Peter B. Berget

Fluorogen-activating single-chain antibodies for imaging cell surface proteins

Imaging of live cells has been revolutionized by genetically encoded fluorescent probes, most famously green and other fluorescent proteins, but also peptide tags that bind exogenous fluorophores. We report here the development of protein reporters that generate fluorescence from otherwise dark molecules (fluorogens). Eight unique fluorogen activating proteins (FAPs) have been isolated by screening a library of human single-chain antibodies (scFvs) using derivatives of thiazole orange and malachite green. When displayed on yeast or mammalian cell surfaces, these FAPs bind fluorogens with nanomolar affinity, increasing green or red fluorescence thousands-fold to brightness levels typical of fluorescent proteins. Spectral variation can be generated by combining different FAPs and fluorogen derivatives. Visualization of FAPs on the cell surface or within the secretory apparatus of mammalian cells can be achieved by choosing membrane permeant or impermeant fluorogens. The FAP technique is extensible to a wide variety of nonfluorescent dyes.

A rainbow of fluoromodules: a promiscuous scFv protein binds to and activates a diverse set of fluorogenic cyanine dyes.

Combined magnetic and fluorescence cell sorting were used to select Fluorogen Activating Proteins (FAPs) from a yeast surface-displayed library for binding to the fluorogenic cyanine dye Dimethyl Indole Red (DIR). Several FAPs were selected that bind to the dye with low nanomolar Kd values and enhance fluorescence more than 100-fold. One of these FAPs also exhibits considerable promiscuity, binding with high affinity to several other fluorogenic cyanine dyes with emission wavelengths covering most of the visible and near-IR regions of the spectrum. This significantly expands the number and wavelength range of scFv-based fluoromodules.

Enhanced Photostability of Genetically Encodable Fluoromodules Based on Fluorogenic Cyanine Dyes and a Promiscuous Protein Partner

Fluoromodules are discrete complexes of biomolecules and fluorogenic dyes. Binding of the dyes to their cognate biomolecule partners results in enhanced dye fluorescence. We exploited a previously reported promiscuous binding interaction between a single-chain, variable fragment antibody protein and a family of cyanine dyes to create new protein-dye fluoromodules that exhibit enhanced photostability while retaining high affinity protein-dye binding. Modifications to the dye structure included electron-withdrawing groups that provide resistance to photo-oxidative damage. Low nanomolar equilibrium dissociation constants were found for the new dyes. Fluorescence microscopy illustrates how yeast can be surface-labeled with three different colors based on a single protein and appropriately chosen dyes.

Determining the subcellular location of new proteins from microscope images using local features

MOTIVATION Evaluation of previous systems for automated determination of subcellular location from microscope images has been done using datasets in which each location class consisted of multiple images of the same representative protein. Here, we frame a more challenging and useful problem where previously unseen proteins are to be classified. RESULTS Using CD-tagging, we generated two new image datasets for evaluation of this problem, which contain several different proteins for each location class. Evaluation of previous methods on these new datasets showed that it is much harder to train a classifier that generalizes across different proteins than one that simply recognizes a protein it was trained on. We therefore developed and evaluated additional approaches, incorporating novel modifications of local features techniques. These extended the notion of local features to exploit both the protein image and any reference markers that were imaged in parallel. With these, we obtained a large accuracy improvement in our new datasets over existing methods. Additionally, these features help achieve classification improvements for other previously studied datasets. AVAILABILITY The datasets are available for download at http://murphylab.web.cmu.edu/data/. The software was written in Python and C++ and is available under an open-source license at http://murphylab.web.cmu.edu/software/. The code is split into a library, which can be easily reused for other data and a small driver script for reproducing all results presented here. A step-by-step tutorial on applying the methods to new datasets is also available at that address. CONTACT murphy@cmu.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Large-Scale Automated Analysis of Location Patterns in Randomly Tagged 3T3 Cells

Location proteomics is concerned with the systematic analysis of the subcellular location of proteins. In order to perform high-resolution, high-throughput analysis of all protein location patterns, automated methods are needed. Here we describe the use of such methods on a large collection of images obtained by automated microscopy to perform high-throughput analysis of endogenous proteins randomly-tagged with a fluorescent protein in NIH 3T3 cells. Cluster analysis was performed to identify the statistically significant location patterns in these images. This allowed us to assign a location pattern to each tagged protein without specifying what patterns are possible. To choose the best feature set for this clustering, we have used a novel method that determines which features do not artificially discriminate between control wells on different plates and uses Stepwise Discriminant Analysis (SDA) to determine which features do discriminate as much as possible among the randomly-tagged wells. Combining this feature set with consensus clustering methods resulted in 35 clusters among the first 188 clones we obtained. This approach represents a powerful automated solution to the problem of identifying subcellular locations on a proteome-wide basis for many different cell types.

