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Updated: Aug 20, 2026

Fast Enzymatic Processing of Proteins for MS Detection with a Flow-through Microreactor
Published on: April 6, 2016
Immobilized enzyme reactors as enabling technologies for automated multidimensional analytical workflows in the era
Wendy Appiagyei Mensah1, Maša Nabergoj2, Sebastijan Peljhan2
1Department of Pharmacy and Biotechnology, Alma Mater Studiorum University of Bologna, via Belmeloro 6, Bologna, 40126, Italy.
Abstract:
Immobilized enzyme reactors (IMERs) are emerging as important components of advanced analytical workflows, in which selective enzymatic transformations are directly combined with continuous-flow operation and high-resolution separation techniques. By converting traditionally offline biochemical reactions into automated, residence-time-controlled modules, IMERs offer major advantages in speed, reproducibility, and compatibility with multidimensional chromatographic and mass spectrometric platforms. In protein analysis, selected IMER-based technologies have reached substantial technical maturity and are increasingly integrated into liquid-chromatography mass spectrometry workflows for peptide mapping, structural characterization, and glycoanalysis, while their routine implementation in regulated quality control remains more limited. In contrast, applications to nucleic acid therapeutics, including oligonucleotides, DNA- and messenger RNA (mRNA)-based modalities, are still at an earlier stage of development but are progressing rapidly. Recent studies highlight growing potential in controlled nuclease processing, online mapping workflows, reusable in vitro transcription platforms, and impurity-oriented analytical strategies. This emerging area is particularly timely because the rapid expansion of nucleic acid medicines is creating analytical demands that align closely with the modular strengths of IMER systems. By examining mature protein applications alongside emerging nucleic acid workflows, this review provides a comparative perspective on how IMER technology is evolving across different classes of macromolecular therapeutics. Current limitations, translational barriers, and future opportunities toward standardized, automated, and data-rich analytical workflows are critically discussed.
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