Selected publications
A perturbed gene network … in leukocytes is linked to ASD genetics and symptom severity. Nature Neuroscience, (2019).
A systematic evaluation of methods for tailoring genome-scale metabolic models. Cell Systems, 4, 1-12 (2017).
A consensus genome-scale reconstruction of Chinese hamster ovary cell metabolism. Cell Systems, 3, 434 (2016).
Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genome. Nature Biotechnology. 31:759 (2013).
Network context and selection in the evolution to enzyme specificity. Science. 337:1101 (2012).
All publications
‡corresponding author, * equal contribution
For a current list, click here.
Preprints
92. Bao, B.*, Kellman, B.P.*, Chiang, A.W.T., York, A.K., Mohammad, M.A., Haymond, M.W., Bode, L., Lewis, N.E. Correcting for sparsity and non-independence in glycomic data through a system biology framework. bioRxiv (2019). DOI: 10.1101/693507
91. Kol, S., Ley, D., Wulff, T., Decker, M., Arnsdorf, J., Gutierrez, J.M., Chiang, A.W.T., Pedersen, L.E., Kildegaard, H.F., Lee, G.M., Lewis, N.E. Multiplex secretome engineering enhances recombinant protein production and purity. bioRxiv (2019). DOI: 10.1101/647214
90. Fouladiha, H., Marashi, S.A., Torkashvand, F., Mahboudi, F., Lewis, N.E., Vaziri, B. A metabolic network-based approach for developing feeding strategies for CHO cells to increase monoclonal antibody production . bioRxiv (2019). DOI: 10.1101/751347
89. 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
88. 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
87. 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
2019
86. la Cour Karottki, K.J., Hefzi, H., Xiong, K., Shamie, I., Hansen, A.H., Li, S., Li, S., Lee, J.S., Lee, G.M., Kildegaard, H.F.‡, Lewis, N.E.‡ Awakening dormant glycosyltransferases in CHO cells with CRISPRa. Biotechnology and Bioengineering, in press (2019). DOI: 10.1002/bit.27199
85. Gazestani, V.H., Pramparo, T., Nalabolu, S., Kellman, B.P., Murray, S., Lopez, L., Pierce, K., Courchesne, E., Lewis, N.E. A perturbed gene network containing PI3K/AKT, RAS/ERK, WNT/β-catenin pathways in leukocytes is linked to ASD genetics and symptom severity. Nature Neuroscience,22, 1624–1634 (2019). DOI: 10.1038/s41593-019-0489-x, bioRxiv: 10.1101/435917, News coverage: Genomeweb, Medical News, Technology Networks, Neuroscience News
84. Toledo, A.G., Golden, G., Campos, A.R., Cuello, H., Sorrentino, J., Lewis, N.E., Varki, N., Nizet, V., Smith, J.W., Esko, J.D. Proteomic atlas of organ vasculopathies triggered by Staphylococcus aureus sepsis. Nature Communications, 10:4656 (2019). doi: 10.1038/s41467-019-12672-x
83. Dahodwala, H., Kaushik, P., Tejwani, V., Kuo, C.C., Menard, P., Henry, M., Voldborg, B.G., Lewis, N.E., Meleady, P., Sharfstein, S.T. Increased mAb titers from amplification are associated with increased interaction of CREB1 with transgene promoter. Current Research in Biotechnology, accepted (2019). doi: 10.1016/j.crbiot.2019.09.001
82. 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. Nature Biotechnology, accepted (2019). bioRxiv DOI: 10.1101/350991
