Michiel Vermeulen

Bio: Michiel Vermeulen is an academic researcher from Radboud University Nijmegen. The author has contributed to research in topics: Chromatin & Histone H3. The author has an hindex of 54, co-authored 175 publications receiving 12430 citations. Previous affiliations of Michiel Vermeulen include Utrecht University & University Medical Center Utrecht.

Quantitative Phosphoproteomics Reveals Widespread Full Phosphorylation Site Occupancy During Mitosis

Abstract: Eukaryotic cells replicate by a complex series of evolutionarily conserved events that are tightly regulated at defined stages of the cell division cycle. Progression through this cycle involves a large number of dedicated protein complexes and signaling pathways, and deregulation of this process is implicated in tumorigenesis. We applied high-resolution mass spectrometry-based proteomics to investigate the proteome and phosphoproteome of the human cell cycle on a global scale and quantified 6027 proteins and 20,443 unique phosphorylation sites and their dynamics. Co-regulated proteins and phosphorylation sites were grouped according to their cell cycle kinetics and compared to publicly available messenger RNA microarray data. Most detected phosphorylation sites and more than 20% of all quantified proteins showed substantial regulation, mainly in mitotic cells. Kinase-motif analysis revealed global activation during S phase of the DNA damage response network, which was mediated by phosphorylation by ATM or ATR or DNA-dependent protein kinases. We determined site-specific stoichiometry of more than 5000 sites and found that most of the up-regulated sites phosphorylated by cyclin-dependent kinase 1 (CDK1) or CDK2 were almost fully phosphorylated in mitotic cells. In particular, nuclear proteins and proteins involved in regulating metabolic processes have high phosphorylation site occupancy in mitosis. This suggests that these proteins may be inactivated by phosphorylation in mitotic cells.

The Perseus computational platform for comprehensive analysis of (prote)omics data.

Abstract: A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

Andromeda: a peptide search engine integrated into the MaxQuant environment

Abstract: A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spect...

Regulation of chromatin by histone modifications

Abstract: Chromatin is not an inert structure, but rather an instructive DNA scaffold that can respond to external cues to regulate the many uses of DNA. A principle component of chromatin that plays a key role in this regulation is the modification of histones. There is an ever-growing list of these modifications and the complexity of their action is only just beginning to be understood. However, it is clear that histone modifications play fundamental roles in most biological processes that are involved in the manipulation and expression of DNA. Here, we describe the known histone modifications, define where they are found genomically and discuss some of their functional consequences, concentrating mostly on transcription where the majority of characterisation has taken place.

Integrative analysis of 111 reference human epigenomes

Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.