Fluorescence- or Förster resonance energy transfer (FRET) is a measurable physical energy transfer phenomenon between appropriate chromophores, when they are in sufficient proximity, usually within 10 nm. This feature has made them incredibly useful tools for many biomedical studies on molecular interactions. Furthermore, this principle is increasingly exploited for the design of biosensors, where two chromophores are linked with a sensory domain controlling their distance and thus the degree of FRET. The versatility of these FRET-biosensors made it possible to assess a vast amount of biological variables in a fast and standardized manner, allowing not only high-throughput studies but also sub-cellular measurements of biological processes. In this review, we aim at giving an overview over the recent advances in genetically encoded, fluorescent-protein based FRET-biosensors, as these represent the largest and most vividly growing group of FRET-based sensors. For easy understanding, we are grouping them into four categories, depending on their molecular mechanism. These are based on: (a) cleavage; (b) conformational-change; (c) mechanical force and (d) changes in the micro-environment. We also address the many issues and considerations that come with the development of FRET-based biosensors, as well as the possibilities that are available to measure them.

The question whether two proteins interact with each other or whether a protein localizes to a certain region of the cell is often addressed with fluorescence microscopy and analysis of a potential colocalization of fluorescence markers. Since a mere visual estimation does not allow quantification of the degree of colocalization, different statistical methods of pixel‐intensity correlation are commonly used to score it. We observed that these correlation coefficients are prone to false positive results and tend to show high values even for molecules that reside in different organelles. Our aim was to improve this type of analysis and we developed a novel method combining object‐recognition based colocalization analysis with pixel‐intensity correlation to calculate an object‐corrected Pearson coefficient. We designed a macro for the Fiji‐version of the software ImageJ and tested the performance systematically with various organelle markers revealing an improved robustness of our approach over classical methods. In order to prove that colocalization does not necessarily mean a physical interaction, we performed FRET (fluorescence resonance energy transfer) microscopy. This confirmed that non‐interacting molecules can exhibit a nearly complete colocalization, but that they do not show any significant FRET signal in contrast to proteins that are bound to each other.

FRET (Fluorescence Resonance Energy Transfer) measurements are commonly applied to proof protein-protein interactions. However, standard methods of live cell FRET microscopy and signal normalization only allow a principle assessment of mutual binding and are unable to deduce quantitative information of the interaction. We present an evaluation and normalization procedure for 3-filter FRET measurements, which reflects the process of complex formation by plotting FRET-saturation curves. The advantage of this approach relative to traditional signal normalizations is demonstrated by mathematical simulations. Thereby, we also identify the contribution of critical parameters such as the total amount of donor and acceptor molecules and their molar ratio. When combined with a fitting procedure, this normalization facilitates the extraction of key properties of protein complexes such as the interaction stoichiometry or the apparent affinity of the binding partners. Finally, the feasibility of our method is verified by investigating three exemplary protein complexes. Altogether, our approach offers a novel method for a quantitative analysis of protein interactions by 3-filter FRET microscopy, as well as flow cytometry. To facilitate the application of this method, we created macros and routines for the programs ImageJ, R and MS-Excel, which we make publicly available.

Background: The IκB kinase (IKK) complex, comprising the two enzymes IKKα and IKKβ, is the main activator of the inflammatory transcription factor NF-κB, which is constitutively active in many cancers. While several connections between NF-κB signaling and the oncogene c-Myc have been shown, functional links between the signaling molecules are still poorly studied.Methods: Molecular interactions were shown by co-immunoprecipitation and FRET microscopy. Phosphorylation of c-Myc was shown by kinases assays and its activity by improved reporter gene systems. CRISPR/Cas9-mediated gene knockout and chemical inhibition were used to block IKK activity. The turnover of c-Myc variants was determined by degradation in presence of cycloheximide and by optical pulse-chase experiments.. Immunofluorescence of mouse prostate tissue and bioinformatics of human datasets were applied to correlate IKKα- and c-Myc levels. Cell proliferation was assessed by EdU incorporation and apoptosis by flow cytometry.Results: We show that IKKα and IKKβ bind to c-Myc and phosphorylate it at serines 67/71 within a sequence that is highly conserved. Knockout of IKKα decreased c-Myc-activity and increased its T58-phosphorylation, the target site for GSK3β, triggering polyubiquitination and degradation. c-Myc-mutants mimicking IKK-mediated S67/S71-phosphorylation exhibited slower turnover, higher cell proliferation and lower apoptosis, while the opposite was observed for non-phosphorylatable A67/A71-mutants. A significant positive correlation of c-Myc and IKKα levels was noticed in the prostate epithelium of mice and in a variety of human cancers.Conclusions: Our data imply that IKKα phosphorylates c-Myc on serines-67/71, thereby stabilizing it, leading to increased transcriptional activity, higher proliferation and decreased apoptosis.

Prostate cancer is very frequent and is, in many countries, the third-leading cause of cancer related death in men. While early diagnosis and treatment by surgical removal is often curative, metastasizing prostate cancer has a very bad prognosis. Based on the androgen-dependence of prostate epithelial cells, the standard treatment is blockade of the androgen receptor (AR). However, nearly all patients suffer from a tumor relapse as the metastasizing cells become AR-independent. In our study we show a counter-regulatory link between AR and NF-κB both in human cells and in mouse models of prostate cancer, implying that inhibition of AR signaling results in induction of NF-κB-dependent inflammatory pathways, which may even foster the survival of metastasizing cells. This could be shown by reporter gene assays, DNA-binding measurements, and immune-fluorescence microscopy, and furthermore by a whole set of computational methods using a variety of datasets. Interestingly, loss of PTEN, a frequent genetic alteration in prostate cancer, also causes an upregulation of NF-κB and inflammatory activity. Finally, we present a mathematical model of a dynamic network between AR, NF-κB/IκB, PI3K/PTEN, and the oncogene c-Myc, which indicates that AR blockade may upregulate c-Myc together with NF-κB, and that combined anti-AR/anti-NF-κB and anti-PI3K treatment might be beneficial.

The transcription factor ERG is known to have divergent roles. On one hand, it acts as differentiation factor of endothelial cells. On the other hand, it has pathological roles in various cancers. Genomic analyses of the ERG gene show that it gives rise to several isoforms. However, functional differences between these isoforms, representing potential reasons for distinct effects in diverse cell types have not been addressed in detail so far. We set out to investigate the major protein isoforms and found that ERG8 contains a unique C-terminus. This isoform, when expressed as GFP-fusion protein, localized mainly to the cytosol, whereas the other major isoforms (ERG1-4) were predominantly nuclear. Using site directed mutagenesis and laser scanning microscopy of live cells, we could identify nuclear localization (NLS) and nuclear export sequences (NES). These analyses indicated that ERG8 lacks a classical NLS and the DNA-binding domain, but holds an additional NES within its distinctive C-terminus. All the tested isoforms were shuttling between nucleus and cytosol and showed a high degree of mobility. ERG's 1 to 4 were transcriptionally active on ERG-promoter elements whereas ERG8 was inactive, which is in line with the absence of a DNA-binding domain. Fluorescence resonance energy transfer (FRET) microscopy revealed that ERG8 can bind to the transcriptionally active ERG's. Knockdown of ERG8 in endothelial cells resulted in upregulation of endogenous ERG-transcriptional activity implying ERG8 as an inhibitor of the active ERG isoforms. Quantitative PCR revealed a different ratio of active ERG's to ERG8 in cancer- versus non-transformed cells.