Skeletal muscle is a key tissue in human aging, which affects different muscle fiber types unequally. We developed a highly sensitive single muscle fiber proteomics workflow to study human aging and ...show that the senescence of slow and fast muscle fibers is characterized by diverging metabolic and protein quality control adaptations. Whereas mitochondrial content declines with aging in both fiber types, glycolysis and glycogen metabolism are upregulated in slow but downregulated in fast muscle fibers. Aging mitochondria decrease expression of the redox enzyme monoamine oxidase A. Slow fibers upregulate a subset of actin and myosin chaperones, whereas an opposite change happens in fast fibers. These changes in metabolism and sarcomere quality control may be related to the ability of slow, but not fast, muscle fibers to maintain their mass during aging. We conclude that single muscle fiber analysis by proteomics can elucidate pathophysiology in a sub-type-specific manner.
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•Single-fiber proteomic analysis of human muscle aging•Oxidative phosphorylation decreases similarly in slow and fast fibers•Enzymes of carbohydrate metabolism increase in slow and decrease in fast aging fibers•Proteomics elucidates why fast fibers age more rapidly than slow ones
Murgia et al. use mass-spectrometry-based proteomics to compare single muscle fibers of younger and older subjects, which revealed that glycolysis and glycogen metabolism decrease strongly in aging fast, but not slow, muscle fibers. The proteomic changes revealed here help to explain differential loss of muscle performance in aging.
Circular RNAs (circRNAs) are broadly expressed in eukaryotic cells, but their molecular mechanism in human disease remains obscure. Here we show that circular antisense non-coding RNA in the INK4 ...locus (circANRIL), which is transcribed at a locus of atherosclerotic cardiovascular disease on chromosome 9p21, confers atheroprotection by controlling ribosomal RNA (rRNA) maturation and modulating pathways of atherogenesis. CircANRIL binds to pescadillo homologue 1 (PES1), an essential 60S-preribosomal assembly factor, thereby impairing exonuclease-mediated pre-rRNA processing and ribosome biogenesis in vascular smooth muscle cells and macrophages. As a consequence, circANRIL induces nucleolar stress and p53 activation, resulting in the induction of apoptosis and inhibition of proliferation, which are key cell functions in atherosclerosis. Collectively, these findings identify circANRIL as a prototype of a circRNA regulating ribosome biogenesis and conferring atheroprotection, thereby showing that circularization of long non-coding RNAs may alter RNA function and protect from human disease.
Extra chromosome copies markedly alter the physiology of eukaryotic cells, but the underlying reasons are not well understood. We created human trisomic and tetrasomic cell lines and determined the ...quantitative changes in their transcriptome and proteome in comparison with their diploid counterparts. We found that whereas transcription levels reflect the chromosome copy number changes, the abundance of some proteins, such as subunits of protein complexes and protein kinases, is reduced toward diploid levels. Furthermore, using the quantitative data we investigated the changes of cellular pathways in response to aneuploidy. This analysis revealed specific and uniform alterations in pathway regulation in cells with extra chromosomes. For example, the DNA and RNA metabolism pathways were downregulated, whereas several pathways such as energy metabolism, membrane metabolism and lysosomal pathways were upregulated. In particular, we found that the p62‐dependent selective autophagy is activated in the human trisomic and tetrasomic cells. Our data present the first broad proteomic analysis of human cells with abnormal karyotypes and suggest a uniform cellular response to the presence of an extra chromosome.
Genomic, transcriptomic and proteomic profiles of human aneuploid cells reveal that mRNA levels increase with gene copy number, but protein levels are partially compensated. Aneuploid cells also exhibit common alterations in several pathways, including an activation of autophagy.
Synopsis
Genomic, transcriptomic and proteomic profiles of human aneuploid cells reveal that mRNA levels increase with gene copy number, but protein levels are partially compensated. Aneuploid cells also exhibit common alterations in several pathways, including an activation of autophagy.
Comparative genomics, transcriptomics and proteomics of model human aneuploid cell lines reveal that whereas the mRNA levels increase proportionally to the chromosome copy numbers, the abundance of some proteins (e.g., subunits of complexes) is decreased to normal levels.
The pattern of up‐ and downregulated pathways was similar in all analyzed aneuploids, indicating that it might be possible to use aneuploidy as a cancer treatment target regardless of the exact chromosome composition of cancer cells.
Autophagy, in particular p62‐dependent selective autophagy, is activated in aneuploid human cell lines.
A comprehensive characterization of the lipidome from limited starting material remains very challenging. Here we report a high-sensitivity lipidomics workflow based on nanoflow liquid chromatography ...and trapped ion mobility spectrometry (TIMS). Taking advantage of parallel accumulation-serial fragmentation (PASEF), we fragment on average 15 precursors in each of 100 ms TIMS scans, while maintaining the full mobility resolution of co-eluting isomers. The acquisition speed of over 100 Hz allows us to obtain MS/MS spectra of the vast majority of isotope patterns. Analyzing 1 µL of human plasma, PASEF increases the number of identified lipids more than three times over standard TIMS-MS/MS, achieving attomole sensitivity. Building on high intra- and inter-laboratory precision and accuracy of TIMS collisional cross sections (CCS), we compile 1856 lipid CCS values from plasma, liver and cancer cells. Our study establishes PASEF in lipid analysis and paves the way for sensitive, ion mobility-enhanced lipidomics in four dimensions.
