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 : dgdp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (10 of 89: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 18
  Gene deletion: STM2421 STM1749 STM2463 STM4275 STM3866 STM3709 STM0974 STM0152 STM4569 STM2338 STM2466 STM3802 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 : 0.015545 (mmol/gDw/h)
  Minimum Production Rate : 0.007990 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_glc__D_e : 5.000000
  EX_nh4_e : 0.211540
  EX_o2_e : 0.083916
  EX_co2_e : 0.061549
  EX_pi_e : 0.029785
  EX_k_e : 0.002761
  EX_so4_e : 0.001895
  EX_mg2_e : 0.000123
  EX_fe2_e : 0.000114
  EX_ca2_e : 0.000074
  EX_cl_e : 0.000074
  EX_cobalt2_e : 0.000049
  EX_cu2_e : 0.000049
  EX_mn2_e : 0.000049
  EX_mobd_e : 0.000049
  EX_zn2_e : 0.000049

Product: (mmol/gDw/h)
  EX_h_e : 9.927005
  EX_lac__D_e : 9.420900
  EX_h2o_e : 0.761394
  EX_pyr_e : 0.337475
  EX_etoh_e : 0.047659
  Auxiliary production reaction : 0.008001
  EX_ac_e : 0.004611
  EX_thym_e : 0.000116

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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