Can I image Coomassie and GFP in gels at the same time with a fluorescence scanner?

I'm working with a GFP-tagged protein and am routinely using a fluorescence imager (GE Typhoon) and a standard optical scanner to capture fluorescent and absorption images, respectively, of my SDS-PAGE gels. The Typhoon supports multiple channels, so is there some way that I can scan for the two on the same device (GFP + total protein)? I assume I can't do absorption on a fluorescence scanner…

I could manually register the two images, but it would be laborious as they are at different resolutions, slightly different rotations, and the gel can stretch ever-so-slightly when placing it on the platens.

Coomassie blue fluoresces in infrared when bound to protein, so if your reader has the appropriate filter set, it should be possible.

Rapid protein-folding assay using green fluorescent protein

Formation of the chromophore of green fluorescent protein (GFP) depends on the correct folding of the protein. We constructed a "folding reporter" vector, in which a test protein is expressed as an N-terminal fusion with GFP. Using a test panel of 20 proteins, we demonstrated that the fluorescence of Escherichia coli cells expressing such GFP fusions is related to the productive folding of the upstream protein domains expressed alone. We used this fluorescent indicator of protein folding to evolve proteins that are normally prone to aggregation during expression in E. coli into closely related proteins that fold robustly and are fully soluble and functional. This approach to improving protein folding does not require functional assays for the protein of interest and provides a simple route to improving protein folding and expression by directed evolution.

Access options

Get full journal access for 1 year

All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.

Get time limited or full article access on ReadCube.

All prices are NET prices.


1. Prepare a 150 &mul recombinant GFP with various concentrations (0.00074 nM - 6.21 &muM) in assay buffer and equilibrate to 25°C. (Assay buffer: 10 mM Tris-HCl (pH 8.0), 10 mM EDTA, 0.02% sodium azide.)

2. Read at excitation wavelengths 485 nm and emission 535 nm.

- 96 Well Polystyrene Microplate, black

3 ug of reduced ab84191 on SDS-PAGE, stained with Coomassie Blue.

Tissue clearing and GFP preservation in the heart

The fast development and usage of tissue clearing techniques relates to the rapid development of imaging methods, such as confocal microscopy and light sheet microscopy. Together these methods can be used to reconstruct the 3D anatomy of the tissue (Costantini etਊl., 2019).

One of the main model organisms in biological research is the mouse model, with its wide array of possible genetical modification including insertion of fluorescently labeled proteins (e.g., GFP) as reporter genes. The first developed tissue clearing methods used hydrophobic compounds, which dehydrate the tissue and dehydration quench the introduced fluorescent proteins (i.e., GFP). To avoid this phenomenon, various hydrophilic (water-based) clearing solutions were developed. However, water-based methods have had lower tissue clearing performance (Silvestri etਊl., 2016), while preserving the fluorescence. Figures 2 C and 2D illustrate preserving GFP fluorescence in embryonic heart of different stages (ED10.5 and ED14.5) by the CUBIC tissue clearing method. Besides using a hydrophilic clearing solution, another approach to maintain fluorescence is a tissue transformation method involving embedding the tissue in acrylamide gel𠅌LARITY (Chung etਊl., 2013).

Examples of immunostaining and preserving GFP fluorescence with tissue clearing on the developing mouse heart

(A and B) Immunohistochemistry combined with BABB on ED 9.5 mouse embryo, smooth muscle actin antibody (SMA) in red labeling the myocardium, CD31 (PECAM-1) in green staining the endocardium (B), and DAPI nuclear staining (not very distinct at this low magnification) in blue.

(C and D) Preservation of natural GFP fluorescence with CUBIC tissue clearing on ED 10.5 (C) and ED 14.5 (D) in mouse Connexin 40 - GFP (Cx40-GFP) embryo hearts with superimposed autofluorescence in red. Ventricular trabeculae and atria are positive for Cx40 at these stages. Autofluorescent blood is present in the ventricles (C). All images were captured with confocal microscopy. Scale bar represents 100 μm in all figures.

Detailed analysis of the fluorescence preservation by various clearing methods was performed by Xu and colleagues (Xu etਊl., 2019b ) on intestinal tissues. They confirmed that most aqueous clearing methods performed better in fluorescence preservation than organic solvent-based ones. On measuring signal to background ratio after tissue clearing, they found that the best method to preserve fluorescence was FRUIT, followed by ScaleS and SeeDB. However, CUBIC and PACT preserved similar levels of fluorescence as 3DISCO and uDISCO, which are the organic hydrophobic clearing agents. They did not include CLARITY and its variations in their testing. Even though their study included heart tissue, the part about fluorescence preservation was performed on intestine, which may react differently from the dense, highly vascularized heart tissue. Therefore, further analysis of 3DISCO, uDISCO, and FRUIT on cardiac tissue is needed. An overview is summarized in Figureਁ .

