RESUMEN
Protein-protein interactions in living plant cells can be measured by changes in fluorescence anisotropy due to homo-FRET (Förster Resonance Energy Transfer). Here, the energy transfer between identical fluorophores, e.g., enhanced green fluorescent protein (EGFP) fused to a protein of interest, serves as a read-out for protein interaction and clustering. By applying homo-FRET imaging, not only dimeric complexes, but also bigger homomeric complex formation can be followed in vivo at high spatial and temporal resolution. Therefore, this method provides a powerful tool to investigate changes in complex formation over time in their natural environment with high precision at a subcellular level. Here, we describe the necessary theoretical background and how homo-FRET imaging is practically carried out. We also discuss potential pitfalls and points of consideration.
Asunto(s)
Transferencia Resonante de Energía de Fluorescencia , Colorantes Fluorescentes , Fenómenos Biofísicos , Polarización de Fluorescencia , Transferencia Resonante de Energía de Fluorescencia/métodos , Proteínas Fluorescentes Verdes/genética , Proteínas Fluorescentes Verdes/metabolismo , Células Vegetales/metabolismoRESUMEN
BACKGROUND: E-science technologies have significantly increased the availability of data. Research grant providers such as the European Union increasingly require open access publishing of research results and data. However, despite its significance to research, the adoption rate of open data technology remains low across all disciplines, especially in Europe where research has primarily focused on technical solutions (such as Zenodo or the Open Science Framework) or considered only parts of the issue. METHODS AND FINDINGS: In this study, we emphasized the non-technical factors perceived value and uncertainty factors in the context of academia, which impact researchers' acceptance of open data-the idea that researchers should not only publish their findings in the form of articles or reports, but also share the corresponding raw data sets. We present the results of a broad quantitative analysis including N = 995 researchers from 13 large to medium-sized universities in Germany. In order to test 11 hypotheses regarding researchers' intentions to share their data, as well as detect any hierarchical or disciplinary differences, we employed a structured equation model (SEM) following the partial least squares (PLS) modeling approach. CONCLUSIONS: Grounded in the value-based theory, this article proclaims that most individuals in academia embrace open data when the perceived advantages outweigh the disadvantages. Furthermore, uncertainty factors impact the perceived value (consisting of the perceived advantages and disadvantages) of sharing research data. We found that researchers' assumptions about effort required during the data preparation process were diminished by awareness of e-science technologies (such as Zenodo or the Open Science Framework), which also increased their tendency to perceive personal benefits via data exchange. Uncertainty factors seem to influence the intention to share data. Effects differ between disciplines and hierarchical levels.