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Selected publications

Genome-scale reconstructions of the mammalian secretory pathway predict … protein secretionNature Communications, (2020).

A perturbed gene network … in leukocytes is linked to ASD genetics and symptom severityNature Neuroscience, (2019).

A systematic evaluation of methods for tailoring genome-scale metabolic modelsCell Systems, 4, 1-12 (2017).

A consensus genome-scale reconstruction of Chinese hamster ovary cell metabolismCell Systems, 3, 434 (2016).

Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genomeNature Biotechnology. 31:759 (2013).

Network context and selection in the evolution to enzyme specificityScience. 337:1101 (2012).

All publications

corresponding author, * equal contribution
For a current list, click here.


110. Schinn S-M, Morrison C, Wei W, Zhang L, Lewis NE. Systematic evaluation of parameterization for genome-scale metabolic models of cultured mammalian cells. bioRxiv (2020). DOI:10.1101/2020.06.24.169938.

109. Kellman, B.P.*, Zhang, Y.*, Logomasini, E., Meinhardt, E., Chiang, A.W.T., Sorrentino, J., Liang, A., Bao, B., Zhou, Y., Akase, S., Sogabe, I, Kuoka, T., Wilson, I.B.H., Campbell, M.P., Neelamegham, S., Krambeck, F.,J., Aoki-Kinoshita, K.F., Lewis, N.E. A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR). bioRxiv (2020).DOI: 10.1101/2020.05.31.126623

108. Gazestani, V., Chiang, A.W.T., Courchesne, E.‡, Lewis, N.E. Autism genetics perturb prenatal neurodevelopment through a hierarchy of broadly-expressed and brain-specific genes. bioRxiv (2020). DOI: 10.1101/2020.05.24.112623

107. Xiong, K., la Cour Karottki, K.J., Hefzi, H., Li, S., Grav, L.M., Li, S., Spahn, P., Lee, J.S., Lee, G.M., Kildegaard, H.F., Lewis, N.E.‡, Pedersen, L.E.‡ Using targeted genome integration for virus-free genome-wide mammalian CRISPR screen. bioRxiv (2020). DOI: 10.1101/2020.05.19.103648

106. Samoudi, M.*, Kuo, C.C.*, Robinson, C.M.*, Shams-Ud-Doha, K., Schinn, S.M., Kol, S., Weiss, L., Bjorn, S.P., Voldborg, B.G., Campos, A.R., Lewis, N.E. In situ detection of protein interactions for recombinant therapeutic enzymes. bioRxiv (2020). DOI: 10.1101/2020.05.06.081885

105. la Cour Karottki, K.J., Hefzi, H., Li, S., Pedersen, L.E., Spahn, P., Ruckerbauer, D., Bort, J.H., Thomas, A., Lee, J.S., Borth, N., Lee, G.M., Kildegaard, H.F.*, Lewis, N.E.* A metabolic CRISPR-Cas9 screen in Chinese hamster ovary cells identifies glutamine-sensitive genes. bioRxiv (2020). DOI: 10.1101/2020.05.07.081604

104. Richelle, A., Kellman, B.P., Wenzel, A.T., Chiang, A.W.T., Reagan, T., Gutierrez, J.M., Joshi, C., Li, S., Liu, J.K., Masson, H., Lee, J., Li, Z., Heirendt, L., Trefois, C., Juarez, E.F., Bath, T., Borland, D., Mesirov, J.P., Robasky, K., Lewis, N.E. What does your cell really do? Model-based assessment of mammalian cells metabolic functionalities from omics data. bioRxiv (2020). DOI:10.1101/2020.04.26.057943

103. Kellman, B.P.*, Baghdassarian, H.M.*,Pramparo, T., Shamie, I., Gazestani, V.H., Begzati, A., Li, S., Nalabolu, S., Murray, S., Lopez, L., Pierce, K., Courchesne, E., Lewis, N.E. Multiple freeze-thaw cycles lead to a loss of consistency in poly(A)-enriched RNA sequencing. bioRxiv (2020). DOI: 10.1101/2020.04.01.020792

