A new route to single-step and non-covalent immobilization of proteins on graphene is exemplified with the first biosensor for nitriles based on a graphene field-effect transistor (GFET). The biological recognition element is a fusion protein consisting of nitrile reductase QueF from Escherichia coli with an N-terminal self-assembling and graphene-binding dodecapeptide. Atomic force microscopy and analysis using a quartz crystal microbalance show that both the oligopeptide and the fusion protein incorporating it form a single adlayer of monomeric enzyme on graphene. The fusion protein has a 6.3-fold increase in binding affinity for benzyl cyanide (BnCN) versus wild-type QueF and a 1.4-fold increase for affinity for the enzyme's natural substrate preQ 0 . Density functional theory analysis of QueF's catalytic cycle with BnCN shows similar transition-state barriers to preQ 0 , but differences in the formation of the initial thioimidate covalent bonding (∆G ‡ = 19.0 kcal mol −1 for preQ 0 vs 27.7 kcal mol −1 for BnCN) and final disassociation step (∆G = −24.3 kcal mol −1 for preQ 0 vs ∆G = +4.6 kcal mol −1 for BnCN). Not only do these results offer a single-step route to GFET modification, but they also present new opportunities in the biocatalytic synthesis of primary amines from nitriles.

Aims This study sought to assess the volatile organic compound (VOC) profiles of ampicillin‐resistant and ‐susceptible Escherichia coli to evaluate whether VOC analysis may be utilized to identify resistant phenotypes. Methods and Results An E. coli BL21 (DE3) strain and its pET16b plasmid transformed ampicillin‐resistant counterpart were cultured for 6 h in drug‐free, low‐ and high‐concentrations of ampicillin. Headspace analysis was undertaken using thermal desorption‐gas chromatography‐mass spectrometry. Results revealed distinct VOC profiles with ampicillin‐resistant bacteria distinguishable from their susceptible counterparts using as few as six compounds. A minimum of 30 compounds (fold change >2, p ≤ 0.05) were differentially expressed between the strains across all set‐ups. Furthermore, three compounds (indole, acetoin and 3‐methyl‐1‐butanol) were observed to be significantly more abundant (fold change >2, p ≤ 0.05) in the resistant strain compared to the susceptible strain both in the presence and in the absence of drug stress. Conclusions Results indicate that E. coli with acquired ampicillin resistance exhibit an altered VOC profile compared to their susceptible counterpart both in the presence and in the absence of antibiotic stress. This suggests that there are fundamental differences between the metabolisms of ampicillin‐resistant and ‐susceptible E. coli which may be detected by means of VOC analysis. Significance and Impact of the Study Our findings suggest that VOC profiles may be utilized to differentiate between resistant and susceptible bacteria using just six compounds. Consequently, the development of machine‐learning models using VOC signatures shows considerable diagnostic applicability for the rapid and accurate detection of antimicrobial resistance.

The yellow rust of wheat (caused by Puccinia striiformis f. sp. tritici) is a devastating fungal infection that is responsible for significant wheat yield losses. The main challenge with the detection of this disease is that it can only be visually detected on the leaf surface between 7 and 10 days after infection, and by this point, counter measures such as the use of fungicides are generally less effective. The hypothesis of this study is to develop and use a compact electrochemical-based biosensor for the early detection of P. striiformis, thus enabling fast countermeasures to be taken. The biosensor that was developed consists of three layers. The first layer mimics the wheat leaf surface morphology. The second layer consists of a sucrose/agar mixture that acts as a substrate and contains a wheat-derived terpene volatile organic compound that stimulates the germination and growth of the spores of the yellow rust pathogen P. s. f. sp. tritici. The third layer consists of a nonenzymatic glucose sensor that produces a signal once invertase is produced by P. striiformis, which comes into contact with the second layer, thereby converting sucrose to glucose. The results show the proof that this innovative biosensor can enable the detection of yellow rust spores in 72 h.