See below for our recent publications in peer-reviewed journals, books, and patents. Also, icons to the right filter publications by major topics. Public presentations and lectures can also be downloaded from here.
‡corresponding/senior author, * equal contribution
For a current list, click here.
Preprints under peer review
Masson H.*, Tat J.*, Di Giusto P.*, Antonakoudis A., Shamie I., Baghdassarian H., Samoudi M., Robinson C. M., Kuo C.C., Koga N., Singh S., Gezalyan A., Li Z., Movsessian A., Richelle A., Lewis N.E.‡ A reconstruction of the mammalian secretory pathway identifies mechanisms regulating antibody production, bioRxiv (2024). doi: 10.1101/2024.11.14.623668
Bai D., Mo S., Zhang R., Luo Y., Gao J., Yang J.P., Wu Q., Singh D., Rahmani H., Amariuta T., Grotjahn D., Zhong S., Lewis N., Wang W., Ideker T., Xing E., Xie P. scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell Transcriptomics, bioRxiv (2024).
Zahiri J., Mirzaie M., Duan K., Xiao Y., Aamodt C., Nazari S., Andreason C., Lopez L., Barnes C. C., Arias S., Nalabolu S., Pierce K., Lewis N., Courchesne E. Beyond the Spectrum: Subtype-Specific Molecular Insights into Autism Spectrum Disorder Via Integrated Transcriptomic Analysis, medRxiv (2024).
Lin W.J., Chiang A.W.T., Zhou E.H., Liang C., Liu C.H., Ma W.L., Cheng W.C., Lewis N.E. iLipidome: enhancing statistical power and interpretability using hidden biosynthetic interdependencies in the lipidome, bioRxiv (2024).
Kellman B., Sandoval D., Zaytseva O., Brock K., Baboo S., Nachmanson D., Irvine E., Armingol E., Mih N., Zhang Y., Jeffris M., Bartels P., Nguyen T., Tam A., Gasman S., Ilan S., Shamie I., Diedrich J., Wang X., van Woudenbergh E., Altman M., Aylward A., Bao B., Castro A., Sorrentino J., Chiang A., Campbell M., Bartsch Y., Aguilar-Calvo P., Sigurdson C., Alter G., Lauc G., Yates J. III, Marks D., Lisacek F., Lewis N.E. Protein structure, a genetic encoding for glycosylation, bioRxiv (2024).
Kellman B., Mariethoz J., Zhang Y., Shaul S., Jeffris M., Sandoval D., Jeffris M., Armingol E., Bao B., Lisacek F., Bojar D., Lewis N.E. Decoding glycosylation potential from protein structure across human glycoproteins with a multi-view recurrent neural network, bioRxiv (2024).
Rocamora F., Schoffelen S., Arnsdorf J., Toth E.A., Abdul Y., Cleveland T.E., Bjorn S.P., Wu Y.M., McElvaney N.G., Voldborg B.G.R., Fuerst T.R., Lewis N.E.‡ Glycoengineered recombinant alpha1-antitrypsin results in comparable in vitro and in vivo activities to human plasma-derived protein, bioRxiv (2024).
Li H*, Peralta A.G.*, Schoffelen S., Hansen A.H., Arnsdorf J., Schinn S., Skidmore J., Choudhury B., Paulchakrabarti M., Voldborg B.G., Chiang A.W.T., Lewis N.E.‡ LeGenD: determining N-glycoprofiles using an explainable AI-leveraged model with lectin profiling, bioRxiv (2024).
Masson H.O., Kuo C.C., Malm M., Lundqvist M., Sievertsson Å, Berling A., Tegel H., Hober S., Uhlén M., Grassi L., Hatton D., Rockberg J.‡, Lewis N.E.‡ Deciphering the determinants of recombinant protein yield across the human secretome, bioRxiv (2022).
Armingol E., Larsen R.O., Cequeira M, Baghdassarian H., Lewis N.E. Unraveling the coordinated dynamics of protein- and metabolite-mediated cell-cell communication. bioRxiv (2022)
Chiang A.W.T., Gazestani V.H., Altieri M.G., Courchesne E., Lewis N.E. Optimal balancing of clinical factors in large scale clinical RNA-Seq studies. bioRxiv (2021). doi: 10.1101/2021.06.30.450639
2024
179. Kavoni H., Savizi I.S.P., Lewis N.E., Shojaosadati S.A. Recent advances in culture medium design for enhanced production of monoclonal antibodies in CHO cells: A comparative study of machine learning and systems biology approaches. Biotechnology Advances, in press (2024).
