Other Organisms

Supplementary Table 1: Available predictive genome-scale metabolic network reconstructions

Adam M. Feist, Markus J. Herrgard, Ines Thiele, Jennie L. Reed, Bernhard Ø. Palsson "Reconstruction of Biochemical Networks in Microbial Organisms", Nat. Rev. Microbiol. 2009 Feb;7(2):129-43.

Supplementary Table 2 - Common issues encountered during metabolic network reconstruction

This list includes genome-scale metabolic network reconstructions that have been converted into predictive genome-scale models and whose predictive power has been validated against experimental data.

This table is managed and updated by Jonathan Monk (jmonk@ucsd.edu). Please send me an email with any missing information.

[Bacteria] [Archaea] [Eukaryotes]

Organism Strain Genes Status Version Genes Metabo-
lites
Reactions Compartments Reference PMID DL Website Date
BACTERIA                          
Acinetobacter
baumannii
AYE
3760
F
AbyMBEL891
650
778
891
2 (c,e)
2/10
Acinetobacter
baylyi
ADP1
3287
F
iAbaylyiV4
774
701
875
3 (c,e,p)
10/08
Bacillus megaterium
WSH002
5273
F
iMZ1055
1055
993
1112
2 (c,e)
4/13
Bacillus subtilis
 
4114
F
model_v3
844
988
1020
2 (c,e)
9/07
Bacillus subtilis
168
4114
F
iBsu1103
1103
1138
1437
2 (c,e)
6/09
Buchnera aphidicola
APS
574
F
iGT196
196
240
263
2 (c,e)
2/09
Chromohalobacter
salexigens
DSM
3043
3352
F
iOA584
584
1411
1386
2 (c,e)
 
1/11
Clostridium
acetobutylicum
ATCC
824
3848
F
 
474
422
552
2 (c,e)
 
 
6/08
Clostridium
acetobutylicum
ATCC
824
3848
F
 
432
479
502
2 (c,e)
 
 
9/08
Clostridium beijerinckii
NCIMB 8052
5243
F
iCB925
925
881
938
2(c,e)
8/11
Clostridium
thermocellum
ATCC
27405
3307
F
iSR432
432
525
577
2 (c,e)
 
3/10
Clostridium
ljungdahlii
F
iHN637
637
698
785
2 (c,e)
 
11/13
Corynebacterium
glutamicum
ATCC
13032
3002
F
 
 
411
446
2 (c,e)
2/09
Corynebacterium
glutamicum
ATCC
13032
3002
F
 
227
423
502
2 (c,e)
 
 
8/09
Dehalococcoides
ethenogenes
 
2061
F
iAI549
549
549
518
2 (c,e)
 
8/10
Escherichia coli
K-12
MG1655
4405
F
iJE660
660
438
627
2 (c,e)
 
 
5/00
Escherichia coli
K-12
MG1655
4405
F
iJR904
904
625
931
2 (c,e)
8/03
Escherichia coli
K-12
MG1655
4405
F
iAF1260
1260
1039
2077
3 (c,e,p)
6/07
Escherichia coli

K-12 
MG1655

4405 F iJO1366 1366 1136 2251 3 (c, e, p) Orth et al. 21988831 SBML UCSD 10/11
Escherichia coli
W (ATCC
9637)
4764
F
iCA1273
1273
1111
2477
3 (c,e,p)
1/11
Francisella tularensis
LVS
1802
F
iRS605
683
586
605
2 (c,e)
 
 
8/10
Geobacter metallireducens
 
3532
F
 
747
769
697
2 (c,e)
 
1/09
Geobacter sulfurreducens
 
3530
F
 
588
541
523
2 (c,e)
 
2/06
Haemophilus influenzae
Rd
1775
F
iJE296
296
343
488
2 (c,e)
 