Only few studies have directly analyzed compatibility of tissue clearing and fluorescence preservation in the adult or embryonic heart tissue. In our previous study (Kolesova etਊl., 2016) we used CLARITY, SCALE, CUBIC, and DBE clearing methods and compared their GFP fluorescence preservation ability in embryonic hearts (illustrated in Figures 2 C, 2D and ​ and3B 3 B with CUBIC tissue clearing on Cx40:GFP trabeculae and coronary vasculature in embryonic hearts). We found that CUBIC cleared the tissue to a deeper level compared with SCALE and therefore was more suitable for analysis of intact hearts. However, although SCALE also preserved the GFP signal, it only cleared the superficial layers of the heart, which may be sufficient for studies of the great vessels of the coronary vasculature (Kolesova etਊl., 2016). The difference between SCALE and CUBIC was more obvious in postnatal hearts, where CUBIC effectively cleared all the way through the hearts, whereas SCALE did not (Shaikh Qureshi etਊl., 2016). Another study tested the ability of CUBIC to preserve various fluorescent signals in the heart tissue (Nehrhoff etਊl., 2016). They found that CUBIC clearing can also preserve other fluorescent proteins such as TdTomato and GFP in 750-μm-thick heart sections.

Coronary vasculature visualization in the developing hearts

(A) Vasculature was injected with DiI in a quail ED9 embryo.

(B) Coronary arteries were visualized on heart surface of an ED18.5 Cx40-GFP mouse embryo cleared with CUBIC. Imaged on a confocal microscope.

(C) Analysis of the DiI injected heart with coronary vessels pseudocolored to indicate depth within the ventricular wall, ED13 quail embryo.

(D) Juvenile mouse heart with coronary vasculature injected with Microfil and main coronary arteries indicated with color: Right coronary artery (orange) and its branch, septal artery (red), and left coronary artery (yellow). Imaged on a micro-CT scanner.

CLARITY also has been shown to preserve many fluorescent proteins such as GFP, mCherry, mOrange, and Cerulean in heart tissue (Sereti etਊl., 2018). Also, modified CLARITY protocols have been used to analyze cardiac tissue. SUT (Scheme Update on tissue Transparency, combination of CUBIC and CLARITY) has been used to analyze fibrotic healing in myocardial infarction (Wang etਊl., 2018). SCM (Simplified CLARITY Method) has been used to analyze heart tissue (Sung etਊl., 2016) however, better results were obtained when the blood was washed from the heart prior to fixation as decolorizing of heme using aminoalcohol treatment reduced YFP fluorescence in heart samples (Sung etਊl., 2016).

The Next-Generation Sequencing Facility (NGSF) is a high-throughput genomics facility located at the University of Saskatchewan. It is supported by the Saskatchewan Cancer Agency and University of Saskatchewan, College of Medicine. The primary goal of the NGSF is to further basic and clinical research by providing access to high-throughput sequencing technologies and expertise.

In addition to library preparation and sequencing services, data analysis and bioinformatics services are also available, either together or each independently.

Visit the main NGSF page for more information, including a list of shared equipment (Qubit, Tapestation, qPCR, iSeq, NextSeq and more). Contact us to discuss your project objectives and obtain a service quote.


Pinheiro, A. V., Han, D., Shih, W. M. & Yan, H. Challenges and opportunities for structural DNA nanotechnology. Nat. Nanotechnol. 6, 763–772 (2011).

Wang, Z. G., Song, C. & Ding, B. Functional DNA nanostructures for photonic and biomedical applications. Small 9, 2210–2222 (2013).

Remaut, H. et al. Donor-strand exchange in chaperone-assisted pilus assembly proceeds through a concerted beta strand displacement mechanism. Mol. Cell 22, 831–842 (2006).

Baranova, E. et al. SbsB structure and lattice reconstruction unveil Ca2+ triggered S-layer assembly. Nature 487, 119–122 (2012).

King, N. P. & Lai, Y. T. Practical approaches to designing novel protein assemblies. Curr. Opin. Struct. Biol. 23, 632–638 (2013).

Howorka, S. Rationally engineering natural protein assemblies in nanobiotechnology. Curr. Opin. Biotechnol. 22, 485–491 (2011).

