High-resolution mass spectrometry (HRMS) has greatly expanded the untargeted annotation of RNA modifications and the investigation of epitranscriptomic profiles at the single-nucleoside level. However, the comprehensive characterization of endogenous modified nucleosides in biological matrices remains challenging due to their low abundance, structural diversity, and isomerism, despite their emerging role as biomarkers of RNA turnover, cellular stress, and disease-related metabolic alterations. We developed an integrated LC-HRMS suspect screening workflow for the structured annotation of modified nucleosides in clinically relevant samples. The approach combines a curated in-house mass list of biologically relevant nucleoside modifications with a dedicated data-processing pipeline, enabling efficient feature prioritization and the annotation of 60 nucleoside-related compounds with different levels of identification confidence. Where authentic analytical standards were available, selected annotations were further confirmed by agreement in accurate mass, retention time, and MS/MS fragmentation. Chromatographic conditions were optimized to resolve isomeric species, while stepped normalized collision energy acquisition provided complementary fragmentation data to support structural annotation. The workflow was further applied to a small pilot set of urine samples from patients with prostate cancer (PCa) and benign prostatic hyperplasia (BPH) to illustrate its applicability in a clinically relevant matrix. Exploratory statistical analysis was used only to visualize preliminary abundance trends between the two groups. The results highlight the ability of the workflow to prioritize modified-nucleoside features for further investigation while requiring minimal sample preparation. Although confirmation of the remaining low-abundance and isomeric annotations and assessment of their biological relevance will require further validation, and larger independent cohorts, the proposed workflow provides a practical framework for systematic modified-nucleoside annotation and hypothesis generation in future metabolomics studies.
Abstract The choice of optical labels for live-cell imaging requires a characterization of interactions with their biological environment. Here, we discuss alterations of the molecular composition and interactions in the endolysosomal pathway of living cells by the fluorescent dye for lysosome labeling LysoSensor Green (LSG) based on vibrational nanospectroscopy using surface-enhanced Raman scattering (SERS) and soft X-ray nanotomography (SXT). A connection between the accumulation of LSG and ultrastructural changes is found by SXT that suggests an impact of the dye on cellular function. The biochemical effects in the endolysosomal system are detailed by different SERS experiments using gold nanoparticles as plasmonic probes, one that includes endolysosomes of all maturation stages and another one probing exclusively the lysosomal stage as the target compartment of the fluorescent label. The differences in SERS signals between the cells exposed to LSG compared to their controls are related to changes in the biochemical environment of the gold nanoparticles in the endolysosomal structures. As indicated by the occurrence of specific signals assigned to the interaction of the nanoprobes with proteins, nucleic acids, lipids, and LSG, respectively, the presence of LSG mainly affects the activity of enzymes that are involved in the degradation of proteins and nucleic acids in the lysosomes. The molecular changes when endolysosomes of all maturation stages contribute to the spectrum further point to LSG affecting cellular function along the whole endolysosomal pathway. The proposed complementary approach for nanoprobe characterization can be used for the validation of existing optical labels in fluorescence and multimodal imaging methods.
Abstract Bead-based electrochemiluminescence (ECL) is inherently limited by the distance between the electrode and the immobilized Ru(bpy)32+ luminophores, requiring sufficiently long-lived reactive diffusive intermediates to enable remote excitation. Tertiary amines, and particularly tri-n-propylamine (TPrA), remain the benchmark coreactant for Ru(bpy)32+-based systems. However, amines are typically used at high concentrations, which, together with their toxicity, volatility, and limited compatibility with aqueous and biological environments, motivates the development of alternative coreactant systems. Here, we introduce an amine-free strategy for the remote excitation of Ru(bpy)32+-labeled beads at unprecedently low onset potential (−0.08 V vs Ag/AgCl) by exploiting a self-sustaining S2O82–-C2O42– radical cascade initiated by the Ru(NH3)63+/2+ redox couple. The cascade generates the complementary SO4•– and CO2•– radicals required for the remote excitation of Ru(bpy)32+, thereby enabling, for the first time, amine-free ECL from bead-bound luminophore. Mechanism investigations further reveal how the incorporation of Ru(bpy)32+ perturbs the reaction network by introducing competitive radical-consuming pathways that divert reactive radicals from propagation toward luminophore excitation. Correlating the ECL intensity with the coulometric descriptor of the cascade radical propagation efficiency, nS, demonstrates that maximum emission arises from a balance between radical propagation and consumption reactions. These results establish an amine-free, low-potential route for bead-based ECL generation and provide mechanistic principles for the rational development of alternative coreactant systems beyond conventional tertiary amines for bead-based ECL.
Abstract Extracellular vesicles (EVs), including those commonly described as exosomes, carry proteins, lipids, and nucleic acids that reflect the molecular state of their parent cells, making them attractive biomarkers for liquid biopsy-based cancer diagnosis. Surface-enhanced Raman spectroscopy (SERS), which builds on conventional Raman spectroscopy (RS), can read this cargo as vibrational fingerprints, label-free or via targeted nanoprobes, with high sensitivity from small sample volumes. This review examines recent advances in SERS-based exosome/EV analysis for cancer diagnosis, following the workflow from sample to diagnostic decision. We discuss how EV isolation, characterization, heterogeneity, and coisolated lipoproteins and proteins shape the measured spectra and review plasmonic substrates, biosensor and microfluidic platforms, label-free versus label-based strategies, and Raman band assignments. Particular emphasis is placed on artificial intelligence (AI) and machine learning (ML) for decoding exosome/EV SERS fingerprints, from conventional classifiers to deep learning (DL) and explainable AI, together with common pitfalls such as small cohorts, spectrum-level data leakage, class imbalance, and a lack of external validation. Applications in cancer detection, classification, subtyping, and monitoring are summarized for prostate, lung, breast, and pancreatic cancers, and representative platforms are compared by analytical performance and clinical readiness and against circulating tumor DNA and circulating tumor cell assays. Finally, we offer perspectives on the standardization, reference materials, shared spectral databases, and multicenter validation needed for clinical translation, positioning AI/ML-assisted SERS as a complementary tool for cancer triage and monitoring.
Abstract Cyanobacteria (blue-green algae) produce geosmin, a volatile organic compound associated with ecological imbalance that adversely affects aquatic organisms by impairing growth and reproduction, weakening immune responses, and reducing aquaculture yields and quality. Herein, we developed a rapid, portable and ultrasensitive approach for geosmin detection based on an aptamer-modified silver-coated porous silicon (Ag-pSi) microarray that serves as a surface-enhanced Raman spectroscopy (SERS) transducer. The Ag-pSi substrate, characterized by a high surface area that efficiently distributed noble metal nanoparticles across the thin film, significantly enhanced Raman scattering, yielding an analytical enhancement factor of 2.17 × 108. The microarray scaffold, comprising 25 discrete sensing spots, exhibited a linear response across geosmin concentrations from 0.001 to 10 μg L–1, with an exceptionally low detection limit of 0.1 ng L–1. The performance evaluation demonstrated high reusability, storage stability and high selectivity, as evidenced by 9 successful regeneration cycles, a 7 week shelf life and negligible interference from coexisting metabolites. The scientific feasibility of the fabricated SERS array was further confirmed across various aqueous media, with recovery rates ranging from 94% to 103%, consistent with the benchmark approach. Overall, the integrated SERS-based approach offers a transformative and practical solution for sensitive monitoring of off-flavor contaminants across aquaculture, food safety, and environmental contexts.
