Author
Jacek R. Wiśniewski
Other affiliations: Analytical Services, Saint Louis University, University of Wrocław ...read more
Bio: Jacek R. Wiśniewski is an academic researcher from Max Planck Society. The author has contributed to research in topics: Proteome & Proteomics. The author has an hindex of 38, co-authored 108 publications receiving 11761 citations. Previous affiliations of Jacek R. Wiśniewski include Analytical Services & Saint Louis University.
Topics: Proteome, Proteomics, Membrane protein, High-mobility group, Hmg protein
Papers published on a yearly basis
Papers
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TL;DR: A method is described, filter-aided sample preparation (FASP), which combines the advantages of in-gel and in-solution digestion for mass spectrometry–based proteomics and allows single-run analyses of organelles and an unprecedented depth of proteome coverage.
Abstract: A method, filter-aided sample preparation (FASP) combines the advantages of in-gel and in-solution digestion for mass spectrometry–based proteomics, allowing deeper proteomic coverage in a shorter analysis time, using small sample amounts. We describe a method, filter-aided sample preparation (FASP), which combines the advantages of in-gel and in-solution digestion for mass spectrometry–based proteomics. We completely solubilized the proteome in sodium dodecyl sulfate, which we then exchanged by urea on a standard filtration device. Peptides eluted after digestion on the filter were pure, allowing single-run analyses of organelles and an unprecedented depth of proteome coverage.
6,096 citations
TL;DR: A stringent experimental and computational workflow, capable of mapping more than 50,000 distinct phosphorylated peptides in a single human cancer cell line, is developed, suggesting that P-Tyr should be considered a functionally separate PTM of eukaryotic proteomes.
809 citations
TL;DR: 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 reveals that the sites always orient toward the extracellular space or toward the lumen of ER, Golgi, lysosome, or peroxisome.
800 citations
TL;DR: The combined method provides a streamlined protocol for rapid and sensitive membrane proteome mapping and provides a generic protocol for combining FASP with StageTip-based ion exchange fractionation, which is generally applicable to proteome analysis.
Abstract: Membrane proteomics is challenging because the desirable strong detergents are incompatible with downstream analysis. Recently, we demonstrated efficient removal of SDS by the filter aided sample preparation method (FASP). Here we combine FASP with our previously described small-scale membrane enrichment protocol. Analysis of a single mouse hippocampus enables identification of more than 1000 membrane proteins in a single LC-MS/MS run without protein or peptide prefractionation. To extend proteome coverage, we developed a simple anion exchange fractionation method in a StageTip format. When separating peptides into six fractions, a duplicate analysis resulted in identification of 4206 proteins of which 64% were membrane proteins. This data set covers 83% of glutamate and GABA receptor subunits identified in hippocampus in the Allen Brain Atlas and adds further isoforms. The combined method provides a streamlined protocol for rapid and sensitive membrane proteome mapping. We also provide a generic protocol...
523 citations
TL;DR: This work shows that the MS signal of histones can be used as a “proteomic ruler” because it is proportional to the amount of DNA in the sample, which in turn depends on the number of cells, and adds an absolute scale to the MS readout and allows estimation of the copy numbers of individual proteins per cell.
495 citations
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TL;DR: The Central Brain Tumor Registry of the United States (CBTRUS), in collaboration with the Centers for Disease Control and Prevention and National Cancer Institute, is the largest population-based registry focused exclusively on primary brain and other central nervous system (CNS) tumors in the US.
