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Current Opinion in Structural Biology Feb 2020Mass spectrometry (MS)-based proteomics is moving beyond the simple generation of protein inventories of biological samples. The ability of MS to quantitatively probe... (Review)
Review
Mass spectrometry (MS)-based proteomics is moving beyond the simple generation of protein inventories of biological samples. The ability of MS to quantitatively probe complex protein mixtures is increasingly being used to study protein structural and biophysical properties at proteome-scale. MS provides a readout for proteome-wide structural alterations, folding and stability, aggregation, and molecular interactions, all in native-like conditions such as cell lysates or even intact cells. We provide an overview of methods that yield such proteome-wide structural information, covering cross-linking-MS, limited proteolysis-MS, co-fractionation-MS, hydroxyl radical footprinting-MS, thermal proteome profiling, and numerous approaches for monitoring molecular interactions at large scale. Methods to determine structural properties of the native proteome will drive structural systems biology.
Topics: Animals; Humans; Mass Spectrometry; Protein Aggregates; Protein Folding; Proteome; Proteomics
PubMed: 31841731
DOI: 10.1016/j.sbi.2019.10.006 -
Nature Communications Aug 2022Enzymatic-based proximity labeling approaches based on activated esters or phenoxy radicals have been widely used for mapping subcellular proteome and protein...
Enzymatic-based proximity labeling approaches based on activated esters or phenoxy radicals have been widely used for mapping subcellular proteome and protein interactors in living cells. However, activated esters are poorly reactive which leads to a wide labeling radius and phenoxy radicals generated by peroxide treatment may disturb redox-sensitive pathways. Herein, we report a photoactivation-dependent proximity labeling (PDPL) method designed by genetically attaching photosensitizer protein miniSOG to a protein of interest. Triggered by blue light and tunned by irradiation time, singlet oxygen is generated, thereafter enabling spatiotemporally-resolved aniline probe labeling of histidine residues. We demonstrate its high-fidelity through mapping of organelle-specific proteomes. Side-by-side comparison of PDPL with TurboID reveals more specific and deeper proteomic coverage by PDPL. We further apply PDPL to the disease-related transcriptional coactivator BRD4 and E3 ligase Parkin, and discover previously unknown interactors. Through over-expression screening, two unreported substrates Ssu72 and SNW1 are identified for Parkin, whose degradation processes are mediated by the ubiquitination-proteosome pathway.
Topics: Esters; Nuclear Proteins; Proteome; Proteomics; Transcription Factors; Ubiquitin-Protein Ligases
PubMed: 35987950
DOI: 10.1038/s41467-022-32689-z -
Advances in Experimental Medicine and... 2021Proteome analysis of model and non-model plants is a genuine scientific field in expansion. Several technological advances have contributed to the implementation of...
Proteome analysis of model and non-model plants is a genuine scientific field in expansion. Several technological advances have contributed to the implementation of different proteomics approaches for qualitative and quantitative analysis of the dynamics of cellular responses at the protein level. The design of time-resolved experiments and the emergent use of multiplexed proteome analysis using chemical or isotopic and isobaric labeling strategies as well as label-free approaches are generating a vast amount of proteomics data that is going to be essential for analysis of protein posttranslational modifications and implementation of systems biology approaches. Through the target proteomics analysis, especially the ones that combine the untargeted methods, we should expect an improvement in the completeness of the identification of proteome and reveal nuances of regulatory cellular mechanisms related to plant development and responses to environmental stresses. Both genomic sequencing and proteomic advancements in the last decades coupled to integrative data analysis are enriching biological information that was once confined to model plants. Therewith, predictions of a changing environment places proteomics as an especially useful tool for crops performance.
Topics: Plants; Protein Processing, Post-Translational; Proteome; Proteomics; Systems Biology
PubMed: 35113395
DOI: 10.1007/978-3-030-80352-0_3 -
Microbiological Research Jan 2021Proteomic approaches are being used to elucidate a better discretion of interactions occurring between host, pathogen, and/or beneficial microorganisms at the molecular... (Review)
Review
Proteomic approaches are being used to elucidate a better discretion of interactions occurring between host, pathogen, and/or beneficial microorganisms at the molecular level. Application of proteomic techniques, unravel pathogenicity, stress-related, and antioxidant proteins expressed amid plant-microbe interactions and good information have been generated. It is being perceived that a fine regulation of protein expression takes place for effective pathogen recognition, induction of resistance, and maintenance of host integrity. However, our knowledge of molecular plant-microbe interactions is still incomplete and inconsequential. This review aims to provide insight into numerous ways used for proteomic investigation including peptide/protein identification, separation, and quantification during host defense response. Here, we highlight the current progress in proteomics of defense responses elicited by bacterial, fungal, and viral pathogens in plants along with which the proteome level changes induced by beneficial microorganisms are also discussed.
Topics: Bacteria; Fungi; Host Microbial Interactions; Plant Diseases; Plant Immunity; Plant Proteins; Plants; Proteome; Proteomics
PubMed: 33022544
DOI: 10.1016/j.micres.2020.126590 -
Methods in Molecular Biology (Clifton,... 2022Top-down proteomics methods have a distinct advantage over bottom-up methods in that they analyze intact proteins rather than digested peptides which can result in loss...
Top-down proteomics methods have a distinct advantage over bottom-up methods in that they analyze intact proteins rather than digested peptides which can result in loss of information regarding the intact protein. However, the analysis of intact proteins using top-down proteomics methods has been impeded by the low resolution of typical separation approaches applied in bottom-up proteomics studies. To increase the coverage of intact proteomes, orthogonal, two-dimensional separation techniques have been developed to improve the separation efficiency; in this chapter, we describe a two-dimensional HPLC separation technique that utilizes a high-pH mobile phase in the first dimension followed by a low-pH mobile phase in the second dimension. This two-dimensional pH-based HPLC approach demonstrates increased separation efficiency of intact proteins and increased proteome coverage when compared to one-dimensional HPLC in the analysis of larger and lower abundance proteoforms.
