Preprints
83. Joshi, C., Schinn, S., Richelle, A., Shamie, I., O’Rourke, E., Lewis, N.E. StanDep: capturing transcriptomic variability improves context-specific metabolic models. bioRxiv, (2019). DOI: 10.1101/594861
82. Lakshmanan, M., Long, S., Ang, K.S., Lewis, N E, Lee, D.Y. On the impact of biomass composition in constraint-based flux analysis. bioRxiv (2019). DOI: 10.1101/652040
81. Gutierrez, J.M.*, Feizi, A.*, Li, S., Kallehauge, T.B., Grav, L.M., Hefzi, H., Ley, D., Baycin Hizal, D., Betenbaugh, M.J., Voldborg, B., Kildegaard, H.F., Lee, G.M., Palsson, B.O., Nielsen, J., Lewis, N.E. Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion. bioRxiv (2018). DOI: 10.1101/351387
80. Lieven, C., Beber, M.E., Olivier, B.G., Bergmann, F.T., Babaei, P., Bartell, J.A., Blank, L.M., Chauhan, S., Correia, K., Diener, C., Dräger, A., Ebert, B.E., Edirisinghe, J.N., Fleming, R.M.T., Garcia-Jimenez, B., van Helvoirt, W., Henry, C., Hermjakob, H., Herrgard, M.J., Kim, H.U., King, Z., Koehorst, J.J., Klamt, S., Klipp, E., Lakshmanan, M., Le Novere, N., Lee, D.Y., Lee, S.Y., Lee, S., Lewis, N.E., Ma, H., Machado, D., Mahadevan, R., Maia, P., Mardinoglu, A., Medlock, G.L., Monk, J., Nielsen, J., Nielsen, L.K., Nogales, J., Nookaew, I., Resendis, O., Palsson, B.O., Papin, J.A., Patil, K.R., Price, N.D., Richelle, A., Rocha, I., Schaap, P., Sheriff, R.S.M., Shoaie, S., Sonnenschein, N., Teusink, B., Vilaca, P., Vik, J.O., Wodke, J.A., Xavier, J.C., Yuan, Q., Zakhartsev, M., Zhang, C. Memote: A community driven effort towards a standardized genome-scale metabolic model test suite. bioRxiv (2018). DOI: 10.1101/350991
2019
78. Richelle, A., Joshi, C., Lewis, N.E. Assessing key decisions for transcriptomic data integration in biochemical networks. PLoS Computational Biology, accepted (2019). DOI: 10.1101/301945
73. Richelle, A., Chiang, A.W.T., Kuo, C.C., Lewis, N.E. Increasing consensus of context-specific metabolic models by integrating data-inferred cell functions. PLoS Computational Biology, 15: e1006867 (2019). DOI: 10.1371/journal.pcbi.1006867
69. Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S.N., Richelle, A., Heinken, A., Haraldsdottir, H.S., Keating, S.M., Vlasov, V., Wachowiak, J., Magnusdottir, S., Ng, C.Y., Preciat, G., Zagare, A., Chan, S.H.J., Aurich, M.K., Clancy, C.M., Modamio, J., Sauls, J.T., Noronha, A., Bordbar, A., Cousins, B., El Assal, D.C., Ghaderi, S., Ahookhosh, M., Ben Guebila, M., Apaolaza, I., Kostromins, A., Le, H.M., Ma, D., Sun, Y., Valcarcel, L.V., Wang, L., Yurkovich, J.T., Vuong, P.T., El Assal, L.P., Hinton, S., Bryant, W.A., Aragon Artacho, F.J., Planes, F.J., Stalidzans, E., Maass, A., Santosh Vempala, Hucka, M., Saunders, M.A., Maranas, C.D., Lewis, N.E., Sauter, T., Palsson, B.Ø., Thiele, I., Fleming, R.M.T. Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0. Nature Protocols, 14:639-702 (2019). DOI: 10.1038/s41596-018-0098-2 ArXiv: 1710.04038
2018
64. Brunk, E.*, Chang, R.L., Xia, J., Hefzi, H., Yurkovich, J., Kim, D., Buckmiller, E., Wang, H.H., Yang, C., Palsson, B.Ø., Church, G.M.‡, Lewis, N.E.*‡ Characterizing post-translational modifications in prokaryotic metabolism using a multi-scale workflow, Proc. Nat. Acad. Sci. USA, 115 (43): 11096-11101 (2018). bioRxiv DOI: 10.1101/180646
61. Witting, M.A., Hastings, J., Rodriguez, N., Joshi, C.J., Hattwell, J.P., Ebert, P.R., van Weeghel, M., Wakelam, M., Houtkooper, R., Mains, A., Le Novère, N., Sadykoff, S., Schroeder, F.,Lewis, N.E., Schirra, H.J., Kaleta, C., Casanueva, O. Modeling meets Metabolomics – The WormJam Consensus Model as basis for Metabolic Studies in the model organism Caenorhabditis elegans, Frontiers in Molecular Biosciences, 5:96 (2018) . DOI:10.3389/fmolb.2018.00096
