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Journal of Proteome Research Mar 2023Accurate protein quantification is key to identifying protein markers, regulatory relationships between proteins, and pathophysiological mechanisms. Realizing this... (Review)
Review
Accurate protein quantification is key to identifying protein markers, regulatory relationships between proteins, and pathophysiological mechanisms. Realizing this potential requires sensitive and deep protein analysis of a large number of samples. Toward this goal, proteomics throughput can be increased by parallelizing the analysis of both precursors and samples using multiplexed data independent acquisition (DIA) implemented by the plexDIA framework: https://plexDIA.slavovlab.net. Here we demonstrate the improved precisions of retention time estimates within plexDIA and how this enables more accurate protein quantification. plexDIA has demonstrated multiplicative gains in throughput, and these gains may be substantially amplified by improving the multiplexing reagents, data acquisition, and interpretation. We discuss future directions for advancing plexDIA, which include engineering optimized mass-tags for high-plexDIA, introducing isotopologous carriers, and developing algorithms that utilize the regular structures of plexDIA data to improve sensitivity, proteome coverage, and quantitative accuracy. These advances in plexDIA will increase the throughput of functional proteomic assays, including quantifying protein conformations, turnover dynamics, modifications states and activities. The sensitivity of these assays will extend to single-cell analysis, thus enabling functional single-cell protein analysis.
Topics: Mass Spectrometry; Proteomics; Algorithms; Proteome
PubMed: 36735898
DOI: 10.1021/acs.jproteome.2c00721 -
Journal of Proteome Research Dec 2017Mapping of the human proteome has advanced significantly in recent years and will provide a knowledge base to accelerate our understanding of how proteins and protein... (Review)
Review
Mapping of the human proteome has advanced significantly in recent years and will provide a knowledge base to accelerate our understanding of how proteins and protein networks can affect human health and disease. However, providing solutions to human health challenges will likely fail if insights are exclusively based on studies of human samples and human proteomes. In recent years, it has become evident that human health depends on an integrated understanding of the many species that make human life possible. These include the commensal microorganisms that are essential to human life, pathogens, and food species as well as the classic model organisms that enable studies of biological mechanisms. The Human Proteome Organization (HUPO) initiative on multiorganism proteomes (iMOP) works to support proteome research undertaken on nonhuman species that remain widely under-studied compared with the progress in human proteome research. This perspective argues the need for further research on multiple species that impact human life. We also present an update on recent progress in model organisms, microbiota, and food species, address the emerging problem of antibiotics resistance, and outline how iMOP activities could lead to a more inclusive approach for the human proteome project (HPP) to better support proteome research aimed at improving human health and furthering knowledge on human biology.
Topics: Animals; Humans; Microbiota; Models, Animal; Proteome; Proteomics; Research
PubMed: 28933156
DOI: 10.1021/acs.jproteome.7b00408 -
Current Opinion in Neurobiology Apr 2023The highly heterogeneous nature of neuronal cell types and their connections presents a major challenge to the characterization of neural circuits at the protein level.... (Review)
Review
The highly heterogeneous nature of neuronal cell types and their connections presents a major challenge to the characterization of neural circuits at the protein level. New approaches now enable an increasingly sophisticated dissection of cell type- and cellular compartment-specific proteomes, as well as the profiling of the protein composition of specific synaptic connections. Here, we provide an overview of these approaches and discuss how they hold considerable promise toward unravelling the molecular mechanisms of neural circuit formation and function. Finally, we provide an outlook of technological developments that may bring the characterization of synaptic proteomes at the single-synapse level within reach.
Topics: Proteome; Proteomics; Synapses; Neurons; Neural Pathways
PubMed: 36805717
DOI: 10.1016/j.conb.2023.102690 -
Cell Reports Methods Oct 2023Here, we present a standardized, "off-the-shelf" proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high...
Here, we present a standardized, "off-the-shelf" proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at -35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (-35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods.
Topics: Humans; Proteomics; Tandem Mass Spectrometry; Reproducibility of Results; Induced Pluripotent Stem Cells; Proteome
PubMed: 37729920
DOI: 10.1016/j.crmeth.2023.100593 -
Journal of Proteome Research Jan 2021Protein -acylation (commonly known as palmitoylation) is a widespread reversible lipid modification, which plays critical roles in regulating protein localization,... (Review)
Review
Protein -acylation (commonly known as palmitoylation) is a widespread reversible lipid modification, which plays critical roles in regulating protein localization, activity, stability, and complex formation. The deregulation of protein -acylation contributes to many diseases such as cancer and neurodegenerative disorders. The past decade has witnessed substantial progress in proteomic analysis of protein -acylation, which significantly advanced our understanding of -acylation biology. In this review, we summarized the techniques for the enrichment of -acylated proteins or peptides, critically reviewed proteomic studies of protein -acylation at eight different levels, and proposed major challenges for the -acylproteomics field. In summary, proteome-scale analysis of protein -acylation comes of age and will play increasingly important roles in discovering new disease mechanisms, biomarkers, and therapeutic targets.