Main, E. R., Phillips, J. J. & Millership, C. Repeat protein engineering: creating functional nanostructures/biomaterials from modular building blocks. Biochem. Soc. Trans. 41, 1152–1158 (2013).

Lai, Y. T. et al. Structure of a designed protein cage that self-assembles into a highly porous cube. Nat. Chem. 6, 1065–1071 (2014).

Sinclair, J. C., Davies, K. M., Vénien-Bryan, C. & Noble, M. E. Generation of protein lattices by fusing proteins with matching rotational symmetry. Nat. Nanotechnol. 6, 558–562 (2011).

King, N. P. et al. Accurate design of co-assembling multi-component protein nanomaterials. Nature 510, 103–108 (2014).

King, N. P. et al. Computational design of self-assembling protein nanomaterials with atomic level accuracy. Science 336, 1171–1174 (2012).

Der, B. S. & Kuhlman, B. Strategies to control the binding mode of de novo designed protein interactions. Curr. Opin. Struct. Biol. 23, 639–646 (2013).

Lai, Y. T., Cascio, D. & Yeates, T. O. Structure of a 16-nm cage designed by using protein oligomers. Science 336, 1129 (2012).

Voet, A. R. et al. Computational design of a self-assembling symmetrical β-propeller protein. Proc. Natl Acad. Sci. USA 111, 15102–15107 (2014).

Matsunaga, R., Yanaka, S., Nagatoishi, S. & Tsumoto, K. Hyperthin nanochains composed of self-polymerizing protein shackles. Nat. Commun. 4, 2211 (2013).

Oohora, K., Onoda, A. & Hayashi, T. Supramolecular assembling systems formed by heme-heme pocket interactions in hemoproteins. Chem. Commun. 48, 11714–11726 (2012).

Carlson, J. C. et al. Chemically controlled self-assembly of protein nanorings. J. Am. Chem. Soc. 128, 7630–7638 (2006).

Brodin, J. D. et al. Metal-directed, chemically tunable assembly of one-, two- and three-dimensional crystalline protein arrays. Nat. Chem. 4, 375–382 (2012).

Lai, Y. T., King, N. P. & Yeates, T. O. Principles for desining ordered protein assemblies. Trends Cell Biol. 22, 653–661 (2012).

Modica, J. A., Skarpathiotis, S. & Mrksich, M. Modular assembly of protein building blocks to create precisely defined megamolecules. Chembiochem 13, 2331–2334 (2012).

Hou, C. et al. Construction of protein nanowires through cucurbit[8]uril-based highly specific host-guest interactions: an approach to the assembly of functional proteins. Angew. Chem. Int. Ed. 52, 5590–5593 (2013).

Fierer, J. O., Veggiani, G. & Howarth, M. SpyLigase peptide-peptide ligation polymerizes affibodies to enhance magnetic cancer cell capture. Proc. Natl Acad. Sci. USA 111, 1176–1181 (2014).

Fegan, A., White, B., Carlson, J. C. & Wagner, C. R. Chemically controlled protein assembly: techniques and applications. Chem. Rev. 110, 3315–3336 (2010).

Hoersch, D., Roh, S. H., Chiu, W. & Kortemme, T. Reprogramming an ATP-driven protein machine into a light-gated nanocage. Nat. Nanotechnol. 8, 928–932 (2013).

Pédelacq, J. D., Cabantous, S., Tran, T., Terwilliger, T. C. & Waldo, G. S. Engineering and characterization of a superfolder green fluorescent protein. Nat. Biotechnol. 24, 79–88 (2006).

Cabantous, S., Terwilliger, T. C. & Waldo, G. S. Protein tagging and detection with engineered self-assembling fragments of green fluorescent protein. Nat. Biotechnol. 23, 102–107 (2005).

Kent, K. P., Childs, W. & Boxer, S. G. Deconstructing green fluorescent protein. J. Am. Chem. Soc. 130, 9664–9665 (2008).

Sample, V., Newman, R. H. & Zhang, J. The structure and function of fluorescent proteins. Chem. Soc. Rev. 38, 2852–2864 (2009).

Ibraheem, A. & Campbell, R. E. Designs and applications of fluorescent protein-based biosensors. Curr. Opin. Chem. Biol. 14, 30–36 (2010).

Lawrence, M. S., Phillips, K. J. & Liu, D. R. Supercharging proteins can impart unusual resilience. J. Am. Chem. Soc. 129, 10110–10112 (2007).

Fasting, C. et al. Multivalency as a chemical organization and action principle. Angew. Chem. Int. Ed. 51, 10472–10498 (2012).

