Biology subjects

Edel, J.

Publications and source records attributed to Edel, J..

4 recordsLinked to original sources

bioRxiv2025

Tracking gene expression of single mitochondria in live neurons using nanotweezers

Neurons are highly polarised cells that depend on mitochondria for energy and signalling homeostasis. Importantly, energy and signalling requirements vary considerably across individual neurons both spatially and temporally. Therefore, to fully understand neuronal mitochondria, methods are needed to analyse mitochondria in live cells over time. The nanotweezer, a minimally invasive single-cell sampling technique, enables precise extraction a individual mitochondria from defined subcellular locations. Here, we combine single-mitochondrial extraction from live neurons with mitochondrial gene expression tracking and mtDNA profiling. By tracking mitochondrial gene expression in the same neurons over time, we reveal a downregulation of mitochondrial genes MT-ND1 and MT-ATP6 following exposure to -synuclein aggregates, independent of the proximity of the aggregates to the sampled mitochondria. Our approach provides precise, dynamic measurements of mitochondrial composition and gene expression in vivo at single-organelle resolution, enabling mechanistic studies of neuronal mitochondrial heterogeneity and its perturbation in models of neurodegeneration.

neuroscience↗

bioRxiv2025

Different data analysis models for detecting miRNAs using nanopores

Nanopore sensors offer exceptional sensitivity for detecting single molecules, making them ideal for early disease diagnostics. In this study, we present a multiplexed nanopore-based assay that combines DNA-barcoded probes with advanced computational analysis to detect microRNAs (miRNAs) with high specificity and quantitative accuracy. Each probe binds selectively to its target biomarker and generates a characteristic delay in the ionic current signal upon translocation through the nanopore, enabling label-free detection. We evaluated three analytical strategies for classifying delayed versus non-delayed events: (1) moving standard deviation (MSD), (2) spectral entropy (SE), and (3) a convolutional neural network (CNN). While MSD and SE rely on manually defined thresholds and exhibit limited sensitivity, the CNN model, trained on image representations of raw current traces, achieved near-perfect classification performance across all metrics. Grad-CAM visualisation confirmed that the CNN focused on biophysically relevant signal regions, enhancing interpretability and generalisability. All methods produced sigmoidal concentration-response curves consistent with expected binding kinetics, and nanopore-derived delay metrics closely matched RT-qPCR validation data. All three methods were capable of distinguishing between signal classes; however, the CNN model demonstrated superior sensitivity and robustness. This work highlights the importance of data interpretation in nanopore sensing and presents a comparative framework for binary event classification. The findings pave the way for the development of machine learning-driven nanopore diagnostics capable of detecting diverse biomarker types at the single-molecule level.

biophysics↗

bioRxiv2025

Formation of amyloid-like HTTex1 aggregates in neurons, downregulation of synaptic proteins and early mortality of Huntington's disease flies are causally linked

Amyloidogenic mutant huntingtin exon-1 (mHTTex1) protein aggregates with pathogenic polyglutamine (polyQ) tracts are the potential root cause of Huntingtons disease (HD). Here, we assessed the gain-of-function toxicity of mHTTex1 aggregation in neurons of HD transgenic flies. We show that the rate of mHTTex1 aggregation in neurons and early mortality of HD transgenic flies are correlated. We observed sequestration of key synaptic proteins into amyloid-like mHTTex1 aggregates and a concomitant decrease of their transcript levels, suggesting that progressive mHTTex1 aggregate stress in neurons leads to an impairment of synaptic function. Machine learning-based data analysis revealed that the abundance of synaptic proteins such as the vesicular monoamine transporter Vmat in the brain is predictive of fly survival. RNAi knockdown of Vmat-encoding transcripts in neurons with pathogenic amyloid-like HTTex1Q97 aggregates further shortened the lifespan of HD flies, supporting the hypothesis that mHTTex1 aggregation drives impairment of synaptic processes and pathogenesis of HD.

molecular biology↗

bioRxiv2022

Highly multiplexed detection of microRNAs, proteins and small molecules using barcoded molecular probes and nanopore sequencing

Currently, most blood tests in a clinical setting only investigate a handful of markers. A low-cost, rapid, and highly multiplexed platform for the quantitative detection of blood biomarkers has the potential to advance clinical diagnostics beyond the single biomarker paradigm. In this study, we perform nanopore sequencing of barcoded molecular probes that have been engineered to recognise a panel of biological targets (miRNAs, proteins, and small molecules such as neurotransmitters), allowing for highly multiplexed simultaneous detection. Our workflow is rapid, from sample preparation to results in 1 hour. We also demonstrate that the strategy can be used to detect biomarkers directly from human serum without extraction or amplification. The established method is easily adaptable, as the number and type of targets detected can be greatly expanded depending on the application required.

biophysics↗