Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.

MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

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.

http://wolfson.huji.ac.il/purification/PDF/Literature/Wisniewski2009.pdf

Universal sample preparation method for proteome analysis

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.

/pdf/the-perseus-computational-platform-for-comprehensive-5a4p3g7pp4.pdf

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

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...

https://pubs.acs.org/doi/pdfplus/10.1021/pr101065j?src=recsys

Andromeda: a peptide search engine integrated into the MaxQuant environment

Lysine acetylation is a reversible posttranslational modification of proteins and plays a key role in regulating gene expression. Technological limitations have so far prevented a global analysis of lysine acetylation's cellular roles. We used high-resolution mass spectrometry to identify 3600 lysine acetylation sites on 1750 proteins and quantified acetylation changes in response to the deacetylase inhibitors suberoylanilide hydroxamic acid and MS-275. Lysine acetylation preferentially targets large macromolecular complexes involved in diverse cellular processes, such as chromatin remodeling, cell cycle, splicing, nuclear transport, and actin nucleation. Acetylation impaired phosphorylation-dependent interactions of 14-3-3 and regulated the yeast cyclin-dependent kinase Cdc28. Our data demonstrate that the regulatory scope of lysine acetylation is broad and comparable with that of other major posttranslational modifications.

https://science.sciencemag.org/content/suppl/2009/07/16/1175371.DC1/Choudhary-SOM.pdf

Lysine Acetylation Targets Protein Complexes and Co-Regulates Major Cellular Functions

Tight control of gene expression networks required for adipose tissue formation and plasticity is essential for adaptation to energy needs and environmental cues. However, little is known about the mechanisms that orchestrate the dramatic transcriptional changes leading to adipocyte differentiation. We investigated the regulation of nascent transcription by the sumoylation pathway during adipocyte differentiation using SLAMseq and ChIPseq. We discovered that the sumoylation pathway has a dual function in differentiation; it supports the initial downregulation of pre-adipocyte-specific genes, while it promotes the establishment of the mature adipocyte transcriptional program. By characterizing sumoylome dynamics in differentiating adipocytes by mass spectrometry, we found that sumoylation of specific transcription factors like Pparγ/RXR and their co-factors is associated with the transcription of adipogenic genes. Our data demonstrate that the sumoylation pathway coordinates the rewiring of transcriptional networks required for formation of functional adipocytes. This study also provides an in-depth resource of gene transcription dynamics, SUMO-regulated genes and sumoylation sites during adipogenesis.

/pdf/waves-of-sumoylation-support-transcription-dynamics-during-3fufnenhy2.pdf

Waves of sumoylation support transcription dynamics during adipocyte differentiation

Sox2 is a master transcriptional regulator of embryonic development. In this study, we determined the protein interactome of Sox2 in the chromatin and nucleoplasm of mouse embryonic stem (mES) cells. Apart from canonical interactions with pluripotency-regulating transcription factors, we identified interactions with several chromatin modulators, including members of the heterochromatin protein 1 (HP1) family, suggesting a role of Sox2 in chromatin-mediated transcriptional repression. Sox2 was also found to interact with RNA binding proteins (RBPs), including proteins involved in RNA processing. RNA immunoprecipitation followed by sequencing revealed that Sox2 associates with different messenger RNAs, as well as small nucleolar RNA Snord34 and the non-coding RNA 7SK. 7SK has been shown to regulate transcription at regulatory regions, which could suggest a functional interaction with Sox2 for chromatin recruitment. Nevertheless, we found no evidence of Sox2 modulating recruitment of 7SK to chromatin when examining 7SK chromatin occupancy by Chromatin Isolation by RNA Purification (ChIRP) in Sox2 depleted mES cells. In addition, knockdown of 7SK in mES cells did not lead to any change in Sox2 occupancy at 7SK-regulated genes. Thus, our results show that Sox2 extensively interact with RBPs, and suggest that Sox2 and 7SK co-exist in a ribonucleoprotein complex whose function is not to regulate chromatin recruitment, but might rather regulate other processes in the nucleoplasm. Summary blurb Sox2 interacts with RNA-binding proteins and diverse RNAs

/pdf/interaction-of-sox2-with-rna-binding-proteins-in-mouse-4lc6r7eunz.pdf

Michael L. Nielsen

Papers

Waves of sumoylation support transcription dynamics during adipocyte differentiation

Interaction of Sox2 with RNA binding proteins in mouse embryonic stem cells

Characterising the RNA-binding protein atlas of the mammalian brain uncovers RBM5 misregulation in mouse models of Huntington’s disease

The SUMO-NIP45 pathway processes toxic DNA catenanes to prevent mitotic failure.

Regulation of Rad52-dependent replication fork recovery through serine ADP-ribosylation of PolD3