Current Approaches Toward Quantitative Mapping of the Interactome

Single-molecule quantification of the oligomeric state of ZIP transporters in mammalian cells with fluorescence correlation spectroscopy

The SLC39 family of transporters, otherwise known as ZIPs for Zrt and Irt-like Proteins, function to increase cytosolic levels of transition metals. ZIP transporters have been identified at all phylogenetic levels and are members of the SoLute Carrier (SLC) superfamily. There are fourteen ZIP transporters encoded in the human genome. ZIP transmembrane proteins are expressed in the plasma membrane or membranes of intracellular organelles and have unique expression profiles across cell types. While direct structural efforts including x-ray crystallography, NMR and ab initio approaches have been effective tools in elucidating the structure of ZIPs, direct elucidation of the oligomeric state of these proteins is essential in understanding how wild type ZIP proteins function and whether mutations alter the oligomeric state of ZIPs. Unfortunately, several tools to quantify oligomeric states of proteins require overexpression of proteins which can lead to artifacts in experimental results. In contrast, fluorescence correlation spectroscopy (FCS) is a single-molecule technique which can be used to quantify the oligomeric state of transmembrane proteins. FCS takes advantage of the observation that the molecular brightness of a cluster of fluorescent molecules is directly proportional to the number of fluorescent molecules within the protein complex. This chapter describes how to implement FCS, focused on ZIP transporters, to quantify the oligomeric state of transmembrane in vivo. Included within this chapter are procedures to design constructs for experiments, transfection of mammalian cells as well as data acquisition and analysis. Taken together, FCS is a powerful mechanism to investigate the oligomeric state of proteins embedded within membranes of cells.

OUP accepted manuscript

Barcode fusion genetics (BFG) utilizes deep sequencing to improve the throughput of protein–protein interaction (PPI) screening in pools. BFG has been implemented in Yeast two-hybrid (Y2H) screens (BFG-Y2H). While Y2H requires test protein pairs to localize in the nucleus for reporter reconstruction, dihydrofolate reductase protein-fragment complementation assay (DHFR-PCA) allows proteins to localize in broader subcellular contexts and proves to be largely orthogonal to Y2H. Here, we implemented BFG to DHFR-PCA (BFG-PCA). This plasmid-based system can leverage ORF collections across model organisms to perform comparative analysis, unlike the original DHFR-PCA that requires yeast genomic integration. The scalability and quality of BFG-PCA were demonstrated by screening human and yeast interactions for >11 000 bait-prey pairs. BFG-PCA showed high-sensitivity and high-specificity for capturing known interactions for both species. BFG-Y2H and BFG-PCA capture distinct sets of PPIs, which can partially be explained based on the domain orientation of the reporter tags. BFG-PCA is a high-throughput protein interaction technology to interrogate binary PPIs that exploits clone collections from any species of interest, expanding the scope of PPI assays.

CellFIE: CRISPR- and Cell Fusion-based Two-hybrid Interaction Mapping of Endogenous Proteins

Numerous genetic methods facilitate the detection of binary protein-protein interactions (PPIs) by exogenous overexpression, which can lead to false results. Here, we describe CellFIE, a CRISPR- and cell fusion-based PPI detection method, which enables the mapping of interactions between endogenously tagged two-hybrid proteins. We demonstrate the specificity and reproducibility of CellFIE in a matrix mapping approach, validating the interactions of VCP with ASPL and UBXD1, and the self-interaction of TDP-43 under endogenous conditions. Furthermore, we show that CellFIE can be used to quantify changes of endogenous PPIs upon stress induction or drug treatment. For the first time, CellFIE facilitates systematic mapping of interactions between endogenously tagged proteins and represents a novel tool to characterize PPIs in live cells under dynamic conditions.