178. Baek M., Kim C.L., Kim S.H., Karottki K.J.L.C., Hefzi H., Grav L.M., Pedersen L.E., Lewis N.E., Lee J.S., Lee G.M. Unraveling productivity-enhancing genes in Chinese hamster ovary cells via CRISPR activation screening using recombinase-mediated cassette exchange system. Metabolic Engineering, in press (2024).
177. Scapin G., Çagdas E., Grav L.M., Lewis N.E., Goletz S., Hafkenscheid L. Implications of glycosylation for the development of selected cytokines and their derivatives for medical use. Biotechnology Advances, in press (2024).
176. Pessentheiner A.R., Spann N.J., Autran C.A., Ramms B., Chiang A.W.T., Grunddal K.V., Wang Y., Quach A., Booshehri L.M., Hammond A., Tognaccini C., Latasiewicz J., Witztum J.L., Hoffman H.M., Lewis N.E., Glass C.K., Bode L., Gordts P.L.S.M. The Human Milk Oligosaccharide 3-Sialyllactose Promotes Inflammation Resolution and Reduces Atherosclerosis Development in Mice. JCI Insight, in press (2024).
175. Hefzi H., Martínez-Monge I., Marin de Mas I., Cowie N.L., Gomez Toledo A., Noh S.M., la Cour Karottki K.J., Decker M., Arnsdorf J., Camacho-Zaragoza J.M., Kol S., Schoffelen S., Pristovšek N., Holmgaard A. H., Miguez A.A., Bjorn S.P., Brøndum K.K., Javidi E.M., Jensen K.L., Stangl L., Kreidl E., Kallehauge T.B., Ley D., Ménard P., Petersen H.M., Sukhova Z., Bauer A., Casanova E., Barron N., Malmström J., Nielsen L.K., Lee G.M., Kildegaard H.F., Voldborg B.G., Lewis N.E. Multiplex genome editing eliminates the Warburg Effect without impacting growth rate in mammalian cells, Nature Metabolism, accepted (2024).
174. Gopalakrishnan S., Johnson W., Valderrama-Gomez M.A., Icten E., Tat J., Lay F., Diep J., Gomez N., Stevens J., Schlegel F., Rolandi P., Kontoravdi C., Lewis N.E.‡ Multi-omic characterization of antibody-producing CHO cell lines elucidates metabolic reprogramming and nutrient uptake bottlenecks. Metabolic Engineering, 85:94-104 (2024). bioRxiv preprint.
173. Yom A., Chiang A.W.T., Lewis N.E.‡. A Boltzmann model predicts glycan structures from lectin binding. Analytical Chemistry, 96:8332–8341 (2024). doi: 10.1021/acs.analchem.3c04992
172. Park S., Choi D., Song J., Lakshmanan M., Richelle A., Yoon S., Kontoravdi C., Lewis N.E., Lee D. Driving towards digital biomanufacturing by CHO genome-scale models. Trends in Biotechnology, accepted (2024)
171. Gopalakrishnan S., Johnson W., Valderrama-Gomez M.A., Icten E., Tat J., Ingram M., Shek C.F., Chan P.K., Schlegel F., Rolandi P., Kontoravdi C., Lewis N.E. COSMIC-dFBA: A novel multi-scale hybrid framework for bioprocess modeling. Metabolic Engineering, 82:183-192 (2024).
170. Liang C., Murray S., Li Y., Lee R., Low A., Sasaki S., Chiang A.W.T., Lin W.J., Mathews J., Barnes W. Lewis N.E. LipidSIM: inferring mechanistic lipid biosynthesis perturbations from lipidomics with a flexible, low-parameter, systematic Markov Modeling framework. Metabolic Engineering, 82:110-122 (2024).
169. Baghdassarian H.M.*, Dimitrov D.*, Armingol E.*, Saez-Rodriguez J.‡, Lewis N.E‡. Combining LIANA and Tensor-cell2cell to decipher cell-cell communication across multiple samples. Cell Reports Methods, 4:100758 (2024).
168. Lewis N.E., Aceves S.S. Eosinophilic Esophagitis: Shifting Immune Complexity Beyond the Eosinophil. J Allergy Clin Immunol, 153: 669-671 (2024).
167. Armingol E.‡, Baghdassarian H., Lewis N.E.‡ The diversification of methods for studying cell–cell interactions and communication. Nature Reviews Genetics, in press (2024).
166. Pong A., Mah C.K., Yeo G.W., Lewis N.E. Computational cell-cell interaction technologies drive mechanistic and biomarker discovery in the tumor microenvironment. Current Opinion in Biotechnology, 85:103048 (2024).
