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 : aicar_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (92 of 92: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: STM3747 STM2421 STM1749 STM2463 STM4275 STM4568 STM4570 STM0506 STM3553 STM0974 STM0152 STM0150 STM4569 STM2338 STM2466 STM3968 STM3885 STM3793 STM3802 STM2196 STM3240 STM2970 STM3243 STM3708 STM2971 STM1826   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.312208 (mmol/gDw/h)
  Minimum Production Rate : 0.484476 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 11.870010
  EX_nh4_e : 5.378476
  EX_glc__D_e : 5.000000
  EX_pi_e : 0.761349
  EX_k_e : 0.055448
  EX_so4_e : 0.038084
  EX_mg2_e : 0.002465
  EX_fe2_e : 0.002288
  EX_cl_e : 0.001479
  EX_ca2_e : 0.001479
  EX_cobalt2_e : 0.000986
  EX_cu2_e : 0.000986
  EX_mn2_e : 0.000986
  EX_mobd_e : 0.000986
  EX_zn2_e : 0.000986

Product: (mmol/gDw/h)
  EX_h2o_e : 23.782790
  EX_co2_e : 10.815469
  EX_h_e : 5.958293
  EX_ac_e : 1.373610
  Auxiliary production reaction : 0.484476
  DM_hmfurn_c : 0.000139

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.

Last updated: 27-Sep-2023
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