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 : ichor_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (51 of 71: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 34
  Gene deletion: STM1203 STM1832 STM1749 STM2463 STM3680 STM2285 STM0169 STM0861 STM1884 STM1465 STM0840 STM0842 STM3068 STM2141 STM1620 STM1647 STM2167 STM0974 STM1566 STM2472 STM1076 STM1211 STM2317 STM0935 STM3179 STM1480 STM1378 STM1888 STM4301 STM3599 STM4325 STM0627 STM0054 STM3353   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.081216 (mmol/gDw/h)
  Minimum Production Rate : 0.211983 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 18.500000
  EX_glc__D_e : 5.000000
  EX_so4_e : 1.363554
  EX_nh4_e : 1.312614
  EX_h_e : 0.693510
  EX_pi_e : 0.072023
  EX_k_e : 0.014424
  EX_mg2_e : 0.000641
  EX_fe2_e : 0.000595
  EX_ca2_e : 0.000385
  EX_cl_e : 0.000385
  EX_cobalt2_e : 0.000256
  EX_cu2_e : 0.000256
  EX_mn2_e : 0.000256
  EX_mobd_e : 0.000256
  EX_zn2_e : 0.000256

Product: (mmol/gDw/h)
  EX_h2o_e : 26.479439
  EX_co2_e : 21.268702
  EX_h2s_e : 1.353647
  EX_4abz_e : 0.417606
  Auxiliary production reaction : 0.211983
  EX_etoh_e : 0.207200
  EX_succ_e : 0.031015
  EX_glyclt_e : 0.004061
  DM_hmfurn_c : 0.000036

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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