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Molecular Cancer Feb 2022Alterations in DNAs could not reveal what happened in proteins. The accumulated alterations of DNAs would change the manifestation of proteins. Therefore, as is the case... (Review)
Review
Alterations in DNAs could not reveal what happened in proteins. The accumulated alterations of DNAs would change the manifestation of proteins. Therefore, as is the case in cancer liquid biopsies, deep proteome profiling will likely provide invaluable and clinically relevant information in real-time throughout all stages of cancer progression. However, due to the great complexity of proteomes in liquid biopsy samples and the limitations of proteomic technologies compared to high-plex sequencing technologies, proteomic discoveries have yet lagged behind their counterpart, genomic technologies. Therefore, novel protein technologies are in urgent demand to fulfill the goals set out for biomarker discovery in cancer liquid biopsies.Notably, conventional and innovative technologies are being rapidly developed for proteomic analysis in cancer liquid biopsies. These advances have greatly facilitated early detection, diagnosis, prognosis, and monitoring of cancer evolution, adapted or adopted in response to therapeutic interventions. In this paper, we review the high-plex proteomics technologies that are capable of measuring at least hundreds of proteins simultaneously from liquid biopsy samples, ranging from traditional technologies based on mass spectrometry (MS) and antibody/antigen arrays to innovative technologies based on aptamer, proximity extension assay (PEA), and reverse phase protein arrays (RPPA).
Topics: Early Detection of Cancer; Humans; Liquid Biopsy; Neoplasms; Proteome; Proteomics
PubMed: 35168611
DOI: 10.1186/s12943-022-01526-8 -
Thrombosis and Haemostasis Jul 2022Proteomics, the simultaneous study of all proteins in a given cell, tissue or organism, is an innovative approach used to identify novel markers for diagnosis, prognosis... (Review)
Review
Proteomics, the simultaneous study of all proteins in a given cell, tissue or organism, is an innovative approach used to identify novel markers for diagnosis, prognosis and the pathophysiological mechanisms associated with diseases. Proteomic methodologies have been used in a variety of contexts such as investigating changes in protein abundance that may occur with disease presence, the response to therapeutic treatments as well as the impacts of age on the plasma proteome.Over the last decade, significant technological advancements in proteomic techniques have resulted in an increase in the use of proteomics in thrombosis and hemostasis research, particularly in order to identify relevant and novel clinical markers associated with bleeding and thrombosis. This mini-review explores the use of proteomics in the setting of thrombosis and hemostasis from 2010-2020, across five main domains (platelets, blood clot composition, stroke, venous thromboembolism, and therapeutics), as well as provides insights into key considerations for conducting proteomic studies.
Topics: Biomarkers; Blood Platelets; Hemostasis; Humans; Proteome; Proteomics; Thrombosis
PubMed: 34753192
DOI: 10.1055/a-1690-8897 -
Molecular Cell Jun 2022Mass spectrometry (MS)-based proteomics has become a powerful technology to quantify the entire complement of proteins in cells or tissues. Here, we review challenges... (Review)
Review
Mass spectrometry (MS)-based proteomics has become a powerful technology to quantify the entire complement of proteins in cells or tissues. Here, we review challenges and recent advances in the LC-MS-based analysis of minute protein amounts, down to the level of single cells. Application of this technology revealed that single-cell transcriptomes are dominated by stochastic noise due to the very low number of transcripts per cell, whereas the single-cell proteome appears to be complete. The spatial organization of cells in tissues can be studied by emerging technologies, including multiplexed imaging and spatial transcriptomics, which can now be combined with ultra-sensitive proteomics. Combined with high-content imaging, artificial intelligence and single-cell laser microdissection, MS-based proteomics provides an unbiased molecular readout close to the functional level. Potential applications range from basic biological questions to precision medicine.
Topics: Artificial Intelligence; Mass Spectrometry; Proteome; Proteomics
PubMed: 35714588
DOI: 10.1016/j.molcel.2022.05.022 -
Molecular & Cellular Proteomics : MCP Nov 2020MS-based proteome profiling has become increasingly comprehensive and quantitative, yet a persistent shortcoming has been the relatively large samples required to... (Review)
Review
MS-based proteome profiling has become increasingly comprehensive and quantitative, yet a persistent shortcoming has been the relatively large samples required to achieve an in-depth measurement. Such bulk samples, typically comprising thousands of cells or more, provide a population average and obscure important cellular heterogeneity. Single-cell proteomics capabilities have the potential to transform biomedical research and enable understanding of biological systems with a new level of granularity. Recent advances in sample processing, separations and MS instrumentation now make it possible to quantify >1000 proteins from individual mammalian cells, a level of coverage that required an input of thousands of cells just a few years ago. This review discusses important factors and parameters that should be optimized across the workflow for single-cell and other low-input measurements. It also highlights recent developments that have advanced the field and opportunities for further development.