 
6/99
Haemophilus influenzae
Rd
1775
F
iCS400
400
451
461
2 (c,e)
4/00
Helicobacter pylori
26695
1632
F
iCS291
291
340
388
2 (c,e)
8/02
Helicobacter pylori
26695
1632
F
iIT341
341
485
476
2 (c,e)
8/05
Ketogulonicigenium vulgare
WSH-001
3054
F
iWZ663
663
650
831
2 (c,e)
9/12
Klebsiella pneumoniae
MGH
78578
5186
F
iYL1228
1228
1658
1970
3 (c,e,p)
4/11
Lactobacillus plantarum
WCFS1
3009
F
 
721
531
643
2 (c,e)
 
12/06
Lactococcus lactis
ssp.
lactisIL1403
2310
F
 
358
422
621
2 (c,e)
6/05
Lactococcus lactis subsp. cremoris
MG1363
2563
F
 
518
650
754
2 (c,e)
10/13
Mannheimia succiniciproducens
MBEL55E
2384
F
 
335
332
373
2 (c,e)
10/04
Mannheimia succiniciproducens
MBEL55E
2384
F
 
425
519
686
2 (c,e)
7/07
Mycobacterium tuberculosis
H37Rv
4402
F
iNJ661
661
828
939
2 (c,e)
6/07
Mycobacterium tuberculosis
H37Rv
4402
F
GSMN-TB
726
739
849
2 (c,e)
8/07
Mycobacterium tuberculosis
H37Rv
4402
F
iNJ661m
663
838
1049
2 (c,e)
11/10
Mycoplasma genitalium
G-37
521
F
iPS189
189
274
262
2 (c,e)
2/09
Neisseria meningitidis
serogroup B
2226
F
 
555
471
496
2 (c,e)
 
8/07
Porphyromonas gingivalis
W83
2015
F
iVM679
 
564
679
2 (c,e)
1/09
Pseudomonas aeruginosa
PA01
5640
F
iMO1056
1056
760
883
2 (c,e)
 
 
1/08
Pseudomonas putida
KT2440
5350
F
iNJ746
746
911
950
3 (c,p,e)
 
8/08
Pseudomonas putida
KT2440
5350
F
iJP815
815
886
877
3 (c,p,e)
 
10/08
Pseudomonas putida
KT2440
5350
F
PpuMBEL1071
900
1044
1071
2 (c,e)
7/10
Rhizobium etli
CFN42
3168
F
iOR363
363
371
387
2 (c,e)
 
10/07
Ralstonia eutropha
H16
6166
F
RehMBEL1391
1256
1391
1171
2 (c,e)
 
10/07
Rhodoferax ferrireducens
 
4770
F
 
744
790
762
2 (c,e)
 
9/09
Salmonella typhimurium
LT2
4489
F
iRR1083
1083
774
1087
2 (c,e)
 
 
4/09
Salmonella typhimurium
LT2
4489
F
iMA945
945
1036
1964
2 (c,e)
8/09
Salmonella typhimurium
LT2
4489
F
STM_v1.0
1270
1119
2201
3 (c,e,p)
 
1/11
Shewanella oneidensis
MR-1
5066
F
iSO783
783
634
774
2 (c,e)
 
6/10
Staphylococcus aureus
N315
2588
F
iSB619
619
571
641
2 (c,e)
3/05
Staphylococcus aureus
N315
2588
F
iMH551
551
604
712
2 (c,e)
12/05
Staphylococcus aureus
N315
2588
F
 
546
1431
1493
2 (c,e)
 
6/09
Streptococcus thermophilus
LMG18311
1889
F
 
429
 
522
2 (c,e)
 
6/09
Streptomyces coelicolor
A3(2)
7825
F
 
700
500
700
2 (c,e)
6/05
Streptomyces coelicolor
A3(2)
7825
F
 
789
759
1015
2 (c,e)
 
3/10
Synechocystis sp. PCC6803
PCC6803
3221
F
 
633
704
831
2 (c,e)
 
