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 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.

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

mTOR Signaling in Growth, Metabolism, and Disease.

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

Cellular fatty acid metabolism and cancer

Among organelles, lipid droplets (LDs) uniquely constitute a hydrophobic phase in the aqueous environment of the cytosol. Their hydrophobic core of neutral lipids stores metabolic energy and membrane components, making LDs hubs for lipid metabolism. In addition, LDs are implicated in a number of other cellular functions, ranging from protein storage and degradation to viral replication. These processes are functionally linked to many physiological and pathological conditions, including obesity and related metabolic diseases. Despite their important functions and nearly ubiquitous presence in cells, many aspects of LD biology are unknown. In the past few years, the pace of LD investigation has increased, providing new insights. Here, we review the current knowledge of LD cell biology and its translation to physiology.

Lipid Droplets and Cellular Lipid Metabolism

Lysosomes are the major cellular site for clearance of defective organelles and digestion of internalized material. Demand on lysosomal capacity can vary greatly, and lysosomal function must be adjusted to maintain cellular homeostasis. Here, we identified an interaction between the lysosome-localized mechanistic target of rapamycin complex 1 (mTORC1) and the transcription factor TFEB (transcription factor EB), which promotes lysosome biogenesis. When lysosomal activity was adequate, mTOR-dependent phosphorylation of TFEB on Ser(211) triggered the binding of 14-3-3 proteins to TFEB, resulting in retention of the transcription factor in the cytoplasm. Inhibition of lysosomal function reduced the mTOR-dependent phosphorylation of TFEB, resulting in diminished interactions between TFEB and 14-3-3 proteins and the translocation of TFEB into the nucleus, where it could stimulate genes involved in lysosomal biogenesis. These results identify TFEB as a target of mTOR and suggest a mechanism for matching the transcriptional regulation of genes encoding proteins of autophagosomes and lysosomes to cellular need. The closely related transcription factors MITF (microphthalmia transcription factor) and TFE3 (transcription factor E3) also localized to lysosomes and accumulated in the nucleus when lysosome function was inhibited, thus broadening the range of physiological contexts under which this regulatory mechanism may prove important.

/pdf/the-transcription-factor-tfeb-links-mtorc1-signaling-to-bzjg7i9xl7.pdf

The Transcription Factor TFEB Links mTORC1 Signaling to Transcriptional Control of Lysosome Homeostasis

Mass spectrometry is a powerful technology for the analysis of large numbers of endogenous proteins. However, the analytical challenges associated with comprehensive identification and relative quantification of cellular proteomes have so far appeared to be insurmountable. Here, using advances in computational proteomics, instrument performance and sample preparation strategies, we compare protein levels of essentially all endogenous proteins in haploid yeast cells to their diploid counterparts. Our analysis spans more than four orders of magnitude in protein abundance with no discrimination against membrane or low level regulatory proteins. Stable-isotope labelling by amino acids in cell culture (SILAC) quantification was very accurate across the proteome, as demonstrated by one-to-one ratios of most yeast proteins. Key members of the pheromone pathway were specific to haploid yeast but others were unaltered, suggesting an efficient control mechanism of the mating response. Several retrotransposon-associated proteins were specific to haploid yeast. Gene ontology analysis pinpointed a significant change for cell wall components in agreement with geometrical considerations: diploid cells have twice the volume but not twice the surface area of haploid cells. Transcriptome levels agreed poorly with proteome changes overall. However, after filtering out low confidence microarray measurements, messenger RNA changes and SILAC ratios correlated very well for pheromone pathway components. Systems-wide, precise quantification directly at the protein level opens up new perspectives in post-genomics and systems biology.

Tobias C. Walther

Papers

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

Cellular fatty acid metabolism and cancer

Lipid Droplets and Cellular Lipid Metabolism

The Transcription Factor TFEB Links mTORC1 Signaling to Transcriptional Control of Lysosome Homeostasis

Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast.