Versatile Labeling and Detection of Endogenous Proteins Using Tag-Assisted Split Enzyme Complementation

Splittable systems in biomedical applications

Splittable systems have emerged as a powerful approach for the precise spatiotemporal control of biological processes. This concept relies on splitting a functional molecule into inactive fragments, which can be reassembled under specific conditions or stimuli to regain activity. Several binding pairs and orthogonal split fragments are introduced by fusing with other modalities to develop more complex and robust designs. One of the pillars of these splittable systems is modularity, which involves decoupling targeting, activation, and effector functions. Challenges, such as off-target effects and overactivation, can be addressed through precise control. This review provides an overview of the design principles, strategies, and applications of splittable systems across diverse fields including immunotherapy, gene editing, prodrug activation, biosensing, and synthetic biology.

Split Proteins and Reassembly Modules for Biological Applications

Split systems, modular entities enabling controlled biological processes, have become instrumental in biological research. This review highlights their utility across applications like gene regulation, protein interaction identification, and biosensor development. Covering significant progress over the last decade, it revisits traditional split proteins such as GFP, luciferase, and inteins, and explores advancements in technologies like Cas proteins and base editors. We also examine reassembly modules and their applications in diverse fields, from gene regulation to therapeutic innovation. This review offers a comprehensive perspective on the recent evolution of split systems in biological research.

Single-molecule tracking (SMT): a window into live-cell transcription biochemistry

How molecules interact governs how they move. Single-molecule tracking (SMT) thus provides a unique window into the dynamic interactions of biomolecules within live cells. Using transcription regulation as a case study, we describe how SMT works, what it can tell us about molecular biology, and how it has changed our perspective on the inner workings of the nucleus. We also describe what SMT cannot yet tell us and how new technical advances seek to overcome its limitations. This ongoing progress will be imperative to address outstanding questions about how dynamic molecular machines function in live cells.

Rapid clonal identification of biallelic CRISPR/Cas9 knock-ins using SNEAK PEEC

One of the challenges faced by current CRISPR/Cas9 editing strategies is the difficulty in rapidly selecting clonal populations of biallelically edited cells. Here we present Surface engiNeered fluorEscence Assisted Kit with Protein Epitope Enhanced Capture (SNEAK PEEC), a platform that combines human genome editing with cell-surface display, which enables the direct identification of biallelically edited clones with minimal screening.

ALIBY: ALFA Nanobody-Based Toolkit for Imaging and Biochemistry in Yeast

Specialized epitope tags continue to be integral components of various biochemical and cell biological applications such as fluorescence microscopy, immunoblotting, immunoprecipitation, and protein purification. However, until recently, no single tag could offer this complete set of functionalities on its own. Here, we present a plasmid-based toolkit named ALIBY (ALFA toolkit for imaging and biochemistry in yeast) that provides a universal workflow to adopt the versatile ALFA tag/NbALFA system within the well-established model organism Saccharomyces cerevisiae. The kit comprises tagging plasmids for labeling a protein of interest with the ALFA tag and detection plasmids encoding fluorescent-protein-tagged NbALFA for live-cell imaging purposes. We demonstrate the suitability of ALIBY for visualizing the spatiotemporal localization of yeast proteins (i.e., the cytoskeleton, nucleus, centrosome, mitochondria, vacuole, endoplasmic reticulum, exocyst, and divisome) in live cells. Our approach has yielded an excellent signal-to-noise ratio without off-target effects or any effect on cell growth. In summary, our yeast-specific toolkit aims to simplify and further advance the live-cell imaging of differentially abundant yeast proteins while also being suitable for biochemical applications. IMPORTANCE In yeast research, conventional fluorescent protein tags and small epitope tags are widely used to study the spatiotemporal dynamics and activity of proteins. Although proven to be efficient, these tags lack the versatility for use across different cell biological and biochemical studies of a given protein of interest. Therefore, there is an urgent need for a unified platform for visualization and biochemical and functional analyses of proteins of interest in yeast. Here, we have engineered ALIBY, a plasmid-based toolkit that expands the benefits of the recently developed ALFA tag/NbALFA system to studies in the well-established model organism Saccharomyces cerevisiae. We demonstrate that ALIBY provides a simple and versatile strain construction workflow for long-duration live-cell imaging and biochemical applications in yeast.

