Recent advances in high-throughput mass spectrometry that accelerates enzyme engineering for biofuel research

Abstract

Enzymes play indispensable roles in producing biofuels, a sustainable and renewable source of transportation fuels. Lacking rational design rules, the development of industrially relevant enzyme catalysts relies heavily on highthroughput screening. However, few universal methods exist to rapidly characterize large-scale enzyme libraries. Therefore, assay development is necessary on an ad hoc basis to link enzyme properties to spectrophotometric signals and often requires the use of surrogate, optically active substrates. On the other hand, mass spectrometry (MS) performs label-free enzyme assays that utilize native substrates and is therefore generally applicable. But the analytical speed of MS is considered rate limiting, mainly due to the use of time-consuming chromatographic separation in traditional MS analysis. Thanks to new instrumentation and sample preparation methods, direct analyte introduction into a mass spectrometer without a prior chromatographic step can be achieved by laser, microfluidics, and acoustics, so that each sample can be analyzed within seconds. Here we review recent advances in MS platforms that improve the throughput of enzyme library screening and discuss how these advances can potentially facilitate biofuel research by providing high sensitivity, selectivity and quantitation that are difficult to obtain using traditional assays. We also highlight the limitations of current MS assays in studying biofuel-related enzymes and propose possible solutions.

Picomolar-Level Sensing of Cannabidiol by Metal Nanoparticles Functionalized with Chemically Induced Dimerization Binders

“…The concentration-dependent CBD sensing results were further quantified by extracting the top 5 μL in a PDMS plate (Figure f), examining their optical extinction (Figure g), and recording the extinction peaking values at the AuNP resonance (560 nm) (Figure h). Clearly, the incubation-based (red line, Figure h) and ICED methods (black line, Figure h) displayed similar concentration-dependent signal modulation; however, the LOD for the ICED method (∼144 pM) was about 5 times better than the incubation-based detection (∼700 pM) and the traditional sandwich ELISA with the same reagents (∼800 pM) …”

“…Clearly, the incubation-based (red line, Figure 2h) and ICED methods (black line, Figure 2h) displayed similar concentration-dependent signal modulation; however, the LOD for the ICED method (∼144 pM) was about 5 times better than the incubation-based detection (∼700 pM) and the traditional sandwich ELISA with the same reagents (∼800 pM). 11 ■ MODULAR ANALYTIC MODEL FOR SENSOR…”

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