Photoswitchable Machine-Engineered Plasmonic Nanosystem with High Optical Response for Ultrasensitive Detection of microRNAs and Proteins Adaptively.

Modulating optoelectronic properties of inorganic nanostructures tethered with light-responsive molecular switches by their conformational change in the solid state is fundamentally important for advanced nanoscale-device fabrication, specifically in biosensing applications. Herein, we present an entirely new solid-state design approach employing the light-induced reversible conformational change of spiropyran (SP)-merocyanine (MC) covalently attached to gold triangular nanoprisms (Au TNPs) via alkylthiolate self-assembled monolayers to produce a large localized surface plasmon resonance response (∼24 nm). This shift is consistent with the increase in thickness of the local dielectric shell-surrounded TNPs and perhaps short-range dipole-dipole (permanent and induced) interactions between TNPs and the zwitterionic MC form. Water contact angle measurement and Raman spectroscopy characterization unequivocally prove the formation of a stable TNP-MC structural motif. Utilizing this form, we fabricated the first adaptable nanoplasmonic biosensor, which uses an identical structural motif for ultrasensitive, highly specific, and programmable detection of microRNAs and proteins at attomolar concentrations in standard human plasma and urine samples, and at femtomolar concentrations from bladder cancer patient plasma (n = 10) and urine (n = 10), respectively. Most importantly, the TNP-MC structural motif displays a strong binding affinity with receptor molecules (i.e., single-stranded DNA and antibody) producing a highly stable biosensor. Taken together, the TNP-MC structural motif represents a multifunctional super biosensor with the potential to expand clinical diagnostics through simplifying biosensor design and providing highly accurate disease diagnosis.

ß Cell microRNAs Function as Molecular Hubs of Type 1 Diabetes Pathogenesis and as Biomarkers of Diabetes Risk.

MicroRNAs (miRNAs) are small non-coding RNAs that play a crucial role in modulating gene expression and are enriched in cell-derived extracellular vesicles (EVs). We investigated whether miRNAs from human islets and islet-derived EVs could provide insight into ß cell stress pathways activated during type 1 diabetes (T1D) evolution, therefore serving as potential disease biomarkers. We treated human islets from 10 cadaveric donors with IL-1ß and IFN-γ to model T1D ex vivo. MicroRNAs were isolated from islets and islet-derived EVs, and small RNA sequencing was performed. We found 20 and 14 differentially expressed (DE) miRNAs in cytokine- versus control-treated islets and EVs, respectively. Interestingly, the miRNAs found in EVs were mostly different from those found in islets. Only two miRNAs, miR-155-5p and miR-146a-5p, were upregulated in both islets and EVs, suggesting selective sorting of miRNAs into EVs. We used machine learning algorithms to rank DE EV-associated miRNAs, and developed custom label-free Localized Surface Plasmon Resonance-based biosensors to measure top ranked EVs in human plasma. Results from this analysis revealed that miR-155, miR-146, miR-30c, and miR-802 were upregulated and miR-124-3p was downregulated in plasma-derived EVs from children with recent-onset T1D. In addition, miR-146 and miR-30c were upregulated in plasma-derived EVs of autoantibody positive (AAb+) children compared to matched non-diabetic controls, while miR-124 was downregulated in both T1D and AAb+ groups. Furthermore, single-molecule fluorescence in situ hybridization confirmed increased expression of the most highly upregulated islet miRNA, miR-155, in pancreatic sections from organ donors with AAb+ and T1D.