Detecting molecular interactions in live-cell single-molecule imaging with proximity-assisted photoactivation (PAPA)

Single-molecule imaging provides a powerful way to study biochemical processes in live cells, yet it remains challenging to track single molecules while simultaneously detecting their interactions. Here, we describe a novel property of rhodamine dyes, proximity-assisted photoactivation (PAPA), in which one fluorophore (the 'sender') can reactivate a second fluorophore (the 'receiver') from a dark state. PAPA requires proximity between the two fluorophores, yet it operates at a longer average intermolecular distance than Förster resonance energy transfer (FRET). We show that PAPA can be used in live cells both to detect protein-protein interactions and to highlight a subpopulation of labeled protein complexes in which two different labels are in proximity. In proof-of-concept experiments, PAPA detected the expected correlation between androgen receptor self-association and chromatin binding at the single-cell level. These results establish a new way in which a photophysical property of fluorophores can be harnessed to study molecular interactions in single-molecule imaging of live cells.

Structural insights into the human PA28-20S proteasome enabled by efficient tagging and purification of endogenous proteins

The ability to produce folded and functional proteins is a necessity for structural biology and many other biological sciences. This task is particularly challenging for numerous biomedically important targets in human cells, including membrane proteins and large macromolecular assemblies, hampering mechanistic studies and drug development efforts. Here we describe a method combining CRISPR-Cas gene editing and fluorescence-activated cell sorting to rapidly tag and purify endogenous proteins in HEK cells for structural characterization. We applied this approach to study the human proteasome from HEK cells and rapidly determined cryogenic electron microscopy structures of major proteasomal complexes, including a high-resolution structure of intact human PA28αβ-20S. Our structures reveal that PA28 with a subunit stoichiometry of 3α/4β engages tightly with the 20S proteasome. Addition of a hydrophilic peptide shows that polypeptides entering through PA28 are held in the antechamber of 20S prior to degradation in the proteolytic chamber. This study provides critical insights into an important proteasome complex and demonstrates key methodologies for the tagging of proteins from endogenous sources.

Vps13-like proteins provide phosphatidylethanolamine for GPI anchor synthesis in the ER

Glycosylphosphatidylinositol (GPI) is a glycolipid membrane anchor found on surface proteins in all eukaryotes. It is synthesized in the ER membrane. Each GPI anchor requires three molecules of ethanolamine phosphate (P-Etn), which are derived from phosphatidylethanolamine (PE). We found that efficient GPI anchor synthesis in Saccharomyces cerevisiae requires Csf1; cells lacking Csf1 accumulate GPI precursors lacking P-Etn. Structure predictions suggest Csf1 is a tube-forming lipid transport protein like Vps13. Csf1 is found at contact sites between the ER and other organelles. It interacts with the ER protein Mcd4, an enzyme that adds P-Etn to nascent GPI anchors, suggesting Csf1 channels PE to Mcd4 in the ER at contact sites to support GPI anchor biosynthesis. CSF1 has orthologues in Caenorhabditis elegans (lpd-3) and humans (KIAA1109/TWEEK); mutations in KIAA1109 cause the autosomal recessive neurodevelopmental disorder Alkuraya-Kučinskas syndrome. Knockout of lpd-3 and knockdown of KIAA1109 reduced GPI-anchored proteins on the surface of cells, suggesting Csf1 orthologues in human cells support GPI anchor biosynthesis.

Methods and tools for spatial mapping of single-cell RNAseq clusters in Drosophila

Single-cell RNA sequencing (scRNAseq) experiments provide a powerful means to identify clusters of cells that share common gene expression signatures. A major challenge in scRNAseq studies is to map the clusters to specific anatomical regions along the body and within tissues. Existing data, such as information obtained from large-scale in situ RNA hybridization studies, cell type specific transcriptomics, gene expression reporters, antibody stainings, and fluorescent tagged proteins, can help to map clusters to anatomy. However, in many cases, additional validation is needed to precisely map the spatial location of cells in clusters. Several approaches are available for spatial resolution in Drosophila, including mining of existing datasets, and use of existing or new tools for direct or indirect detection of RNA, or direct detection of proteins. Here, we review available resources and emerging technologies that will facilitate spatial mapping of scRNAseq clusters at high resolution in Drosophila. Importantly, we discuss the need, available approaches, and reagents for multiplexing gene expression detection in situ, as in most cases scRNAseq clusters are defined by the unique coexpression of sets of genes.