165. Masson H.O., Samoudi M., Robinson C.M., Kuo C.C., Weiss L., Shams-Ud-Doha K., Campos A.R., Tejwani V., Dahodwala H., Menard P., Voldborg B.G., Sharfstein S.T., Lewis N.E. Inferring secretory and metabolic pathway activity from omic data with secCellFie. Metabolic Engineering, 81, 273-285 (2024). bioRxiv preprint
164. Rawson R., Duong L., Tkachenko E., Chiang A.W.T., Okamoto K., Dohil R., Lewis N.E., Kurten R., Abud E.M., Aceves S.S. Mechanotransduction Induced Interplay between Phospholamban and Yes Activated Protein Induces Smooth Muscle Cell Hypertrophy. Mucosal Immunology, in press (2024).
163. Baghdassarian H., Lewis N.E. Resource Allocation in Mammalian Systems. Biotechnology Advances, 71, 108305 (2024). Preprint
162. Siddharth T., Lewis N.E. Predicting pathways for old and new metabolites through clustering. Journal of Theoretical Biology, 578, 111684 (2024). preprint
2023
161. Toledo A.G., Bratanis E., Velásquez E., Chowdhury S., Sorrentino J.T., Karlsson C., Lewis N.E., Esko J.D., Collin M., Shannon O., Malmström J. Pathogen-driven degradation of endogenous and therapeutic antibodies in vivo during streptococcal infections. Nature Communications, 14(1):6693 (2023). doi:10.1038/s41467-023-42572-0
160. Kim S.H., Shin S.H., Baek M, Xiong K., Karottki K.J.L.C., Hefzi H., Grav L.M., Pedersen L.E., Kildegaard H.F., Lewis N.E., Lee J.S., Lee G.M. Identification of hyperosmotic stress-responsive genes in Chinese hamster ovary cells via genome-wide virus-free CRISPR/Cas9 screening. Metabolic Engineering, 80:66-77 (2023). doi:10.1016/j.ymben.2023.09.006
159. Aamodt CM, Lewis, NE. Single-cell A/B testing for cell-cell communication, Cell Systems, 14, 428-429 (2023).
158. Rocamora F., Peralta A.G., Shin S., Sorrentino J., Wu M., Toth E.A., Fuerst T.A., Lewis N.E. Glycosylation Shapes the Efficacy and Safety of Diverse Protein, Gene and Cell Therapies, Biotechnology Advances, 67, 108206 (2023). preprint
157. Baghdassarian H., Blackstone S.A., Clay O.S., Philips R., Matthiasardottir B., Nehrebecky M., Hua V.K., McVicar R., Liu Y., Tucker S.M., Randazzo D., Deuitch N., Rosenzweig S., Mark A., Sasik R., Fisch K.M., Chavan P.P., Eren E., Watts N.R., Gadina M., Schwartz D.M., Sanyal A., Werner G., Murdock D.R., Horita N., Chowdhury S., Dimmock D., Jepsen K., Remmers E.F., Goldbach-Mansky R., Gahl W.A., O’Shea J.J., Milner J.D., Lewis N.E., Chang J., Kastner D.L., Torok K., Oda H., Putnam C.D., Broderick L. Variant STAT4 and Response to Ruxolitinib in an Autoinflammatory Syndrome. New England Journal of Medicine, 388(24):2241-2252 (2023). doi: 10.1056/NEJMoa2202318
156. Ghaddar A., Armingol E., Huynh C., Gevirtzman L., Lewis N.E., Waterston R., O’Rourke E. Whole-body gene expression atlas of an adult metazoan, Science Advances, 9:eadg0506. (2023).
155. Choi YM, Choi DH, Lee YQ, Koduru L, Lewis, NE, Lakshmanan M, Lee, D.Y. Mitigating biomass composition uncertainties in flux balance analysis using ensemble representations. Computational and Structural Biotechnology Journal, 21:3736-3745 (2023). doi: 10.1016/j.csbj.2023.07.025
154. Azadiana S., Doustmohammadi A., Naseri M., Khodarahmi M., Arab S.S., Yazdanifar M., Zahiri J.*, Lewis N.E.* Reconstructing the Cell-Cell Interaction Network Among Mouse Immune Cells. Biotechnology & Bioengineering, 120(9), 2756-2764 (2023). doi: 10.1002/bit.28431
153. Liang C., Chiang A.W.T.‡, Lewis N.E.‡ GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data, STAR Protocols, 4, 102244 (2023). doi: 10.1016/j.xpro.2023.102244.