57. Abdel-Haleem, A.M., Hefzi, H., Mineta, K., Gao, X., Gojobori, T., Palsson, B.O., Lewis, N.E., Jamshidi, N. Functional interrogation of Plasmodium genus metabolism identifies species- and stage-specific differences in nutrient essentiality and drug targeting. PLoS Computational Biology, 14(1): e1005895 (2018). DOI: 10.1371/journal.pcbi.1005895
2017
55. Abdel-Haleem, A.M., Lewis, N.E., Jamshidi, N., Mineta, K., Gao, X., Gojobori, T. The emerging facets of noncancerous Warburg effect. Frontiers in Endocrinology, 8:297 (2017). DOI: 10.3389/fendo.2017.00279
54. Richelle, A., Lewis, N.E.. Improvements in protein production in mammalian cells from targeted metabolic engineering. Current Opinion in Systems Biology, 6:1-6 (2017). DOI: 10.1016/j.coisb.2017.05.019
52. Opdam, S.*, Richelle, A.*, Kellman, B., Li, S., Zielinski, D.C., Lewis, N.E.‡ A systematic evaluation of methods for tailoring genome-scale metabolic models. Cell Systems, 4:1-12 (2017). DOI:10.1016/j.cels.2017.01.010
51. Spahn, P.N., Hansen, A.H., Kol, S., Voldborg, B.G., Lewis, N.E.‡ Predictive glycoengineering of biosimilars using a Markov chain glycosylation model. Biotechnology Journal,12:1600489 (2017). DOI:10.1002/biot.201600489
46. Hastings, J., et al. WormJam: Consensus C. elegans metabolic reconstruction and metabolomics community. Worm, 6:e1373939 (2017). DOI:10.1080/21624054.2017.1373939
2016
45. Hefzi, H.*, Ang, K.S.*, Hanscho, M.*, Bordbar, A., Ruckerbauer, D., Lakshmanan, M., Orellana, C.A., Baycin-Hizal, D., Huang, H., Ley, D., Martínez, V.S., Kyriakopoulos, S., Jiménez, N.E., Zielinski, D.C., Quek, L.E., Wulff, T., Arnsdorf, J., Li, S., Lee, J.S., Paglia, G., Loira, N., Spahn, P.N., Pedersen, L.E., Gutierrez, J.M., King, Z.A., Lund, A.M., Nagarajan, H., Thomas, A., Abdel-Haleem, A.M., Zanghellini, J., Kildegaard, H.F., Voldborg, B.G., Gerdtzen, Z.P., Betenbaugh, M.J., Palsson, B.O., Andersen, M.R., Nielsen, L.K., Borth, N.‡, Lee, D.Y.‡, Lewis, N.E.‡ A consensus genome-scale reconstruction of Chinese hamster ovary cell metabolism. Cell Systems, 3, 434-443 (2016). DOI:10.1016/j.cels.2016.10.020
Press releases at phys.org, UCSD Health Sciences
43. Swainston, N., Smallbone, K., Hefzi, H., Dobson, P.D., Brewer, J., Hanscho, M., Zielinski, D.C., Ang, K.S., Gardiner, N.J., Gutierrez, J.M., Kyriakopoulos, S., Lakshmanan, M., Li, S., Liu, J.K., Martínez, V.S., Orellana, C.A., Quek, L.E., Thomas, A., Zanghellini, J., Borth, N., Lee, D.Y., Nielsen, L.K., Kell, D.B., Lewis, N.E., Mendes, P. Recon 2.2: from reconstruction to model of human metabolism. Metabolomics, 12:109 (2016). DOI: 10.1007/s11306-016-1051-4
42. Huang, S., Chong, N., Lewis, N.E., Jia, W., Xie, G., Garmire, L.X. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis. Genome Medicine, 8(1):1 (2016). DOI: 10.1186/s13073-016-0289-9
40. King, Z.A., Lu, J., Dräger, A., Miller, P., Federowicz, S., Lerman, J., Ebrahim, A., Palsson, B.O., Lewis, N.E.‡ BiGG Models: A platform for integrating, standardizing, and sharing genome-scale models. Nucleic Acids Research, 44(D1):D515-22 (2016). DOI: 10.1093/nar/gkv1049 BiGG Models website
39. Spahn, P.N., Hansen, A.H., Hansen, H.G., Arnsdorf, J., Kildegaard, H.F., Lewis, N.E.‡ A Markov chain model for N-linked protein glycosylation – towards a low-parameter tool for model-driven glycoengineering. Metabolic Engineering, 33: 52–66 (2016). DOI:10.1016/j.ymben.2015.10.007
2015
