# Advanced multiplexing technologies with innovative Dual-Channel Dark-FRET biosensors for dynamic monitoring of alpha-synuclein pathophysiology: From cellular to in vivo models

> **NIH NIH R21** · UNIVERSITY OF MINNESOTA · 2024 · $222,886

## Abstract

ABSTRACT:
Alpha-synuclein (aSyn) accumulation and misfolding is implicated in the pathogenesis of Parkinson's Disease
(PD) and related synucleinopathies. These disorders include multiple cellular dysfunctions including impaired
proteostasis (e.g., the dysregulation of the autophagy lysosomal pathway [ALP]). As preclinical disease models
become more complex to better recapitulate disease relevant pathophysiology— i.e., monoculture ➔ 2D co-
culture ➔ 3D organoids (both mono- and co-cultured) ➔ in vivo — advanced multiplexing technologies that are
capable of dynamic temporal and spatial monitoring of protein-protein interactions (e.g., aSyn oligomerization
and misfolding) and pathological phenotypes are required. Existing fluorescence-based biosensors are limited
by their static nature and inability to differentiate signals across distinct cell types within multi-cellular
environments. To address this, our proposal introduces Dark-FRET (DF) and Dual-Channel DF (DCDF) cellular
biosensors that utilize the Shadow-G/Y/R series of acceptor protein which were engineered as to have reduced
quantum yield and negligible fluorescence emission, eliminating emission spillover from acceptor proteins which
facilitates improved live-cell multiplexing for multiple protein-protein interaction (PPI) fluorescence assays.
This cutting-edge approach enables real-time monitoring of both aSyn folding (ShadowY-aSyn-mNeongreen)
and aggregation (aSyn-mScarlet-I3/ShadowR) FRET biosensors expressed in distinct cellular populations. We
expand on these capabilities by multiplexing the aSyn DCDF biosensors with our TFEB (the master regulator of
ALP), FRET and nuclear translocation biosensors. Aim 1 involves applying these biosensors to CNS-resident
cell lines (neurons, microglia, astrocytes) to establish mono-, bi-, and tri-culture cellular models for dynamically
tracking cell-specific aSyn interactions and ALP phenotype. Aim 2 extends DCDF technology to in vivo models
using novel C. elegans strains expressing aSyn DCDF and ALP biosensors in specific tissues. By enabling
simultaneous monitoring of aSyn oligomerization and phenotypic dysfunction, this approach provides a valuable
tool for investigating synucleinopathies. Its potential applications extend to 3D organoids and hiPSC models,
offering insights into diverse cell-type pathways and enabling the identification of compounds modulating aSyn
oligomerization and pathological phenotypes in these advanced preclinical models.
In summary, our DF/DCDF technology presents a groundbreaking approach, enabling dynamic monitoring of
aSyn aggregation and pathological phenotypes across complex disease models, paving the way to address
biological questions on the supporting roles of microglia and astrocytes on neuronal health and function.
Furthermore, these multiplexed biosensors represent an innovative preclinical therapeutic discovery platform
that holds promise for enhancing the drug discovery process, potentially filling the therapeut...

## Key facts

- **NIH application ID:** 10998417
- **Project number:** 1R21AG089930-01
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Jonathan N Sachs
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $222,886
- **Award type:** 1
- **Project period:** 2024-07-15 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10998417

## Citation

> US National Institutes of Health, RePORTER application 10998417, Advanced multiplexing technologies with innovative Dual-Channel Dark-FRET biosensors for dynamic monitoring of alpha-synuclein pathophysiology: From cellular to in vivo models (1R21AG089930-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10998417. Licensed CC0.

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