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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 -
Expert Review of Proteomics Mar 2022Mass spectrometry-based proteomics reveals dynamic molecular signatures underlying phenotypes reflecting normal and perturbed conditions in living systems. Although...
INTRODUCTION
Mass spectrometry-based proteomics reveals dynamic molecular signatures underlying phenotypes reflecting normal and perturbed conditions in living systems. Although valuable on its own, the proteome has only one level of moleclar information, with the genome, epigenome, transcriptome, and metabolome, all providing complementary information. Multi-omic analysis integrating information from one or more of these other domains with proteomic information provides a more complete picture of molecular contributors to dynamic biological systems.
AREAS COVERED
Here, we discuss the improvements to mass spectrometry-based technologies, focused on peptide-based, bottom-up approaches that have enabled deep, quantitative characterization of complex proteomes. These advances are facilitating the integration of proteomics data with other 'omic information, providing a more complete picture of living systems. We also describe the current state of bioinformatics software and approaches for integrating proteomics and other 'omics data, critical for enabling new discoveries driven by multi-omics.
EXPERT COMMENTARY
Multi-omics, centered on the integration of proteomics information with other 'omic information, has tremendous promise for biological and biomedical studies. Continued advances in approaches for generating deep, reliable proteomic data and bioinformatics tools aimed at integrating data across 'omic domains will ensure the discoveries offered by these multi-omic studies continue to increase.
Topics: Proteomics; Proteome; Computational Biology; Software; Mass Spectrometry
PubMed: 35466851
DOI: 10.1080/14789450.2022.2070476 -
Cells Aug 2022Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and...
Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of proteins in single cells. However, significant challenges remain in analyzing an extremely small amount of proteins collected from a single cell, as a proteome-wide amplification of proteins is not currently feasible. Here, we report an integrated spectral library-based single-cell proteomics (SLB-SCP) platform that is ultrasensitive and well suited for a large-scale analysis. To overcome the low MS/MS signal intensity intrinsically associated with a single-cell analysis, this approach takes an alternative approach by extracting a breadth of information that specifically defines the physicochemical characteristics of a peptide from MS1 spectra, including monoisotopic mass, isotopic distribution, and retention time (hydrophobicity), and uses a spectral library for proteomic identification. This conceptually unique MS platform, coupled with the DIRECT sample preparation method, enabled identification of more than 2000 proteins in a single cell to distinguish different proteome landscapes associated with cellular types and heterogeneity. We characterized individual normal and cancerous pancreatic ductal cells (HPDE and PANC-1, respectively) and demonstrated the substantial difference in the proteomes between HPDE and PANC-1 at the single-cell level. A significant upregulation of multiple protein networks in cancer hallmarks was identified in the PANC-1 cells, functionally discriminating the PANC-1 cells from the HPDE cells. This integrated platform can be built on high-resolution MS and widely accepted proteomic software, making it possible for community-wide applications.
Topics: Peptides; Proteome; Proteomics; Software; Tandem Mass Spectrometry
PubMed: 35954294
DOI: 10.3390/cells11152450 -
Journal of Proteome Research May 2020Multiplexed quantitative analyses of complex proteomes enable deep biological insight. While a multitude of workflows have been developed for multiplexed analyses, the...
Multiplexed quantitative analyses of complex proteomes enable deep biological insight. While a multitude of workflows have been developed for multiplexed analyses, the most quantitatively accurate method (SPS-MS3) suffers from long acquisition duty cycles. We built a new, real-time database search (RTS) platform, Orbiter, to combat the SPS-MS3 method's longer duty cycles. RTS with Orbiter eliminates SPS-MS3 scans if no peptide matches to a given spectrum. With Orbiter's online proteomic analytical pipeline, which includes RTS and false discovery rate analysis, it was possible to process a single spectrum database search in less than 10 ms. The result is a fast, functional means to identify peptide spectral matches using Comet, filter these matches, and more efficiently quantify proteins of interest. Importantly, the use of Comet for peptide spectral matching allowed for a fully featured search, including analysis of post-translational modifications, with well-known and extensively validated scoring. These data could then be used to trigger subsequent scans in an adaptive and flexible manner. In this work we tested the utility of this adaptive data acquisition platform to improve the efficiency and accuracy of multiplexed quantitative experiments. We found that RTS enabled a 2-fold increase in mass spectrometric data acquisition efficiency. Orbiter's RTS quantified more than 8000 proteins across 10 proteomes in half the time of an SPS-MS3 analysis (18 h for RTS, 36 h for SPS-MS3).