37. Ebrahim, A., Almaas, E., Bauer, E., Bordbar, A., Burgard, A.P., Chang, R.L., Dräger, A., Famili, I., Feist, A.M., Fleming, R.M.T., Fong, S.S., Hatzimanikatis, V., Herrgård, M.J., Holder, A., Hucka, M., Hyduke, D., Jamshidi, N., Lee, S.Y., Le Novère, N., Lerman, J.A., Lewis, N.E., Ma, D., Mahadevan, R., Maranas, C., Nagarajan, H., Navid, A., Nielsen, J., Nielsen, L.K., Nogales, J., Noronha, A., Pal, C., Palsson, B.O., Papin, J.A., Patil, K.R., Price, N.D., Reed, J., Saunders, M., Senger, R.S., Sonnenschein, N., Sun, Y., Thiele, I. Do genome‐scale models need exact solvers or clearer standards?. Molecular Systems Biology, 11: 831 (2015). DOI: 10.15252/msb.20156157
35. King, Z.A., Dräger, A., Ebrahim, A., Sonnenschein, N., Lewis, N.E., Palsson, B.O. Escher: A web application for building, sharing, and embedding data-rich visualizations of biological pathways. PLoS Computational Biology, 11:e1004321 (2015). DOI: 10.1371/journal.pcbi.1004321
34. Swann, J., Jamshidi, N., Lewis, N.E., Winzeler, E.A.. Systems analysis of host–parasite interactions. WIREs: Systems Biology and Medicine, 7(6), 381–400 (2015). DOI: 10.1002/wsbm.1311
33. Gutierrez, J.M., Lewis, N.E.‡ Optimizing eukaryotic cell hosts for protein production through systems biotechnology and genome-scale modeling. Biotechnology Journal, 10:939–949 (2015). DOI: 10.1002/biot.201400647
32. Rodriguez, R.*, Thomas, A.*, Watanabe, L., Vazirabad, I.Y., Kofia, V., Gómez, H.F., Mittag, F., Matthes, J., Rudolph, J., Wrzodek, F., Netz, E., Diamantikos, A., Eichner, J., Keller, R., Wrzodek, C., Fröhlich, S., Lewis, N.E., Myers, C.J., Le Novère, N., Palsson, B.O., Hucka, M., Dräger, A. JSBML 1.0: providing a smorgasbord of options to encode systems biology models. Bioinformatics, 31(20):3383-3386 (2015). DOI: 10.1093/bioinformatics/btv341
2014
29. Spahn, P., Lewis, N.E.‡ Systems glycomics for glycoengineering. Current Opinion in Biotechnology, 30:218–224 (2014). DOI: 10.1016/j.copbio.2014.08.004
28. Hefzi, H., Lewis, N.E.‡ From random mutagenesis to systems biology in metabolic engineering of mammalian cells. Pharmaceutical Bioprocessing, 2:355-358 (2014). DOI: 10.4155/pbp.14.36
27. Kumar, A., Harrelson, T., Lewis, N.E., Gallagher, E., LeRoith, D., Shiloach, J., Betenbaugh, M.J.Multi-tissue computational modeling analyzes pathophysiology of Type 2 Diabetes in MKR mice. PLoS One, 9(7): e102319. DOI: 10.1371/journal.pone.0102319
26. Bordbar, A., Nagarajan, H., Lewis, N.E., Schellenberger, J., Latif, H., Federowicz, S., Ebrahim, A., Palsson, B.O. Minimal metabolic pathway structure is consistent with associated biomolecular interactions. Molecular Systems Biology, 10:737 (2014). DOI: 10.15252/msb.20145243
2013
24. Lewis, N.E.‡, Abdel-Haleem, A.M. The evolution of genome-scale models of cancer metabolism. Front. Physiol. 4:237 (2013). DOI: 10.3389/fphys.2013.00237 ‡ corresponding author
21. Hyduke, D.R., Lewis, N.E., Palsson, B.Ø. Analysis of omics data with genome-scale models of metabolism. Molecular BioSystems, 9:167 (2013). doi: 10.1039/c2mb25453k
2012
20. Nam, H.J.*, Lewis, N.E.‡*, Lerman, J.A., Lee, D.H., Chang, R.L., Kim, D., Palsson, B.Ø.‡ Network context and selection in the evolution to enzyme specificity. Science. 337:1101-1104 (2012). ‡ corresponding author, * equal contribution
19. Noor, E.‡, Lewis, N.E.‡, Milo, R. A proof for loop-law constraints in stoichiometric metabolic networks. BMC Systems Biology. 6:140 (2012). Highly Accessed. ‡ corresponding author
17. Hefzi, H., Palsson, B.Ø., Lewis, N.E.‡. Reconstruction of genome-scale metabolic networks. In Handbook of Systems Biology. 229 (2013). doi:10.1016/B978-0-12-385944-0.00012-5 ‡ corresponding author
16. Lerman, J.A., Hyduke, D.R., Latif, H., Portnoy, V.A., Lewis, N.E., Orth, J.D., Schrimpe-Rutledge, A.C., Smith, R.D., Adkins, J.N., Zengler, K.A., Palsson, B.Ø. In silico method for modelling metabolism and gene product expression at genome scale. Nature Communications. 3:929 (2012).