10/08
Synechocystis sp. PCC6803
PCC6803
3221
F
iSyn669
669
790
882
2 (c,e)
 
11/10
Synechocystis sp. PCC6803
PCC6803
3221
F
iJN678
678
795
863
3(c,p,e)
2/12
Thermotoga maritima
MSB8
1917
F
 
478
503
562
2 (c,e)
9/09
Vibrio vulnificus
CMCP6
2896
F
VvuMBEL943
673
792
943
2 (c,e)
1/11
Yersinia pestis
91001
4037
F
iAN818m
818
825
1020
2 (c,e)
 
1/09
Yersinia pestis
CO92
4306
F
iPC815
815
963
1678
3 (c,e,p)
 
10/11
Zymomonas mobilis
ZM4
1808
F
ZmobMBEL601
347
579
601
2 (c,e)
pdfpdf
 
11/10
Zymomonas mobilis
ZM4
1808
F
iZM363
363
704
747
2 (c,e)
 
3/11
ARCHAEA                          
Halobacterium salinarum R-1 2867 F   490 557 711 2 (c,e) Gonzalez et al. 18213408 xls Mol Biosys 2/08
Methanosarcina barkeri Fusaro 5072 F iAF692 692 558 619 2 (c,e) Feist et al. 16738551 SBML UCSD 1/06
Methanosarcina barkeri Fusaro 5072 F iMG746 746 719 741 2 (c,e) Gonnerman et al. 23420771 zip ISB 3/13
Methanosarcina acetivorans C2A 4540 F iVS941 941 708 705 2 (c,e) Satish Kumar et al. 21324125 SBML Penn State 2/11
Methanosarcina acetivorans C2A 4540 F iMB745 745 715 756 2 (c,e) Benedict et al. 22139506   ISB 12/11
Natronomonas pharaonis DSM 2160 2892 F   654 597 683 2 (c,e) Gonzalez et al. 20543878 SBML   6/10
EUKARYOTES                          
Arabidopsis thaliana   27,379 F AraGEM 1419 1748 1567 6 (c,e,m,
s,v,x)
de Oliveira Dal'Molin et al. 20044452 SBML UQ 2/10
Aspergillus nidulans   9451 F iHD666 666 732 794 4 (c,e,m,o) David et al. 18405346 SBML Chalmers 4/08
Aspergillus niger CBS 513.88 14,165 F iMA871 871 1045 1190 3 (c,e,m) Andersen et al. 18364712 SBML Chalmers 3/08
Aspergillus oryzae RIB40 12,074 F   1314 1073 1053 3 (c,e,m,x) Vongsangnak et al. 18500999 SBML Chalmers 5/08
Aspergillus terreus NIH2624 10,406 F iJL1454 1454 1155 1451 3 (c,e,m) Jie Liu et al 23624532 Molecular BioSystems 4/13
Candida glabrata   CBS138 F iNX804 804 1025 1287 6 (c,e,m,x,g,v) Nan Xu et al. 23172360   Molecular BioSystems 11/12
Cryptosporidium hominis   3884 F iNV213 213   540 2 (c,e) Vanee et al. 20491062     5/10
Chlamydomonas reinhardtii   16,709 F iRC1080 1080 1068 2190 10 (c, e, h, s, f, x, g, m, n, u) Chang et al. 21811229 SBML UCSD 8/11
Drosophila Melongaster   15,431 F fly_model Feala et al. 19740440 XML (error) UCSD 9/09
Homo sapiens   28,783 F Recon 1 1,496 2,766 3,311 8 (c,e,m,x
,n,r,v,g)
Duarte et al. 17267599 SBML PNAS 1/07
Leishmania major Friedlin 8370 F iAC560 560 1,101 1,112 8 (a,f,y,c,
e,m,r,n)
Chavali et al. 18364711 SBML Mol Biosys 3/08
Mus musculus   28,287 F   473 872 1,220 3 (c,e,m) Sheikh et al. 15903248     1/05
