A proximity proteomics pipeline with improved reproducibility and throughput
Ontology highlight
ABSTRACT:
SUBMITTER: Xiaofang Zhong
PROVIDER: S-SCDT-10_1038-S44320-024-00049-2 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description: Not available
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Project description:Proximity labeling coupled with mass spectrometry (proximity proteomics) have emerged as a powerful technique to map proximal protein interactions in living cells. However, the large-scale and unbiased sample analysis in proximity proteomics necessitates a universal and high-throughput workflow to reduce hands-on time and increase quantitative reproducibility. To address this issue, we developed a systematic and automated approach, including generation and characterization of monoclonal cell lines, automated enrichment of biotinylated proteins in a 96-well format, optimization of quantitative mass spectrometry acquisition methods, and advanced computational framework to deconvolute spatial and temporal protein interaction networks. The quantitative reproducibility and accuracy of this streamlined workflow clearly outperforms the conventional manual enrichment. We first applied this approach to investigate subcellular proteomics, including cytosol, endosome, Golgi, lysosome, and plasma membrane. Moreover, using serotonin receptor (5HT2A) as a model, we mapped dynamic protein-protein interactions of GPCR induced by agonist. Collectively, this systematic approach could be widely used in proximity proteomics with high throughput, high reproducibility, and minimal manual intervention.
2024-07-26 | PXD040762 | Pride
Project description:Mass spectrometry-based clinical proteomics requires high throughput, reproducibility, robustness, and comprehensive coverage to serve the needs of clinical diagnosis, prognosis, and personalized medicine. Oftentimes these requirements are contradictory to each other. We report the development of a streamlined High-Throughput Plasma Proteomics (sHTPP) platform for untargeted profiling of the blood plasma proteome, which includes 96-well plates and simplified procedures for sample preparation, disposable trap column for peptide loading, robust liquid chromatographic system for separation, data-independent acquisition in tandem mass spectrometry, and DIA-NN, FragPipe, and in-house peptide spectral library-based data analysis. Using the optimized platform at a throughput of 60 samples per day, over 600 protein groups including 57 FDA-approved biomarkers can be consistently identified from whole human plasma, and more than 85% of the detected proteins have 100% completeness in quantitative values across 300 samples. The balance achieved between proteome coverage, throughput, and reproducibility of this sHTPP platform makes it promising in clinical settings, where a large number of samples are to be measured quickly and reliably to support various needs of clinical medicine.
| S-EPMC10080683 | biostudies-literature
Project description:Within cells, proteins can co-assemble into functionally integrated and spatially restricted multicomponent complexes. Often, the affinities between individual proteins are relatively weak, and proteins within such clusters may interact only indirectly with many of their other protein neighbors. This makes proteomic characterization difficult using methods such as immunoprecipitation or cross-linking. Recently, several groups have described the use of enzyme-catalyzed proximity labeling reagents that covalently tag the neighbors of a targeted protein with a small molecule such as fluorescein or biotin. The modified proteins can then be isolated by standard pulldown methods and identified by mass spectrometry. Here we will describe the techniques as well as their similarities and differences. We discuss their applications both to study protein assemblies and to provide a new way for characterizing organelle proteomes. We stress the importance of proteomic quantitation and independent target validation in such experiments. Furthermore, we suggest that there are biophysical and cell-biological principles that dictate the appropriateness of enzyme-catalyzed proximity labeling methods to address particular biological questions of interest.
| S-EPMC4638030 | biostudies-literature
Project description:While cilia are recognized as important signaling organelles, the extent of ciliary functions remains unknown because of difficulties in cataloguing proteins from mammalian primary cilia. We present a method that readily captures rapid snapshots of the ciliary proteome by selectively biotinylating ciliary proteins using a cilia-targeted proximity labeling enzyme (cilia-APEX). Besides identifying known ciliary proteins, cilia-APEX uncovered several ciliary signaling molecules. The kinases PKA, AMPK, and LKB1 were validated as bona fide ciliary proteins and PKA was found to regulate Hedgehog signaling in primary cilia. Furthermore, proteomics profiling of Ift27/Bbs19 mutant cilia correctly detected BBSome accumulation inside Ift27(-/-) cilia and revealed that ?-arrestin 2 and the viral receptor CAR are candidate cargoes of the BBSome. This work demonstrates that proximity labeling can be applied to proteomics of non-membrane-enclosed organelles and suggests that proteomics profiling of cilia will enable a rapid and powerful characterization of ciliopathies.
| S-EPMC4662609 | biostudies-literature
Project description:Protein-protein interactions are critically important for cellular functions, including regulation of ion channels. Ion channels are typically part of large macromolecular complexes that impact their function. These complexes have traditionally been elucidated via standard biochemical techniques including immunoprecipitation, pull-down assays and mass spectrometry. Recently, several methods have been developed to provide a more complete depiction of the microenvironment or "neighborhood" of proteins of interest. These new methods, which fall broadly under the category of proximity-dependent labeling techniques, aim to overcome the limitations imposed by antibody-based techniques and mass spectrometry. In this chapter, we describe the use of proximity labeling to elucidate the cardiac CaV1.2 macromolecular complex under basal conditions and after β-adrenergic stimulation. Using these methodologies, we have identified the mechanism underlying adrenergic stimulation of the Ca2+ current in the heart.
