arXiv subjects

Yuge Liang

Publications and source records attributed to Yuge Liang.

2 recordsLinked to original sources

arXiv2026

SERS study of single-live-cell electrical permeabilization dynamics via plasmonic nanotubes

There is a growing demand for minimally invasive methods to analyze intracellular processes and signaling activities in individual living cells, including the identification of tumorigenic cell subpopulations. However, most conventional analytical methods require cell lysis, precluding repeated measurements in the same cell over time, or rely on exogenous labels and reporters that may perturb cellular function. Various applications based on vertical nanotubes have been developed that enable live cell monitoring and analysis by electroporation with low voltages. However, the extent and duration of membrane permeability and kinetics of membrane repair remain elusive. Here, we built a plasmonic platform with the capacity of surface enhanced Raman spectroscopy (SERS) to monitor the electroporation-induced membrane permeability dynamics in individual live cells attached onto 100-nm diameter nanotubes of 2 um height. Fibronectin was employed as extracellular matrix (ECM)-coating to facilitate cell attachment onto nanotubes. Using fluorescent-dye delivery as an independent validation method, we show that the fabricated nanostructures induce localized electrical permeabilization of the plasma membrane and enable monitoring of its subsequent recovery. We further use SERS to track molecular changes at the membrane during permeabilization and resealing. The SERS spectra provide molecular-level insight into changes in membrane-associated components and the ECM during electroporation and subsequent membrane recovery. Real time monitoring of pulse induced molecular changes holds great promise for characterizing intracellular signaling, cellular states, and cellular heterogeneity at the single cell level, including the identification of tumorigenic subpopulations. This capacity could facilitate the development of novel biosensing assay.

physics.app-ph↗

arXiv2026

Label-free SERS Discrimination of Native Proline Hydroxylation at Single-molecule peptide by Deep Learning-assisted plasmonic nanopore

Post-translational modifications (PTMs) play essential roles in regulating protein structure, function, and cellular signalling. However, peptide level discrimination of hydroxylation at the single-molecule level remains difficult. Here, we report a particle-in-pore single-molecule surface-enhanced Raman spectroscopy (SERS) platform combined with peak occurrence frequency (POF) analysis and a one-dimensional convolutional neural network (1D-CNN) for discriminating hydroxylated and non-hydroxylated HIF peptide fragments. Three peptide pairs containing the Pro-564 hydroxylation site, with lengths of 7, 9, and 15 amino acids (AAs), were investigated. POF analysis revealed reproducible hydroxylation-dependent spectral changes in the 7AA and 9AA peptide pairs, which were attributed to changes in adsorption conformation and surface interactions. CNN-based classification achieved post-evaluation accuracies of 72.98%, 78.55%, and 89.74% for the 7AA, 9AA, and 15AA peptide pairs, respectively, with AUC values above 0.80 for all the pairs, indicating a reliable discrimination. Gradient-weighted feature visualization further showed that CNN-sensitive regions overlapped with recurrent POF features, supporting the chemical relevance of the learned classification patterns. Notably, for the 15AA peptide pair, the enhanced citrate-associated band suggests that hydroxylation can substantially alter peptide-gold nanoparticle adsorption behaviour. This adsorption-mediated effect may amplify hydroxylation-induced spectral differences and contribute to the improved discrimination accuracy despite the increased structural complexity. These results demonstrate that the particle-in-pore sensor, assisted by deep learning, can capture hydroxylation-induced spectral and adsorption changes in peptide fragments, providing a promising strategy for ultrasensitive analysis of weak PTM signatures in peptides.

physics.bio-ph↗