Embedded Files
2026
Rational design of serum-free media for cultivated meat
Nature Reviews Bioengineering.
Ho, Y.Y., Sivakumar, S., Ho, Y.S.*, Lakshmanan, M.*
Highlights
Development of cost-effective media for cultivated meat
Multi-omics and genome scale metabolic modelling for cell line-specific media design
Evaluation of sustainable nutrient alternatives from valorized streams
AI-assisted optimization of serum-free culture media
A community reconstruction of Chinese hamster metabolism and structural systems biology elucidate metabolic rewiring in lactate-free CHO cells
Cell Systems. Advance online publication.
Di Giusto, P., Choi, D. H., Antonakoudis, A., Duraikannan, V. G., Craveur, P., Cowie, N. L., Ganapathy, T., Ramesh, K., Benavidez-Lopez, S., Orellana, C.A., Jimnez, N.E., Dworkin, L.A., Morrissey, J., de Mas, I.G., Strain, B., Valdez-Cruz, N.A., Trujillo-Roldan, M.A., Marzluf, J., Martinez, V.S., Zhetener, L., Altamirano, C., Vega-Letter, A.M., Priem, B., Cao, H.C., Hold, M., Ma, J., Hong, Y.F., Gopalakrihnan, S., Enuh, B.M., Tarzi, C., Pang, K.T., Angione, C., Zanghellini, J., Kontravdi, C., Hefzi, H., Betenbaugh, M.J., Nielsen, L.K., Lakshmanan, M.*, Lee, D.-Y.*, Richelle, A.*, Lewis, N.E.*
Highlights
Presents iCHO3K, the most comprehensive genome-scale metabolic (GEM) reconstruction of the Chinese hamster to date.
Integrates a layer of structural biology data on top of genes, reactions and metabolites.
Enables multi-omics integration and structure-guided engineering to significantly improve cellular efficiency and rationalize the bioprocess development.
Towards sustainable serum-free media development from alternative sources for cultivated meat
Sivakumar, S., Manayankath, A., Hong, Y. F., Thrivikraman, G., Tekkatte, C., Choudhury, D., Pang, K. T.*, & Lakshmanan, M.*
Highlights
Serum alternatives are investigated to reduce cost of CM cell culture media
Categorized current works into 2 categories: serum replacement and serum reduction
Highlighted critical gaps in current studies such as the lack of demonstration of cost-effectiveness, scalability and long-term applicability
Proposed multi-omics, HTS, and ML based framework for media design
2025
Is green algae polysaccharide a ‘green path’ to health?
Kai, S.O. J., Myint, M., Tan, C.F., Hong, Y.F., Lakshmanan, M., Ho, Y.S., Wheeler, T.T., Bi, X., Walsh, I., Chia, S., Pang K.T.
Highlights
Reviews polysaccharides extracted from green algae that have exhibited bioactivity which might make them great nutraceutical.
Highlights the possible advantage of polysaccharide extracts as compared to whole algae.
Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products
npj Systems Biology and Applications.
Lee, Y.Q., Choi, Y.-M., Park, S.-Y., Kim, S.-K., Lee, M., Kim, D., Koduru, L., Lakshmanan, M., Jung, S., Kim, M.J., Choe, Y.H., Lee, D.-Y.
Highlights
Presents a model-guided framework for characterizing Live Biotherapeutic Products (LBP) candidate strains and their metabolic interactions with adjacent microbiome and host cells at a systems level using genome-scale metabolic models (GEMs).
Further outlines GEM-based strategy for screening, assessment, and design of personalized multi-strain LBPs..
Differential polyamine metabolism in CHO cell lines: Insights into cell growth and antibody quality
Kang, D.E., Senthilkumar, D., Jeon, J.H., You, W.-K., Ganapathy, T., Lakshmanan, M.*, Hong, J-K*
Highlights
CHO-K1 displayed significant PUT (putrescine) auxotrophy in the culture performance over CHO -DG44.
Distinct responses to PUT withdrawal showed correlation with differential gene expression involved in polyamine metabolism.
PUT depletion increased antibody galactosylation, suggesting PUT adjustment could enhance antibody quality.
2024
Genome-scale modeling of CHO cells unravel the critical role of asparagine in cell culture feed media
Pang, K.T., Hong, Y.F., Shozui, F., Furomitsu, S., Myint, M., Ho, Y.S., Silberberg, Y.R., Walsh, I.*, Lakshmanan, M.*
Highlights
Explores the roles of asparagine and aspartate in feed media of CHO cell cultures using Genome Scale Models (GEMs).
Critical role of asparagine and aspartate in the feed media as anaplerotic sources is identified through in silico simulations and experimental validations.
