Research Overview

Our laboratory uses synthetic biology to engineer living medicines.
We program cells to sense and respond to their environment, enhancing specificity and therapeutic efficacy. Much of our work focuses on engineering bacteria to fight cancer, designing microbes that produce molecules locally in tumors. Compared with conventional drugs, this strategy can reduce systemic toxicities and directly reprogram the tumor microenvironment. Beyond cancer, we extend our approach to other disease indications, and we design cooperative therapies where engineered bacteria work with modalities like CAR-T cells, oncolytic viruses, and nanoparticles. We also use time-lapse microscopy, sequencing, and computational methods to uncover how gene networks behave at the single-cell level, guiding the design of next-generation microbial therapeutics. Our ultimate goal is to bring these technologies to patients.

The research in the lab spans diverse topics that fall under three themes:

1. Programming bacteria for cancer applications
Bacteria have unique advantages as cancer therapies: they selectively colonize tumors, deliver drugs locally that would be too toxic systemically, stimulate immune responses, and can be genetically programmed for precision and safety. Our lab focuses on developing new strategies to engineer microbes and to design cooperative therapies that work alongside other modalities.

Representative publications:
1. Engineered probiotics for local tumor delivery of checkpoint blockade nanobodies
Gurbatri, C., Iona, L., Vincent, R., Coker, C., Castro, S., Treuting, P., Hinchliffe, T.E., Arpaia, N., Danino, T.
Science Translational Medicine 12(530):eaax0876, (2020)
2. Programmable bacteria induce durable tumor regression and systemic antitumor immunity
Chowdhury, S., Castro, S., Coker, C., Hinchliffe, T.E., Arpaia, N.*, Danino, T.*
Nature Medicine 25(7), 1057–1063 (2019)
3. Probiotic-guided CAR-T cells for solid tumor targeting
Vincent, R.L.*, Gurbatri, C.R.*, Li, F., Vardoshvili, A., Coker, C., Im, J., Ballister, E.R., Rouanne, M., Savage, T., de los Santos-Alexis, K., Redenti, A., Brockmann, L., Komaranchath, M., Arpaia, N., Danino, T.
Science 382(6667), 211-218 (2023)
4. Engineered bacteria launch and control an oncolytic virus
Singer, Z.S.*, Pabón, J.*, Huang, H., Sun, W., Luo H., Grant, K.R., Obi, I., Coker, C., Rice, C.M., Danino, T.
Nature Biomedical Engineering (2025) doi.org/10.1038/s41551-025-01476

2. Synthetic biology : Gene circuit design
We apply engineering principles to design genetic circuits in microbes, guided by computational modeling and validated in bacterial systems. These circuits include biosensors, communication modules such as quorum sensing, and control of motility or swarming. Such engineered behaviors can be harnessed for biomedical and environmental applications.

Representative publications:
1. Engineered bacterial swarm patterns as spatial records of environmental inputs
Doshi, A., Shaw, M., Tonea, R., Moon, S., Minyety, R., Doshi, A., Laine, A., Guo, J., Danino, T.
Nature Chemical Biology (2023). doi: 10.1038/s41589-023-01325-2
2. Enhancing the tropism of bacteria via genetically programmed biosensors
Chien, T.*, Harimoto, T.*, Kepecs, B., Gray, K., Coker, C., Hou, N., Pu, K., Azad, T., Nolasco, A., Pavlicova, M., Danino, T.
Nature Biomedical Engineering 6, 94-104 (2021)
3. Engineered bacterial production of volatile methyl salicylate
Chien, T., Jones, D.R. , and Danino, T.
ACS Synthetic Biology 10(1), 204-208 (2020)

3. Quantitative and data science approaches in biological systems
We combine experimental tools such as time-lapse microscopy and next-generation sequencing with computational methods including machine learning and mathematical modeling. This allows for quantitative study of gene networks and microbial populations at single-cell resolution. These insights can inspire the design of new genetic circuits and therapeutic strategies.

Representative publications:
1. A deep learning pipeline for segmentation of Proteus mirabilis colony patterns
Doshi, A.*, Shaw, M.*, Tonea, R., Minyety, R., Moon, S., Laine, A., Guo, J., Danino, T.
IEEE International Symposium on Biomedical Imaging (ISBI) 1-5 (2022)
2. Quantitative measurements of early alphaviral replication dynamics in single cells reveals the basis for superinfection exclusion
Singer, Z.S., Ambrose, P.M., Danino, T.*, Rice, C.M.*
Cell Systems 12(3), 210-219 (2021)
3. Segmentation with residual attention U-Net and an edge-enhancement approach preserves cell shape features
Zhu, N.*, Liu, C.*, Forsyth, B., Singer, Z., Laine, A., Danino, T., Guo, J.
IEEE Engineering in Medicine & Biology Society (EMBC) 2115-2118 (2022)

Introductory Videos