Mammen, M., Choi, S.-K. & Whitesides, G. M. Polyvalent interactions in biological systems: implications for design and use of multivalent ligands and inhibitors. Angew. Chem. Int. Ed. 37, 2754–2794 (1998).

Kiessling, L. L., Gestwicki, J. E. & Strong, L. E. Synthetic multivalent ligands as probes of signal transduction. Angew. Chem. Int. Ed. 45, 2348–2368 (2006).

Levine, P. M., Carberry, T. P., Holubb, J. M. & Kirshenbaum, K. Crafting precise multivalent architectures. Med. Chem. Commun. 4, 493–509 (2013).

Englund, E. A. et al. Programmable multivalent display of receptor ligands using peptide nucleic acid nanoscaffolds. Nat. Commun. 3, 614 (2012).

Jung, Y., Lee, J. M., Jung, H. & Chung, B. H. Self-directed and self-oriented immobilization of antibody by protein G-DNA conjugate. Anal. Chem. 79, 6534–6541 (2007).

Munoz, E. M., Correa, J., Riguera, R. & Fernandez-Megia, E. Real-time evaluation of binding mechanisms in multivalent interactions: a surface plasmon resonance kinetic approach. J. Am. Chem. Soc. 135, 5966–5969 (2013).

Li, M. H., Choi, S. K., Leroueil, P. R. & Baker, J. R. J. Evaluating binding avidities of populations of heterogeneous multivalent ligand-functionalized nanoparticles. ACS Nano 8, 5600–5609 (2014).

Hartman, N. C. & Groves, J. T. Signaling clusters in the cell membrane. Curr. Opin. Cell. Biol. 23, 370–376 (2011).

Conway, A. et al. Multivalent ligands control stem cell behaviour in vitro and in vivo. Nat. Nanotechnol. 8, 831–838 (2013).

Shaw, A. et al. Spatial control of membrane receptor function using ligand nanocalipers. Nat. Methods 11, 841–846 (2014).

Cho, M. H. et al. A magnetic switch for the control of cell death signalling in in vitro and in vivo systems. Nat. Mater. 11, 1038–1043 (2012).

Spangler, J. B. et al. Combination antibody treatment down-regulates epidermal growth factor receptor by inhibiting endosomal recycling. Proc. Natl Acad. Sci. USA 107, 13252–13257 (2010).

Friedman, L. M. et al. Synergistic down-regulation of receptor tyrosine kinases by combinations of mAbs: implications for cancer immunotherapy. Proc. Natl Acad. Sci. USA 102, 1915–1920 (2005).

Oliveira, S. et al. Downregulation of EGFR by a novel multivalent nanobody-liposome platform. J. Control Release 145, 165–175 (2010).

Bharde, A. A. et al. Magnetic nanoparticles as mediators of ligand-free activation of EGFR signaling. PLoS One 8, e68879 (2013).

Li, P. et al. Phase transitions in the assembly of multivalent signalling proteins. Nature 483, 336–340 (2012).

Dustin, M. L. & Groves, J. T. Receptor signaling clusters in the immune synapse. Annu. Rev. Biophys. 41, 543–556 (2012).


In this paper we describe the creation of a binding scaffold based on GFP. By using binding elements derived from antibody HCDR3s and inserting them into up to four defined positions of a form of GFP evolved for stability and folding robustness, we have combined the advantages of antibodies (specific, high affinity binding) with those of GFP (intrinsic fluorescence, stability and high expression levels). However, unlike GFP–antibody fragment fusion proteins 22 , the fluorescence is intrinsic to the binding ligand. Transition from the denatured to the folded state was accompanied by reacquisition of both binding activity and fluorescence, allowing us to determine concentrations of functional fluorobodies as well as to determine affinities (Figs. 5c,d). Although this is likely to be the usual state, it is known that the folding of GFP to the β-can structure is relatively rapid (t/2 = 10 min), as is the subsequent formation of the reduced chromophore. However, the creation of the oxidized fluorescent chromophore is far slower (t/2 = 76 min) 23 , suggesting that if the correct conformation of the binding loops is generated at the same time as the folding of the β-can, it may be possible to artificially create an intermediate short-lived fluorobody state in which binding activity exists without fluorescence, although this is unlikely to exist under normal circumstances. Whether it may be possible to eliminate binding activity in the presence of continued fluorescence by, for example, proteolytic cleavage of the binding loops, has not been determined.

