Fast impedimetric immunosensing of IgGs associated with peanut and hazelnut allergens

Food allergies trigger a variety of clinical adverse symptoms and clinical evidence suggests that the presence of food allergy-related IgG can be helpful in the diagnosis when analyzed at the peptide-epitope level. To validate and select the peptides based on their specificity toward hazelnut or peanut epitopes, the authors of this study developed a silicon-based microchip coupled with click-chemistry bound peptides identified by the Fraunhofer Institute for Cell Therapy and Immunology. Peptides related to hazelnut and peanut allergies were identified and used to develop a silicon-based microchip. Peptides were coupled with click-chemistry to the sensor surface. The immunosensor was developed by electrografting diazotized amino phenylacetic acid and subsequently, dibenzocyclooctyne-amine (DBCO-NH2) was used as click-chemistry to allow coupling of the peptides with a C-terminal linker and azide structure. Energy-dispersive X-ray spectroscopy, electrochemical impedance spectroscopy (EIS), and fluorescence microscopy techniques have been used to analyze the bio-functionalization of the developed electrode. The peptide-epitope recognition was studied for seven allergen-derived peptides. The electrochemical responses were studied with sera from rabbits immunized with hazelnut and peanut powder. The microchips functionalized with the chosen peptides (peanut peptides T12 and EO13 and hazelnut peptides S4 and EO14 with an RSD of 4%, 3%, 9%, and 1% respectively) demonstrated their ability to specifically detect prevalent anti-nut related IgGs in rabbit sera in a range of dilutions from 1:500000 (0.0002%) until 1:50000 (0.002%). In addition, the other peptides showed promising differentiation abilities which can be further studied to perform multivariable detection fingerprint of anti-allergens in blood sera.

Detection and quantification of folic acid in serum via a dual-emission fluorescence nanoprobe

Folic acid (FA) is an essential vitamin in humans, and thus, rapid, accurate, and sensitive methods for its quantification in different biological samples are needed. This work describes a novel, simple, and effective dual-emission fluorescence nanoprobe for FA detection and quantification. The probe was covalently linked to amino-modified orange quantum dots (QDs) and carboxyl-modified blue graphene quantum dots (GQDs). The resulting material exhibited two emission peaks at 401 and 605 nm upon excitation at 310 nm. The probe had good selectivity and sensitivity toward FA with an exceptionally low detection limit (LOD = 0.09 nM). This probe was effectively used to quantify FA in animal serum samples. The method has potential utility for FA analysis in different types of biological samples. Graphical abstract.

Top-down and bottom-up lipidomic analysis of rabbit lipoproteins under different metabolic conditions using flow field-flow fractionation, nanoflow liquid chromatography and mass spectrometry

This study demonstrated the performances of top-down and bottom-up approaches in lipidomic analysis of lipoproteins from rabbits raised under different metabolic conditions: healthy controls, carrageenan-induced inflammation, dehydration, high cholesterol (HC) diet, and highest cholesterol diet with inflammation (HCI). In the bottom-up approach, the high density lipoproteins (HDL) and the low density lipoproteins (LDL) were size-sorted and collected on a semi-preparative scale using a multiplexed hollow fiber flow field-flow fractionation (MxHF5), followed by nanoflow liquid chromatography-ESI-MS/MS (nLC-ESI-MS/MS) analysis of the lipids extracted from each lipoprotein fraction. In the top-down method, size-fractionated lipoproteins were directly infused to MS for quantitative analysis of targeted lipids using chip-type asymmetrical flow field-flow fractionation-electrospray ionization-tandem mass spectrometry (cAF4-ESI-MS/MS) in selected reaction monitoring (SRM) mode. The comprehensive bottom-up analysis yielded 122 and 104 lipids from HDL and LDL, respectively. Rabbits within the HC and HCI groups had lipid patterns that contrasted most substantially from those of controls, suggesting that HC diet significantly alters the lipid composition of lipoproteins. Among the identified lipids, 20 lipid species that exhibited large differences (>10-fold) were selected as targets for the top-down quantitative analysis in order to compare the results with those from the bottom-up method. Statistical comparison of the results from the two methods revealed that the results were not significantly different for most of the selected species, except for those species with only small differences in concentration between groups. The current study demonstrated that top-down lipid analysis using cAF4-ESI-MS/MS is a powerful high-speed analytical platform for targeted lipidomic analysis that does not require the extraction of lipids from blood samples.