From Multistep Enzyme Monitoring to Whole-Cell Biotransformations: Development of Real-Time Ultraviolet Resonance Raman Spectroscopy.

Process analytical technologies (PAT) are used within industry to give real-time measurements of critical quality parameters, ultimately improving the quality by design (QbD) of the final product and reducing manufacturing costs. Spectroscopic and spectrophotometric methods are readily employed within PAT due to their ease of use, compatibility toward a range of sample types, robustness, and multiplexing capabilities. We have developed a UV resonance Raman (UVRR) spectroscopy approach to quantify industrially relevant biotransformations accurately, focusing on nitrile metabolizing enzymes: nitrile hydratase (NHase) and amidase versus nitrilase activity. Sensitive detection of the amide intermediate by UVRR spectroscopy enabled discrimination between the two nitrile-hydrolyzing pathways. Development of a flow-cell apparatus further exemplifies its suitability toward PAT measurements, incorporating in situ analysis within a closed system. Multivariate curve resolution-alternating least-squares (MCR-ALS) was applied to the UVRR spectra, as well as off-line HPLC measurements, to enable absolute quantification of substrate, intermediate, and product. Further application of hard modeling to MCR-ALS deconvolved concentration profiles enabled accurate kinetic determinations, thus removing the requirement for comparative off-line HPLC. Finally, successful quantitative measurements of in vivo activity using whole-cell biotransformations, where two Escherichia coli strains expressing either NHase (transforming benzonitrile to benzamide) or amidase (further conversion of benzamide to benzoic acid), illustrate the power, practicality, and sensitivity of this novel approach of multistep and, with further refinement, we believe, multiple micro-organism biotransformations.

Real-Time Monitoring of Enzyme-Catalysed Reactions using Deep UV Resonance Raman Spectroscopy.

For enzyme-catalysed biotransformations, continuous in situ detection methods minimise the need for sample manipulation, ultimately leading to more accurate real-time kinetic determinations of substrate(s) and product(s). We have established for the first time an on-line, real-time quantitative approach to monitor simultaneously multiple biotransformations based on UV resonance Raman (UVRR) spectroscopy. To exemplify the generality and versatility of this approach, multiple substrates and enzyme systems were used involving nitrile hydratase (NHase) and xanthine oxidase (XO), both of which are of industrial and biological significance, and incorporate multistep enzymatic conversions. Multivariate data analysis of the UVRR spectra, involving multivariate curve resolution-alternating least squares (MCR-ALS), was employed to effect absolute quantification of substrate(s) and product(s); repeated benchmarking of UVRR combined with MCR-ALS by HPLC confirmed excellent reproducibility.

A Structure-Guided Switch in the Regioselectivity of a Tryptophan Halogenase.

Flavin-dependent halogenases are potentially useful biocatalysts for the regioselective halogenation of aromatic compounds. Haloaromatic compounds can be utilised in the synthesis and biosynthesis of pharmaceuticals and other valuable products. Here we report the first X-ray crystal structure of a tryptophan 6-halogenase (SttH), which enabled key residues that contribute to the regioselectivity in tryptophan halogenases to be identified. Structure-guided mutagenesis resulted in a triple mutant (L460F/P461E/P462T) that exhibited a complete switch in regioselectivity; with the substrate 3-indolepropionate 75 % 5-chlorination was observed with the mutant in comparison to 90 % 6-chlorination for the wild-type SttH. This is the first clear example of how regiocomplementary halogenases can be created from a single parent enzyme. The biocatalytic repertoire of SttH was also expanded to include a range of indolic and non-indolic substrates.

Achieving optimal SERS through enhanced experimental design.

One of the current limitations surrounding surface-enhanced Raman scattering (SERS) is the perceived lack of reproducibility. SERS is indeed challenging, and for analyte detection, it is vital that the analyte interacts with the metal surface. However, as this is analyte dependent, there is not a single set of SERS conditions that are universal. This means that experimental optimisation for optimum SERS response is vital. Most researchers optimise one factor at a time, where a single parameter is altered first before going onto optimise the next. This is a very inefficient way of searching the experimental landscape. In this review, we explore the use of more powerful multivariate approaches to SERS experimental optimisation based on design of experiments and evolutionary computational methods. We particularly focus on colloidal-based SERS rather than thin film preparations as a result of their popularity. © 2015 The Authors. Journal of Raman Spectroscopy published by John Wiley & Sons, Ltd.