Topics: Databases, Factual; Mass Spectrometry; Peptides; Proteome; Proteomics
PubMed: 32126768
DOI: 10.1021/acs.jproteome.9b00860 -
The FEBS Journal Nov 2013The elucidation of the subcellular distribution of proteins under different conditions is a major challenge in cell biology. This challenge is further complicated by the... (Review)
Review
The elucidation of the subcellular distribution of proteins under different conditions is a major challenge in cell biology. This challenge is further complicated by the multicompartmental and dynamic nature of protein localization. To address this issue, quantitative proteomics workflows have been developed to reliably identify the protein complement of whole organelles, as well as for protein assignment to subcellular location and relative protein quantification based on different cell culture conditions. Here, we review quantitative MS-based approaches that combine cellular fractionation with proteomic analysis. The application of these methods to the characterization of organellar composition and to the determination of the dynamic nature of protein complexes is improving our understanding of protein functions and dynamics.
Topics: Cell Fractionation; Cell Line; Computational Biology; Humans; Mass Spectrometry; Organelles; Proteome; Proteomics; Subcellular Fractions
PubMed: 24034475
DOI: 10.1111/febs.12502 -
Briefings in Bioinformatics Jan 2021Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers... (Review)
Review
Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.
Topics: Biomarkers; Body Fluids; Humans; Proteome; Proteomics
PubMed: 32020158
DOI: 10.1093/bib/bbz160 -
Current Opinion in Neurobiology Jun 2018Understanding signaling pathways in neuroscience requires high-resolution maps of the underlying protein networks. Proximity-dependent biotinylation with engineered... (Review)
Review
Understanding signaling pathways in neuroscience requires high-resolution maps of the underlying protein networks. Proximity-dependent biotinylation with engineered enzymes, in combination with mass spectrometry-based quantitative proteomics, has emerged as a powerful method to dissect molecular interactions and the localizations of endogenous proteins. Recent applications to neuroscience have provided insights into the composition of sub-synaptic structures, including the synaptic cleft and inhibitory post-synaptic density. Here we compare the different enzymes and small-molecule probes for proximity labeling in the context of cultured neurons and tissue, review existing studies, and provide technical suggestions for the in vivo application of proximity labeling.
Topics: Animals; Biotinylation; Humans; Neurobiology; Neuroimaging; Proteome; Proteomics
PubMed: 29125959
DOI: 10.1016/j.conb.2017.10.015 -
Analytical Methods : Advancing Methods... Feb 2023Complete enzymatic digestion of proteins for bottom-up proteomics is substantially improved by use of detergents for denaturation and solubilization. Detergents however,...
Complete enzymatic digestion of proteins for bottom-up proteomics is substantially improved by use of detergents for denaturation and solubilization. Detergents however, are incompatible with many proteases and highly detrimental to LC-MS/MS. Recently; filter-based methods have seen wide use due to their capacity to remove detergents and harmful reagents prior to digestion and mass spectrometric analysis. We hypothesized that non-specific protein binding to negatively charged silica-based filters would be enhanced by addition of lyotropic salts, similar to DNA purification. We sought to exploit these interactions and investigate if low-cost DNA purification spin-filters, 'Minipreps,' efficiently and reproducibly bind proteins for digestion and LC-MS/MS analysis. We propose a new method, Miniprep Assisted Proteomics (MAP), for sample preparation. We demonstrate binding capacity, performance, recovery and identification rates for proteins and whole-cell lysates using MAP. MAP recovered equivalent or greater protein yields from 0.5-50 μg analyses benchmarked against commercial trapping preparations. Nano UHPLC-MS/MS proteome profiling of lysates of had 99.3% overlap existing approaches and reproducibility of replicate minipreps was 98.8% at the 1% FDR protein level. Label Free Quantitative proteomics was performed and 91.2% of quantified proteins had a %CV <20% (2044/2241). Miniprep Assisted Proteomics can be performed in minutes, shows low variability, high recovery and proteome depth. This suggests a significant role for adventitious binding in developing new proteomics sample preparation techniques. MAP represents an efficient, ultra-low-cost alternative for sample preparation in a commercially obtainable device that costs ∼$0.50 (USD) per miniprep.