152. Masson H.O., Karottki K.J.L.C., Tat J., Hefzi H.‡, Lewis N.E.‡ From Observational to Actionable: rethinking Omics in Biologics Production, Trends in Biotechnology, 41(9), 1127-1138 (2023). preprint doi: 10.1016/j.tibtech.2023.03.009
151. Zhang Y., Krishnan S., Bao B., Chiang A.W.T., Sorrentino J.T., Schinn S.M., Kellman B.P.‡, Lewis N.E.‡ Preparing glycomics data for robust statistical analysis with GlyCompareCT, STAR Protocols, 4 (2), 102162 (2023). doi: 10.1016/j.xpro.2023.102162
150. Masson H.O., Borland D., Reilly J., Telleria A., Shrivastava S., Watson M., Bustillo L., Li Z., Capps L., Kellman B.P., King Z.A., Richelle A., Lewis N.E.‡, Robasky K.‡ ImmCellFie: A user-friendly web-based platform to infer metabolic function from omics data. STAR Protocols, 4 (1), 102069 (2023) doi: 10.1016/j.xpro.2023.102069
149. Ha TK*, Òdena A*, Karottki KJLC, Kim CL, Hefzi H, Lee GM, Kildegaard HF, Nielsen LK, Grav LM, Lewis NE. Enhancing CHO cell productivity through a dual selection system in glutamine free medium. Biotechnology & Bioengineering, 120 (4), 1159-1166. (2023). doi: 10.1002/bit.28318, Preprint
148. Gopalakrishnan S., Joshi C.J., Valderrama Gomez M., Icten E., Rolandi P., Johnson W., Kontoravdi C., Lewis N.E. Guidelines for extracting biologically relevant context-specific metabolic models using gene expression data, Metabolic Engineering, 75, 181-191 (2023). doi: 10.1016/j.ymben.2022.12.003, bioRxiv preprint
147. Kotidis P., Donini R., Arnsdorf J., Hansen A.H., Voldborg B.G.R., Chiang A.W.T., Haslam S., Betenbaugh M., Jimenez del Val I., Lewis N.E., Krambeck F, Kontoravdi C. CHOGlycoNET: Comprehensive Glycosylation Reaction Network for CHO cells, Metabolic Engineering, 76, 87-96 (2023). doi: 10.1016/j.ymben.2022.12.009
2022
146. Armingol E., Ghaddar A., Joshi C.J., Baghdassarian H.M., Shamie I., Chan J., Her H.L., Berhanu S., Dar A., Rodriguez-Armstrong F., Yang O., O’Rourke E.J.‡, Lewis N.E.‡ Inferring the spatial code of cell-cell interactions across a whole animal body. PLoS Computational Biology, 18(11): e1010715 (2022). DOI: 10.1371/journal.pcbi.1010715 (see https://lewislab.ucsd.edu/cell2cell/ for cell2cell code)
145. Kenefake D., Armingol E., Lewis N.E., Pistikopoulos E.N. An Improved Algorithm for Flux Variability Analysis. BMC Bioinformatics, 23, 550 (2022).
144. Sasmal A., Khan N., Khedri Z., Kellman B.P., Srivastava S., Verhagen A., Yu H., Bruntse A.B., Diaz S., Varki N., Beddoe T., Paton A.W., Paton J.C., Chen X., Lewis N.E., Varki A. Simple and practical sialoglycan encoding system reveals vast diversity in nature and identifies a universal sialoglycan-recognizing probe derived from AB5 toxin B subunits. Glycobiology, 32, 1101-1115 (2022). doi: 10.1093/glycob/cwac057
143. Bao B.*, Zahiri J.*, Gazestani V.H.*, Lopez L., Xiao Y., Kim R., Wen T., Chiang A.W.T., Nalabolu S., Pierce K., Robasky K., Wang T., Hoekzema T., Eichler E.E., Lewis N.E.‡, Courchesne, E.‡. A Predictive Ensemble Classifier for the Molecular Diagnosis of ASD at Ages 1 to 4 Years. Molecular Psychiatry, (2022). doi: 10.1038/s41380-022-01826-x
142. Sorrentino JT, Golden GJ, Morris C, Painter C, Nizet V, Campos AR, Smith JW, Karlsson C, Malmström J, Lewis NE, Esko JD, Toledo AG. Vascular proteome responses precede organ dysfunction in a murine model of Staphylococcus aureus bacteremia, mSystems, 7(4) (2022). doi: 10.1128/msystems.00395-22
141. Li H., Chiang A.W.T.‡, Lewis N.E.‡. Artificial Intelligence in the analysis of glycosylation data. Biotechnology Advances, 60, 108008 (2022). doi: 10.1016/j.biotechadv.2022.108008
140. Joshi C.J., Ke W., Drangowska-Way A., O’Rourke E.J.‡, Lewis N.E.‡ What are housekeeping genes? PLoS Computational Biology, 18:e1010295 (2022).