From a small (10 7 ) library of fluorobodies, we selected specific binders against a number of different antigens with nanomolar affinities. These fluorobodies were functional in different experimental formats in which antibodies are traditionally used, with the advantage that only a single incubation is required, and that the read out of binding is immediate rather than dependent upon secondary reagents. It is very encouraging that the fluorobody affinities obtained were similar to those from antibody libraries of a similar size 4,24 . This is in contrast to many other scaffolds which, unless they are based on the immunoglobulin fold 25,26,27 , tend to have affinities no greater than micromolar. Although not formally demonstrated, we attribute these high affinities to the fluorobody design features: antibody CDRs used as binding elements at one end of a stable scaffold with a similar footprint (see Fig. 1) to the antibody Fv domain.

One striking difference between fluorobodies and antibodies, however, is the diversity of the binders obtained. Of the 25 anti-ubiquitin fluorobodies sequenced, all were different, a diversity not encountered in much larger antibody libraries 5,28,29 , unless many more clones are analyzed early in the selection process. This restriction in diversity in antibody selection is probably due to the negative selective influences of toxicity and growth effects. It is likely that fluorobodies, lacking the toxicity of antibody fragments, and having far better expression levels, do not suffer from these problems, allowing the survival of a wider range of clones, even after a number of rounds of selection.

Previous attempts to use GFP as a binding scaffold have generally met with poor results 9,10 , with strongly reduced, or absent, fluorescence after the insertion of either linkers or random peptides at specific or random sites. The success of our strategy is likely to due to the use of precisely defined binding loops, rather than random amino acids, and the use of a highly stable GFP as scaffold (superfolder GFP, S. Cabantous, H. Cai, T. Terwilliger and G.S.W., unpublished, contains six additonal mutations which increase stability and folding see Supplementary Methods online for more detail). In addition to the experiments reported here, we also created a library using degenerate oligonucleotides (NNK) encoding six amino acids at each position in the same GFP scaffold (data not shown). The percentage of green colonies was lower in this library (20%), more rounds of selection were required to obtain positive binders and the diversity of selected clones was found to be far less. This is perhaps not surprising, given that a high percentage of stop codons (79%) would be expected in 24 degenerate codons.

We have shown that fluorobodies have fluorescence excitation/emission properties very similar to the GFP scaffold used, except that some of the fluorobodies appeared to be only 50% as bright. Changes in relative fluorescence with GFP mutations are common (see ref. 30 for a review), and from this point of view, fluorobodies are GFP mutations. Although the fluorobodies described here emit green fluorescence, there is no reason fluorobodies of other colors cannot also be created, either by introducing known mutations into selected green fluorobodies (e.g., Y66H to create blue fluorescent protein), or by creating similar fluorobody libraries based on alternative scaffold colors.

We have used phage display to select functional fluorobodies however, as they are very well expressed in both cytoplasm and periplasm, any display format (bacterial, yeast, ribosome or puromycin-based display) is likely to be suitable, including genetic strategies, such as yeast or bacterial 31 two-hybrid systems. The ease with which fluorobodies can be selected, expressed, purified and used will facilitate their application in biology experiments in high-throughput systems. In particular, fluorobodies should prove especially useful in a number of array formats, including antibody, tissue or reverse format arrays, avoiding the need for labeling and additional steps.

Fluorobodies are functional in all primary assays in which antibodies are traditionally used. For immunofluorescence and flow cytometry, results are indistinguishable from those obtained using traditional reagents, and they will likely be effective reagents for immunoprecipitation and mass spectrometry, as previously shown for scFvs 32 . However, their use in intracellular immunization to create conditional knockouts, for which antibodies have been traditionally used, is likely to be especially effective. In addition to avoiding the need to create specialized libraries of antibodies which are stable and functional in the intracellular milieu 33 , fluorobodies will also provide information on target localization by virtue of their intrinsic fluorescence, as well as providing instant confirmation of appropriate fluorobody expression. In this sense they are likely to provide complementary data to RNAi 34 , which is unable to give any information on localization, and has recently been shown to affect off-target genes 35,36,37 . Similar advantages are likely to pertain to their use in microinjection studies.

In summary, fluorobodies promise to be extremely effective binding ligands, for both standard and high-throughput systems-wide research. Their intrinsic fluorescence renders them immediately applicable in many fluorescent-based assays currently used in target validation and drug development and they have clear potential in diagnostics, biosensors and in vivo imaging.


We have an extensive set of microscopy instruments including widefield microscopes, incubator microscopes, a digital slide scanner, a high-content reader, a confocal microscope, a super-resolution microscope and light sheet technologies.

Our team can provide you with consultation, training, development or assisted sessions.