81. Li, S.*, Richelle, A.*, Lewis, N.E. Enhancing product and bioprocess attributes using genome-scale models of CHO metabolism. Cell Culture Engineering: Recombinant Protein Production , p.73 (2019). ISBN: 978-3-527-34334-8
80. Cyrielle, C., Joshi, C., Lewis, N.E., Laetitia, M., Andersen, M.R.Adaption of Generic Metabolic Models to Specific Cell Lines for Improved Modeling of Biopharmaceutical Production and Prediction of Processes. Cell Culture Engineering: Recombinant Protein Production , p.127 (2019). ISBN: 978-3-527-34334-8
79. Richelle, A., Joshi, C., Lewis, N.E. Assessing key decisions for transcriptomic data integration in biochemical networks. PLoS Computational Biology, 15(7): e1007185 (2019). DOI: 10.1371/journal.pcbi.1007185
78. Chiang, A.W.T., Li, S., Kellman, B.P., Chattopadhyay, G., Zhang, Y., Kuo, C.C., Gutierrez, J.M., Ghazi, F., Schmeisser, H., Menard, P., Bjorn, S.P., Voldborg, B.G., Rosenberg, A.S., Puig, M.‡, Lewis, N.E.‡ Combating viral contaminants in CHO cells by engineering innate immunity. Scientific Reports, 9:8827 (2019). DOI: 10.1038/s41598-019-45126-x
77. Li, S., Cha, S.W., Heffner, K., Baycin-Hizal, D., Bowen, M., Chaerkady, R., Cole, R., Tejwani, V., Kaushik, P., Henry, M., Meleady, P., Sharfstein, S., Betenbaugh, M.J., Bafna, V., Lewis, N.E. Proteogenomic annotation of the Chinese hamster reveals extensive novel translation events and endogenous retroviral elements. Journal of Proteome Research, 18:2433-2445 (2019). bioRxiv: 10.1101/468181
Download genome and annotation here
76. Gazestani, V.H., Lewis, N.E. From Genotype to Phenotype: Augmenting Deep Learning with Networks and Systems Biology, Current Opinion in Systems Biology, 15:68-73 (2019). DOI: 10.1016/j.coisb.2019.04.001
75. Xiong, K.*, Marquart, K.F.*, la Cour Karottki, K.J.*, Li, S., Shamie, I., Lee, J.S., Signe Gerling, S., Yeo, N.C., Chavez, A., Lee, G.M., Lewis, N.E.‡, Kildegaard, H.F.‡, Reduced Apoptosis in Chinese Hamster Ovary Cells via Optimized CRISPR Interference. Biotechnology and Bioengineering, 116:1813-1819 (2019). DOI: 10.1002/bit.26969
74. 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
73. Pristovsek, N., Nallapareddy, S., Grav, L.M., Hefzi, H., Lewis, N.E., Rugbjerg, P., Hansen, H.G., Lee, G.M., Andersen, M.R., Kildegaard, H.F. Systematic Evaluation of Site-Specific Recombinant Gene Expression for Programmable Mammalian Cell Engineering. ACS Synthetic Biology, 8:758–774 (2019). DOI: 10.1021/acssynbio.8b00453
72. Lytle, N., Ferguson, L.P., Rajbhandari, N., Gilroy, K., Fox, R.G., Robertson, N., Deshpande, A., Schürch, C., Hamilton, M., Robertson, N., Lin, W., Noel, P., Wartenberg, M, Zlobec, I., Eichmann, M., Galván, J.A., Karamitopoulou, E., Gilderman, T., Esparza, L.A., Shima, Y., Spahn, P., French, R., Lewis, N.E., Fisch, K.M., Sasik, R., Rosenthal, S.B., Kritzik, M., Von Hoff, D., Han, H., Ideker, T., Deshpande, A., Lowy, A.M., Adams, P., Reya, T. A multiscale map of the stem cell state in pancreatic adenocarcinoma. Cell, 177:572-586 (2019).
