Publications

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Selected publications

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.

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 frameworkbioRxiv (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 puritybioRxiv (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 modelsbioRxiv, (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 analysisbioRxiv (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 secretionbioRxiv (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 severityNature 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 suiteNature 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 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

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 subtypesNature 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 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

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 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

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

Press releases at phys.orgUCSD Health Sciences

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/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 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

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 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.

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 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

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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

2013

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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

2012

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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.

2011

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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).

2010

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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).

2009

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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

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 spectrometryJ. 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.