Alzheimer’s Disease

Protein Aggregation and FLIM Analysis

Alzheimer’s Disease (AD) is marked by the aggregation of amyloid-beta (Aβ) and tau proteins, leading to neuronal toxicity. We employ Time-Correlated Single-Photon Counting Fluorescence Lifetime Imaging Microscopy (TCSPC-FLIM) to study aggregation in vitro, in cellulo, and in vivo. Using Caenorhabditis elegans as a model organism allows us to track protein misfolding over time, offering insights into disease progression and drug screening.

Intracellular Aβ42 aggregation leads to cellular thermogenesis

CW Chung, AD Stephens, T Konno, E Ward, E Avezov, CF Kaminski, et al. Journal of the American Chemical Society 144 (22), 10034-10041

A unified in vitro to in vivo fluorescence lifetime screening platform yields amyloid β aggregation inhibitors

S Collins, L van Vliet, F Gielen, M Janeček, SW Valladolid, C Poudel, et al. bioRxiv, 2022.03. 28.485913

Structural progression of amyloid-β Arctic mutant aggregation in cells revealed by multiparametric imaging

M Lu, N Williamson, A Mishra, CH Michel, CF Kaminski, A Tunnacliffe, et al. Journal of Biological Chemistry 294 (5), 1478-1487

Imaging Aβ (1–42) fibril elongation reveals strongly polarised growth and growth incompetent states

LJ Young, GSK Schierle, CF Kaminski. Physical Chemistry Chemical Physics 19 (41), 27987-27996

Machine Learning for FLIM Optimisation

Traditional FLIM methods require long acquisition times. We have developed a deep learning model to accelerate the process, allowing for real-time tracking of Aβ aggregation in freely moving C. elegans. This method eliminates the need for immobilization, preserving natural physiological processes for more accurate results.

Deep learning for fluorescence lifetime predictions enables high-throughput in vivo imaging

S Kapsiani, NF Läubli, EN Ward, A Fernandez-Villegas, Bismoy Mazumder, CF Kaminski, GS Kaminski Schierle. bioRxiv, 2025.02.20.639036

Amyloid Beta in iPSCs and Microfluidics

We investigate Aβ uptake in iPSC-derived glutamatergic neurons, analyzing its impact on DNA integrity and synaptic function. Our microfluidic platforms and transparent microelectrode arrays allow us to study synaptic alterations in response to Aβ exposure.

Cholesterol Sensor for AD Research

Cholesterol metabolism is increasingly linked to Alzheimer’s pathology. We are developing organic electrochemical transistor (OECT) sensors to measure 24-hydroxycholesterol (24-HC) levels in the brain, providing a rapid diagnostic tool for early detection of Alzheimer’s.

Spike Sorting for AD Research

Our team is developing advanced computational tools to analyse neural firing patterns in AD models.

PseudoSorter: A self-supervised spike sorting approach applied to reveal Tau-induced reductions in neuronal activity

M Brockhoff, J Träuble, S Middya, T Fuchsberger, A Fernandez-Villegas, et al. Science Advances 11, eadr4155 (2025).

Collaborations

We collaborate with international optical imaging and bioengineering experts, including Prof. Clemens Kaminski (University of Cambridge, UK), Prof. George Malliaras (University of Cambridge, UK), and Prof. Janine Kirstein (Leibniz Institute on Aging, Germany), to advance AD research.