Hen's egg white has been the subject of intensive chemical, biochemical and food technological research for many decades, because of its importance in human nutrition, its importance as a source of ...easily accessible model proteins, and its potential use in biotechnological processes. Recently the arsenal of tools used to study the protein components of egg white has been complemented by mass spectrometry-based proteomic technologies. Application of these fast and sensitive methods has already enabled the identification of a large number of new egg white proteins. Recent technological advances may be expected to further expand the egg white protein inventory.
Using a dual pressure linear ion trap Orbitrap instrument, the LTQ Orbitrap Velos, in conjunction with data analysis in the MaxQuant software package, we identified 158 proteins in chicken egg white with two or more sequence unique peptides. This group of proteins identified with very high confidence included 79 proteins identified in egg white for the first time. In addition, 44 proteins were identified tentatively.
Our results, apart from identifying many new egg white components, indicate that current mass spectrometry technology is sufficiently advanced to permit direct identification of minor components of proteomes dominated by a few major proteins without resorting to indirect techniques, such as chromatographic depletion or peptide library binding, which change the composition of the proteome.
Single‐cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing. However, proteins are the main drivers of cellular function and in‐depth ...characterization of individual cells by mass spectrometry (MS)‐based proteomics would thus be highly valuable and complementary. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow‐rate chromatography, and a novel trapped ion mobility mass spectrometer, resulting in a more than 10‐fold improved sensitivity. We precisely and robustly quantify proteomes and their changes in single, FACS‐isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single‐cell proteomes to transcriptome data revealed a stable‐core proteome despite perturbation, while the transcriptome appears stochastic. Our technology can readily be applied to ultra‐high sensitivity analyses of tissue material, posttranslational modifications, and small molecule studies from small cell counts to gain unprecedented insights into cellular heterogeneity in health and disease.
Synopsis
A new ultra‐high sensitivity LC‐MS workflow increases sensitivity by up to two orders of magnitude and enables true single‐cell proteome analysis. In‐depth comparison indicates that the single‐cell transcriptome is stochastic while the single‐cell proteome is complete and stable.
A highly optimized data independent acquisition powered single‐cell proteomics workflow including sub‐µl sample preparation, very low flow chromatography and trapped ion mobility mass spectrometry (diaPASEF) is presented.
Single‐cell proteome analysis is performed by injecting cells one‐by‐one across the cell cycle into the LC‐MS and correctly identifies cell states.
Single‐cell proteome information is highly complementary to single‐cell transcriptome information.
At the single‐cell level the proteome is quantitatively and qualitatively stable, while the transcriptome is stochastic.
A new ultra‐high sensitivity LC‐MS workflow increases sensitivity by up to two orders of magnitude and enables true single‐cell proteome analysis. In‐depth comparison indicates that the single‐cell transcriptome is stochastic while the single‐cell proteome is complete and stable.
The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected ...proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using quantitative proteomics, we detect specific interactions, estimate interaction stoichiometries, and measure cellular abundances of interacting proteins. These three quantitative dimensions reveal that the protein network is dominated by weak, substoichiometric interactions that play a pivotal role in defining network topology. The minority of stable complexes can be identified by their unique stoichiometry signature. This study provides a rich interaction dataset connecting thousands of proteins and introduces a framework for quantitative network analysis.
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•Human interactome dataset connecting 5,400 proteins with 28,500 interactions•Three quantitative dimensions measure specificities, stoichiometries, and abundances•Stable complexes are rare but stand out by a signature of balanced stoichiometries•Weak interactions dominate the network and have critical topological properties
Weak interactions shape the cellular protein interaction network as determined from proteomic measures of cellular interaction specificities, the strength of those interactions, and the cellular copy numbers of the proteins involved.
High-resolution mass spectrometry (MS)-based proteomics has progressed tremendously over the years. For model organisms like yeast, we can now quantify complete proteomes in just a few hours. ...Developments discussed in this Perspective will soon enable complete proteome analysis of mammalian cells, as well, with profound impact on biology and biomedicine.
N-linked glycosylation is a biologically important protein modification, but only a small fraction of modification sites have been mapped. We developed a “filter aided sample preparation” ...(FASP)-based method in which glycopeptides are enriched by binding to lectins on the top of a filter and mapped 6367 N-glycosylation sites on 2352 proteins in four mouse tissues and blood plasma using high-accuracy mass spectrometry. We found 74% of known mouse N-glycosites and discovered an additional 5753 sites on a diverse range of proteins. Sites almost always have the N-!P-S|T-!P (where !P is not proline) and rarely the N-X-C motif or nonconsensus sequences. Combining the FASP approach with analysis of subcellular glycosite localization reveals that the sites always orient toward the extracellular space or toward the lumen of ER, Golgi, lysosome, or peroxisome. The N-glycoproteome contains a plethora of modification sites on factors important in development, organ-specific functions, and disease.
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► Mass spectrometry mapped over 6000 sites of mammalian protein N-glycosylation ► There is no evidence for nuclear, cytosolic, or mitochondrial N-glycosylation ► More than 99% of the sites match two different N-glycosylation consensus sequences' Quantitative proteomic studies now enable comparative analysis of N-glycoproteomes
Despite the availabilty of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance ...measurements. Here, we introduce Deep Visual Proteomics (DVP), which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated single-cell or single-nucleus laser microdissection and ultra-high-sensitivity mass spectrometry. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. By individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and uncharacterized proteins. In an archived primary melanoma tissue, DVP identified spatially resolved proteome changes as normal melanocytes transition to fully invasive melanoma, revealing pathways that change in a spatial manner as cancer progresses, such as mRNA splicing dysregulation in metastatic vertical growth that coincides with reduced interferon signaling and antigen presentation. The ability of DVP to retain precise spatial proteomic information in the tissue context has implications for the molecular profiling of clinical samples.
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