71. Lee, J.S., Kildegaard, H.F., Lewis, N.E., Lee, G.M. Deciphering Clonal Variation in Recombinant Mammalian Cell Lines. Trends in Biotechnology, in press (2019). DOI: 10.1016/j.tibtech.2019.02.007
70. 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
69. LaMonte, G., Orjuela-Sanchez, P., Wang, L., Li, S., Swann, J., Cowell, A., Zou, B.Y., Abdel-Haleem, A.M., Villa-Galarce, Z., Moreno, M., Tong-Rios, C., Vinetz, J., Lewis, N.E., Winzeler, E.A. Dual RNAseq shows the human mucosal immunity protein, MUC13, is a hallmark of Plasmodium exoerythrocytic infection. Nature Communications, 10:488 (2019). DOI: 10.1038/s41467-019-08349-0
68. Landig, C.S., Hazel, A., Kellman, B.P., Fong, J.J., Schwarz, F., Agarwal, S., Varki, N., Massari, P., Lewis, N.E., Ram, S., Varki, A. The exclusively human-pathogen Neisseria gonorrhoeae engages 4 immunoregulatory siglecs in a species-specific manner. Evolutionary Applications, 12:337-349 (2019). DOI: 10.1111/eva.12744
2018
67. Lombardo, M.V., Pramparo, T., Gazestani, V., Warrier, V., Bethlehem, R.AI., Barnes, C.C., Lopez, L., Lewis, N.E., Eyler, L., Pierce, K., Courchesne, E. Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes, Nature Neuroscience, 21, 1680–1688 (2018). DOI: 10.1038/s41593-018-0281-3
66. Lee, J.S., Park, J.H., Ha, T.K., Samoudi, M., Lewis, N.E., Palsson, B.O., Kildegaard, H.F., Lee, G.M. Revealing key determinants of clonal variation in transgene expression in recombinant CHO cells using targeted genome editing, ACS Synthetic Biology, 7 (12):2867-2878 (2018). DOI: 10.1021/acssynbio.8b00290
65. 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
64. Grav, L.M., Sergeeva, D., Lee, J.S., Marin de Mas, I., Lewis, N.E., Andersen, M.R., Nielsen, L.K., Lee, G.M., Kildegaard, H.F. Minimizing clonal variation during mammalian cell line engineering for improved systems biology data generation, ACS Synthetic Biology, 7 (9):2148–2159. DOI:10.1021/acssynbio.8b00140
63. Yeo, N.C., Chavez, A., Lance-Byrne, A., Chan, Y., Menn, D., Milanova, D., Kuo, C.C., Guo, X., Sharma, S., Tung, A., Cecchi, R.J., Tuttle, M., Pradhan, S., Lim, E.T., Davidsohn, N., Ebrahimkhani, M.R., Collins, J.J., Lewis, N.E., Kiani, S., Church, G.M. An enhanced CRISPR repressor for targeted mammalian gene regulation, Nature Methods, 15:611-616 (2018) . DOI:10.1038/s41592-018-0048-5
62. 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
61. Rupp, O.*, MacDonald, M.L.*, Li, S.*, Dhiman, H.*, Polson, S., Griep, S., Heffner, K., Hernandez, I., Brinkrolf, K., Jadhav, V., Samoudi, M., Hou, H., Kingham, B., Goesmann, A., Betenbaugh, M.J. ‡, Lewis, N.E.‡, Borth, N.‡, Lee, K.‡ A reference genome of the Chinese hamster based on a hybrid assembly strategy, Biotechnology and Bioengineering, 115:2087-2100 (2018). DOI: 10.1002/bit.26722
60. Courchesne, E., Pramparo, T., Gazestani, V.H., Lombardo, M.V., Pierce, K., Lewis, N.E. (2018) The ASD living biology: From cell proliferation to clinical phenotype. Molecular Psychiatry, 24:88-107. DOI: 10.1038/s41380-018-0056-y
59. Kuo, C.C., Chiang, A.W.T., Shamie, I., Samoudi, M., Gutierrez, J.M., Lewis, N.E.‡ The emerging role of systems biology for engineering protein production in CHO cells. Current Opinion in Biotechnology, 51:64–69 (2018). DOI: 10.1016/j.copbio.2017.11.015
58. 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
57. Uhlen, M, Tegel, H, Sivertsson, Å, Kuo, C C, Gutierrez, J M, Lewis, N E, Forsström, B, Dannemeyer, M, Fagerberg, L, Rockberg, J, Malm, M, Vunk, H, Edfors, F, Hober, A, Sjöstedt, E, Mulder, J, Mardinoglu, A, Schwenk, J, Nilsson, P, Zwahlen, M, von Feilitzen, K, Lindskog, C, Ponten, F, Nielsen, J, Voldborg, B G, Palsson, B O, Volk, A L R, Lundqvist, M, Berling, A, Svensson, A S, Kanje, A, Enstedt, H, Afshari, D, Ekblad, S, Scheffel, J, Xu, L L, Mihai, R, Bremer, L, Westin, M, Muse, M, Mayr, L, Knight, S, Göpel, S, Davies, R, Varley, P, Hatton, D, Takanen, J O, Schiavone, L H, Hober, S. The human secretome – the proteins secreted from human cells. bioRxiv (2018). DOI: 10.1101/465815