139. Tsai CM, Caldera JR, Hajam IA, Chiang AWT, Tsai CH, Li H, Lázaro-Díez M, Gonzalez C, Trieu D, Martins GA, Underhill DM, Arditi M, Lewis NE, Liu GY. Non-protective immune imprint underlies failure of S. aureus IsdB vaccine. Cell Host and Microbe, 30, 1163-1172 (2022).
138. Armingol E.*, Baghdassarian H.*, Martino C., Perez-Lopez A., Aamodt C., Knight R., Lewis N.E. Context-aware deconvolution of cell-cell communication with Tensor-cell2cell. Nature Communications, 13, 3665 (2022). doi: 10.1038/s41467-022-31369-2 , Nature Portfolio Bioengineering (see https://lewislab.ucsd.edu/cell2cell/ for more info)
137. Kellman B.P.*, Richelle A.*, Yang J.Y.E., Chapla D.G., Chiang A.W.T., Najera J., Liang C, Fürst A, Bao B., Koga N., Mohammad M.A., Bruntse A.B., Haymond M.W., Moremen K.W., Bode L., Lewis N.E.. Elucidating Human Milk Oligosaccharide biosynthetic genes through network-based multi-omics integration. Nature Communications, 13, 2455 (2022). doi: 10.1038/s41467-022-29867-4
136. Malm M.*, Kuo C.C.*, Barzadd M.M., Mebrahtu A., Wistbacka N., Razavi R., Volk A.L., Lundqvist M., Kotol D., Edfors F., Gräslund T., Chotteau V., Field R., Varley P.G., Roth R.G., Lewis N.E.‡, Hatton D., Rockberg J.‡ Harnessing secretory pathway differences between HEK293 and CHO to rescue production of difficult to express proteins. Metabolic Engineering, 72, 171-187 (2022). bioRxiv doi: 10.1101/2021.08.16.455786, DOI: 10.1016/j.ymben.2022.03.009, PMCID: PMC9189052
135. Thacker B.E., Thorne K.J., Cartwright C., Park J., Glass K., Chea A., Kellman B.P., Lewis N.E., Wang Z., Di Nardo A., Sharfstein S.T., Jeske W., Walenga J., Hogwood J., Gray E., Mulloy B., Esko J.D., Glass C.A. Multiplex genome editing of mammalian cells for producing recombinant heparin. Metabolic Engineering, 70, 155-165 (2022). doi: 10.1016/j.ymben.2022.01.002
134. Stanley P., Moremen K.W., Lewis N.E., Taniguchi N., Aebi M. N-Glycans, in Essentials of Glycobiology, 4th Edition (2022), Cold Spring Harbor Laboratory Press.
133. Spahn, P.N.*, Zhang, X.*, Hu, Q., Hamaker, N., Hefzi, H., Li, S., Kuo, C.C., Huang, Y., Lee, J.C., Ly, P. , Lee, K.H.,‡ Lewis, N.E.‡ Restoration of deficient DNA Repair Genes Mitigates Genome Instability and Increases Productivity of Chinese Hamster Ovary Cells. Biotechnology & Bioengineering, 119, 963-982 (2022). doi: 10.1002/bit.28016, bioRxiv doi: 10.1101/2021.01.07.425558
132. Xiao Y, Wen TH, Kupis L, Eyler L, Goel D, Vaux K, Lombardo MV, Lewis NE, Pierce K, Courchesne E. Neural responses to affective speech, including motherese, map onto clinical and social eye tracking profiles in ASD toddlers. Nature Human Behavior, 6, 443–454 (2022).
131. Savizi I.S.P., Maghsoudi N., Motamedian E., Lewis N.E., Shojaosadati S.A. Valine feeding reduces ammonia production through rearrangement of metabolic fluxes in central carbon metabolism of CHO cells. Applied Microbiology and Biotechnology, 106, 1113–1126 (2022). doi:10.1007/s00253-021-11755-4, Authorea preprint
130. Manresa M.C., Wu A., Nhu Q., Chiang A.W.T., Okamoto K., Miki H., Kurten R., Pham E., Duong L.D., Lewis N.E., Akuthota P., Croft M. Aceves S.S. LIGHT controls distinct homeostatic and inflammatory gene expression profiles in esophageal fibroblasts via differential HVEM and LTβR-mediated mechanisms. Mucosal Immunology, 15, 327–337 (2022).
