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Tal Gilboa, PhD




Research Fellow




Postdoctoral research fellow




Tal Gilboa,* Zoe Swank,* Maia Norman,* Elizabeth Flynn,* David Walt

A digital seed amplification assay for the quantitative diagnosis and staging of Parkinson’s disease

I see great importance in promoting women in science, medicine, and engineering. During my academic journey, I have volunteered in multiple organizations to promote women and mentored young female scientists and high school students. Serving as a role model is the best way to fulfill this goal, and the Women in Medicine & Science Symposium is a great platform for presenting the fantastic things women scientists can accomplish. My main research interest is to continue integrating principles from bioengineering, nanotechnology, and biophysics and collaborating with clinicians to develop tools for the early detection of neurodegenerative diseases.


Parkinson’s disease (PD) is a devastating neurological movement disorder for which there are currently no approved diagnostics and few effective therapies. PD severity correlates with the accumulation of intraneuronal α-synuclein aggregates. ⍺-synuclein aggregates can be detected in the Cerebrospinal Fluid (CSF) using seed amplification assays (SAAs). However, current bulk SAAs are qualitative, not reproducible, and false positives can occur.


We are developing a digital SAA to quantify single a-synuclein aggregates and monitor individual filaments’ growth with high throughput. To accomplish this digitization, we confine the sample to either microwells or droplets; then, we run the aggregation reaction with monomers and an amyloid staining dye, enabling us to monitor the filaments’ growth in real-time.


Our digital SAA can detect pre-formed aggregates spiked into CSF down to 2 pg/ml concentrations. We improved the sensitivity and specificity of our assay by performing the digital SAA on beads coated with antibodies against the aggregated form of ⍺-synuclein. We also show that our assay can be used for drug screening.


The digital SAA that we are developing could transform the ability to detect PD and other neurodegenerative diseases early, monitor disease progression, and evaluate the efficacy of new drugs.