102. 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 frameworkbioRxiv (2019). DOI: 10.1101/693507

101. Lin, D., Yalamanchili, H., Zhang, X., Lewis, N.E., Alves, C.L., Groot, J., Arnsdorf, J., Bjørn, S.P., Wulff, T., Voldborg, B.G., Zhou, Y., Zhang, B. CHOmics: a web-based tool for multi-omics data analysis and interactive visualization in CHO cell linesbioRxiv (2020). DOI: 10.1101/2020.03.17.995290

100. Fouladiha, H., Marashi, S.A., Li, S., Li, Z., Masson, H.O., Vaziri, B., Lewis, N.E. Systematically gap-filling the genome-scale model of CHO cells. bioRxiv (2020). DOI: 10.1101/2020.01.27.921296

99. Lakshmanan, M., Long, S., Ang, K.S., Lewis, N E,  Lee, D.Y. On the impact of biomass composition in constraint-based flux analysisbioRxiv (2019). DOI: 10.1101/652040


98. Zhao P, Praissman JL, Grant OC, Cai Y, Xiao T, Rosenbalm KE, Aoki K, Kellman BP, Bridger R, Barouch DH, Brindley MA, Lewis NE, Tiemeyer M, Chen B, Woods RJ, Wells L. Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor. Cell Host & Microbe. accepted (2020). DOI:10.1101/2020.06.25.172403

97. Manresa MC, Chiang AWT, Kurten RC, Dohil R, Brickner H, Dohil L, Herro R, Akuthota P, Lewis NE, Croft M, Aceves SS. Increased Production of LIGHT by T Cells in Eosinophilic Esophagitis Promotes Differentiation of Esophageal Fibroblasts Toward an Inflammatory Phenotype. Gastroenterology. S0016-5085(20)34997-0 (2020). DOI: 10.1053/j.gastro.2020.07.035.

96. Kol, S., Ley, D., Wulff, T., Decker, M., Arnsdorf, J., Schoffelen, S., Hansen, A.H., Gutierrez, J.M., Chiang, A.W.T., Masson, H.O., Palsson, B.O., Voldborg, B.G., Pedersen, L.E., Kildegaard, H.F., Lee, G.M., Lewis, N.E. Multiplex secretome engineering enhances recombinant protein production and purityNature Communications, 11:1908 (2020). DOI: 10.1038/s41467-020-15866-w. News coverage: Nature Bioengineering, UCSD Jacobs,, Genetic Engineering and Biotechnology News,

95. Saba*, J. A. , Ke*, W. , Yao, C. , Drangowska-Way, A. , Joshi, C., Mony, V.K., Hilzendeger, M., Liu, X., Liu, J., Benjamin, S., Locasale, J., Patti, G., Lewis, N.E.‡, O’Rourke, E.J.‡ Dietary serine enhances chemotherapeutic toxicity in C. elegans through promoting thymidine deficiency in the microbiota. Nature Communications, 11:2587 (2020). DOI: 10.1038/s41467-020-16220-w News coverage: UVAToday

94. Szeliova, D., Ruckerbauer, D.E., Galleguillos, S.N., Petersen, L.B., Natter, K., Hanscho, M., Troyer, C. Causon, T., Schoeny, H., Christensen, H.B., Lee, D.Y., Lewis, N.E., Koellensperger, G., Hann, S., Nielsen, L., Borth, N., Zanghellini, J. What CHO is made of: Variations in the biomass composition of Chinese hamster ovary cell lines. Metabolic Engineering, accepted (2020). DOI: 10.1016/j.ymben.2020.06.002

93. Weiss, R.J.*, Spahn, P.N.*, Chiang, A.W.T., Li, J., Kellman, B.P., Benner, C., Glass, C.K., Gordts, P.L.S.M., Lewis, N.E.‡, Esko, J.D.‡ ZNF263 is a novel transcriptional regulator of heparin and heparan sulfate biosynthesis, Proc. Nat. Acad. Sci. USA, 117:9311-9317 (2020). DOI: 10.1073/pnas.1920880117 News coverage: UCSD Jacobs,, Genetic Engineering and Biotechnology News, Biopharma Reporter