Quantitative Yeast-Yeast Two Hybrid for the Discovery and Binding Affinity Estimation of Protein-Protein Interactions

Quantifying the binding affinity of protein-protein interactions is important for elucidating connections within biochemical signaling pathways, as well as characterization of binding proteins isolated from combinatorial libraries. We describe a quantitative yeast-yeast two-hybrid (qYY2H) system that not only enables the discovery of specific protein-protein interactions but also efficient, quantitative estimation of their binding affinities (K_D). In qYY2H, the bait and prey proteins are expressed as yeast cell surface fusions using yeast surface display. We developed a semiempirical framework for estimating the K_D of monovalent bait-prey interactions, using measurements of bait-prey yeast-yeast binding, which is mediated by multivalent interactions between yeast-displayed bait and prey. Using qYY2H, we identified interaction partners of SMAD3 and the tandem WW domains of YAP from a cDNA library and characterized their binding affinities. Finally, we showed that qYY2H could also quantitatively evaluate binding interactions mediated by post-translational modifications on the bait protein.

Exploring the protein-protein interaction landscape in plants

Protein-protein interactions (PPIs) represent an essential aspect of plant systems biology. Identification of key protein players and their interaction networks provide crucial insights into the regulation of plant developmental processes and into interactions of plants with their environment. Despite the great advance in the methods for the discovery and validation of PPIs, still several challenges remain. First, the PPI networks are usually highly dynamic, and the in vivo interactions are often transient and difficult to detect. Therefore, the properties of the PPIs under study need to be considered to select the most suitable technique, because each has its own advantages and limitations. Second, besides knowledge on the interacting partners of a protein of interest, characteristics of the interaction, such as the spatial or temporal dynamics, are highly important. Hence, multiple approaches have to be combined to obtain a comprehensive view on the PPI network present in a cell. Here, we present the progress in commonly used methods to detect and validate PPIs in plants with a special emphasis on the PPI features assessed in each approach and how they were or can be used for the study of plant interactions with their environment.

Discovering cellular protein-protein interactions: Technological strategies and opportunities

The analysis of protein interaction networks is one of the key challenges in the study of biology. It connects genotypes to phenotypes, and disruption often leads to diseases. Hence, many technologies have been developed to study protein-protein interactions (PPIs) in a cellular context. The expansion of the PPI technology toolbox however complicates the selection of optimal approaches for diverse biological questions. This review gives an overview of the binary and co-complex technologies, with the former evaluating the interaction of two co-expressed genetically tagged proteins, and the latter only needing the expression of a single tagged protein or no tagged proteins at all. Mass spectrometry is crucial for some binary and all co-complex technologies. After the detailed description of the different technologies, the review compares their unique specifications, advantages, disadvantages, and applicability, while highlighting opportunities for further advancements.

Detection of Heterodimerization of Protein Isoforms Using an in Situ Proximity Ligation Assay

Regulated protein-protein interactions are a guiding principle for many signaling events, and the detection of such events is an important element in understanding how such pathways are organized and how they function. There are many methods to detect protein-protein interactions in cells, but relatively few can be used to detect interactions between endogenous proteins. One such method, the proximity ligation assay (PLA), has several advantages to recommend its use. Compared to other common methods of protein-protein interaction analysis, PLA has relatively high sensitivity and specificity, can be performed with minimal cell manipulation, and, in the protocol described herein, requires only two target-specific antibodies derived from different species (e.g., from mouse and rabbit) and one specialized reagent: a set of secondary antibodies that are covalently linked to specific oligonucleotides that, when brought in close proximity of one another, create an amplifiable platform for in situ PCR or rolling circle amplification. In this presentation, we show how to apply the PLA technique to visualize changes in MST1 and MST2 proximity in fixed cells. The technique described in this manuscript is particularly applicable for the analysis of cell signaling studies.

LuTHy: a double-readout bioluminescence-based two-hybrid technology for quantitative mapping of protein-protein interactions in mammalian cells

Information on protein-protein interactions (PPIs) is of critical importance for studying complex biological systems and developing therapeutic strategies. Here, we present a double-readout bioluminescence-based two-hybrid technology, termed LuTHy, which provides two quantitative scores in one experimental procedure when testing binary interactions. PPIs are first monitored in cells by quantification of bioluminescence resonance energy transfer (BRET) and, following cell lysis, are again quantitatively assessed by luminescence-based co-precipitation (LuC). The double-readout procedure detects interactions with higher sensitivity than traditional single-readout methods and is broadly applicable, for example, for detecting the effects of small molecules or disease-causing mutations on PPIs. Applying LuTHy in a focused screen, we identified 42 interactions for the presynaptic chaperone CSPα, causative to adult-onset neuronal ceroid lipofuscinosis (ANCL), a progressive neurodegenerative disease. Nearly 50% of PPIs were found to be affected when studying the effect of the disease-causing missense mutations L115R and ∆L116 in CSPα with LuTHy. Our study presents a robust, sensitive research tool with high utility for investigating the molecular mechanisms by which disease-associated mutations impair protein activity in biological systems.