Mus musculus   28,287 F   1399 2179 2037 3 (c,e,m) Quek and Nielsen 19425150 SBML JSBI 12/08
Mus musculus   28,287 F   724 1287 1494 3 (c,e,m) Selvarasu et al. 20024077 xls RSC 1/10
Mus musculus   28,287 F iMM1415 1415 2774 3726 8 (c,e,g,l,
m,n,r,x)
Sigurdsson et al. 20959003     10/10
Pichia pastoris DSMZ
70382
5450 F PpaMBEL1254 540 1147 1254 8 (c,e,g,m
,n,r,v,x)
Sohn et al. 20503221 pdf Biotechnol J 5/10
Pichia pastoris GS115 5313 F iPP668 668 1177 1361 8 (c,e,g,m
,n,r,v,x)
Chung et al. 20594333 xls   7/10
Pichia pastoris GS115 5313 F iLC915 915 899 1423 7 (c,m,p,v,r,g,n) Caspeta et al. xls Chalmers 5/12
Pichia stipitis CBS 6054 5841 F iSS884 884 992 1332 4 (c,m,p,v) Caspeta et al. xls Chalmers 5/12
Plasmodium falciparum 3D7 5615 F   579 1622 1375 6 (c,i,m,n,r,v) Huthmacher et al. 20807400 SBML   8/10
Plasmodium falciparum 3D7 5615 F   366 616 1001 4 (c,e,i,m) Plata et al. 20823846 SBML MSB 9/10
Saccharomyces cerevisiae Sc288 6183 F iFF708 708 584 1,175 3 (c,e,m) Forster et al. 12566402 SBML Chalmers 2/03
Saccharomyces cerevisiae Sc288 6183 F iND750 750 646 1,149 8 (c,e,m,
x,n,r,v,g)
Duarte et al. 15197165 SBML UCSD 7/04
Saccharomyces cerevisiae Sc288 6183 F iLL672 672 636 1,038 3 (c,e,m) Kuepfer et al. 16204195 xls   10/05
Saccharomyces cerevisiae Sc288 6183 F iIN800 800 1013 1446 3(c,e,m) Nookaew et al. 18687109 SBML Chalmers 8/08
Saccharomyces cerevisiae Sc288 6183 F iMH805/775 832 1168 1857 15(c,e,g,m,n, r
,v,x, gm,mm,
nm,pm,rm, vm,xm,)
Herrgård et al. 18846089 SBML UCSD 10/08
Saccharomyces cerevisiae Sc288 6183 F iMM904 904 713 1,412 8(c,e,m,x
,n,r,v,g)
Mo et al. 19321003 xls UCSD 3/09
Saccharomyces pombe Sz-0205 4940 F SpoMBEL1693 605 1744 1693 8(c,e,m,x
,n,r,v,g)
Sohn et al. BMC SysBio 5/12
Scheffersomyces stipitis CBS 6054 5816 F iTL885 885 589 1240 3(c,e,m) Liu et al. 22998943 xls Biotechnology for Biofuels 9/12
Toxoplasma gondii 382 F 382 384 571 5 (a,c, rm, m, mm) Song et al. 24247825‎ xml Mol Sys Bio 11/13

Reconstruction status: 

P = In progress, D = draft, F = Finish

Compartment abbreviations:

* a: acidocalcisome * c: cytoplasm * e: extra-organism/extracellular * f: flagellum * g: golgi * h: chloroplast * i: apicoplast * l: lysosome * m: mitochondrion * n: nucleus * o: glyoxysomes * p: periplasm * r: ER * s: plastid *u: thykaloid lumen * v: vacuole * x: peroxisome * y: glycosome * gm: golgi membrane * mm: mitochondrial membrane * nm: nuclear membrane * pm: plasma membrane * rm: ER membrane * vm: vacuolar membrane * xm: peroxisomal membrane

