Mass spectrometry in high-throughput proteomics: ready for the big time

Nilsson, Tommy; Mann, Matthias; Aebersold, Ruedi; Yates, John R.; Bairoch, Amos Marc; Bergeron, John J.M.

doi:10.1038/nmeth0910-681

Cited by 444 publications

(396 citation statements)

References 43 publications

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“…Comprehensive studies on the proteomes of cells, tissues, or organisms have been reported (e.g. Addona et al , 2009; Nilsson et al , 2010; Beck et al , 2011; Nagaraj et al , 2011; for review, see Bensimon et al , 2012; Kulak et al , 2014; Wilhelm et al , 2014; Hein et al , 2015; Richards et al , 2015), but accurate quantitative information on proteins expressed at low levels remains scarce. As a consequence, published estimates for the abundance of specific proteins sometimes vary over several orders of magnitude.…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

et al. 2016

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Centrioles are essential for the formation of centrosomes and cilia. While numerical and/or structural centrosomes aberrations are implicated in cancer, mutations in centriolar and centrosomal proteins are genetically linked to ciliopathies, microcephaly, and dwarfism. The evolutionarily conserved mechanisms underlying centrosome biogenesis are centered on a set of key proteins, including Plk4, Sas‐6, and STIL, whose exact levels are critical to ensure accurate reproduction of centrioles during cell cycle progression. However, neither the intracellular levels of centrosomal proteins nor their stoichiometry within centrosomes is presently known. Here, we have used two complementary approaches, targeted proteomics and EGFP‐tagging of centrosomal proteins at endogenous loci, to measure protein abundance in cultured human cells and purified centrosomes. Our results provide a first assessment of the absolute and relative amounts of major components of the human centrosome. Specifically, they predict that human centriolar cartwheels comprise up to 16 stacked hubs and 1 molecule of STIL for every dimer of Sas‐6. This type of quantitative information will help guide future studies of the molecular basis of centrosome assembly and function.

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Section: Introductionmentioning

confidence: 99%

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

et al. 2016

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“…25 Recently, some researches based on microarray and label-free quantification method have been found to be valuable for the understanding of miRNAs and their target interactions; even though microarray technology suffers from limitations in sensitivity and specificity, 26 and also the sensitivity of most proteomic analysis based on label-free quantification method by spectrometers is modulated by the nature of the processed samples. 27 In this research, we improve the sensitivity of miRNA and protein identification by deep sequencing and iTRAQ quantitative proteomics respectively. A novelty of our research is that we identified more than one hundred potential miRNA-target pairs from computationally predicted targets, considering a negative relationship of the expression patterns between miRNA and their target protein is the most important parameter for accessing their interactions.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential microRNA–target pairs associated with osteopetrosis by deep sequencing, iTRAQ proteomics and bioinformatics

Zhang

Dai

et al. 2013

Eur J Hum Genet

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MicroRNAs aberrantly express in many human diseases including some metabolic bone disorders. They have been found to be associated with osteoclast differentiation and function, which makes them attractive candidates for the therapy of bone. However, the potential clinical application of microRNAs in therapeutics rests heavily upon our in-depth understanding of microRNAs and their targets. To identify potential microRNA-target pairs associated with osteopetrosis, we performed a system approach including deep sequencing, iTRAQ quantitative proteomics, and bioinformatics in the peripheral blood mononuclear cells (PBMCs) taken from patients with osteopetrosis and health donors. Notably, 123 differently expressed microRNAs, 173 differently expressed proteins, and 117 computationally predicted microRNA-target pairs with reciprocally expressed level in PBMCs were found in the two sample groups. Functional annotation identified that the microRNA-target pairs were involved in cell growth, differentiation, cellular signaling network, and the network highlighted the microRNA-target pair of has-miR-320a and ADP ribosylation factor 1 (Arf1) potentially associated with CLCN7 mutations in osteopetrosis. The pair of has-miR-320a and Arf1 was further verified by real-time PCR, western blot, and the interaction between has-miR-320a and its targeted sequence on the Arf1 mRNAs was confirmed by luciferase assay. Collectively, the present study established a new system approach for the investigation of microRNAs, and the microRNA-target pairs, particular has-miR-320a and Arf1, may have important roles in osteopetrosis.

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“…Although proteins can be reliably identified by the well known discovery proteomics methods at high throughput 11 and their 3D structures can be determined experimentally or computationally 12, there remain numerous unsolved problems relating to their structure and function in the context of network biology. Measuring proteins poses technical challenges, particularly in higher eukaryotes which are made‐up of trillions of cells that are categorized, somewhat arbitrarily, into more than 400 different cell types 13.…”

Section: Introductionmentioning

confidence: 99%

Applications of targeted proteomics in systems biology and translational medicine

et al. 2015

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Biological systems are composed of numerous components of which proteins are of particularly high functional significance. Network models are useful abstractions for studying these components in context. Network representations display molecules as nodes and their interactions as edges. Because they are difficult to directly measure, functional edges are frequently inferred from suitably structured datasets consisting of the accurate and consistent quantification of network nodes under a multitude of perturbed conditions. For the precise quantification of a finite list of proteins across a wide range of samples, targeted proteomics exemplified by selected/multiple reaction monitoring (SRM, MRM) mass spectrometry has proven useful and has been applied to a variety of questions in systems biology and clinical studies. Here, we survey the literature of studies using SRM‐MS in systems biology and clinical proteomics. Systems biology studies frequently examine fundamental questions in network biology, whereas clinical studies frequently focus on biomarker discovery and validation in a variety of diseases including cardiovascular disease and cancer. Targeted proteomics promises to advance our understanding of biological networks and the phenotypic significance of specific network states and to advance biomarkers into clinical use.

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Mass spectrometry in high-throughput proteomics: ready for the big time

Abstract: Mass spectrometry has evolved and matured to a level where it is able to assess the complexity of the human proteome. We discuss some of the expected challenges ahead and promising strategies for success.

Cited by 444 publications

References 43 publications

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

Identification of potential microRNA–target pairs associated with osteopetrosis by deep sequencing, iTRAQ proteomics and bioinformatics

Applications of targeted proteomics in systems biology and translational medicine

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