Research Interests

• Systematic bioprocess development for biopharmaceutical andcultivated meatmanufacturing
• Data-driven cell line development for biopharmaceutical manufacturing
• Next-generation probiotics design through data-driven approaches
• Computational systems biology for clinical marker identifications
• Multi-omics data integration and constraint-based modelling algorithm

Selected Publications

Complete list of publications can be found on Google Scholar scopus

(* Equal contribution; Corresponding author)

1. 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.

2. Yeo, H.C., Park, S., Tan, T., Ng, S. K., Lakshmanan, M., Lee, D.-Y. (2022) Combined multivariate statistical and flux balance analyses uncover media bottlenecks to the growth and productivity of CHO cell cultures, Biotechnology & Bioengineering, 119(7):1740-1754.

3. Koduru, L., Lakshmanan, M., Hoon, S., Lee, D.-Y., Lee, Y.K., Ow, D.S.-K. (2022). “Systems biology of gut microbiota-human receptor interactions: Toward anti-inflammatory probiotics”, Frontiers in Microbiology, 13:846555.

4. 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.

5. Ankrah, N., Bernstein, D., Biggs, M. Carey, M., Engevik, M., Garc a-Jim nez, B., Lakshmanan, M., Pacheco, A., Sulheim, S., Medlock, G. (2021) Enhancing microbiome research through genome-scale metabolic modeling, mSystems, 6(6): e00599-21.

6. 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 & Bioengineering 118(11):4305-4316.

7. Yeo, H.C., Hong, J.K., Lakshmanan, M., Lee, D.-Y. (2019) Enzyme capacity based genome-scale modelling of CHO cells, Metabolic Engineering, 60:138 147.

8. 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., Dr ger, A., Ebert, B.E., Edirisinghe, J.N., Fleming, R.M.T., Garc a-Jim nez, B., van Helvoirt, W., Henry, C.S., Hermjakob, H., Herrg rd, M.J., Kim, H.U., King, Z., Koehorst, J.J., Klamt, S., Klipp, E., Lakshmanan, M., Le Nov re, 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., Vila a, 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.

9. Hong, J.K., Yeo, H.C., Lakshmanan, M., Han, S.-H., Cha, H.M., Han, M., Lee, D.-Y. (2020) In silico model-based characterization of metabolic response to harsh sparging stress in fed-batch CHO cell cultures, Journal of Biotechnology, 308:10-20.

10. 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 & Bioengineering, 116(9):2117-2129.

11. 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.

12. 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.

13. 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., Jimnez, 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.

14. 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.

15. Lakshmanan, M., Lim, S.-H., Mohanty, B., Kim, J.K., Ha, S.-H., Lee, D.-Y. (2015) Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis, Plant Physiology, 169(4):3002-20.

16. 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. One of the top 5 highly cited paper in Briefings in Bioinformatics (2014).

17. Lakshmanan, M.*, Zhaoyang, Z., Mohanty B., Kwon, J.-Y., Kim, D.-I., Lee, D.-Y. (2013) Elucidating the metabolism of rice cells under flooding and drought stresses using flux-based modeling and analysis, Plant Physiology, 162(4):2140-50.