2021
129. Golden, GJ, Toledo, AG, Marki, A, Sorrentino, JT, Morris, C, Riley, RJ, Spliid, C, Chen, Q, Cornax, I, Lewis, NE, Varki, N, Le, D, Malmström, J, Karlsson, C, Ley, K, Nizet, V, Esko, JD. Endothelial Heparan Sulfate Mediates Hepatic Neutrophil Trafficking and Injury during Staphylococcus aureus Sepsis, mBio,12(5):e0118121 (2021). PMCID: PMC8546592
128. Zhu, Y.P., Shamie, I., Lee, J.C., Nowell, C.J., Peng, W., Angulo, S., Le, L.N.N., Liu, Y., Miao, H., Xiong, H., Pena, C.J., Moreno, E., Griffis, E., Labou, S.G., Franco, A., Broderick, L., Hoffman, H.M. Shimizu, C. Lewis, N.E. Kanegaye, J.T., Tremoulet, A.H., Burns, J.C., Croker, B.A. Immune response to intravenous immunoglobulin in patients with Kawasaki disease and MIS-C. Journal of Clinical Investigation, 131(20):e147076 (2021). PMCID: PMC8516453
127. Bao, B.*, Kellman, B.P.*, Chiang, A.W.T., Zhang, Y., Sorrentino, J.T., York, A.K., Mohammad, M.A., Haymond, M.W., Bode, L., Lewis, N.E. Correcting for sparsity and interdependence in glycomic data by accounting for glycan biosynthesis. Nature Communications, 12, 4988 (2021). doi: 10.1038/s41467-021-25183-5, PMCID: PMC8371009
126. Khaleghi M.K., Savizi I.S.P., Lewis N.E., Shojaosadati S.A. Synergisms of machine learning and constraint-based modeling of metabolism for analysis and optimization of fermentation parameters. Biotechnology Journal, 16:2100212. (2021). doi: 10.22541/au.162083622.21592768/v1
125. Lombardo MV, Eyler L, Pramparo T, Gazestani VH, Hagler Jr. DJ, Chen CH, Dale AM, Seidlitz J, Bethlehem RAI, Bertelsen N, Barnes CC, Lopez L, Campbell K, Lewis NE, Pierce K, Courchesne E. Atypical genomic patterning of the cerebral cortex in autism with poor early language outcome, Science Advances, 7: eabh1663 (2021). doi:10.1126/sciadv.abh1663
124. Robasky K., Kim R., Yi H., Xu H., Bao B., Chiang A.W.T., Courchesne E., Lewis N.E. Transfer learning improves outcome predictions for ASD from gene expression in blood. bioRxiv (2021). doi: 10.1101/2021.06.26.449864
123. Xiong, K., Karottki, K.J.L.C., Hefzi, H., Li, S., Grav, L.M., Li, S., Spahn, P., Lee, J.S., Lee, G.M., Lewis, N.E., Kildegaard, H.F.,Pedersen, L.E. An optimized genome-wide, virus-free CRISPR screen for mammalian cells. Cell Reports Methods, 1:100062 (2021). bioRxiv doi: 10.1101/2020.05.19.103648
122. Shamie I.*, Duttke S.H.*, Karottki K.J.L.C., Han C.Z., Hansen A.H., Hefzi H., Xiong K., Li S., Roth S., Tao J., Lee G.M., Glass C.K., Kildegaard H.F., Benner C., Lewis N.E. A Chinese hamster transcription start site atlas that enables targeted editing of CHO cells. NAR Genomics and Bioinformatics, 3: lqab061 (2021). doi: 10.1093/nargab/lqab061
121. Kuo, C.C., Chiang, A.W.T., Baghdassarian H.M., Lewis, N.E. Dysregulation of the secretory pathway connects Alzheimer’s disease genetics to aggregate formation. Cell Systems, 12: P873-884.E4, (2021). doi: 10.1016/j.cels.2021.06.001 bioRxiv doi: 10.1101/2020.08.10.243634, PMCID: PMC8505362. Highlighted by ScienceNews.dk
120. 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. Model-based assessment of mammalian cells metabolic functionalities from omics data. Cell Reports Methods, 1:100040 (2021). doi: 10.1016/j.crmeth.2021.100040
119. Samoudi M, Masson H, Kuo CC, Robinson C, Lewis NE. From omics to cellular mechanisms in mammalian cell factory development, Curr Opin in Chem Eng, 32: 100688 (2021). doi: 10.1016/j.coche.2021.100688
118. Chiang A.W.T.‡, Baghdassarian H.M., Kellman B.P., Bao B., Sorrentino J.T., Liang C., Kuo C.C., Masson H.O., Lewis N.E. Systems glycobiology for discovering drug targets, biomarkers, and rational designs for glyco-immunotherapy. Journal of Biomedical Science, 28:50 (2021). doi: 10.1186/s12929-021-00746-2, PMCID: PMC8218521
117. Savizi I.S.P., Motamedian E., Maghsoudi N., Lewis N.E., Jimenez del Val I., Shojaosadati S.A. An integrated modular framework for modeling the effect of ammonium on the sialylation process of monoclonal antibodies produced by CHO cells. Biotechnology Journal, 16:2100019 (2021). doi: 10.1002/biot.202100019
116. Weiss RJ*, Spahn PN*, Chiang AWT, Liu Q, Li J, Hamill KM, Rother S, Clausen TM, Hoeksema MA, Timm BM, Godula K, Glass CK, Tor Y, Gordts PLSM, Lewis NE‡, Esko JD‡. Genome-wide screens uncover KDM2B as a modifier of protein binding to heparan sulfate. Nature Chemical Biology, 17: 684–692 (2021). PMCID: PMC8218521
115. Karottki, K.J.L.C., 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. Metabolic Engineering, 66:114-122 (2021). doi: 10.1016/j.ymben.2021.03.017. bioRxiv doi: 10.1101/2020.05.07.081604, PMCID: PMC8193919
114. Schinn S-M, Morrison C, Wei W, Zhang L, Lewis NE. Systematic evaluation of parameterization for genome-scale metabolic models of cultured mammalian cells. Metabolic Engineering, 66:21-30 (2021). bioRxiv doi:10.1101/2020.06.24.169938.
