Designed Proteins as Novel Imaging Reagents in Living Escherichia coli

Uncovering diffusive states of the yeast membrane protein, Pma1, and how labeling method can change diffusive behavior

We present and analyze video-microscopy-based single-particle-tracking measurements of the budding yeast (Saccharomyces cerevisiae) membrane protein, Pma1, fluorescently labeled either by direct fusion to the switchable fluorescent protein, mEos3.2, or by a novel, light-touch, labeling scheme, in which a 5 amino acid tag is directly fused to the C-terminus of Pma1, which then binds mEos3.2. The track diffusivity distributions of these two populations of single-particle tracks differ significantly, demonstrating that labeling method can be an important determinant of diffusive behavior. We also applied perturbation expectation maximization (pEMv2) (Koo and Mochrie in Phys Rev E 94(5):052412, 2016), which sorts trajectories into the statistically optimum number of diffusive states. For both TRAP-labeled Pma1 and Pma1-mEos3.2, pEMv2 sorts the tracks into two diffusive states: an essentially immobile state and a more mobile state. However, the mobile fraction of Pma1-mEos3.2 tracks is much smaller ([Formula: see text]) than the mobile fraction of TRAP-labeled Pma1 tracks ([Formula: see text]). In addition, the diffusivity of Pma1-mEos3.2's mobile state is several times smaller than the diffusivity of TRAP-labeled Pma1's mobile state. Thus, the two different labeling methods give rise to very different overall diffusive behaviors. To critically assess pEMv2's performance, we compare the diffusivity and covariance distributions of the experimental pEMv2-sorted populations to corresponding theoretical distributions, assuming that Pma1 displacements realize a Gaussian random process. The experiment-theory comparisons for both the TRAP-labeled Pma1 and Pma1-mEos3.2 reveal good agreement, bolstering the pEMv2 approach.

Transient Fluorescence Labeling: Low Affinity-High Benefits

Fluorescent labeling is an established method for visualizing cellular structures and dynamics. The fundamental diffraction limit in image resolution was recently bypassed with the development of super-resolution microscopy. Notably, both localization microscopy and stimulated emission depletion (STED) microscopy impose tight restrictions on the physico-chemical properties of labels. One of them-the requirement for high photostability-can be satisfied by transiently interacting labels: a constant supply of transient labels from a medium replenishes the loss in the signal caused by photobleaching. Moreover, exchangeable tags are less likely to hinder the intrinsic dynamics and cellular functions of labeled molecules. Low-affinity labels may be used both for fixed and living cells in a range of nanoscopy modalities. Nevertheless, the design of optimal labeling and imaging protocols with these novel tags remains tricky. In this review, we highlight the pros and cons of a wide variety of transiently interacting labels. We further discuss the state of the art and future perspectives of low-affinity labeling methods.

PAINT using proteins: A new brush for super-resolution artists

PAINT (points accumulation for imaging in nanoscale topography) refers to methods that achieve the sparse temporal labeling required for super-resolution imaging by using transient interactions between a biomolecule of interest and a fluorophore. There have been a variety of different implementations of this method since it was first described in 2006. Recent papers illustrate how transient peptide-protein interactions, rather than small molecule binding or DNA oligonucleotide duplex formation, can be employed to perform PAINT-based single molecule localization microscopy (SMLM). We discuss the different approaches to PAINT using peptide and protein interactions, and their applications in vitro and in vivo. We highlight the important parameters to consider when selecting suitable peptide-protein interaction pairs for such studies. We also note the opportunities for protein scientists to apply their expertise in guiding the choice of peptide and protein pairs that are used. Finally, we discuss the potential for expanding super-resolution imaging methods based on transient peptide-protein interactions, including the development of simultaneous multicolor imaging of multiple proteins and the study of very high and very low abundance proteins in live cells.

Engineering repeat proteins of the immune system

Limitations associated with immunoglobulins have motivated the search for novel binding scaffolds. Repeat proteins have emerged as one promising class of scaffolds, but often are limited to binding protein and peptide targets. An exception is the repeat proteins of the immune system, which have in recent years served as an inspiration for binding scaffolds which can bind glycans and other classes of biomolecule. Like other repeat proteins, these proteins can be very stable and have a monomeric mode of binding, with elongated and highly variable binding surfaces. The ability to target glycans and glycoproteins fill an important gap in current tools for research and biomedical applications.

A new method for post-translationally labeling proteins in live cells for fluorescence imaging and tracking

We present a novel method to fluorescently label proteins, post-translationally, within live Saccharomycescerevisiae. The premise underlying this work is that fluorescent protein (FP) tags are less disruptive to normal processing and function when they are attached post-translationally, because target proteins are allowed to fold properly and reach their final subcellular location before being labeled. We accomplish this post-translational labeling by expressing the target protein fused to a short peptide tag (SpyTag), which is then covalently labeled in situ by controlled expression of an open isopeptide domain (SpyoIPD, a more stable derivative of the SpyCatcher protein) fused to an FP. The formation of a covalent bond between SpyTag and SpyoIPD attaches the FP to the target protein. We demonstrate the general applicability of this strategy by labeling several yeast proteins. Importantly, we show that labeling the membrane protein Pma1 in this manner avoids the mislocalization and growth impairment that occur when Pma1 is genetically fused to an FP. We also demonstrate that this strategy enables a novel approach to spatiotemporal tracking in single cells and we develop a Bayesian analysis to determine the protein's turnover time from such data.