Topics: Chromatography, High Pressure Liquid; Peptides; Proteome; Proteomics; Tandem Mass Spectrometry
PubMed: 35657585
DOI: 10.1007/978-1-0716-2325-1_4 -
Molecular & Cellular Proteomics : MCP Sep 2023Data-independent acquisition (DIA) mass spectrometry-based proteomics generates reproducible proteome data. The complex processing of the DIA data has led to the...
Data-independent acquisition (DIA) mass spectrometry-based proteomics generates reproducible proteome data. The complex processing of the DIA data has led to the development of multiple data analysis tools. In this study, we assessed the performance of five tools (OpenSWATH, EncyclopeDIA, Skyline, DIA-NN, and Spectronaut) using six DIA datasets obtained from TripleTOF, Orbitrap, and TimsTOF Pro instruments. By comparing identification and quantification metrics and examining shared and unique cross-tool identifications, we evaluated both library-based and library-free approaches. Our findings indicate that library-free approaches outperformed library-based methods when the spectral library had limited comprehensiveness. However, our results also suggest that constructing a comprehensive library still offers benefits for most DIA analyses. This study provides comprehensive guidance for DIA data analysis tools, benefiting both experienced and novice users of DIA-mass spectrometry technology.
Topics: Mass Spectrometry; Proteomics; Proteome; Gene Library; Data Analysis
PubMed: 37481071
DOI: 10.1016/j.mcpro.2023.100623 -
Molecular & Cellular Proteomics : MCP May 2024We describe deep analysis of the human proteome in less than 1 h. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation,...
We describe deep analysis of the human proteome in less than 1 h. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation, chromatographic separations, and data analysis tools, and by using the new Orbitrap Astral mass spectrometer equipped with a quadrupole mass filter, a high-field Orbitrap mass analyzer, and an asymmetric track lossless (Astral) mass analyzer. The system offers high tandem mass spectrometry acquisition speed of 200 Hz and detects hundreds of peptide sequences per second within data-independent acquisition or data-dependent acquisition modes of operation. The fast-switching capabilities of the new quadrupole complement the sensitivity and fast ion scanning of the Astral analyzer to enable narrow-bin data-independent analysis methods. Over a 30-min active chromatographic method consuming a total analysis time of 56 min, the Q-Orbitrap-Astral hybrid MS collects an average of 4319 MS scans and 438,062 tandem mass spectrometry scans per run, producing 235,916 peptide sequences (1% false discovery rate). On average, each 30-min analysis achieved detection of 10,411 protein groups (1% false discovery rate). We conclude, with these results and alongside other recent reports, that the 1-h human proteome is within reach.
Topics: Humans; Proteome; Tandem Mass Spectrometry; Proteomics; Time Factors
PubMed: 38579929
DOI: 10.1016/j.mcpro.2024.100760 -
Methods in Molecular Biology (Clifton,... 2023This chapter focuses on upstream immunodepletion of high-abundance proteins from plasma samples and subsequent analysis by fluorescence two-dimensional difference gel...
This chapter focuses on upstream immunodepletion of high-abundance proteins from plasma samples and subsequent analysis by fluorescence two-dimensional difference gel electrophoresis (2D-DIGE). The abundances of proteins in biofluid proteomes, such as serum, plasma, saliva, and bronchoalveolar lavage fluid (BALF), can exceed ten orders of magnitude. This substantial dynamic range is problematic for the detection of medium and low-abundance proteins by 2D-DIGE analysis. To increase the detection, quantification, and identification of medium-low-abundance proteins, the targeted depletion of known abundant proteins with antibody columns has been successfully employed. From the literature, it is clear that the performance of abundant protein depletion with immunodepletion columns has been successful in broadening the coverage of the biofluid proteome and facilitating the identification of disease-specific biomarkers. The task for a successful biomarker strategy involves the combination of a reproducible and robust fractionation method, coupled with a highly accurate quantitative method, a task that is exemplified by combining both immunodepletion and 2D-DIGE together to discover significant proteins associated with the disease phenotype.
Topics: Blood Proteins; Proteomics; Two-Dimensional Difference Gel Electrophoresis; Proteome; Biomarkers; Electrophoresis, Gel, Two-Dimensional
PubMed: 36378451
DOI: 10.1007/978-1-0716-2831-7_25 -
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 -
Expert Review of Proteomics Jan 2021: Proteomic profiling plays an important role in the exploration of cancer from molecular mechanisms to clinical diagnosis and treatment. In recent years, the advent of... (Review)
Review
: Proteomic profiling plays an important role in the exploration of cancer from molecular mechanisms to clinical diagnosis and treatment. In recent years, the advent of new technologies has promoted oncoproteomics from the initial global style to a refined single-cell level.: Among them, the development of microfluidic devices, the improvement of liquid mass spectrometry in accuracy and trace sample handling processes, and the emergence of protein sequencing have contributed to the oncoproteomic analysis at the single-cell level.: The proteomic analysis at the global level and the single-cell level gives different perspectives while combining them can reveal more comprehensive oncoproteomics and help cancer research and treatment strategies.
Topics: Humans; Mass Spectrometry; Neoplasms; Proteome; Proteomics; Single-Cell Analysis
PubMed: 33571016
DOI: 10.1080/14789450.2021.1890036