Surveying the landscape of optogenetic methods for detection of protein-protein interactions

Mapping the protein-protein interaction (PPi) landscape is of critical importance to furthering our understanding how cells and organisms function. Optogenetic methods, that is, approaches that utilize genetically encoded fluorophores or fluorogenic enzyme reactions, uniquely enable the visualization of biochemical phenomena in live cells with high spatial and temporal accuracy. Applying optogenetic methods to the detection of PPis requires the engineering of protein-based systems in which an optical signal undergoes a substantial change when the two proteins of interest interact. In recent years, researchers have developed a number of creative and effective optogenetic methods that achieve this goal, and used them to further elaborate our map of the PPi landscape. In this review, we provide an introduction to the general principles of optogenetic PPi detection, and then provide a number of representative examples of how these principles have been applied. We have organized this review by categorizing methods based on whether the signal generated is reversible or irreversible in nature, and whether the signal is localized or nonlocalized at the subcellular site of the PPi. We discuss these techniques giving both their benefits and drawbacks to enable rational choices about their potential use. This article is categorized under: Laboratory Methods and Technologies > Imaging Laboratory Methods and Technologies > Macromolecular Interactions, Methods Analytical and Computational Methods > Analytical Methods.

Quantitative Tandem Affinity Purification, an Effective Tool to Investigate Protein Complex Composition in Plant Hormone Signaling: Strigolactones in the Spotlight

Phytohormones tightly regulate plant growth by integrating changing environmental and developmental cues. Although the key players have been identified in many plant hormonal pathways, the molecular mechanisms and mode of action of perception and signaling remain incompletely resolved. Characterization of protein partners of known signaling components provides insight into the formed protein complexes, but, unless quantification is involved, does not deliver much, if any, information about the dynamics of the induced or disrupted protein complexes. Therefore, in proteomics research, the discovery of what actually triggers, regulates or interrupts the composition of protein complexes is gaining importance. Here, tandem affinity purification coupled to mass spectrometry (TAP-MS) is combined with label-free quantification (LFQ) to a highly valuable tool to detect physiologically relevant, dynamic protein-protein interactions in Arabidopsis thaliana cell cultures. To demonstrate its potential, we focus on the signaling pathway of one of the most recently discovered phytohormones, strigolactones.

Generation of an immortalized mesenchymal stem cell line producing a secreted biosensor protein for glucose monitoring

Diabetes is a chronic disease characterized by high levels of blood glucose. Diabetic patients should normalize these levels in order to avoid short and long term clinical complications. Presently, blood glucose monitoring is dependent on frequent finger pricking and enzyme based systems that analyze the drawn blood. Continuous blood glucose monitors are already on market but suffer from technical problems, inaccuracy and short operation time. A novel approach for continuous glucose monitoring is the development of implantable cell-based biosensors that emit light signals corresponding to glucose concentrations. Such devices use genetically modified cells expressing chimeric genes with glucose binding properties. MSCs are good candidates as carrier cells, as they can be genetically engineered and expanded into large numbers. They also possess immunomodulatory properties that, by reducing local inflammation, may assist long operation time.

Here, we generated a novel immortalized human MSC line co-expressing hTERT and a secreted glucose biosensor transgene using the Sleeping Beauty transposon technology. Genetically modified hMSCs retained their mesenchymal characteristics. Stable transgene expression was validated biochemically. Increased activity of hTERT was accompanied by elevated and constant level of stem cell pluripotency markers and subsequently, by MSC immortalization. Furthermore, these cells efficiently suppressed PBMC proliferation in MLR transwell assays, indicating that they possess immunomodulatory properties. Finally, biosensor protein produced by MSCs was used to quantify glucose in cell-free assays. Our results indicate that our immortalized MSCs are suitable for measuring glucose concentrations in a physiological range. Thus, they are appropriate for incorporation into a cell-based, immune-privileged, glucose-monitoring medical device.