Image by Cellular Imaging core staff

We operate two scanners and dedicated software for the imaging and quantitative analysis of gels, blots and plates, including applications such as Northern, Southern and Western blots, In-Cell Westerns and more.

Our team provides training for all first-time users. Upon request, our team can scan and analyze your blots.

Image by Cellular Imaging core staff

Karyotyping is the analysis of chromosomes in a cell. A karyotype determines the number and appearance of chromosomes and detects chromosomal abnormalities such as missing or extra chromosomes (aneuploidies), as well as a variety of chromosomal aberrations (such as deletions and translocations). We offer a limited karyotyping service for research only — for example, to test cell lines. We karyotype human and mouse cells and may consider other species.

Image by Cellular Imaging core staff

BiFCbimolecular fluorescence complementation
BiLCbimolecular luminescence complementation
BRETbioluminescence resonance energy transfer
CBBCoomassie brilliant blue
CFPcyan FP
coBiFCco-localization of BiFC complexes
ECLenhanced chemo luminescence
FPfluorescent protein
FP C FP C-terminal fragment
FP N FP N-terminal fragment
FRETfluorescence resonance energy transfer
GFPgreen FP
iBiSCisolation of BiFC stabilized complexes
mcBiFCmulticolor BiFC
OD600optical density at 600 nm
PCAprotein fragment complementation assay
PPIprotein-protein interaction
PVDFpolyvinylidene fluoride
RLucRenilla reniformis luciferase
SUSsplit-ubiquitin system
TEVtobacco etch virus protease
UbFCubiquitin-mediated fluorescence complementation
YFPyellow FP

1 Before generating BiFC-fusion constructs, use web resources to analyze topology, sub-cellular localization and targeting signals of proteins of interest (e.g. [100] [101] and links therein). Fusion of BiFC-tags to the wrong terminal end could mask targeting signals and affect protein localization. On the other hand, expression levels of some proteins are drastically reduced when a certain tag orientation is used. It is recommended to generate full-length FP fusion constructs in a vector backbone similar to the BiFC-vectors used and to analyze proper localization and expression of fusion proteins before generating the BiFC constructs. If expression and proper localization could be confirmed by microscopic analyses the use of a similar BiFC-tag orientation is recommended. If no information about the protein localization is available, generate FP fusion constructs with respective N- and C-terminal FP-tag orientations (e.g. CFP-query and query-YFP) and perform co-localization analyses. If both tag-orientations are possible, use C-terminal BiFC-tag fusions (query-BiFC) as N-terminal BiFC-tag fusions may result in higher background signals (Waadt and Kudla, unpublished results).

Proper controls are the key for adequate semiquantitative BiFC analyses as BiFC is irreversible and may stabilize randomly formed protein complexes (9, 39). The best negative control is the use of a different family member of one of the investigated proteins. Point mutations that disrupt interaction or deletion constructs of the interacting domain may also be suitable. It is important that the negative control is localized in the same cellular compartment and exhibits a similar expression level compared to the reference protein. The use of empty-vector controls is not recommended as the expression of FP-fragments alone does not fulfill the requirements mentioned above.

2 In order to suppress plant immune responses one might also consider co-expression of the Pseudomonas syringae type III effector AvrPto (102).

3 Additional to the infiltration of wild type plants, BiFC experiments could also be conducted in mutant plants, in GVG-AvrPto plants (102) that enable dexametasone inducible immune response suppression or in the rdr6-11 mutant (103) that is deficient in post translational gene silencing.

4 N. benthamiana plants can be either grown in the greenhouse or in a growth room with long day conditions, 90 – 120 㯎 m 𢄢 s 𢄡 light intensity and 22 – 27 ଌ.

Optimal growth conditions for Arabidopsis plants are short day conditions (8 h light/16 h dark) with 90 㯎 m 𢄢 s 𢄡 light intensity at 23 ଌ (94, 95). However, transient expression is also achieved in long day conditions (16 h light/8 h dark) with 50 – 80 㯎 m 𢄢 s 𢄡 light intensity at 27 ଌ. Most important for achieving high protein expression levels, is the use of young leaves of plants in the pre-bolting stage. Two to three days prior to infiltration Arabidopsis plants should be stopped watering and the evening prior infiltration plants should be kept under constant darkness until the infiltration procedure. This minimizes the syringe pressure needed for the infiltration procedure. High syringe pressure during infiltration could damage the leaves. After infiltration Arabidopsis plants need to be rewatered and kept under high humidity by water spraying and covering with a plastic cover for at least 24 h.

