Yeast surface display (YSD) is a powerful tool for protein engineering, yet its broader application is often limited by suboptimal display efficiency. To address this, we systematically investigated the combinatorial effects of three key genetic determinants—promoter strength, anchoring protein identity, and fusion orientation (N- vs. C-terminal)—on the surface display level of enhanced green fluorescent protein (eGFP) in S. cerevisiae. A library of recombinant yeast strains was constructed, each harboring distinct combinations of these elements, and their display efficiencies were quantitatively assessed via fluorescence spectroscopy-based analysis. Our results demonstrate that the synergistic optimization of all three parameters is essential for maximizing YSD performance. Among all constructs tested, the novel plasmid system pYGAL1-Sed1p-eGFP-C—which combines the strong inducible GAL1promoter, the Sed1p cell wall anchor, and a C-terminal eGFP fusion—exhibited the highest display efficiency. This optimal configuration achieved a mean fluorescence intensity over 10.3-fold higher than the baseline system (pYSED1-Aga1p-eGFP-C) and 9.5-fold higher than the alternative N-terminal fusion design (pYSED1-eGFP-Aga1p-N). These findings establish a clear design principle for engineering high-efficiency YSD platforms. The pYGAL1-Sed1p-eGFP-C system not only provides a robust and highly efficient chassis for displaying eGFP but also holds significant promise as a versatile scaffold for the surface presentation of diverse heterologous proteins in yeast, thereby expanding the utility of YSD in biotechnology and synthetic biology.
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.
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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.