Sepideh Dolatshahi


Primary Appointment

, Biomedical Engineering


  • PhD, Biomedical Engineering, Georgia Institute of Technology

Research Disciplines

Biotechnology, Cancer Biology, Computational Biology, Epigenetics, Immunology, Molecular Biology, Translational Science

Research Interests

Systems Immunology, Cancer Systems Biology, , Neonatal and Maternal Immunology

Research Description

Research in the Dolatshahi lab combines multiplex experimental measurements with computational methods (including statistical machine learning, network inference, information theory, signal processing and kinetic-dynamic modeling) to solve problems in the context of cancer, infectious disease and maternal-neonatal immunology.
The immune system is complex and ubiquitous. Numerous immune cell types either reside in a particular tissue or circulate throughout the body. Each cell type has its unique roles and approaches in sensing problems, communicating with other cells, and eliciting their immune functions. The Dolatshahi lab takes a systems approach to understand the interconnecting pathways that control immune responses spanning across multiple biological systems and scales.
This understanding will enable us to optimize immune responses to confront specific issues, ranging from infections to cancer. By building computational models and machine-learning strategies that integrate experimental data across various molecular and cellular scales, Dolatshahi laboratory seeks to: (1) ascertain how biophysical properties of the immune factors (defined as their subclass and post-translational modifications) determine their function, (2) uncover mechanisms responsible for dysregulation of these properties in disease states, and (3) use this knowledge to guide biomarkers for early disease diagnosis, patient stratification and optimized immunotherapies. Another key step in translational immunotherapies is the design of maximally informative animal studies for reliable prediction of the outcome in humans. To this end, Dolatshahi lab also (4) creates predictive computational transfer functions to relate mechanistic models of cellular processes in animals to those in humans. Such functions will enable inter-species translation of molecules to phenotypes.


  • Interdisciplinary Training Program in Immunology

Selected Publications


Wessel, R. E., & Dolatshahi, S. (2023). Quantitative mechanistic model reveals key determinants of placental IgG transfer and informs prenatal immunization strategies.. PLoS computational biology, 19(11), e1011109. doi:10.1371/journal.pcbi.1011109

Erdogan, R. R., & Dolatshahi, S. (2023). Quantitative mechanistic model reveals key determinants of placental IgG transfer and informs prenatal immunization strategies.. bioRxiv. doi:10.1101/2023.04.18.537285

Nziza, N., Tran, T. M., DeRiso, E. A., Dolatshahi, S., Herman, J. D., de Lacerda, L., . . . Alter, G. (2023). Accumulation of Neutrophil Phagocytic Antibody Features Tracks With Naturally Acquired Immunity Against Malaria in Children. JOURNAL OF INFECTIOUS DISEASES, 228(6), 759-768. doi:10.1093/infdis/jiad115


Dolatshahi, S., Butler, A. L., Pou, C., Henckel, E., Bernhardsson, A. K., Gustafsson, A., . . . Alter, G. (2022). Selective transfer of maternal antibodies in preterm and fullterm children. SCIENTIFIC REPORTS, 12(1). doi:10.1038/s41598-022-18973-4

Dolatshahi, S., Butler, A. L., Siedner, M. J., Ngonzi, J., Edlow, A. G., Adong, J., . . . Bebell, L. M. (2022). Altered Maternal Antibody Profiles in Women With Human Immunodeficiency Virus Drive Changes in Transplacental Antibody Transfer. CLINICAL INFECTIOUS DISEASES, 75(8), 1359-1369. doi:10.1093/cid/ciac156


Grace, P. S., Dolatshahi, S., Lu, L. L., Cain, A., Palmieri, F., Petrone, L., . . . Alter, G. (2021). Antibody Subclass and Glycosylation Shift Following Effective TB Treatment. FRONTIERS IN IMMUNOLOGY, 12. doi:10.3389/fimmu.2021.679973


Fischinger, S., Dolatshahi, S., Jennewein, M. F., Rerks-Ngarm, S., Pitisuttithum, P., Nitayaphan, S., . . . Alter, G. (2020). IgG3 collaborates with IgG1 and IgA to recruit effector function in RV144 vaccinees. JCI INSIGHT, 5(21). doi:10.1172/jci.insight.140925


Jennewein, M. F., Goldfarb, I., Dolatshahi, S., Cosgrove, C., Noelette, F. J., Krykbaeva, M., . . . Alter, G. (2019). Fc Glycan-Mediated Regulation of Placental Antibody Transfer. CELL, 178(1), 202-+. doi:10.1016/j.cell.2019.05.044

Chang, M. M., Gaidukov, L., Jung, G., Tseng, W. A., Scarcelli, J. J., Cornell, R., . . . Weiss, R. (2019). Small-molecule control of antibody N-glycosylation in engineered mammalian cells. NATURE CHEMICAL BIOLOGY, 15(7), 730-+. doi:10.1038/s41589-019-0288-4

Sumit, M., Dolatshahi, S., Chu, A. -H. A., Cote, K., Scarcelli, J. J., Marshall, J. K., . . . Figueroa, B. J. (2019). Dissecting N-Glycosylation Dynamics in Chinese Hamster Ovary Cells Fed-batch Cultures using Time Course Omics Analyses. ISCIENCE, 12, 102-+. doi:10.1016/j.isci.2019.01.006


Dolatshahi, S., Pishgar, E., & Jamali, R. (2016). Does serum 25 hydroxy vitamin D level predict disease activity in ulcerative colitis patients?. ACTA CLINICA BELGICA, 71(1), 46-50. doi:10.1080/17843286.2015.1110895

Dolatshahi, S., Fonseca, L. L., & Voit, E. O. (2016). New insights into the complex regulation of the glycolytic pathway in Lactococcus lactis. II. Inference of the precisely timed control system regulating glycolysis. MOLECULAR BIOSYSTEMS, 12(1), 37-47. doi:10.1039/c5mb00726g

Dolatshahi, S., & Voit, E. O. (2016). Identification of Metabolic Pathway Systems. FRONTIERS IN GENETICS, 7. doi:10.3389/fgene.2016.00006


Dolatshahi, S., Fonseca, L. L., & Voit, E. O. (2016). New insights into the complex regulation of the glycolytic pathway in Lactococcus lactis. I. Construction and diagnosis of a comprehensive dynamic model. MOLECULAR BIOSYSTEMS, 12(1), 23-36. doi:10.1039/c5mb00331h


Dolatshahi, S., Vidakovic, B., & Voit, E. O. (2014). A constrained wavelet smoother for pathway identification tasks in systems biology. COMPUTERS & CHEMICAL ENGINEERING, 71, 728-733. doi:10.1016/j.compchemeng.2014.07.019


Polak, A. C., Dolatshahi, S., & Goeckel, D. L. (2011). Identifying Wireless Users via Transmitter Imperfections. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 29(7), 1469-1479. doi:10.1109/JSAC.2011.110812