113. Granados, J.C., Richelle, A., Gutierrez, J.M., Zhang, P., Bhatnagar, V., Lewis, N.E., Nigam, S.K. Coordinate regulation of systemic and kidney tryptophan metabolism by the drug transporters OAT1 and OAT3. Journal of Biological Chemistry. 296:100575 (2021). doi: 10.1016/j.jbc.2021.100575, PMCID: PMC8102410
112. Schinn S.M., Morrison C., Wei W., Zhang L., Lewis N.E. A genome-scale metabolic network model and machine learning predict amino acid concentrations in Chinese Hamster Ovary cell cultures. Biotechnology & Bioengineering, 118:2118-2123 (2021). doi: 10.1002/bit.27714 bioRxiv doi: 10.1101/2020.09.02.279687
111. Askarian, F., Uchiyama, S.*, Masson, H.*, Bunæs, A.C., Golten, O., Mekasha, S., Røhr, Å.K., Kommedal, E., Ludvigsen, J.A., Sørensen, H.V., Arntzen, M.Ø., Schmidt, B., van Sorge, N.M., Eijsink, V.G.H, Krengel, U., Mollnes, T.E., Lewis, N.E., Nizet, V., Vaaje-Kolstad, G. The lytic polysaccharide monooxygenase CbpD promotes Pseudomonas aeruginosa virulence in systemic infection. Nature Communications, 12: 1230 (2021). doi: 10.1038/s41467-021-21473-0, PMCID: PMC7902821
110. Toledo, A.G., Sorrentino, J., Sandoval, D., Malmström, J., Lewis, N.E., Esko, J.D. A Systems View of the Heparan Sulfate Interactome. Journal of Histochemistry & Cytochemistry, 69(2):105–119 (2021). doi: 10.1369/0022155420988661, PMCID: PMC7841697
109. Hsieh LY, Chiang AWT, Duong LD, Kuo CC, Dong S, Dohil R, Kurten R, Lewis NE, Aceves SS. A Unique Esophageal Extracellular Matrix Proteome Alters Normal Fibroblast Function in Severe Eosinophilic Esophagitis. Journal of Allergy and Clinical Immunology, 148, 486-494 (2021). doi: 10.1016/j.jaci.2021.01.023, PMCID: PMC8342625
108. 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. BMC Genomics, 22, 69 (2021). doi: 10.1186/s12864-021-07381-z, PMCID: PMC7818915
107. Armingol, E.*, Officer, A.*, Harismendy, O.‡, Lewis, N.E.‡ Deciphering cell-cell interactions and communication from gene expression. Nature Reviews Genetics, 22:71–88 (2021). doi: 10.1038/s41576-020-00292-x
106. Chiang AWT, Duong LD, Shoda T, Nhu QM, Ruffner M, Hara T, Aaron B, Joplin E, Manresa M, Abonia JP, Dellon E, Hirano I, Gonsalves N, Gupta S, Furuta G, Rothenberg ME, Lewis NE, Muir AB, Aceves SS, CEGIR Investigator Group. Type 2 Immunity and Age Modify Gene Expression of COVID19 Receptors in Eosinophilic Gastrointestinal Disorders. J Pediatr Gastroenterol Nutr, 72:718-722 (2021). doi: 10.1097/MPG.0000000000003032.
