Research Overview

Our laboratory uses synthetic biology to engineer living medicines. We genetically program cells to sense and respond to diverse environments, enhanc­ing their spec­ificity and efficacy as therapeutic modalities. The primary focus of our research is to engineer bacteria as a cancer therapy, where we design microbes to produce molecules that activate anti-tumor immunity. This approach has key advantages in mitigating toxicities observed with systemic therapies, enabling immunoengi­neering of the tumor microenvironment. Beyond this focus, we apply our methodology to broad disease indications such as inflammation and infec­tion, and engineer other modalities such as CAR-T cells and oncolytic viruses to act as cooperative therapies that interact with bacteria. Lastly, our lab also utilizes time-lapse microscopy, next-generation sequencing, and data science approaches to quantitatively understand the dynamics of cellular gene networks at the single-cell level, in turn feeding into the design of new genetic circuits for microbial therapeutics. Our ultimate aim is to advance these technologies to patients in the near term. 

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

1. Programming bacteria for cancer applications
Bacteria have several key advantages as a cancer therapy, including: (1) selective colonization a broad array of cancer types with high specificity, (2) a versatile platform to engineer local production and delivery of therapeutics that otherwise may have toxicities or immune-related adverse events (irAEs) when delivered systemically, (3) enhanced therapeutic activity via co-delivery of bacteria adjuvants, and (4) programmability of “sense and respond” genetic circuits to provide additional specificity and containment. We use synthetic biology approaches to develop effective candidates for preclinical and clinical testing. Some of our newer work has to applied this principles to new disease indications and to work cooperatively with other modalities such CAR-T cells.

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. Rapid screening of engineered microbial therapies in a 3-D multicellular model
Harimoto, T., Singer, Z.S., Velazquez, O.S., Zhang, J., Castro, S., Hinchliffe, T.E., Mather, W., Danino, T.
PNAS 116(18), 9002-9007 (2019)
4. 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)

2. Synthetic biology : Gene circuit design
Our lab uses engineering principles to design, build, and test genetic circuits in microbes. This begins from computational-guided design of dynamic gene circuits, with subsequent implementation and testing in model bacterial systems. We build bacteria biosensors, communication systems (e.g. quorum-sensing), and modulate motility and swarming systems to produce behaviors that can be applied to environmental and biomedical 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 & Data-science approaches in biological systems
The design of new genetic circuits and microbial therapeutics is often inspired by native biological systems. Our lab utilizes experimental approaches (time-lapse microscopy, next-gen sequencing) coupled with computational approaches (machine learning, mathematical modeling) to quantitatively understand the dynamics of gene networks and microbial populations in a variety of systems at a single-cell level.

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