The experimental data revealed CHO cell preference for asparagine compared with aspartate in feed culture.
Antibody glycan quality predicted from CHO cell culture media markers and machine learning
Computational and Structural Biotechnology Journal.
Lakshmanan, M., Chia, S., Pang, K.T., Sim, L.C., Teo, G., Mak, S.Y., Chen, S., Lim, H.S., Lee, A.P., Mahfut, F.B., Ng, S.K., Yang, Y., Soh, A., Tan, A.H.-M., Choo, A., Ho, Y.S., Ngyuyen-Khuong, T., Walsh, I.
Highlights
Explores the potential of machine learning (ML) to forecast the abundances of N-glycan types based on variables related to the growth media.
Experimental inputs to ML model led to small subset of media markers in CHO cell cultures which is further used to model N-glycan relative abundance.
ML models built showed it can infer N-glycan critical quality attributes from extracellular media as a proxy with potential applications in biomaufactucuring.
Driving towards digital biomanufacturing by CHO genome-scale models
Park, S.-Y., Choi, D.-H., Song, J., Lakshmanan, M., Richelle, A., Yoon, S., Kontoravdi, C., Lewis, N.E., Lee, D.-Y.
Highlights
Highlights the application of CHO-GEMs in cell line and process development.
Reviews the use of integrative model structure that can incorporate multiple layers and capture condition-specific cell regulation.
Explores the integration of CHO-GEMs with artificial intelligence (AI) and advanced algorithms will enable for digital biomanufacturing.
2023
Mitigating biomass composition uncertainties in flux balance analysis using ensemble representations
Computational and Structural Biotechnology Journal.
Choi, Y., Long, S., Ang, K.S., Lewis, N.E., Lakshmanan, M.*, Lee, D.-Y*.
Highlights
Highlights the irregularities in macromolecular composition of cells across different environmental conditions which is the basis for de facto objective function in flux balance analysis (FBA) used in GEMs.
Experimental investigation of macromolecular building blocks showed notable changes whereas the changes in fundamental biomass monomer units were not appreciable. The flux prediction sensitivity showed the same trend.
Proposes ensemble representations of biomass equation in FBA to account for the natural variation of cellular constituents. Which better predicted the flux through anabolic reactions.
Before 2023
Koduru, L.†, Lakshmanan, M.†, Yu, L.P., Banu, M., Ow, D. S.-K., Lee, D.-Y. (2022) “Systematic evaluation of genome-wide metabolic landscapes in lactic acid bacteria reveals diet-induced and strain-specific probiotic idiosyncrasies”, Cell Reports, 41(10): 111735; DOI: 10.1016/j.celrep.2022.111735
Walsh, I.*, Myint, M., Nguyen-Khuong, T., Ho, Y.S., Ng, S.K., Lakshmanan, M.* (2022) “Harnessing the potential of machine learning for advancing “Quality by Design” in biomanufacturing”, mAbs, 6(6): e00599-21. DOI: 10.1080/19420862.2021.2013593
Lee A.P.†, Kok, Y.J.†, Lakshmanan, M.† et al. (2021) “Multi-omics profiling of a CHO cell culture system unravels the effect of culture pH on cell growth, antibody titer and product quality”, Biotechnology and Bioengineering, 118(11):4305-4316. DOI: 10.1002/bit.27899.
Yeo, H.C., Hong, J.K., Lakshmanan, M.*, Lee, D.-Y.* (2020) “Enzyme capacity–based genome-scale modelling of CHO cells”, Metabolic Engineering, 60:138–147. DOI: 10.1016/j.ymben.2020.04.005.
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., García-Jiménez, B., van Helvoirt, W., Henry, C.S., Hermjakob, H., Herrgård, M.J., Kim, H.U., King, Z., Koehorst, J.J., Klamt, S., Klipp, E., Lakshmanan, M., Le Novère, N., Lee, D.-Y., Lee, S.Y., Lee, S., Lewis, N.E., Ma, H., Machado, M., Mahadevan, R., Maia, P., Mardinoglu, A., Medlock, G.L., Monk, J.M., Nielsen, J., Nielsen, L.K., Nogales, J., Nookaew, I., Resendis-Antonio, O., Palsson, B.O., Papin, J.A., Patil, K.R., Price, N.D., Richelle, A., Rocha, I., Schaap, P.J., Sheriff, R.S.M., Shoaie, S., Sonnenschein, N., Teusink, B., Vilaça, P., Vik, J.O., Wodke, J.A., Xavier, J.C., Yuan, Q., Zakhartsev, M., Zhang. C. (2020) “Memote: A community driven effort towards a standardized genome-scale metabolic model test suite”, Nature Biotechnology, 38:272–276. DOI: 10.1038/s41587-020-0446-y.