15. Lewis, N.E., Nagarajan, H., Palsson, B.Ø. Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods. Nature Reviews Microbiology.10:291-305 (2012). Click here for accompanying website with a catalog of constraint-based methods.
2011
13. Schellenberger, J., Que, R., Fleming, R.T., Thiele, I., Orth, J., Feist, A.M., Zielinski , D.C., Bordbar, A., Lewis, N.E., Rahmanian, S., Kang, J., Hyduke, D., Palsson, B.Ø. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nature Protocols, 6:1290-307 (2011).
12. Nam, H.J.*, Conrad, T.M., Lewis, N.E.*‡. The role of cellular objectives and selective pressures in metabolic pathway evolution. Current Opinion in Biotechnology, 22:595-600 (2011). * equal contribution, ‡ corresponding author
11. Conrad, T.M., Lewis, N.E., Palsson, B.Ø. Microbial Laboratory Evolution in the Era of Genome-Scale Science. Molecular Systems Biology, 7:509 (2011).
10. Schellenberger, J., Lewis, N.E., Palsson, B.Ø. Elimination of thermodynamically infeasible loops in steady state metabolic models. Biophysical Journal, 100:544-53 (2011).
2010
9. Lewis, N.E., Schramm, G., Bordbar, A., Schellenberger, J., Andersen, M.P., Cheng, J.K., Patel, N., Yee, A., Lewis, R.A., Eils, R., König, R., Palsson, B.Ø. Large-scale in silico modeling of metabolic interactions between cell types in the human brain. Nature Biotechnology, 28:1279–1285 (2010). Paper highlighted by Nature Methods (January 2011).
7. Bordbar, A., Lewis, N.E., Schellenberger, J., Palsson, B.Ø., Jamshidi, N. Insight into human alveolar macrophage and M. tuberculosis interactions via metabolic reconstructions. Molecular Systems Biology, 6:422 (2010).
6. Portnoy, V.A., Scott, D.A., Lewis, N.E., Tarasova, Y., Osterman, A.L., Palsson, B.Ø. Deletion of genes encoding cytochrome oxidases and quinol monooxygenase blocks the aerobic-anaerobic shift in Escherichia coli K-12 MG1655. Appl. Environ. Microbiol., 76:6529-40 (2010).
5. Lewis, N.E., Hixson, K.K., Conrad, T.M., Lerman, J.A., Charusanti, P., Polpitiya, A.D., Adkins, J.N., Schramm, G., Purvine, S.O., Lopez-Ferrer, D., Weitz, K.K., Eils, R., König, R., Smith, R.D., Palsson, B.Ø. Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models. Molecular Systems Biology, 6:390 (2010).
4. Bar-Even, A., Noor, E., Lewis, N.E., Milo, R. Design and analysis of synthetic carbon fixation pathways. Proc. Natl. Acad. Sci. USA., 107:8889-8894 (2010).
2009
3. Lewis, N.E., Cho, B.K., Knight, E.M. Palsson, B. Ø. Gene expression profiling and the use of genome-scale in silico models of Escherichia coli for analysis: providing context for content. J. Bacteriol., 191:3437-44 (2009).
2. Lewis, N.E., Jamshidi, N., Thiele, I. & Palsson, B.Ø. Metabolic systems biology: a constraint-based approach. In Encyclopedia of Complexity and Systems Science 5535 (Springer, New York, 2009). DOI:10.1007/978-3-642-27737-5_329-2
Patents and patent applications
3. Hefzi, H., Lewis, N.E. Mammalian cells devoid of lactate dehydrogenase activity WO Patent WO2017192437A1.
2. Spahn, P., Lewis, N.E. Systems and methods for predicting glycosylation on proteins. WO Patent 2016187341 A1.
1. Herrgard, M. J., Pedersen, L.E., Lewis, N.E., Bruntse, A.B. Methods for modeling Chinese hamster ovary (CHO) cell metabolism. WO Patent WO2015010088-A1.
