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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 -
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 -
Molekuliarnaia Biologiia 2018A critical analysis of proteomes provides a basis for understanding the operation of complex biochemical systems. A personalized approach to therapy takes into account... (Review)
Review
A critical analysis of proteomes provides a basis for understanding the operation of complex biochemical systems. A personalized approach to therapy takes into account biological uniqueness of each patient at genome, transcriptome, and proteome levels, and is a priority area in molecular medicine. The identification of proteoforms, which have dramatic impact on the phenotype of a disease, is a fundamental task of personal molecular profiling. Considerable progress of proteomic approaches presented new avenues for accurate, specific, and high-performance protein analysis. Thus, the identification of new efficient bio-markers can be expected based on studies of aberrant proteoforms associated with various diseases.
Topics: Animals; Humans; Molecular Medicine; Precision Medicine; Proteome; Proteomics
PubMed: 29989573
DOI: 10.7868/S0026898418030047 -
Electrophoresis Dec 2012While neurovascular diseases such as ischemic and hemorrhagic stroke are the leading causes of disability in the world, the repertoire of therapeutic interventions has... (Review)
Review
While neurovascular diseases such as ischemic and hemorrhagic stroke are the leading causes of disability in the world, the repertoire of therapeutic interventions has remained remarkably limited. There is a dire need to develop new diagnostic, prognostic, and therapeutic options. The study of proteomics is particularly enticing for cerebrovascular diseases such as stroke, which most likely involve multiple gene interactions resulting in a wide range of clinical phenotypes. Currently, rapidly progressing neuroproteomic techniques have been employed in clinical and translational research to help identify biologically relevant pathways, to understand cerebrovascular pathophysiology, and to develop novel therapeutics and diagnostics. Future integration of proteomic with genomic, transcriptomic, and metabolomic studies will add new perspectives to better understand the complexities of neurovascular injury. Here, we review cerebrovascular proteomics research in both preclinical (animal, cell culture) and clinical (blood, urine, cerebrospinal fluid, microdialyates, tissue) studies. We will also discuss the rewards, challenges, and future directions for the application of proteomics technology to the study of various disease phenotypes. To capture the dynamic range of cerebrovascular injury and repair with a translational targeted and discovery approach, we emphasize the importance of complementing innovative proteomic technology with existing molecular biology models in preclinical studies, and the need to advance pharmacoproteomics to directly probe clinical physiology and gauge therapeutic efficacy at the bedside.
Topics: Animals; Biomarkers; Cerebrovascular Disorders; Humans; Mass Spectrometry; Nerve Tissue Proteins; Proteome; Proteomics
PubMed: 23161401
DOI: 10.1002/elps.201200481 -
Journal of the American Society For... Sep 2023Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases...
Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers. However, existing procedures are slow and laborious, requiring 2 h of mass spectrometry time per single muscle fiber; 50 fibers would take approximately 4 days to analyze. Thus, to capture the high variability in fibers both within and between individuals requires advancements in high throughput single muscle fiber proteomics. Here we use a single cell proteomics method to enable quantification of single muscle fiber proteomes in 15 min total instrument time. As proof of concept, we present data from 53 isolated skeletal muscle fibers obtained from two healthy individuals analyzed in 13.25 h. Adapting single cell data analysis techniques to integrate the data, we can reliably separate type 1 and 2A fibers. Ninety-four proteins were statistically different between clusters indicating alteration of proteins involved in fatty acid oxidation, oxidative phosphorylation, and muscle structure and contractile function. Our results indicate that this method is significantly faster than prior single fiber methods in both data collection and sample preparation while maintaining sufficient proteome depth. We anticipate this assay will enable future studies of single muscle fibers across hundreds of individuals, which has not been possible previously due to limitations in throughput.
Topics: Humans; Proteome; Proteomics; Workflow; Muscle Fibers, Skeletal; Muscle, Skeletal
PubMed: 37463334
DOI: 10.1021/jasms.3c00072 -
Science China. Life Sciences Jun 2011Viruses replicate and proliferate in host cells while continuously adjusting to and modulating the host environment. They encode a wide spectrum of multifunctional... (Review)
Review
Viruses replicate and proliferate in host cells while continuously adjusting to and modulating the host environment. They encode a wide spectrum of multifunctional proteins, which interplay with and modify proteins in host cells. Viral genomes were chronologically the first to be sequenced. However, the corresponding viral proteomes, the alterations of host proteomes upon viral infection, and the dynamic nature of proteins, such as post-translational modifications, enzymatic cleavage, and activation or destruction by proteolysis, remain largely unknown. Emerging high-throughput techniques, in particular quantitative or semi-quantitative mass spectrometry-based proteomics analysis of viral and cellular proteomes, have been applied to define viruses and their interactions with their hosts. Here, we review the major areas of viral proteomics, including virion proteomics, structural proteomics, viral protein interactomics, and changes to the host cell proteome upon viral infection.
Topics: Animals; Electrophoresis, Gel, Two-Dimensional; Host-Pathogen Interactions; Humans; Isotope Labeling; Mass Spectrometry; Proteome; Proteomics; RNA Interference; RNA Viruses; Viral Proteins; Virion; Virus Diseases; Viruses
PubMed: 21706410
DOI: 10.1007/s11427-011-4177-7 -
Molecular & Cellular Proteomics : MCP Jul 2023Recent advances in mass spectrometry-based proteomics enable the acquisition of increasingly large datasets within relatively short times, which exposes bottlenecks in...
