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Genetically modified bacteria as a tool to detect microscopic solid tumor masses with triggered release of a recombinant biomarker.

Authors :
Panteli JT
Forkus BA
Van Dessel N
Forbes NS
Source :
Integrative biology : quantitative biosciences from nano to macro [Integr Biol (Camb)] 2015 Apr; Vol. 7 (4), pp. 423-34.
Publication Year :
2015

Abstract

Current tomographic methods of cancer detection have limited sensitivity and are unable to detect malignant masses smaller than half a centimeter in diameter. Mortality from tumor recurrence and metastatic disease would be reduced if small lesions could be detected earlier. To overcome this limitation, we created a detection system that combines the specificity of tumor-targeting bacteria with the sensitivity of a synthetic biomarker. Bacteria, specifically Salmonella, preferentially accumulate in tumors and microscopic metastases as small as five cell layers thick. To create tumor detecting bacteria, an attenuated strain of Salmonella was engineered to express and release the fluorescent protein ZsGreen. A single-layer antibody method was developed to measure low concentrations of ZsGreen. Engineered bacteria were administered to a microfluidic tumor-on-a-chip device to measure protein production. In culture, half of produced ZsGreen was released by viable bacteria at a rate of 87.6 fg bacterium(-1) h(-1). Single-layer antibody dots were able to detect bacterially produced ZsGreen at concentrations down to 4.5 ng ml(-1). Bacteria colonized in 0.12 mm(3) of tumor tissue in the microfluidic device released ZsGreen at a rate of 23.9 μg h(-1). This release demonstrates that ZsGreen readily diffuses through tissue and accumulates at detectable concentrations. Based on a mathematical pharmacokinetic model, the measured rate of release would enable detection of 0.043 mm(3) tumor masses, which is 2600 times smaller than the current limit of tomographic techniques. Tumor-detecting bacteria would provide a sensitive, minimally invasive method to detect tumor recurrence, monitor treatment efficacy, and identify the onset of metastatic disease.

Details

Language :
English
ISSN :
1757-9708
Volume :
7
Issue :
4
Database :
MEDLINE
Journal :
Integrative biology : quantitative biosciences from nano to macro
Publication Type :
Academic Journal
Accession number :
25737274
Full Text :
https://doi.org/10.1039/c5ib00047e