Topics: Cells, Cultured; Chromatography, Liquid; Humans; Mass Spectrometry; Proteome; Proteomics; RNA-Seq; Single-Cell Analysis
PubMed: 32847821
DOI: 10.1074/mcp.R120.002234 -
International Journal of Molecular... Mar 2023Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical... (Review)
Review
Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC-MS/MS analysis, and data analysis. LC-MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, it is prone to errors and has low reproducibility and throughput. In-solution digestion and filter-aided sample preparation are the typical and widely used methods. In the past decade, novel methods to improve and facilitate the entire sample preparation process or integrate sample preparation and fractionation have been reported to reduce time, increase throughput, and improve reproducibility. In this review, we have outlined the current methods used for sample preparation in proteomics, including on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping. Additionally, we have summarized and discussed current devices and methods for integrating different steps of sample preparation and peptide fractionation.
Topics: Chromatography, Liquid; Tandem Mass Spectrometry; Proteomics; Reproducibility of Results; Peptides; Proteome
PubMed: 36982423
DOI: 10.3390/ijms24065350 -
Cancer Cell Aug 2022The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of...
The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.
Topics: Biomarkers, Tumor; Cell Line; Humans; Neoplasms; Proteome; Proteomics
PubMed: 35839778
DOI: 10.1016/j.ccell.2022.06.010 -
Cell Reports. Medicine Jun 2022Parkinson's disease (PD) is a growing burden worldwide, and there is no reliable biomarker used in clinical routines to date. Cerebrospinal fluid (CSF) is routinely...
Parkinson's disease (PD) is a growing burden worldwide, and there is no reliable biomarker used in clinical routines to date. Cerebrospinal fluid (CSF) is routinely collected in patients with neurological symptoms and should closely reflect alterations in PD patients' brains. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomics workflow for CSF proteome profiling. From two independent cohorts with over 200 individuals, our workflow reproducibly quantifies over 1,700 proteins from minimal CSF amounts. Machine learning determines OMD, CD44, VGF, PRL, and MAN2B1 to be altered in PD patients or to significantly correlate with clinical scores. We also uncover signatures of enhanced neuroinflammation in LRRK2 G2019S carriers, as indicated by increased levels of CTSS, PLD4, and HLA proteins. A comparison with our previously acquired urinary proteomes reveals a large overlap in PD-associated changes, including lysosomal proteins, opening up new avenues to improve our understanding of PD pathogenesis.
Topics: Biomarkers; Heterozygote; Humans; Parkinson Disease; Proteome; Proteomics
PubMed: 35732154
DOI: 10.1016/j.xcrm.2022.100661 -
Cell Apr 2023Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by...
Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.
Topics: Proteomics; Proteome; Genomics; Genome; Saccharomyces cerevisiae
PubMed: 37080200
DOI: 10.1016/j.cell.2023.03.026 -
Cell Nov 2023Neurons build synaptic contacts using different protein combinations that define the specificity, function, and plasticity potential of synapses; however, the diversity...
Neurons build synaptic contacts using different protein combinations that define the specificity, function, and plasticity potential of synapses; however, the diversity of synaptic proteomes remains largely unexplored. We prepared synaptosomes from 7 different transgenic mouse lines with fluorescently labeled presynaptic terminals. Combining microdissection of 5 different brain regions with fluorescent-activated synaptosome sorting (FASS), we isolated and analyzed the proteomes of 18 different synapse types. We discovered ∼1,800 unique synapse-type-enriched proteins and allocated thousands of proteins to different types of synapses (https://syndive.org/). We identify shared synaptic protein modules and highlight the proteomic hotspots for synapse specialization. We reveal unique and common features of the striatal dopaminergic proteome and discover the proteome signatures that relate to the functional properties of different interneuron classes. This study provides a molecular systems-biology analysis of synapses and a framework to integrate proteomic information for synapse subtypes of interest with cellular or circuit-level experiments.
Topics: Animals; Mice; Brain; Mice, Transgenic; Proteome; Proteomics; Synapses; Synaptosomes
PubMed: 37918396
DOI: 10.1016/j.cell.2023.09.028 -
Nature Methods Jan 2020We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the...
We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves the identification and quantification performance in conventional DIA proteomic applications, and is particularly beneficial for high-throughput applications, as it is fast and enables deep and confident proteome coverage when used in combination with fast chromatographic methods.
Topics: HeLa Cells; High-Throughput Screening Assays; Humans; Mass Spectrometry; Neural Networks, Computer; Proteome; Proteomics; Software; Species Specificity; Zea mays
PubMed: 31768060
DOI: 10.1038/s41592-019-0638-x