A-YFP N / B-YFP C / CFP or RFP (sample)

C-YFP N / B-YFP C / CFP or RFP (negative control)

A-YFP N / D-YFP C / CFP or RFP (negative control)

Amutation-YFPN / B-YFP C / CFP or RFP (negative control)

A-YFP N / Bmutation-YFPC / CFP or RFP (negative control)

Adeletion-YFPN / B-YFP C / CFP or RFP (negative control)

A-YFP N / Bdeletion-YFPC / CFP or RFP (negative control)

Here, C and D belong to the respective protein family of A and B and mutation or deletion indicates possible modifications in the respective interaction domains. The BiFC-tag orientation should be determined according to Note 1 . For infiltration of N. benthamiana, co-infiltration of the p19 silencing suppressor strain is recommended (97).

6 For infiltration of N. benthamiana leaves the OD600 of Agrobacteria could be adjusted between 0.05 and 2, where higher OD600 typically leads to higher expression levels.

For infiltration of Arabidopsis leaves the OD600 of Agrobacteria could be adjusted between 0.4 and 0.9 to obtain an appropriate expression level but should not exceed a total OD600 of 1.2 as this induces strong necrosis formations. OD600 of 0.3 and lower on the other hand drastically reduces transient expression efficiencies (95).

7 The choice of leaves for infiltration is critical for performing adequate semiquantitative BiFC analyses in N. benthamiana. N. benthamiana leaves of different age vary in their transient expression efficiencies. To compare BiFC efficiencies of different construct combinations, it is recommended infiltrating each construct combination into leaves of different plants but of the same age, size and physiological status. The use of different leaves of the same plant is not recommended. Alternatively, two different BiFC combinations could be infiltrated into one leaf on both sides of the leaf mid-vein. More than two different infiltrations per leaf are not recommended as for semiquantitative BiFC analyses samples from the same leaf area are needed (see Note 8 ).

8 Semiquantitative BiFC analyses are critical for the evaluation of positive BiFC results. The best system to perform BiFC quantification analyses is N. benthamiana epidermal cells, as these cells are easy to image and exhibit, depending on the proteins to be expressed, a remarkable high expression efficiency when BiFC samples are co-expressed with the silencing suppressor p19. It is recommended to infiltrate samples to be compared into leaves of similar physiological status. Samples for microscopic or western-blot analyses also need to be harvested form similar leaf areas. Expression levels in infiltrated N. benthamiana leaves vary dependent on the time point after infiltration. Usually strongly expressed protein constructs are already detectable at day two after infiltration and expression increases until day five after infiltration. However, it is strongly recommended to perform semiquantitative BiFC analyses only on days 3 – 4 after infiltration because of a maximal signal/noise-ratio during that time phase.

As an example for BiFC analyses in N. benthamiana the well known interaction of the calcineurin B-like (CBL) calcium sensor CBL10 and the CBL interacting protein kinase CIPK24 was investigated ( Figure 2 , 49, 104). As negative control the CIPK24NAFΔ construct was used, in which the NAF-domain, that is necessary and sufficient for CBL calcium sensor interaction (105), is deleted. Imaging was conducted using an inverted spinning disc confocal microscope. Higher resolution overview images and maximum projections of a z-stack including 32 focal planes were taken with a 60× objective ( Figure 2a ) and indicate CIPK24/CBL10 complex formations (yellow) at the vacuolar membrane that is clearly distinguishable from SCFP3A (cyan) localization in the cytoplasm and nucleus. For semiquantitative analyses images were taken with a 20× objective and quantified 3 days after infiltration ( Figure 2b ). After p19 background subtraction BiFC intensities were normalized to CIPK24/CBL10 interaction. Here, the use of the NAF domain deletion construct (CIPK24NAFΔ) resulted in reduced BiFC intensities of 41 % (BiFC constructs only) and 44 % (co-expressed with SCFP3A). Normalization of the BiFC/SCFP3A (Y/C)-ratios resulted in a reduced BiFC efficiency for CIPK24NAFΔ/CBL10 of 57 %. These data indicate that compared to CIPK24 wild type protein CIPK24NAFΔ interacts less efficient with CBL10 (49, 106). For western analyses, proteins were extracted using 1× SDS sample buffer, separated in 10 % Acrylamide/Bisacrylamide SDS gels and blotted onto PVDF membranes. Immuno detection of the different BiFC and SCFP3A construct combinations resulted in comparable expression levels of the respective fusion proteins ( Figure 2c ). Samples infiltrated only with the p19 strain were used as background controls and did not exhibit a respective signal in the western blots. PageBlue staining of the large RuBisCO subunit was used as loading control.