Lakshmanan, M., Kok, Y.J., Lee, A.P., Kyriakopoulos, S., Lim, H.L., Teo, G., Poh, S.L., Tang, W.Q., Hong, J., Tan, A.H.-M., Bi, X., Ho, Y.S., Zhang, P., Ng, S.K., Lee, D.-Y. (2019) “Multi-omics profiling of CHO parental hosts reveals cell line-specific variations in bioprocessing traits”, Biotechnology and Bioengineering, 116(9):2117-2129; DOI: 10.1002/bit.27014.
Hong, J.K.†, Lakshmanan, M.†, Lee, D.-Y. (2018) “Towards next generation CHO cell line development and engineering by systems approaches”, Current Opinion in Chemical Engineering, 22:1-10. DOI: 10.1016/j.coche.2018.08.002.
Kyriakopoulos, S., Ang, K.S., Lakshmanan, M., Huang, Z., Yoon, S., Gunawan, R., Lee, D.-Y. (2018) “Kinetic modeling of mammalian cell culture bioprocessing: the quest to advance biomanufacturing”, Biotechnology Journal, 13(3):e1700229. DOI: 10.1002/biot.201700229.
Koduru, L., Kim, Y., Bang, J., Lakshmanan, M., Han, N.S., Lee, D.-Y. (2017) “Genome-scale modeling and transcriptome analysis of Leuconostoc mesenteroides unravel the redox governed metabolic states in obligate heterofermentative lactic acid bacteria”, Scientific Reports, 7: 15721. DOI: 10.1038/s41598-017-16026-9.
Yusufi, F.N.K.†, Lakshmanan, M.†, Ho, Y.S.*, Loo, B.L.W., Yeo, H.C., Ariyaratne, P., Lee, T.S., Yang, Y.S., Ng, S.K., Tan, T.R.M., Lim, H.S., Ng, S.W., Hiu, A.P., Chow, C.P., Wan, C., Teo, G., Song, G., Chin, J.X., Ruan, X., Sung, K.W.K., Hu, W.-S., Yap, M.G.S., Bardor, M., Nagarajan, N., Lee, D.-Y. (2017) “Mammalian systems biotechnology reveals global cellular adaptations in a recombinant CHO cell line”, Cell Systems, 4(5):530-542. DOI: 10.1016/j.cels.2017.04.009
Hefzi, H., Ang, K.S., Hanscho, M., Bordbar, A., Ruckerbauer, D., Lakshmanan, M., Orellana, C.A., Baycin-Hizal, D., Huang, Y., Ley, D., Martinez, 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., 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. (2016) “A consensus genome-scale reconstruction of CHO cell metabolism for improved biotherapeutic protein production”, Cell Systems, 3(5):434-443. DOI: 10.1016/j.cels.2016.10.020.
Swainston, N., Smallbone, K., Hefzi, H., Dobson, P.D., Brewer, J., Gardiner, N.J., Zielinski, D.C., Ang, K.S., Gutierrez, J.M., Hanscho, M., Kyriakopoulos, S., Lakshmanan, M., Li, S., Liu, J.K., Martinez, V.S., Orellana, C.A., Quek, L.-E., Thomas, A., Borth, N., Lee, D.-Y., Nielsen, L.K., Kell, D.B., Mendes, P. (2016) “Recon 2.2: from reconstruction to model of human metabolism”, Metabolomics, 12:109. DOI: 10.1007/s11306-016-1051-4.
Lakshmanan, M., Koh, G., Chung, B.K.S., Lee, D.-Y. (2014) “Software applications for flux balance analysis”, Briefings in Bioinformatics, 15(1):108-22. DOI:10.1093/bib/bbs069. One of the top 5 highly cited paper in Briefings in Bioinformatics (2014).
Book Chapters
Ang K.S., Hong, J.K., Lakshmanan, M., Lee, D.-Y. (2019) “Towards integrated multi-omics analysis for improving CHO cell bioprocessing”, In G. M. Lee and H. F. Kidegaard (Ed.), Advanced Biotechnology, Wiley, DOI: 10.1002/9783527811410.ch7.
Lakshmanan, M., Koduru, L., Lee, D.-Y. (2017) “Software applications for phenotype analysis and strain design of cellular systems”, In H. N. Chang, S.-Y. Lee, J. B. Nielsen and G. Stephanopolous (Ed.), Emerging Areas in Bioengineering, Wiley, DOI:10.1002/9783527803293.ch44
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