92. Joshi, C., Schinn, S., Richelle, A.Shamie, I., O’Rourke, E., Lewis, N.E. StanDep: capturing transcriptomic variability improves context-specific metabolic modelsPLoS Computational Biology, 16(5): e1007764. (2020). DOI: 10.1371/journal.pcbi.1007764

91. Courchesne, E.*, Gazestani, V.H.*, Lewis, N.E.* Prenatal origins of ASD: The when, what and how of ASD development. Trends in Neurosciences, 43:326 (2020).

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 productionBioprocess and Biosystems Engineering (2020). DOI: 10.1007/s00449-020-02332-6

89. Liang, C.*, Chiang,. A.W.T.*, Hansen, A.H., Arnsdorf, J., Schoffelen, S., Sorrentino, J.T., Kellman, B.P., Bao, B., Voldborg, B.G., Lewis, N.E. A Markov model of glycosylation elucidates isozyme specificity and glycosyltransferase interactions for glycoengineering. Current Research in Biotechnology. 2:22-36 (2020). DOI: 10.1016/j.crbiot.2020.01.001 News coverage: Bioanalysis Zone

88.  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 secretionNature Communications, 11:68 (2020). DOI: 10.1038/s41467-019-13867-y News coverage:

87. Speir, M., Nowell, C.J., Chen, A.A., O’Donnell, J.A., Shamie, I., Lakin, P.R., D’Cruz, A.A., Braun, R.O., Babon, J.J., Lewis, R.S., Bliss-Moreau, M., Shlomovitz, I., Wang, S., Cengia, L.H., Stoica, A.I., Hakem, R., Kelliher, M.A., O’Reilly, L.A., Patsiouras, H., Lawlor, K.E., Weller, E., Lewis. N.E., Roberts, A.W., Gerlic, M., Croker, B.A. PTPN6 inhibits caspase-8- and RIPK3/MLKL-dependent inflammation. Nature Immunology, 21:54–64 (2020). DOI:10.1038/s41590-019-0550-7

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, 117, 593-598 (2020). DOI: 10.1002/bit.27199

85.  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 suiteNature Biotechnology, 38:272–276 (2020). DOI: 10.1038/s41587-020-0446-y


84. 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 severityNature Neuroscience, 22, 1624–1634 (2019). DOI: 10.1038/s41593-019-0489-x, bioRxiv: 10.1101/435917, News coverage: Spectrum News, Genomeweb, Medical News, Technology Networks, Neuroscience News

83. 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

82. 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, 1:49-57 (2019). doi: 10.1016/j.crbiot.2019.09.001

81. Li, S.*, Richelle, A.*, Lewis, N.E. Enhancing product and bioprocess attributes using genome-scale models of CHO metabolismCell 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 ProcessesCell 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 networksPLoS 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 immunityScientific 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 elementsJournal 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 BiologyCurrent 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 InterferenceBiotechnology 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 functionsPLoS 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 EngineeringACS 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 adenocarcinomaCell, 177:572-586 (2019).

71. Lee, J.S., Kildegaard, H.F., Lewis, N.E., Lee, G.M. Deciphering Clonal Variation in Recombinant Mammalian Cell LinesTrends in Biotechnologyin 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 v3.0Nature 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 infectionNature 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 mannerEvolutionary Applications, 12:337-349 (2019). DOI: 10.1111/eva.12744


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 subtypesNature Neuroscience, 21, 1680–1688 (2018). DOI: 10.1038/s41593-018-0281-3 News Coverage:

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 editingACS 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 workflowProc. 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 generationACS 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 regulationNature 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 elegansFrontiers 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 strategyBiotechnology 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 phenotypeMolecular 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 cellsCurrent 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 targetingPLoS 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 cellsbioRxiv (2018). DOI: 10.1101/465815