Topics: Acylation; Lipoylation; Protein S; Proteome; Proteomics
PubMed: 33253586
DOI: 10.1021/acs.jproteome.0c00409 -
Analytical Chemistry Jul 2022Recent advances in single-cell proteomics highlight the promise of sensitive analyses in limited cell populations. However, technical challenges remain for sample...
Recent advances in single-cell proteomics highlight the promise of sensitive analyses in limited cell populations. However, technical challenges remain for sample recovery, throughput, and versatility. Here, we first report a water droplet-in-oil digestion (WinO) method based on carboxyl-coated beads and phase transfer surfactants for proteomic analysis using limited sample amounts. This method was developed to minimize the contact area between the sample solution and the container to reduce the loss of proteins and peptides by adsorption. This method increased protein and peptide recovery 10-fold. The proteome profiles obtained from 100 cells using the WinO method highly correlated with those from 10,000 cells using the in-solution digestion method. We successfully applied the WinO method to single-cell proteomics and quantified 462 proteins. Using the WinO method, samples can be easily prepared in a multi-well plate, making it a widely applicable and suitable method for single-cell proteomics.
Topics: Digestion; Peptides; Proteome; Proteomics; Water
PubMed: 35817413
DOI: 10.1021/acs.analchem.1c05487 -
STAR Protocols Jun 2022RNA-sequencing and quantitative proteomic profiling simultaneously measure thousands of molecules and provide opportunities to decipher the transcriptomic and proteomic...
RNA-sequencing and quantitative proteomic profiling simultaneously measure thousands of molecules and provide opportunities to decipher the transcriptomic and proteomic landscapes of cohort specimens for basic and health research. We present a protocol for the analysis of paired transcriptome and proteome data to identify and compare molecular subgroups among cohort specimens. We demonstrate a streamlined analysis workflow, applicable for both transcriptome and proteome data, which allows the comparison of two data types for RNA-protein variations and for derivation of biological implications. For complete details on the use and execution of this protocol, please refer to Yang et al. (2021).
Topics: Base Sequence; Humans; Proteome; Proteomics; RNA; Sequence Analysis, RNA
PubMed: 35634361
DOI: 10.1016/j.xpro.2022.101283 -
Proteomics Oct 2022Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine... (Review)
Review
Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application.
Topics: Proteomics; Proteome; Tandem Mass Spectrometry; Isotope Labeling; Peptides; Biomarkers; Lipids
PubMed: 35687565
DOI: 10.1002/pmic.202100256 -
Briefings in Functional Genomics &... Jan 2008Toxicoproteomics uses the discovery potential of proteomics in toxicology research by applying global protein measurement technologies to biofluids and tissues after... (Review)
Review
Toxicoproteomics uses the discovery potential of proteomics in toxicology research by applying global protein measurement technologies to biofluids and tissues after host exposure to injurious agents. Toxicoproteomic studies thus far have focused on protein profiling of major organs and biofluids such as liver and blood in preclinical species exposed to model toxicants. The slow pace of discovery for new biomarkers, toxicity signatures and mechanistic insights is partially due to the limited proteome coverage derived from analysis of native organs, tissues and body fluids by traditional proteomic platforms. Improved toxicoproteomic analysis would result by combining higher data density LC-MS/MS platforms with stable isotope labelled peptides and parallel use of complementary platforms. Study designs that remove abundant proteins from biofluids, enrich subcellular structures and include cell specific isolation from heterogeneous tissues would greatly increase differential expression capabilities. By leveraging resources from immunology, cell biology and nutrition research communities, toxicoproteomics could make particular contributions in three inter-related areas to advance mechanistic insights and biomarker development: the plasma proteome and circulating microparticles, the adductome and idiosyncratic toxicity.
Topics: Animals; Biomarkers; Blood Proteins; Drug Hypersensitivity; Humans; Proteome; Proteomics; Toxicology
PubMed: 18270218
DOI: 10.1093/bfgp/eln004 -
Physiological Research 2014Teeth have been a focus of interest for many centuries--due to medical problems with them. They are the hardest part of the human body and are composed of three... (Review)
Review
Teeth have been a focus of interest for many centuries--due to medical problems with them. They are the hardest part of the human body and are composed of three mineralized parts--enamel, dentin and cementum, together with the soft pulp. However, saliva also has a significant impact on tooth quality. Proteomic research of human teeth is now accelerating, and it includes all parts of the tooth. Some methodological problems still need to be overcome in this research field--mainly connected with calcified tissues. This review will provide an overview of the current state of research with focus on the individual parts of the tooth and pellicle layer as well as saliva. These proteomic results can help not only stomatology in terms of early diagnosis, identifying risk factors, and systematic control.
Topics: Gene Expression Profiling; Humans; Proteome; Proteomics; Saliva; Tissue Distribution; Tooth
PubMed: 24564654
DOI: 10.33549/physiolres.932702