Multiple cell type interaction models

Human alveolar macrophage and M. tuburculosis: Bordbar A, Lewis NE, Schellenberger J, Palsson BØ, Jamshidi N. *Insight into human alveolar macrophage and M. tuberculosis interactions via metabolic reconstructions*. Mol Syst Biol. 2010 Oct 19;6:422. PMID: [20959820]
Mesophyll and bundle sheath cells in C4 plants: de Oliveira Dal'molin CG, Quek LE, Palfreyman RW, Brumbley SM, Nielsen LK. C4GEM, *a Genome-Scale Metabolic Model to Study C4 Plant Metabolism*. Plant Physiol. 2010 Dec;154(4):1871-85. PMID: [20974891
Human brain cells: Lewis NE, Schramm G, Bordbar A, Schellenberger J, Andersen MP, Cheng JK, Patel N, Yee A, Lewis RA, Eils R, König R, Palsson BØ. *Large-scale in silico modeling of metabolic interactions between cell types in the human brain*. Nat Biotechnol. 2010 Dec;28(12):1279-85. PMID: [21102456]

Smaller scale reconstructions/models

Aspergillus niger: David H, Akesson M, Nielsen J, "Reconstruction of the central metabolism of Aspergillus niger", European Journal of Biochemistry, 270(21):4243-4253 (2003). PMID: [14622289].
Chlamydomonas rheinhardtii: Boyle NR, Morgan JA. "Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii.",BMC Syst Biol. 2009 Jan 7;3(1):4. PMID: [19128495].
Desulfovibrio vulgaris/Methanococcus maripaludis: Stolyar S, Van Dien S, Hillesland KL, Pinel N, Lie TJ, Leigh JA, Stahl DA. "Metabolic modeling of a mutualistic microbial community" Mol Syst Biol. 2007;3:92. PMID: [17353934
Pichia pastoris: Tortajada M, Llaneras F, Pico J. "Validation of a constraint-based model of Pichia pastors metabolism under data scarcity", BMC Syst Biol, 4:115 (2010). PMID: [20716335
Synechocystis sp PCC 6803: Shastri AA, Morgan JA, “Flux balance analysis of photoautotrophic metabolism”, Biotechnol Prog, 21(6):1617-1626 (2005). PMID: [16321043].
Synechocystis sp PCC 6803: Hong SJ, Lee CG. “Evaluation of Central Metabolism Based on a Genomic Database of Synechocystis PCC6803”, Biotechnol Bioprocess Eng, 12:165-173 (2007). 
Trypanosoma cruzi: Roberts SB, Robichaux JL, Chavali AK, Manque PA, Lee V, Lara AM, Papin JA, Buck GA. "Proteomic and network analysis characterize stage-specific metabolism in Trypanosoma cruzi". BMC Syst Biol. 2009 May 16;3:52. PMID: [19445715]. 
Zymomonas mobilis: Tsantili IC, Karim MN, Klapa MI. “Quantifying the metabolic capabilities of engineered Zymomonas mobilis using linear programming analysis.” Microb. Cell Fact. 6:8 (2007). PMID: [17349037].

Metabolic reconstructions with no modeling:

Mannheimia succiniproducens: Hong SH, Kim JS, Lee SY, In YH, Choi SS, Rih JK, Kim CH, Jeong H, Hur CG, Kim JJ, "The genome sequence of the capnophilic rumen bacterium Mannheimia succiniciproducens" Nature Biotechnology, 22:1275-1281 (2004). PMID: [15378067]
Plasmodium falciparum: Yeh I, Hanekamp T, Tsoka S, Karp PD, Altman RB, "Computational analysis of Plasmodium falciparum metabolism: organizing genomic information to facilitate drug discovery" Genome Research, 14:917-924 (2004). PMID: [15078855]
Human: Romero P, Wagg J, Green ML, Kaiser D, Krummenacker M, Karp PD, "Computational prediction of human metabolic pathways from the complete human genome" Genome Biology, 6:R2.1-R2.17 (2004). PMID: [15642094]
Methanococcus jannaschii: Tsoka S, Simon D, Ouzounis CA, "Automated metabolic reconstruction for Methanococcus jannaschii" Archaea, 1:223-229 (2004). PMID: [15810431]
Bos taurus: Soh S, Lewin HA, *Reconstruction of metabolic pathways for the cattle genome BMC Systems Biology*. 2009 Mar 12;3:33. PMID: [19284618]
Fish (5 species: Zebrafish, Medaka, Takifugu, Tetraodon, Stickleback) Li S, Pozhitkov A, Ryan RA, Manning CS, Brown-Peterson N, Brouwer M. *Constructing a fish metabolic network model*. Genome Biol. 2010 Nov 29;11(11):R115. PMID: [21114829]