2017
56. Spahn, P.N., Bath, T., Weiss, R.J., Kim, J., Esko, J.D., Lewis, N.E.‡, Harismendy, O.‡. PinAPL-Py: a web-service for the analysis of CRISPR-Cas9 Screens. Scientific Reports, 15854 (2017). DOI: 10.1038/s41598-017-16193-9
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
53. Autran, C.A.*, Kellman, B. *, Asztalos, E., Blood, A., Hamilton Spense, E.C., Patel, A.L., Kim, J.H., Hou, J., Lewis, N.E., Bode, L. Human milk oligosaccharide composition predicts risk of necrotizing enterocolitis in preterm infants. Gut, 67:312819. DOI: 10.1136/gutjnl-2016-312819
Highlighted in Nature Reviews Gastroenterology and Chemical and Engineering News
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
50. Kallehauge, T.B., Li, S., Pedersen, L.E., Ha, T.K., Ley, D., Andersen, M.R., Kildegaard, H.F., Lee, G.M.‡, Lewis, N.E.‡ Ribosome profiling-guided depletion of an mRNA increases cell growth rate and protein secretion. Scientific Reports, 7:40388 (2017). DOI:10.1038/srep40388
49. Shen, J.P., Zhao, D., Sasik, R., Luebeck, J., Birmingham, A., Bojorquez-Gomez, A., Licon, K., Klepper, K., Pekin, D., Beckett, A.N., Sanchez, K.S., Thomas, A., Kuo, C.C., Du, D., Roguev, A., Lewis, N.E., Chang, A.N., Kreisberg, J.F., Krogan, N., Qi, L., Ideker, T., Mali, P.M. Combinatorial CRISPR–Cas9 screens for de novo mapping of genetic interactions. Nature Methods, 14:573-576 (2017). DOI:10.1038/nmeth.4225
48. van Wijk, X.M., Döhrmann, S., Hallström, B.M., Li, S., Voldborg, B.G., Meng, B.X., McKee, K.K., van Kuppevelt, T.H., Yurchenco, P.D., Palsson, B.O., Lewis, N.E., Nizet, V., Esko, J.D.Whole Genome Sequencing of Invasion-Resistant Cells Identifies Laminin a2 as a Host Factor For Bacterial Invasion. mBio, 8:e02128-16 (2017). DOI:10.1128/mBio.02128-16
47. Lombardo, M.V., Courchesne, E., Lewis, N.E., Pramparo, T. Hierarchical cortical transcriptome disorganization in autism. Molecular Autism, 8:29 (2017). DOI: 10.1186/s13229-017-0147-7
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
44. Chiang, A.W.T., Li, S., Spahn, P.N., Richelle, A., Kuo, C.C., Samoudi, M., Lewis, N.E. Modulating carbohydrate-protein interactions through glycoengineering of monoclonal antibodies to impact cancer physiology. Current Opinion in Structural Biology, 10, 104–111 (2016). DOI: 10.1016/j.sbi.2016.08.008
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
41. Golabgir, A.*, Gutierrez, J.M.*, Hefzi, H., Li, S., Palsson, B.O., Herwig, C.‡, Lewis, N.E.‡ Quantitative feature extraction from the Chinese Hamster Ovary bioprocess bibliome using a novel meta-analysis workflow . Biotechnology Advances, 34(5):621–633 (2016). DOI:10.1016/j.biotechadv.2016.02.011 * equal contribution, listed alphabetically The CHO Bibliome website
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
38. Pramparo, T., Campbell, K., Barnes, C.C., Marinero, S., Solso, S., Young, J., Mayo, M., Dale, A., Ahrens-Barbeau, C., Murray, S.S., Lopez, L., Lewis, N.E., Pierce, K., Courchesne, E. Cell Cycle Networks link Gene Expression Dysregulation, Mutation and Brain Maldevelopment in Autistic Toddlers. Molecular Systems Biology, 11: 841 (2015). DOI:10.15252/msb.20156108
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
36. Kumar, A., Baycin-Hizal, D., Wolozny, D., Pedersen, L.E., Lewis, N.E., Heffner, K., Chaerkady, R., Cole, R.N., Shiloach, J., Zhang, H., Bowen, M.A., Betenbaugh, M.J. Elucidation of the CHO Super-Ome (CHO-SO) by ProteoInfomatics. Journal of Proteome Research, 14 (11), pp 4687–4703 (2015). DOI: 10.1021/acs.jproteome.5b00588
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
31. Lee, J.S., Grav, L.M., Lewis, N.E., Kildegaard, H.F. CRISPR/Cas9-mediated genome engineering of CHO cell factories: Application and perspectives. Biotechnology Journal, 10:979–994 (2015). DOI: 10.1002/biot.201500082.
