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 : camp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (95 of 100: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: STM3010 STM2927 STM1463 STM3747 STM0051 STM2421 STM0413 STM1749 STM2463 STM4275 STM0661 STM3709 STM0974 STM0152 STM4569 STM2338 STM2466 STM3968 STM3802 STM2196 STM3240 STM2970 STM3243 STM2971 STM1826 STM3334   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.347519 (mmol/gDw/h)
  Minimum Production Rate : 0.269636 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 12.111371
  EX_nh4_e : 5.177886
  EX_glc__D_e : 5.000000
  EX_pi_e : 0.577824
  EX_k_e : 0.061719
  EX_so4_e : 0.042391
  EX_mg2_e : 0.002744
  EX_fe2_e : 0.002547
  EX_ca2_e : 0.001646
  EX_cl_e : 0.001646
  EX_cu2_e : 0.001097
  EX_mn2_e : 0.001097
  EX_mobd_e : 0.001097
  EX_zn2_e : 0.001097
  EX_cobalt2_e : 0.001097

Product: (mmol/gDw/h)
  EX_h2o_e : 24.427788
  EX_co2_e : 11.342013
  EX_h_e : 5.284010
  EX_ac_e : 1.259332
  Auxiliary production reaction : 0.269636
  DM_hmfurn_c : 0.000155

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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