Aug 2026· Protein Expression and Purification· pp.
106993
· 0 citations· 31 references
Medicine
Abstract
Engineering mRNA stability is a promising yet underexplored approach for improving recombinant protein production in bacterial systems. In this study, we evaluated the effect of synthetic 3'-UTR hairpin structures on mRNA stability and protein yield in Escherichia coli using two SUMO-fusion expression systems. Hairpin elements with defined structural features were introduced downstream of the coding sequence. In all constructs, 3'-UTR hairpins increased mRNA half-life, with stabilization ranging from approximately 2-fold to 3-fold (n = 3 biological replicates). In the SUMO-SARS-CoV-2-derived peptide system, enhanced transcript stability was accompanied by a marked increase in specific cellular fusion-protein content, reaching up to 6.8-fold relative to the control (n = 3). In the SUMO-liraglutide-derived peptide system, mRNA stabilization was also pronounced, and the increase in specific cellular fusion-protein content reached approximately 3-fold (p < 0.001, n = 6). These findings show that 3'-UTR engineering is an effective strategy for modulating mRNA stability in *E. coli*, but the quantitative relationship between transcript persistence and protein accumulation is context-dependent and likely influenced by additional factors, including translation efficiency. Overall, engineering of 3'-terminal RNA structures provides a practical tool for post-transcriptional tuning of recombinant expression systems.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· SSE@SIGSOFT FSE· 56 citations· ⚡4
This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.
Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.