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 : methf_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (57 of 126: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: STM3010 STM2927 STM3747 STM2421 STM1749 STM2463 STM4275 STM0596 STM4568 STM4570 STM1511 STM3709 STM0974 STM0152 STM0150 STM3279 STM2338 STM2466 STM2332 STM0208 STM2196 STM3240 STM2970 STM3243 STM2971 STM1826   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.248965 (mmol/gDw/h)
  Minimum Production Rate : 0.386247 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 11.680031
  EX_nh4_e : 5.447364
  EX_glc__D_e : 5.000000
  EX_pi_e : 0.220788
  EX_k_e : 0.044216
  EX_so4_e : 0.030369
  EX_mg2_e : 0.001966
  EX_fe3_e : 0.001825
  EX_ca2_e : 0.001179
  EX_cl_e : 0.001179
  EX_cobalt2_e : 0.000786
  EX_cu2_e : 0.000786
  EX_mn2_e : 0.000786
  EX_mobd_e : 0.000786
  EX_zn2_e : 0.000786

Product: (mmol/gDw/h)
  EX_h2o_e : 25.041082
  EX_co2_e : 10.453494
  EX_h_e : 6.297894
  EX_ac_e : 1.095456
  Auxiliary production reaction : 0.386247
  DM_hmfurn_c : 0.000111

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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