Yeast-based assays for detecting protein-protein/drug interactions and their inhibitors

Understanding cellular processes at molecular levels in health and disease requires the knowledge of protein-protein interactions (PPIs). In line with this, identification of PPIs at genome-wide scale is highly valuable to understand how different cellular pathways are interconnected, and it eventually facilitates designing effective drugs against certain PPIs. Furthermore, investigating PPIs at a small laboratory scale for deciphering certain biochemical pathways has been demanded for years. In this regard, yeast two hybrid system (Y2HS) has proven an extremely useful tool to discover novel PPIs, while Y2HS derivatives and novel yeast-based assays are contributing significantly to identification of protein-drug/inhibitor interaction at both large- and small-scale set-ups. These methods have been evolving over time to provide more accurate, reproducible and quantitative results. Here we briefly describe different yeast-based assays for identification of various protein-protein/drug/inhibitor interactions and their specific applications, advantages, shortcomings, and improvements. The broad range of yeast-based assays facilitates application of the most suitable method(s) for each specific need.

Mapping, modeling, and characterization of protein-protein interactions on a proteomic scale

Proteins effect a number of biological functions, from cellular signaling, organization, mobility, and transport to catalyzing biochemical reactions and coordinating an immune response. These varied functions are often dependent upon macromolecular interactions, particularly with other proteins. Small-scale studies in the scientific literature report protein-protein interactions (PPIs), but slowly and with bias towards well-studied proteins. In an era where genomic sequence is readily available, deducing genotype-phenotype relationships requires an understanding of protein connectivity at proteome-scale. A proteome-scale map of the protein-protein interaction network provides a global view of cellular organization and function. Here, we discuss a summary of methods for building proteome-scale interactome maps and the current status and implications of mapping achievements. Not only do interactome maps serve as a reference, detailing global cellular function and organization patterns, but they can also reveal the mechanisms altered by disease alleles, highlight the patterns of interaction rewiring across evolution, and help pinpoint biologically and therapeutically relevant proteins. Despite the considerable strides made in proteome-wide mapping, several technical challenges persist. Therefore, future considerations that impact current mapping efforts are also discussed.

Simultaneously measuring multiple protein interactions and their correlations in a cell by Protein-interactome Footprinting

Quantitatively detecting correlations of multiple protein-protein interactions (PPIs) in vivo is a big challenge. Here we introduce a novel method, termed Protein-interactome Footprinting (PiF), to simultaneously measure multiple PPIs in one cell. The principle of PiF is that each target physical PPI in the interactome is simultaneously transcoded into a specific DNA sequence based on dimerization of the target proteins fused with DNA-binding domains. The interaction intensity of each target protein is quantified as the copy number of the specific DNA sequences bound by each fusion protein dimers. Using PiF, we quantitatively reveal dynamic patterns of PPIs and their correlation network in E. coli two-component systems.

Global profiling of protein complexes: current approaches and their perspective in biomedical research

INTRODUCTION

Despite the rapid evolution of proteomic methods, protein interactions and their participation in protein complexes - an important aspect of their function - has rarely been investigated on the proteome-wide level. Disease states, such as muscular dystrophy or viral infection, are induced by interference in protein-protein interactions within complexes. The purpose of this review is to describe the current methods for global complexome analysis and to critically discuss the challenges and opportunities for the application of these methods in biomedical research. Areas covered: We discuss advancements in experimental techniques and computational tools that facilitate profiling of the complexome. The main focus is on the separation of native protein complexes via size exclusion chromatography and gel electrophoresis, which has recently been combined with quantitative mass spectrometry, for a global protein-complex profiling. The development of this approach has been supported by advanced bioinformatics strategies and fast and sensitive mass spectrometers that have allowed the analysis of whole cell lysates. The application of this technique to biomedical research is assessed, and future directions are anticipated. Expert commentary: The methodology is quite new, and has already shown great potential when combined with complementary methods for detection of protein complexes.