Reconstructions and models of other cellular networks:

Jak-Stat signaling network: Papin, J.A. and Palsson, B.Ø., "The JAK-STAT Signaling Network in the Human B-Cell: An Extreme Signaling Pathway Analysis ", Biophysical Journal, 87: 37-46(2004). PMID: [15240442]
Toll-like receptor signaling network: Li, F., Thiele, I., Jamshidi, N., and Palsson, B.Ø.,"Identification of Potential Pathway Mediation Targets in Toll-Like Receptor Signaling", PLoS Comp Biol. PMID:[19229310]
Transcriptional and translational machinery: Thiele, I., Jamshidi, N., Fleming, M.T., Palsson, B.Ø., "Genome-scale reconstruction of E. coli 's transcriptional and translational machinery: A knowledge-base, its mathematical formulation, and its functional characterization.", PLoS Comp Biol. PMID: [19282977]

Integrated networks and models:

Metabolism and transcriptional regulation

  • Covert MW, Knight EM, Reed JL, Herrgård MJ, Palsson BØ. "Integrating high-throughput and computational data elucidates bacterial networks." Nature. 2004. 429(6987): 92-6. PMID: [15129285]
  • Goelzer A, Bekkal Brikci F, Martin-Verstraete I, Noirot P, Bessières P, Aymerich S, Fromion V. "Reconstruction and analysis of the genetic and metabolic regulatory networks of the central metabolism of Bacillus subtilis." BMC Syst Biol. 2008 Feb 26;2:20. PMID: [18302748]
  • Chandrasekaran S, Price ND. "Probabilistic integrative modeling of genome-scale metabolic and regulatory networks in Escherichia coli and Mycobacterium tuberculosis." Proc Natl Acad Sci U S A. 2010 Oct 12;107(41):17845-50. PMID: [20876091]
  • Barua D, Kim J, Reed JL. "An automated phenotype-driven approach (GeneForce) for refining metabolic and regulatory models." PLoS Comput Biol. 2010 Oct 28;6(10):e1000970. PMID: [21060853]

Metabolism, signaling, transcriptional regulation 

  • Covert MW, Xiao N, Chen TJ, and Karr JR. "Integrated Flux Balance Analysis Model of Escherichia coli" Bioinformatics. 2008. 24(18): 2044-2050. PMID: [18621757]
  • Min Lee J, Gianchandani EP, Eddy JA, Papin JA. " Dynamic analysis of integrated signaling, metabolic, and regulatory networks." PLoS Comput Biol. 2008 May 23;4(5):e1000086. [18483615]

Additional Review Articles on Metabolic Reconstructions and Methods

Computational Modeling Software and Tools

  • Grafahrend-Belau E, Klukas C, Junker BH, Schreiber F. "FBA-SimVis Interactive visualisation of constraint-based metabolic models." Bioinformatics. 2009 Jul 3 [19578041]
  • Le Fèvre F, Smidtas S, Combe C, Durot M, d'Alché-Buc F, Schachter V. "CycSim-an online tool for exploring and experimenting with genome-scale metabolic models." Bioinformatics. 2009 Aug 1;25(15):1987-8. [19420054]
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