scFv-based fluorogen activating proteins and variable domain inhibitors as fluorescent biosensor platforms

Single chain antibodies (scFvs) are engineered proteins composed of IgG variable heavy (VH) and variable light (VL) domains tethered together by a flexible peptide linker. We have characterized the individual VH or VL domain activities of several scFvs isolated from a yeast surface‐display library for their ability to bind environmentally sensitive fluorogenic dyes causing them to fluoresce. For many of the scFvs, both VH and VL domains are required for dye binding and fluorescence. The analysis of other scFvs, however, revealed that either the VH or the VL domain alone is sufficient to cause the fluorogenic dye activation. Furthermore, the inactive complementary domains in the original scFvs either contribute nothing to, or actually inhibit the activity of these active single domains. We have explored the interactions between active variable domains and inactive complementary domains by extensive variable domain swapping through in vitro gene manipulations to create hybrid scFvs. In this study, we demonstrate that significant alteration of the fluorogenic dye activation by the active VH or VL domains can occur by partnering with different VH or VL complementary domains in the scFv format. Hybrid scFvs can be generated that have fluorogen‐activating domains that are completely inhibited by interactions with other domains. Such hybrid scFvs are excellent platforms for the development of several types of genetically encoded, fluorescence‐generating biosensors.

Directed Evolution of a Fluorogen-Activating Single Chain Antibody for Function and Enhanced Brightness in the Cytoplasm

Directed evolution is an exceptionally powerful tool that uses random mutant library generation and screening techniques to engineer or optimize functions of proteins. One class of proteins for which this process is particularly effective is antibodies, where properties such as antigen specificity and affinity can be selected to yield molecules with improved efficacy as molecular labels or in potential therapeutics. Typical antibody structure includes disulfide bonds that are required for stability and proper folding of the domains. However, these bonds are unable to form in the reducing environment of the cytoplasm, stymieing the effectiveness of optimized antibodies in many research applications. We have removed disulfide-forming cysteine residues in a single chain antibody fluorogen-activating protein (FAP), HL4, and employed directed evolution to select a derivative that is capable of activity in the cytoplasm. A subsequent round of directed evolution was targeted at increasing the overall brightness of the fluoromodule (FAP–fluorogen complex). Ultimately, this approach produced a novel FAP that exhibits strong activation of its cognate fluorogen in the reducing environment of the cytoplasm, significantly expanding the range of applications for which fluoromodule technology can be utilized.

The spectrum of Trp- mutants isolated as 5-fluoroanthranilate-resistant clones in Saccharomyces bayanus, S. mikatae and S. paradoxus.

5‐Fluoroanthranilic acid (FAA)‐resistant mutants were selected in homothallic diploids of three Saccharomyces species, taking care to isolate mutants of independent origin. Mutations were assigned to complementation groups by interspecific complementation with S. cerevisiae tester strains. In all three species, trp3, trp4 and trp5 mutants were recovered. trp1 mutants were also recovered if the selection was imposed on a haploid strain. Thus, FAA selection may be more generally applicable than was previously described. Copyright

Cell cycle dependence of protein subcellular location inferred from static, asynchronous images

Protein subcellular location is one of the most important determinants of protein function during cellular processes. Changes in protein behavior during the cell cycle are expected to be involved in cellular reprogramming during disease and development, and there is therefore a critical need to understand cell-cycle dependent variation in protein localization which may be related to aberrant pathway activity. With this goal, it would be useful to have an automated method that can be applied on a proteomic scale to identify candidate proteins showing cell-cycle dependent variation of location. Fluorescence microscopy, and especially automated, high-throughput microscopy, can provide images for tens of thousands of fluorescently-tagged proteins for this purpose. Previous work on analysis of cell cycle variation has traditionally relied on obtaining time-series images over an entire cell cycle; these methods are not applicable to the single time point images that are much easier to obtain on a large scale. Hence a method that can infer cell cycle-dependence of proteins from asynchronous, static cell images would be preferable. In this work, we demonstrate such a method that can associate protein pattern variation in static images with cell cycle progression. We additionally show that a one-dimensional parameterization of cell cycle progression and protein feature pattern is sufficient to infer association between localization and cell cycle.

An Enlightening Structure-Function Relationship

Mutation and structural data elucidate distinct mechanisms by which different antibodies bind and induce luminescence of dye molecules.