Topics: Tandem Mass Spectrometry; Chromatography, Liquid; Proteome; Detergents; Proteomics; Reproducibility of Results; Escherichia coli; DNA
PubMed: 36373982
DOI: 10.1039/d2ay01549h -
PloS One 2022Cyanobacteria are prokaryotic Gram-negative organisms prevalent in nearly all habitats. A detailed proteomics study of Cyanobacteria has not been conducted despite...
Cyanobacteria are prokaryotic Gram-negative organisms prevalent in nearly all habitats. A detailed proteomics study of Cyanobacteria has not been conducted despite extensive study of their genome sequences. Therefore, we conducted a proteome-wide analysis of the Cyanobacteria proteome and found Calothrix desertica as the largest (680331.825 kDa) and Candidatus synechococcus spongiarum as the smallest (42726.77 kDa) proteome of the cyanobacterial kingdom. A Cyanobacterial proteome encodes 312.018 amino acids per protein, with a molecular weight of 182173.1324 kDa per proteome. The isoelectric point (pI) of the Cyanobacterial proteome ranges from 2.13 to 13.32. It was found that the Cyanobacterial proteome encodes a greater number of acidic-pI proteins, and their average pI is 6.437. The proteins with higher pI are likely to contain repetitive amino acids. A virtual 2D map of Cyanobacterial proteome showed a bimodal distribution of molecular weight and pI. Several proteins within the Cyanobacterial proteome were found to encode Selenocysteine (Sec) amino acid, while Pyrrolysine amino acids were not detected. The study can enable us to generate a high-resolution cell map to monitor proteomic dynamics. Through this computational analysis, we can gain a better understanding of the bias in codon usage by analyzing the amino acid composition of the Cyanobacterial proteome.
Topics: Isoelectric Point; Proteome; Proteomics; Selenocysteine; Synechococcus
PubMed: 36190972
DOI: 10.1371/journal.pone.0275148 -
Dermatology (Basel, Switzerland) 2022The skin is the largest organ in the human body and serves as a multilayered protective shield from the environment as well as a sensor and thermal regulator. However,... (Review)
Review
BACKGROUND
The skin is the largest organ in the human body and serves as a multilayered protective shield from the environment as well as a sensor and thermal regulator. However, despite its importance, many details about skin structure and function at the molecular level remain incompletely understood. Recent advances in liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics have enabled the quantification and characterization of the proteomes of a number of clinical samples, including normal and diseased skin.
SUMMARY
Here, we review the current state of the art in proteomic analysis of the skin. We provide a brief overview of the technique and skin sample collection methodologies as well as a number of recent examples to illustrate the utility of this strategy for advancing a broader understanding of the pathology of diseases as well as new therapeutic options.
KEY MESSAGES
Proteomic studies of healthy skin and skin diseases can identify potential molecular biomarkers for improved diagnosis and patient stratification as well as potential targets for drug development. Collectively, efforts such as the Human Skinatlas offer improved opportunities for enhancing clinical practice and patient outcomes.
Topics: Chromatography, Liquid; Dermatology; Humans; Proteome; Proteomics; Tandem Mass Spectrometry
PubMed: 34062531
DOI: 10.1159/000516764