Abstract: The Central Brain Tumor Registry of the United States (CBTRUS), in collaboration with the Centers for Disease Control (CDC) and National Cancer Institute (NCI), is the largest population-based registry focused exclusively on primary brain and other central nervous system (CNS) tumors in the United States (US) and represents the entire US population. This report contains the most up-to-date population-based data on primary brain tumors (malignant and non-malignant) and supersedes all previous CBTRUS reports in terms of completeness and accuracy. All rates (incidence and mortality) are age-adjusted using the 2000 US standard population and presented per 100,000 population. The average annual age-adjusted incidence rate (AAAIR) of all malignant and non-malignant brain and other CNS tumors was 23.79 (Malignant AAAIR=7.08, non-Malignant AAAIR=16.71). This rate was higher in females compared to males (26.31 versus 21.09), Blacks compared to Whites (23.88 versus 23.83), and non-Hispanics compared to Hispanics (24.23 versus 21.48). The most commonly occurring malignant brain and other CNS tumor was glioblastoma (14.5% of all tumors), and the most common non-malignant tumor was meningioma (38.3% of all tumors). Glioblastoma was more common in males, and meningioma was more common in females. In children and adolescents (age 0-19 years), the incidence rate of all primary brain and other CNS tumors was 6.14. An estimated 83,830 new cases of malignant and non-malignant brain and other CNS tumors are expected to be diagnosed in the US in 2020 (24,970 malignant and 58,860 non-malignant). There were 81,246 deaths attributed to malignant brain and other CNS tumors between 2013 and 2017. This represents an average annual mortality rate of 4.42. The 5-year relative survival rate following diagnosis of a malignant brain and other CNS tumor was 23.5% and for a non-malignant brain and other CNS tumor was 82.4%.
9,802 citations
TL;DR: A method is described, filter-aided sample preparation (FASP), which combines the advantages of in-gel and in-solution digestion for mass spectrometry–based proteomics and allows single-run analyses of organelles and an unprecedented depth of proteome coverage.
Abstract: A method, filter-aided sample preparation (FASP) combines the advantages of in-gel and in-solution digestion for mass spectrometry–based proteomics, allowing deeper proteomic coverage in a shorter analysis time, using small sample amounts. We describe a method, filter-aided sample preparation (FASP), which combines the advantages of in-gel and in-solution digestion for mass spectrometry–based proteomics. We completely solubilized the proteome in sodium dodecyl sulfate, which we then exchanged by urea on a standard filtration device. Peptides eluted after digestion on the filter were pure, allowing single-run analyses of organelles and an unprecedented depth of proteome coverage.
6,096 citations
TL;DR: The Perseus software platform was developed to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data and it is anticipated that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
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.
5,165 citations
TL;DR: A new intensity determination and normalization procedure called MaxLFQ is developed that is fully compatible with any peptide or protein separation prior to LC-MS analysis, which accurately detects the mixing ratio over the entire protein expression range, with greater precision for abundant proteins.
3,732 citations
TL;DR: An updated protocol covering the most important basic computational workflows for mass-spectrometry-based proteomics data analysis, including those designed for quantitative label-free proteomics, MS1-level labeling and isobaric labeling techniques is presented.
Abstract: MaxQuant is one of the most frequently used platforms for mass-spectrometry (MS)-based proteomics data analysis Since its first release in 2008, it has grown substantially in functionality and can be used in conjunction with more MS platforms Here we present an updated protocol covering the most important basic computational workflows, including those designed for quantitative label-free proteomics, MS1-level labeling and isobaric labeling techniques This protocol presents a complete description of the parameters used in MaxQuant, as well as of the configuration options of its integrated search engine, Andromeda This protocol update describes an adaptation of an existing protocol that substantially modifies the technique Important concepts of shotgun proteomics and their implementation in MaxQuant are briefly reviewed, including different quantification strategies and the control of false-discovery rates (FDRs), as well as the analysis of post-translational modifications (PTMs) The MaxQuant output tables, which contain information about quantification of proteins and PTMs, are explained in detail Furthermore, we provide a short version of the workflow that is applicable to data sets with simple and standard experimental designs The MaxQuant algorithms are efficiently parallelized on multiple processors and scale well from desktop computers to servers with many cores The software is written in C# and is freely available at http://wwwmaxquantorg
2,811 citations