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 ScreensScientific 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 effectFrontiers 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 engineeringCurrent 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 infantsGut, 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 modelsCell 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 modelBiotechnology 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 secretionScientific 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 interactionsNature 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 InvasionmBio, 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 autismMolecular Autism, 8:29 (2017). DOI: 10.1186/s13229-017-0147-7

46. Hastings, J., et al. WormJam: Consensus C. elegans metabolic reconstruction and metabolomics communityWorm, 6:e1373939 (2017). DOI:10.1080/21624054.2017.1373939


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 metabolismCell Systems, 3, 434-443 (2016). DOI:10.1016/j.cels.2016.10.020

News coverage: phys.orgUCSD Health Sciences, Nordic Life Science News, Novo Nordisk Fonden

44. Chiang, A.W.T., Li, S., Spahn, P.N., Richelle, A., Kuo, C.C., Samoudi, M.,  Lewis, N.EModulating carbohydrate-protein interactions through glycoengineering of monoclonal antibodies to impact cancer physiologyCurrent Opinion in Structural Biology, 10, 104–111 (2016). DOI: 10.1016/

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 metabolismMetabolomics, 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 diagnosisGenome 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 glycoengineeringMetabolic Engineering,  33: 52–66 (2016). DOI:10.1016/j.ymben.2015.10.007


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 ToddlersMolecular 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 modelingBiotechnology 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 modelsBioinformatics, 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.


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 cellsMolecular Systems Biology, 10:760 (2014). DOI: 10.15252/msb.20145508. * equal contribution

29. Spahn, P., Lewis, N.E.‡ Systems glycomics for glycoengineeringCurrent 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 cellsPharmaceutical 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 micePLoS 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 interactionsMolecular 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 SequencingNature Reviews Genetics. 15:56–62 (2014). DOI: 10.1038/nrg3655  corresponding author, * equal contribution


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24. Lewis, N.E.‡, Abdel-Haleem, A.M. The evolution of genome-scale models of cancer metabolismFront. 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 genomeNature 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 BiotechnologyCurrent 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 metabolismMolecular BioSystems, 9:167 (2013). doi: 10.1039/c2mb25453k


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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 specificityScience. 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 networksBMC 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 cellsJournal 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 scaleNature 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 methodsNature Reviews Microbiology.10:291-305 (2012). Click here for accompanying website with a catalog of constraint-based methods.


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14. Xu, X.*, Nagarajan, H.*, Lewis, N.E.*, Pan, S.*,et al. The Genomic Sequence of the Chinese Hamster Ovary (CHO) K1 cell lineNature 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 v2.0Nature 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 evolutionCurrent 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 ScienceMolecular Systems Biology, 7:509 (2011).

10. Schellenberger, J., Lewis, N.E., Palsson, B.Ø. Elimination of thermodynamically infeasible loops in steady state metabolic modelsBiophysical Journal, 100:544-53 (2011).


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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 brainNature 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 mediaProc. 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 reconstructionsMolecular 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 MG1655Appl. 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 modelsMolecular Systems Biology, 6:390 (2010).

4. Bar-Even, A., Noor, E., Lewis, N.E., Milo, R. Design and analysis of synthetic carbon fixation pathwaysProc. Natl. Acad. Sci. USA., 107:8889-8894 (2010).


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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 contentJ. 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


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 spectrometryJ. Biomol. Tech., 15:238-48 (2004).

Patents and applications

9. Lewis, N.E., Chiang, W.T., Liang, C., Sorrentino, J.T. Method of Measuring Complex Carbohydrates at the Nano-Scale. Patent pending – provisional.

8. Martino, C., Kellman, B., Lewis, N.E., Knight, R., Sandoval, D., Esko, J., Mandel-Clausen, T. Application of microbial glycosidase as a therapeutic or anti-viral. Patent pending – provisional.

7. Lewis, N.E., Liang, C., Chiang, W.T. Methods of Designing Carbohydrates. Patent pending – provisional.

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.