Frankenbody and Other Novel scFvs
Constructs and Methods for Live-cell Imaging
Figure 1 : Representative images depicting an scFv that binds the HA epitope (scFv-GFP, green) labeling 1×HA or 10×HA spaghetti monster (smHA) tagged mitochondrial protein mitoNEET (Mito, magenta) in living U2OS cells.
Scale bars, 10 μm.
At A Glance
Researchers at Colorado State University have developed technology to quickly generate genetically encodable intracellular single-chain variable fragments (scFvs) that selectively bind various epitopes with high affinity in living cells that can be used to quantify tagged protein translation, localization, and dynamics. A number of scFvs generated in this way are available, including an scFv that binds the HA epitope as well as one that binds the FLAG epitope.
The genetic encodability of these engineered scFvs are of great value to researchers. With our new scFv, researchers can simply transfect cells expressing a specifically tagged protein with a plasmid encoding the scFv fused to a fluorescent protein. This enables the visualization and quantification of the tagged protein translation, localization, and dynamics in a fully natural context – which is not possible with traditional techniques!
Check out the Stasevich Lab’s publication in Nature below!
For more detailed information about our various scFvs – please contact our office.
Live-cell imaging is critical for tracking the dynamics of cell signaling. The discovery and development of the green fluorescent protein (GFP), for example, has revolutionized the field of cell biology. GFP can be genetically fused to a protein of interest (POI) to track its expression and localization in vivo. While powerful, GFP-tagging has limitations to image the full lifecycles of proteins, such as: (1) long fluorophore maturation times prevent translational imaging; (2), GFP tags cannot discriminate post-translational modifications (PTM) of proteins, nor can they discriminate protein conformational changes; and (3) GFP tags are large, permanently attached, and dim.
To address the limitations of GFP, an alternative live-cell imaging methodology has emerged that uses antibody-based probes. In this methodology, probes built from antibodies, such as antigen binding fragments (Fabs), single-chain variable fragments (scFvs), and camelid nanobodies, are conjugated or genetically fused with mature fluorophores. When expressed or loaded into cells, the probes bind and light up epitopes within POIs as soon as the epitopes are accessible. With this methodology, it is possible to visualize and quantify the co-translational dynamics of nascent peptide chains, capture the dynamics of short-lived transcription factors, track single molecules for extended periods of time, and selectively track the spatiotemporal dynamics of PTMs and protein conformational changes.
While there is potential for antibody-based probes in live-cell imaging, so far only a handful have been developed. One option is Fab, which can be digested from commercially available antibodies and physically loaded into cells. However, Fabs have not been widely adopted as they are: (1) difficult to load into living systems; (2) expensive; and (3) change considerably from batch to batch, leading to unwanted variability between experiments.
Genetically encoded probes, however, are an attractive alternative. Since these probes can be integrated into plasmids. But these probes are not straightforward to develop – even after antibody sequences are determined, there is a good chance that antibody-based probes derived from the sequences will not fold and function properly in vivo. The problem is antibodies have evolved to be secreted from cells, so their folding and maturation is often disrupted when expressed within the reduced intracellular environment. Thus, protein engineering, directed evolution, and mutagenesis are typically needed to generate an ideal antibody-based probe that functions in vivo.
- Enables visualization and quantification of tagged protein translation, localization and dynamics in fully natural context
state-of-the-art live-cell imaging of protein dynamics
HA-tagged protein expression and kinetics
genome modulation, editing, and engineering
Zhao, N., Kamijo, K., Fox, P.D. et al. A genetically encoded probe for imaging nascent and mature HA-tagged proteins in vivo. Nat Commun 10, 2947 (2019). https://doi.org/10.1038/s41467-019-10846-1
Cecchetelli, Alyssa. “HA Frankenbody, a New Imaging Tool to Visualize Single Molecules and Nascent Peptides.” Addgene Blog Share Science, 10 Oct. 2019, https://blog.addgene.org/ha-frankenbody-a-new-imaging-tool-to-visualize-single-molecules-and-nascent-peptides.
Colorado State University. “It’s not an antibody, it’s a frankenbody: A new tool for live-cell imaging: Antibody-based probe works in living systems and targets the classic HA tag.” ScienceDaily. ScienceDaily, 3 July 2019. www.sciencedaily.com/releases/2019/07/190703121440.htm
Manning, Anne. “It’s Not an Antibody, It’s a Frankenbody: A New Tool for Live-Cell Imaging.” College of Natural Sciences, 3 July 2019, https://natsci.source.colostate.edu/its-not-an-antibody-its-a-frankenbody-a-new-tool-for-live-cell-imaging/.
Last updated: August 2021
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#CSUInvents – #TechTuesday! Live-cell #imaging is critical for tracking the dynamics of cell signaling. Researchers at Colorado State University in the Stasevich Research Lab have developed technology to quickly generate genetically encodable intracellular single-chain variable fragments (scFvs) that selectively bind various #epitopes with high affinity in living #cells that can be used to quantify tagged #protein #translation, #localization, and #dynamics. With our new scFv, researches can simply transfect cells expressing a specifically tagged protein with a #plasmid encoding the scFv fused to a #fluorescent protein. This enables the #visualization and quantification of the tagged protein translation, localization, and dynamics in a fully natural context – which is not possible with traditional techniques! Inventors include Professor Tim Stasevich ,Ning Zhao from CSU, and Hiroshi Kimura, and Yuko Sato from the Tokyo Institute of Technology.