Taken together, co-expression of a reference FP, here SCFP3A (107), is not necessarily needed for BiFC quantification in N. benthamiana but it could minimize differences in BiFC signals due to differences in expression efficiencies between different leaves or leaf areas. Semiquantitative BiFC analyses in N. benthamiana as presented in Figure 2 are only applicable for PPIs that are localized in the plasma membrane, the cytoplasm, the cytoplasm including the nucleus, the endoplasmatic reticulum and the tonoplast. Such BiFC quantifications are not applicable for smaller compartments or organelles like the nucleus, peroxisomes, chloroplasts, mitochondria and the endosomal compartments as subtraction of the background signals from entire images most likely would lead to undetectable signals. Here, signal intensities of individual organelles from different samples need to be compared.

As transient expression in Arabidopsis is less robust than expression in N. benthamiana, co-expression of a reference FP is recommended for semiquantitative BiFC analyses. In addition, prior to BiFC analyses, it is recommended to infiltrate single FP-fusions of proteins, which should be investigated, to verify proper expression. Infiltration of YN-CIPK24/CBL10-YC into Arabidopsis did not result in detectable BiFC signals, possibly due to silencing or inefficient expression of YN-CIPK24 (data not shown). Type 2C protein phosphatases interact with SnRK2 protein kinases (108�). Interaction of the SnRK2 kinase OST1 (112) and the PP2C phosphatase ABI1 (108, 110) was exemplarily investigated in infiltrated N. benthamiana and Arabidopsis leaves. YFP N173 was fused to the N-terminus of OST1 (YN-OST1) and YFP C155 was fused to the N-terminus of ABI1 (YC-ABI1), infiltrated into N. benthamiana and Arabidopsis leaves and analyzed four and seven days after infiltration, respectively ( Figure 2d ). BiFC analyses in both plant species indicate OST1/ABI1 complex formations with similar cytoplasmic and nuclear localization patterns.

9 A representative cell ideally harbors the nucleus in the center of the cell when looking on the z-axis. The nucleus is the best orientation point in a cell because it allows to distinguish between certain localization patterns. Plasma membrane localization of fluorescent proteins or protein complexes is characterized by a fluorescence signal only at the cell border. Here, plasmolysis may allow the appearance of Hechtian strands. Endoplasmatic reticulum localization displays a ring like structure around the nucleus and a net/mesh-like architecture. The vacuolar membrane is characterized by forming a pocket around the nucleus and most likely pushing the nucleus at the cell border. Here also membraneous invaginations and cytoplasmic strands are visible, forming a tunnel system through the large central vacuole (CIPK24/CBL10 complexes in Figure 2a ). In some cases also ring like structures are visible. Cytoplasmic localization is visible by fluorescence of cytoplasmic strands. In addition to that the cytoplasm is forced in close proximity to the cell borders and the nucleus as the central vacuole occupies more than 90 % of the cell volume. Cytoplasmic proteins or protein complexes are often dually localized and also found in the nucleus (SCFP3A in Figure 2a , OST1/ABI1 complexes in Figure 2d ), except of those that have a nuclear export signal or are too large to pass the nuclear pores passively. To distinguish between plasma membrane, vacuolar membrane, cytoplasm and endoplasmatic reticulum it is recommended to search for cytoplasmic strands, fluorescence around the nucleus and to carefully analyze the architecture of the fluorescence signal at the cell border in a top or bottom cell view or in a maximum projection (see Figure 2a ). The nucleus is the largest organelle in the cell and fluorescence is often excluded from the nucleolus. The second largest organelles are chloroplasts. However compared to mesophyll cells, in epidermal cells chloroplasts are smaller and in lower quantity. Chloroplasts exhibit an elliptical structure and are often localized at the cell borders or around the nucleus. Chloroplasts can be easily visualized by chlorophyll auto-fluorescence. However, chlorophyll auto-fluorescence may also appear if too high excitation energy or exposure times are used, especially when FP or BiFC signals are weak. It is more difficult to identify other small cellular organelles like peroxisomes, the golgi apparatus or other endosomes. Here co-localization studies using fluorescent markers are recommended.

For representative images it is recommended displaying one overview image with the focal plane through the nucleus and the cell center. In addition a maximum projection of a z-stack is the first choice to visualize an entire cell, as here multiple focal planes through the cell are merged in one image (see Figure 2 ).

Watch the video: ΦΕΚ Πρωτοκύριακο - Ο Πολιούχος της Κέρκυρας (January 2022).