Here we report a lateral flow aptasensor (LFA) for the simultaneous detection of platelet-derived growth factor-BB (PDGF-BB) and thrombin. Two pairs of aptamers, which are specific against PDGF-BB and thrombin, respectively, were used to prepare the LFA. Thiolated aptamers were immobilized on a gold nanoparticle (AuNP) surface and biotinylated aptamers were immobilized on the test zones of an LFA nitrocellulose membrane. The assay involved the capture of PDGF-BB and thrombin simultaneously in sandwich-type formats between the capture aptamers on the test zones of LFA and AuNP-labeled detection aptamers. AuNPs were thus captured on the test zones of the LFA and gave red bands to enable the visual detection of target proteins. Quantitative results were obtained by reading the test band intensities with a portable strip reader. By combining the highly specific molecular recognition properties of aptamers with the unique properties of lateral flow assay (low-cost, short assay time and a user-friendly format), the optimized aptasensor was capable of simultaneously detecting 1.0 nM of PDGF-BB and 1.5 nM of thrombin in association with a 10-min assay time. The biosensor was also successfully applied to detect PDGF-BB and thrombin in spiked human serum samples. The LFA shows great promise for the development of aptamer-based lateral flow strip biosensors for point-of-care or for the in-field detection of disease-related protein biomarkers.

Lateral flow nucleic acid biosensors (LFNABs) have attracted extensive attention due to their rapid turnaround time, low cost, and results that are visible to the naked eye. One of the key steps to develop LFNABs is to prepare DNA–gold nanoparticle (DNA–AuNP) conjugates, which affect the sensitivity of LFNABs significantly. To date, various conjugation methods—including the salt-aging method, microwave-assisted dry heating method, freeze–thaw method, low-pH method, and butanol dehydration method—have been reported to prepare DNA–AuNP conjugates. In this study, we conducted a comparative analysis of the analytical performances of LFNABs prepared with the above five conjugation methods, and we found that the butanol dehydration method gave the lowest detection limit. After systematic optimization, the LFNAB prepared with the butanol dehydration method had a detection limit of 5 pM for single-strand DNA, which is 100 times lower than that of the salt-aging method. The as-prepared LFNAB was applied to detect miRNA-21 in human serum, with satisfactory results. The butanol dehydration method thus offers a rapid conjugation approach to prepare DNA–AuNP conjugates for LFNABs, and it can also be extended to other types of DNA biosensors and biomedical applications.

JUNCAO wine fermentation metabolites are closely related to the final quality of the product. Currently, there are no studies of dynamic metabolite changes during fermentation of JUNCAO wine. Here, we used gas chromatography quadrupole time-of-flight mass spectrometry (GC-QTOF-MS) metabolomics and multivariate statistical analysis to explore the relationship between metabolites and fermentation time. A total of 189 metabolites were annotated throughout the fermentation process. The principal component analysis (PCA) revealed a clear separation between the samples in the early and late stages of fermentation. A total of 60 metabolites were annotated as differential during the fermentation (variable importance in the projection, VIP > 1, and p < 0.05), including 21 organic acids, 10 amino acids, 15 sugars and sugar alcohols, and 14 other metabolites. Pathway analysis showed that the most commonly influenced pathways (impact value > 0.1 and p < 0.05) were tricarboxylic acid cycle, alanine, aspartic acid and glutamic acid metabolism, pyrimidine metabolism, and other 10 metabolic pathways. Moreover, integrated metabolic pathways are generated to understand the conversion and accumulation of differential metabolites. Overall, these results provide a comprehensive overview of metabolite changes during fermentation of JUNCAO wine.