2014
30. Busskamp, V.*, Lewis, N.E.*, Guye, P.*, Ng, A.H.M., Shipman, S.L., Byrne, S.M., Sanjana, N.E., Murn, J., Li, Y., Li, S., Stadler, M., Weiss, R., Church, G.M. Rapid neurogenesis through transcriptional activation in human stem cells. Molecular Systems Biology, 10:760 (2014). DOI: 10.15252/msb.20145508. * equal contribution
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
25. Robasky, K.*, Lewis, N.E.‡*, Church, G.M. The Role of Replicates for Error Mitigation in Next-Generation Sequencing. Nature Reviews Genetics. 15:56–62 (2014). DOI: 10.1038/nrg3655 ‡ corresponding author, * equal contribution
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
23. Lewis, N.E.*, Liu, X.*, Li, Y.*, Nagarajan, H.*, Yerganian, G., O’Brien, E., Bordbar, A., Roth, A.M., Rosenbloom, J., Bian, C., Xie, M., Chen, W., Li, N., Baycin-Hizal, D., Latif, H., Forster, J., Betenbaugh, M.J., Famili, I., Xu, X., Wang, J., Palsson, B.O. Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genome. Nature Biotechnology. 31:759-65 (2013). doi: 10.1038/nbt.2624. * equal contribution
22. Kildegaard, H.F., Baycin-Hizal, D., Lewis, N.E., Betenbaugh, M.J. The Emerging CHO Systems Biology Era: Harnessing the ‘Omics Revolution for Biotechnology. Current Opinion in Biotechnology. S0958-1669(13):00021-9 (2013). doi: 10.1016/j.copbio.2013.02.007
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
18. Baycin-Hizal, D., Tabb, D.L., Chaerkady, R., Chen, L., Lewis, N.E., Nagarajan, H., Sarkaria, V., Kumar, A., Wolozny, D., Colao, J., Jacobson, E., Tian, Y., O’Malley, R.N., Krag, S., Cole, R.N., Palsson, B.O., Zhang, H., Betenbaugh, M.J. Proteomic analysis of Chinese hamster ovary cells. Journal of Proteome Research. 11:5265-76 (2012).
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
14. Xu, X.*, Nagarajan, H.*, Lewis, N.E.*, Pan, S.*,et al. The Genomic Sequence of the Chinese Hamster Ovary (CHO) K1 cell line. Nature Biotechnology, 29:735-41 (2011). * equal contribution
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).
8. Conrad, T.M., Frazier, M., Joyce, A.R., Cho, B. K., Knight, E. M., Lewis, N.E., Landick, R., Palsson, B.Ø. RNA polymerase mutants found through adaptive evolution re-program Escherichia coli K-12 MG1655 for optimal growth in minimal media. Proc. Nat. Acad. Sci. USA, 107:20500-5 (2010).
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
2004
1. Merrell, K., Southwick, K., Graves, S.W., Esplin, M.S., Lewis, N.E., Thulin, C.D. Analysis of low-abundance, low-molecular-weight serum proteins using mass spectrometry. J. Biomol. Tech., 15:238-48 (2004).
Patents and patent applications
6. Lewis, N.E., Spahn, P., Li, S., Hefzi, H. Methods to Stabilize Mammalian Cells. Patent pending – provisional.
5. Lewis, N.E., Chiang, W.T., Puig, M., Zhang, Y., Rosenberg, A. Method to Suppress Viral Infection of Mammalian Cells. Patent PCT/US2019/048361.
4. Lewis, N.E., Gazestani, V., Pramparo, T., Courchesne, E. Expression-based diagnosis, prognosis, and treatment of complex diseases. Patent PCT/US2019/041618.
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.
