c-Jun N-terminal kinases (JNKs) are central integrators of cell stress and are responsible for a multitude of signaling and gene expression changes in response to various environmental cues. Here, we describe the development of JNKAR2, a second-generation FRET-based JNK biosensor. JNKAR2 exhibits a ∼3.9-fold higher response amplitude over JNKAR1 while maintaining robust response dynamics and selectivity. Using JNKAR2 to illuminate JNK activation driven by angiotensin II (Ang II)/Ang II receptor type 1 (AT1R) signaling in HEK293 cells, we found that AT1R-mediated JNK activation is independent of β-arrestin but requires Gαq/11. Supporting a mechanism of Gαq/11-mediated JNK activation downstream of G protein-coupled receptors, stimulating the Gαq/11 coupling muscarinic acetylcholine M5 and M3 as well as endothelin type B receptors also induced robust JNKAR2 responses. On the other hand, neither the Gαi/o-preferring μ-opioid receptor nor the Gαs-preferring β2-adrenergic receptor was able to support JNK activation. The improved dynamic range of JNKAR2 further enabled us to probe Ang II-induced JNK signals in primary vascular smooth muscle cells, which were abolished by Gαq/11 inhibition. Targeting JNKAR2 to various subcellular compartments revealed that anisomycin induced global JNK signals, while AT1R-mediated JNK activation was absent from the plasma membrane and early endosomes. Together, we report on a second-generation JNK biosensor with substantially improved response amplitude that enables sensitive and selective visualization of JNK activation in real time and with subcellular resolution. JNKAR2 facilitates the dissection of the molecular mechanisms underlying JNK signaling.
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 seque...
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.