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 : uaccg_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (43 of 91: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 18
  Gene deletion: STM2421 STM2451 STM4004 STM2285 STM1750 STM1620 STM0974 STM3359 STM1566 STM2472 STM1211 STM2317 STM3179 STM4569 STM4301 STM3599 STM4325 STM0627   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.281558 (mmol/gDw/h)
  Minimum Production Rate : 0.126573 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 16.067013
  EX_glc__D_e : 5.000000
  EX_nh4_e : 3.482526
  EX_pi_e : 0.502839
  EX_k_e : 0.050005
  EX_so4_e : 0.034345
  EX_mg2_e : 0.002223
  EX_fe2_e : 0.002064
  EX_ca2_e : 0.001334
  EX_cl_e : 0.001334
  EX_cu2_e : 0.000889
  EX_mn2_e : 0.000889
  EX_mobd_e : 0.000889
  EX_zn2_e : 0.000889
  EX_cobalt2_e : 0.000889

Product: (mmol/gDw/h)
  EX_h2o_e : 25.254213
  EX_co2_e : 15.612594
  EX_h_e : 3.122352
  EX_succ_e : 0.234093
  Auxiliary production reaction : 0.126573
  EX_glyclt_e : 0.014078
  DM_hmfurn_c : 0.000126

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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