105. 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. Biotechnology & Bioengineering, 118 (2):890-904 (2021). doi: 10.1002/bit.27621, PMCID: PMC7855575
104. Kellman, B.P., Lewis, N.E. Big-data glycomics: tools to connect glycan biosynthesis to extracellular communication. Trends in Biochemical Sciences, 46:P284-300, (2021). doi: 10.1016/j.tibs.2020.10.004, PMCID: PMC7954846
103. 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. Biotechnology Letters, 43:73–87 (2021). doi: 10.1007/s10529-020-03021-w, bioRxiv: 10.1101/2020.01.27.921296
2020
102. Martino, C.*, Kellman, B.P.*, Sandoval, D.R.*, Clausen, T.M., Marotz, C., Song, S.J., Wandro, S., Zaramela, L., Benítez, R.A.S., Zhu, Q., Armingol, E., Vázquez-Baeza, Y., McDonald, D., Sorrentino, J., Taylor, B., Belda-Ferre, P., Liang, C., Zhang, Y., Schifanella, L., Klatt, N.R., Havulinna, A.S., Jousilahti, P., Huang, S., Haiminen, N., Parida, L., Kim, H.C., Swafford, A.D., Zengler, K., Cheng, S., Inouye, M., Niiranen, T., Jain, M., Salomaa, V., Esko, J.D.‡, Lewis, N.E.‡, Knight, R.‡ Bacterial modification of the host glycosaminoglycan heparan sulfate modulates SARS-CoV-2 infectivity. bioRxiv, (2020). DOI: 10.1101/2020.08.17.238444. News Coverage: Medical News
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 lines. PLoS Computational Biology, 16: e1008498 (2020). doi: 10.1371/journal.pcbi.1008498
100. 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
99. Kellman, B.P.*, Zhang, Y.*, Logomasini, E., Meinhardt, E., Godinez-Macias, K.P., Chiang, A.W.T., Sorrentino, J., Liang, A., Bao, B., Zhou, Y., Akase, S., Sogabe, I, Kuoka, T., Winzeler, E.A., 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). Beilstein Journal of Organic Chemistry, 16, 2645–2662 (2020). doi: 10.3762/bjoc.16.215, PMCID: PMC7607430
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. 28, P586-601.E6 (2020). doi:10.1016/j.chom.2020.08.004, PMCID: PMC7443692
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. PMCID: PMC7726704
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 purity. Nature Communications, 11:1908 (2020). doi: 10.1038/s41467-020-15866-w. News coverage: Nature Bioengineering, UCSD Jacobs, Phys.org, Genetic Engineering and Biotechnology News, ScienceNews.dk
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, 61:288-300 (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, Phys.org, 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 models. PLoS 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 production. Bioprocess and Biosystems Engineering, 43, 1381–1389 (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 secretion. Nature Communications, 11:68 (2020). doi: 10.1038/s41467-019-13867-y News coverage: ScienceNews.dk
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. Karottki, K.J.L.C., 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 & 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 suite. Nature Biotechnology, 38:272–276 (2020). doi: 10.1038/s41587-020-0446-y
2019
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 severity. Nature 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 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.*, Karottki, K.J.L.C.*, 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 & 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, 37, 931-942 (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 News Coverage: ScienceNews.dk
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 & 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, News coverage: phys.org, UCSD 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.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 applications
13. Kellman, BP, Lewis, NE, Sandoval, D, Nachmenson, D, Chiang, AWT. Glycosylation engineering. Patent pending – provisional.
12. Lewis, N.E., Chiang, W.T., Kellman, B.P., Bao, B., Schinn, M.S. Clinical diagnostics using glycans. Patent WO2023034383A3.
11. Hefzi, H., Lewis, N.E., Karottki, K.J.L.C., Kildegaard, H. Asparaginase Based Selection System for Heterologous Protein Expression in Mammalian Cells. Patent pending.
10. Fuerst, T.R., Toth, E.A., Lewis, N.E., Voldborg, B.G., Chiang, W.T. Compositions and methods for producing glyco-modified viral antigens. Patent PCT/US2022/014338.
9. Lewis, N.E., Chiang, W.T., Liang, C., Sorrentino, J.T. Method of Measuring Complex Carbohydrates. Patent PCT/US2021/044139.
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 PCT/US2021/046144.
7. Lewis, N.E., Liang, C., Chiang, W.T. Methods of Designing Carbohydrates. Patent PCT/EP2020/082713.
6. Lewis, N.E., Spahn, P., Li, S., Hefzi, H., Shamie, I. Methods to Stabilize Mammalian Cells. Patent PCT/EP2020/078435.
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 Patent US11242510B2.
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.