Recent advances in mass spectrometry-based proteomics enable the acquisition of increasingly large datasets within relatively short times, which exposes bottlenecks in the bioinformatics pipeline. Although peptide identification is already scalable, most label-free quantification (LFQ) algorithms scale quadratic or cubic with the sample numbers, which may even preclude the analysis of large-scale data. Here we introduce directLFQ, a ratio-based approach for sample normalization and the calculation of protein intensities. It estimates quantities via aligning samples and ion traces by shifting them on top of each other in logarithmic space. Importantly, directLFQ scales linearly with the number of samples, allowing analyses of large studies to finish in minutes instead of days or months. We quantify 10,000 proteomes in 10 min and 100,000 proteomes in less than 2 h, a 1000-fold faster than some implementations of the popular LFQ algorithm MaxLFQ. In-depth characterization of directLFQ reveals excellent normalization properties and benchmark results, comparing favorably to MaxLFQ for both data-dependent acquisition and data-independent acquisition. In addition, directLFQ provides normalized peptide intensity estimates for peptide-level comparisons. It is an important part of an overall quantitative proteomic pipeline that also needs to include high sensitive statistical analysis leading to proteoform resolution. Available as an open-source Python package and a graphical user interface with a one-click installer, it can be used in the AlphaPept ecosystem as well as downstream of most common computational proteomics pipelines.
Topics: Proteome; Proteomics; Ecosystem; Peptides; Mass Spectrometry; Software
PubMed: 37225017
DOI: 10.1016/j.mcpro.2023.100581 -
Free Radical Research 2015Lipid peroxidation is responsible for the generation of chemically reactive, diffusible lipid-derived electrophiles (LDEs) that covalently modify cellular protein... (Review)
Review
Lipid peroxidation is responsible for the generation of chemically reactive, diffusible lipid-derived electrophiles (LDEs) that covalently modify cellular protein targets. These protein modifications modulate protein activity and macromolecular interactions and induce adaptive and toxic cell signaling. Protein modifications induced by LDEs can be identified and quantified by affinity enrichment and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based techniques. Tagged LDE analog probes with different electrophilic groups can be covalently captured by click chemistry for LC-MS/MS analyses, thereby enabling in-depth studies of proteome damage at the protein and peptide sequence levels. Conversely, click-reactive, thiol-directed probes can be used to evaluate thiol damage caused by LDE by difference. These analytical approaches permit systematic study of the dynamics of protein damage caused by LDE and mechanisms by which oxidative stress contribute to toxicity and diseases.
Topics: Chromatography, Liquid; Humans; Lipid Peroxidation; Protein Processing, Post-Translational; Proteome; Proteomics; Tandem Mass Spectrometry
PubMed: 25819163
DOI: 10.3109/10715762.2015.1019348 -
International Journal of Molecular... Nov 2015Maize (Zea mays L.) is a host to numerous pathogenic species that impose serious diseases to its ear and foliage, negatively affecting the yield and the quality of the... (Review)
Review
Maize (Zea mays L.) is a host to numerous pathogenic species that impose serious diseases to its ear and foliage, negatively affecting the yield and the quality of the maize crop. A considerable amount of research has been carried out to elucidate mechanisms of maize-pathogen interactions with a major goal to identify defense-associated proteins. In this review, we summarize interactions of maize with its agriculturally important pathogens that were assessed at the proteome level. Employing differential analyses, such as the comparison of pathogen-resistant and susceptible maize varieties, as well as changes in maize proteomes after pathogen challenge, numerous proteins were identified as possible candidates in maize resistance. We describe findings of various research groups that used mainly mass spectrometry-based, high through-put proteomic tools to investigate maize interactions with fungal pathogens Aspergillus flavus, Fusarium spp., and Curvularia lunata, and viral agents Rice Black-streaked Dwarf Virus and Sugarcane Mosaic Virus.
Topics: Disease Resistance; Host-Pathogen Interactions; Plant Diseases; Plant Proteins; Proteome; Proteomics; Zea mays
PubMed: 26633370
DOI: 10.3390/ijms161226106 -
Journal of Proteomics May 2019The complex interactions among proteins and of proteins with small molecular weight protein ligands are overturned every time one of the components of the network is... (Review)
Review
The complex interactions among proteins and of proteins with small molecular weight protein ligands are overturned every time one of the components of the network is missing. For study purposes, animal models lacking one protein are obtained by experimental manipulation of the genome: in the knocking out approach, a gene is altered through the insertion of an artificial DNA sequence, which halts the transcription-translation sequence of events. In this review we have compiled the research papers that analyze the effects of knocking out individual genes on the proteomes of various tissues/organs throughout the body. We have gathered and organized all the available evidence and then compared the proteomic data in order to stress the context-specificity of the outcome every time two or more organs were investigated in the same KO mice. Finally, in a symmetrical approach to the above, we surveyed whether there is any obvious overlap among the effects of different KO on the same organ, marking affection of general pathways or lacking specificity of the gene targeting. Specific attention was put on the possible involvement of cellular stress markers.
Topics: Animals; Gene Silencing; Mice; Mice, Knockout; Models, Animal; Proteome; Proteomics
PubMed: 30876943
DOI: 10.1016/j.jprot.2019.03.008