2o_e : 546.058861
  EX_co2_e : 32.817210
  EX_ac_e : 3.286535
  EX_succ_e : 0.423929
  Auxiliary production reaction : 0.214708
  EX_ura_e : 0.073584
  EX_for_e : 0.000997
  DM_5drib_c : 0.000091
  DM_4crsol_c : 0.000091

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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