MetNetComp Database [1] / Core Genes A set of core genes for simulation-based growth-coupled production. You can also see minimal gene deletions.

Model : iMM904 [2].
Target metabolite : dd2coa_x
Core genes for growth-coupled production (at least stoichioemetrically feasible)
  #Remaining genes : 252
  Remaining genes: YGL184C YCR034W YMR307W YMR306W YMR169C YDR284C YBR029C YDR487C YBR249C YGL055W YDR454C YJR016C YDR354W YER090W YKL211C YLR134W YHR018C YOR236W YOL058W YKL216W YCR053W YDR127W YDR158W YGL154C YMR009W YBR115C YEL038W YJL167W YPR145W YER073W YOR348C YPL028W YIL160C YNR016C YJL130C YER052C YLR027C YER069W YMR062C YMR108W YPR128C YCL009C YER055C YGR199W YGL205W YPR183W YPL036W YKL182W YPL231W YNR043W YLR355C YBR153W YOL066C YLR304C YBL099W YBR039W YKL016C YJR121W YOL140W YDL004W YPL078C YLR295C YLR153C YKR009C YDR298C YDR377W YDL181W Q0085 Q0080 Q0130 YPL271W YMR323W YBL030C YDR226W YNL280C YOL052C YHR042W YJR105W YGL012W YGL001C YLR100W YKL188C YPL147W YGR060W YML022W YKL001C YLR359W YNL220W YDR256C YDL052C YEL039C YER043C YGR037C YLR028C YOR128C YPR060C YFL018C YKL060C YGL148W YDR111C YCR005C YJR103W YHR051W YMR256C YDL067C YGL187C YLR038C YGL191W Q0275 YMR217W YNL052W Q0045 YLR395C Q0250 YBL045C YGR204W YDR529C YEL024W YGR256W YPR191W YGR183C YJL166W Q0105 YFR033C YOR065W YGR012W YLR438W YOR130C YDL022W YML106W YIL145C YPR167C YGR209C YNL241C YBR218C YBL033C YHL012W YNL071W YGR193C YPR192W YBR221C YLR081W YDR234W YER178W YJR009C YGR157W YMR205C YDR408C YGR240C YBL011W YIL074C YCR012W YIL094C YCL030C YDL021W YFR025C YKL127W YLR058C YHR137W YKR058W YLR258W YPR035W YLR450W YML126C YER023W YJR139C YPR113W YJR077C YHR025W YAL062W YIL116W YCL040W YMR300C YJL198W YER053C YLR174W YBR248C YOR202W YFL045C YOR074C YJR148W YMR220W YDR050C YDR531W YMR261C YMR020W YBR011C YDR074W YBR126C YHR216W YNL316C YOR245C YPL117C YGL026C YGL234W YDR007W YCL018W YGL009C YAR015W YOR108W YGR061C YIL020C YKL024C YKL181W YNL169C YER026C YHR007C YGR208W YHR072W YNL268W YAL038W YOL143C YBR256C YEL017C_A YCR024C_A YJL121C YOR095C YNR050C YML081C_A YIR034C YJR010W YDL055C YER003C YHR001W_A YCR073W_A YDL078C YDR502C YER091C YML082W YGR125W YLR146C YMR208W YJR073C YGR175C YHR190W YHR046C YJL153C YBR176W YFR030W YLR017W YPL023C YDR453C YMR145C YML120C YLR109W YKL218C YKL067W YPR138C YPR074C YJL088W YOR184W YEL021W   (List of alternative genes)
  Computed by: AddGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.033205 (mmol/gDw/h)
  Minimum Production Rate : 0.031764 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_nh4_e : 3.174203
  EX_glc__D_e : 2.657920
  EX_o2_e : 2.000000
  EX_pi_e : 0.169188
  EX_so4_e : 0.034330

Product: (mmol/gDw/h)
  EX_h2o_e : 6.811141
  EX_h_e : 3.937539
  EX_ala__L_e : 2.531565
  EX_co2_e : 2.456882
  EX_2hb_e : 0.426513
  EX_2mbald_e : 0.152573
  EX_fum_e : 0.140725
  EX_gly_e : 0.063528
  EX_mal__L_e : 0.035131
  EX_pap_e : 0.033666
  Auxiliary production reaction : 0.031764
  EX_succ_e : 0.002607
  EX_lys__L_e : 0.001302

Visualization
  1. Download JSON file.
  2. Go to Escher site [3].
  3. Select "Data > Load reaction data" and apply the downloaded file.

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.

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Last updated: 27-Sep-2023
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