Integrated Approach from Sample-to-Answer for Grapevine Varietal Identification on a Portable Graphene Sensor Chip.

Identifying grape varieties in wine, related products, and raw materials is of great interest for enology and to ensure its authenticity. However, these matrices' complexity and low DNA content make this analysis particularly challenging. Integrating DNA analysis with 2D materials, such as graphene, offers an advantageous pathway toward ultrasensitive DNA detection. Here, we show that monolayer graphene provides an optimal test bed for nucleic acid detection with single-base resolution. Graphene's ultrathinness creates a large surface area with quantum confinement in the perpendicular direction that, upon functionalization, provides multiple sites for DNA immobilization and efficient detection. Its highly conjugated electronic structure, high carrier mobility, zero-energy band gap with the associated gating effect, and chemical inertness explain graphene's superior performance. For the first time, we present a DNA-based analytic tool for grapevine varietal discrimination using an integrated portable biosensor based on a monolayer graphene field-effect transistor array. The system comprises a wafer-scale fabricated graphene chip operated under liquid gating and connected to a miniaturized electronic readout. The platform can distinguish closely related grapevine varieties, thanks to specific DNA probes immobilized on the sensor, demonstrating high specificity even for discriminating single-nucleotide polymorphisms, which is hard to achieve with a classical end-point polymerase chain reaction or quantitative polymerase chain reaction. The sensor was operated in ultralow DNA concentrations, with a dynamic range of 1 aM to 0.1 nM and an attomolar detection limit of ∼0.19 aM. The reported biosensor provides a promising way toward developing decentralized analytical tools for tracking wine authenticity at different points of the food value chain, enabling data transmission and contributing to the digitalization of the agro-food industry.

The In Vitro Inhibitory Effect of Selected Asteraceae Plants on Pancreatic Lipase Followed by Phenolic Content Identification through Liquid Chromatography High Resolution Mass Spectrometry (LC-HRMS).

Pancreatic lipase (PNLIP, EC 3.1.1.3) plays a pivotal role in the digestion of dietary lipids, a metabolic pathway directly related to obesity. One of the effective strategies in obesity treatment is the inhibition of PNLIP, which is possible to be achieved by specific phenolic compounds occurring in high abundance in some plants. In this study, a multidisciplinary approach is presented investigating the PNLIP inhibitory effect of 33 plants belonging in the Asteraceae botanical family. In the first stage of the study, a rapid and cost-efficient PNLIP assay in a 96-microwell plate format was developed and important parameters were optimized, e.g., the enzyme substrate. Upon PNLIP assay optimization, aqueous and dichloromethane Asteraceae plant extracts were tested and a cut-off inhibition level was set to further analyze only the samples with a significant inhibitory effect (inhibitory rate > 40%), using an ultra-high-performance liquid chromatography hybrid quadrupole time-of-flight mass spectrometry (UHPLC-q-TOF-MS) method. Specifically, a metabolomic suspect screening was performed and 69 phenolic compounds were tentatively identified, including phenolic acids, flavonoids, flavonoid-3-O-glycosides, and flavonoid-7-O-glycosides, amongst others. In the case of aqueous extracts, phytochemicals known for inducing PNLIP inhibitory effect, e.g., compounds containing galloyl molecules or caffeoylquinic acids, were monitored in Chrysanthemum morifolium, Grindella camporum and Hieracium pilosella extracts. All in all, the presented approach combines in vitro bioactivity measurements to high-end metabolomics to identify phenolic compounds with potential medicinal and/or dietary applications.