| S-EPMC9569177 | biostudies-literature
Project description:Protein-protein interactions are essential for cellular structure and function. To delineate how the intricate assembly of protein interactions contribute to cellular processes in health and disease, new methodologies that are both highly sensitive and can be applied at large scale are needed. Here, we develop HiPLA (high-throughput imaging proximity ligation assay), a method that employs the well-established antibody-based proximity ligation assay in a high-throughput imaging screening format as a novel means to systematically visualize protein interactomes. Using HiPLA with a library of antibodies targeting nuclear proteins, we probe the interaction of 60 proteins and associated post-translational modifications (PTMs) with the nuclear lamina in a model of the premature aging disorder Hutchinson-Gilford progeria syndrome (HGPS). We identify a subset of proteins that differentially interact with the nuclear lamina in HGPS. Using HiPLA in combination with quantitative indirect immunofluorescence, we find that the majority of differential interactions are accompanied by corresponding changes in expression of the interacting protein. Taken together, HiPLA offers a novel approach to probe cellular protein-protein interaction at a large scale and reveals mechanistic insights into the assembly of protein complexes.
| S-EPMC6401276 | biostudies-literature
Project description:Proximity biotinylation workflows typically require CRISPR-based genetic manipulation of target cells. To overcome this bottleneck, we fused the TurboID proximity biotinylation enzyme to Protein A. Upon target cell permeabilization, the ProtA-Turbo enzyme can be targeted to proteins or post-translational modifications of interest using bait-specific antibodies. Addition of biotin then triggers bait-proximal protein biotinylation. Biotinylated proteins can subsequently be enriched from crude lysates and identified by mass spectrometry. We demonstrate this workflow by targeting Emerin, H3K9me3 and BRG1. Amongst the main findings, our experiments reveal that the essential protein FLYWCH1 interacts with a subset of H3K9me3-marked (peri)centromeres in human cells. The ProtA-Turbo enzyme represents an off-the-shelf proximity biotinylation enzyme that facilitates proximity biotinylation experiments in primary cells and can be used to understand how proteins cooperate in vivo and how this contributes to cellular homeostasis and disease.
| S-EPMC8373943 | biostudies-literature
Project description:High-throughput RNA proximity ligation assays are molecular methods that are used to simultaneously analyze the spatial proximity of many RNAs in living cells. Their principle is based on cross-linking, fragmentation, and subsequent religation of RNAs, followed by high-throughput sequencing. The generated fragments have two different types of splits, one resulting from pre-mRNA splicing and the other formed by the ligation of spatially close RNA strands. Here, we present RNAcontacts, a universal pipeline for detecting RNA-RNA contacts in high-throughput RNA proximity ligation assays. RNAcontacts circumvents the inherent problem of mapping sequences with two distinct types of splits using a two-pass alignment, in which splice junctions are inferred from a control RNA-seq experiment on the first pass and then provided to the aligner as bona fide introns on the second pass. Compared to previously developed methods, our approach allows for a more sensitive detection of RNA contacts and has a higher specificity with respect to splice junctions that are present in the biological sample. RNAcontacts automatically extracts contacts, clusters their ligation points, computes the read support, and generates tracks for visualizing through the UCSC Genome Browser. The pipeline is implemented in Snakemake, a reproducible and scalable workflow management system for rapid and uniform processing of multiple datasets. RNAcontacts is a generic pipeline for the detection of RNA contacts that can be used with any proximity ligation method as long as one of the interacting partners is RNA. RNAcontacts is available via the GitHub repository https://github.com/smargasyuk/ RNAcontacts/.
| S-EPMC10154773 | biostudies-literature
Project description:BackgroundSingle nucleotide polymorphisms (SNPs) as defined here are single base sequence changes or short insertion/deletions between or within individuals of a given species. As a result of their abundance and the availability of high throughput analysis technologies SNP markers have begun to replace other traditional markers such as restriction fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs) and simple sequence repeats (SSRs or microsatellite) markers for fine mapping and association studies in several species. For SNP discovery from chromatogram data, several bioinformatics programs have to be combined to generate an analysis pipeline. Results have to be stored in a relational database to facilitate interrogation through queries or to generate data for further analyses such as determination of linkage disequilibrium and identification of common haplotypes. Although these tasks are routinely performed by several groups, an integrated open source SNP discovery pipeline that can be easily adapted by new groups interested in SNP marker development is currently unavailable.ResultsWe developed SNP-PHAGE (SNP discovery Pipeline with additional features for identification of common haplotypes within a sequence tagged site (Haplotype Analysis) and GenBank (-dbSNP) submissions. This tool was applied for analyzing sequence traces from diverse soybean genotypes to discover over 10,000 SNPs. This package was developed on UNIX/Linux platform, written in Perl and uses a MySQL database. Scripts to generate a user-friendly web interface are also provided with common queries for preliminary data analysis. A machine learning tool developed by this group for increasing the efficiency of SNP discovery is integrated as a part of this package as an optional feature. The SNP-PHAGE package is being made available open source at http://bfgl.anri.barc.usda.gov/ML/snp-phage/.ConclusionSNP-PHAGE provides a bioinformatics solution for high throughput SNP discovery, identification of common haplotypes within an amplicon, and GenBank (dbSNP) submissions. SNP selection and visualization are aided through a user-friendly web interface. This tool is useful for analyzing sequence tagged sites (STSs) of genomic sequences, and this software can serve as a starting point for groups interested in developing SNP markers.
| S-EPMC1626092 | biostudies-literature