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.
Deep proteomic analysis of mammalian cell lines would yield an inventory of the building blocks of the most commonly used systems in biological research. Mass spectrometry-based proteomics can ...identify and quantify proteins in a global and unbiased manner and can highlight the cellular processes that are altered between such systems. We analyzed 11 human cell lines using an LTQ-Orbitrap family mass spectrometer with a “high field” Orbitrap mass analyzer with improved resolution and sequencing speed. We identified a total of 11,731 proteins, and on average 10,361 ± 120 proteins in each cell line. This very high proteome coverage enabled analysis of a broad range of processes and functions. Despite the distinct origins of the cell lines, our quantitative results showed surprisingly high similarity in terms of expressed proteins. Nevertheless, this global similarity of the proteomes did not imply equal expression levels of individual proteins across the 11 cell lines, as we found significant differences in expression levels for an estimated two-third of them. The variability in cellular expression levels was similar for low and high abundance proteins, and even many of the most highly expressed proteins with household roles showed significant differences between cells. Metabolic pathways, which have high redundancy, exhibited variable expression, whereas basic cellular functions such as the basal transcription machinery varied much less. We harness knowledge of these cell line proteomes for the construction of a broad coverage “super-SILAC” quantification standard. Together with the accompanying paper (Schaab, C. MCP 2012, PMID: 22301388) (17) these data can be used to obtain reference expression profiles for proteins of interest both within and across cell line proteomes.
Proteomic maps of breast cancer subtypes Tyanova, Stefka; Albrechtsen, Reidar; Kronqvist, Pauliina ...
Nature communications,
01/2016, Letnik:
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Systems-wide profiling of breast cancer has almost always entailed RNA and DNA analysis by microarray and sequencing techniques. Marked developments in proteomic technologies now enable very deep ...profiling of clinical samples, with high identification and quantification accuracy. We analysed 40 oestrogen receptor positive (luminal), Her2 positive and triple negative breast tumours and reached a quantitative depth of >10,000 proteins. These proteomic profiles identified functional differences between breast cancer subtypes, related to energy metabolism, cell growth, mRNA translation and cell-cell communication. Furthermore, we derived a signature of 19 proteins, which differ between the breast cancer subtypes, through support vector machine (SVM)-based classification and feature selection. Remarkably, only three proteins of the signature were associated with gene copy number variations and eleven were also reflected on the mRNA level. These breast cancer features revealed by our work provide novel insights that may ultimately translate to development of subtype-specific therapeutics.
Proteomics technology aims to map the protein landscapes of biological samples, and it can be applied to a variety of samples, including cells, tissues, and body fluids. Because the proteins are the ...main functional molecules in the cells, their levels reflect much more accurately the cellular phenotype and the regulatory processes within them than gene levels, mutations, and even mRNA levels. With the advancement in the technology, it is possible now to obtain comprehensive views of the biological systems and to study large patient cohorts in a streamlined manner. In this review we discuss the technological advancements in mass spectrometry–based proteomics, which allow analysis of breast cancer tissue samples, leading to the first large-scale breast cancer proteomics studies. Furthermore, we discuss the technological developments in blood-based biomarker discovery, which provide the basis for future development of assays for routine clinical use. Although these are only the first steps in implementation of proteomics into the clinic, extensive collaborative work between these worlds will undoubtedly lead to major discoveries and advances in clinical practice.
Cell biologists studying cell adhesion have already figured out that cell–extracellular matrix connections, mediated by integrin receptors, are diverse and extremely complex structures. Dozens of ...adaptors — linking integrins with the cytoskeleton, and numerous enzymes and signaling proteins — regulating adhesion site dynamics, collectively referred to as the integrin adhesome, cooperate in mediating adhesion and activating specific signaling networks. Recent proteomic studies indicate that the known adhesome complexity is just the tip of the iceberg. In each existing category of molecular function the number of candidate components more than double the known components and several new categories are suggested. Proteomic analysis of different integrin heterodimers points to integrin-specific variations in composition and analysis of adhesion complexes under varying tension regimes highlights the force-dependent recruitment of different components, most notably LIM domain proteins.
The orbitrap mass analyzer combines high sensitivity, high resolution, and high mass accuracy in a compact format. In proteomics applications, it is used in a hybrid configuration with a linear ion ...trap (LTQ-Orbitrap) where the linear trap quadrupole (LTQ) accumulates, isolates, and fragments peptide ions. Alternatively, isolated ions can be fragmented by higher energy collisional dissociation. A recently introduced stand-alone orbitrap analyzer (Exactive) also features a higher energy collisional dissociation cell but cannot isolate ions. Here we report that this instrument can efficiently characterize protein mixtures by alternating MS and “all-ion fragmentation” (AIF) MS/MS scans in a manner similar to that previously described for quadrupole time-of-flight instruments. We applied the peak recognition algorithms of the MaxQuant software at both the precursor and product ion levels. Assignment of fragment ions to co-eluting precursor ions was facilitated by high resolution (100,000 at m/z 200) and high mass accuracy. For efficient fragmentation of different mass precursors, we implemented a stepped collision energy procedure with cumulative MS readout. AIF on the Exactive identified 45 of 48 proteins in an equimolar protein standard mixture and all of them when using a small database. The technique also identified proteins with more than 100-fold abundance differences in a high dynamic range standard. When applied to protein identification in gel slices, AIF unambiguously characterized an immunoprecipitated protein that was barely visible by Coomassie staining and quantified it relative to contaminating proteins. AIF on a benchtop orbitrap instrument is therefore an attractive technology for a wide range of proteomics analyses.
Cellular life depends on continuous transport of lipids and small molecules between mitochondria and the endomembrane system. Recently, endoplasmic reticulum-mitochondrial encounter structure (ERMES) ...was identified as an important yet nonessential contact for such transport. Using a high-content screen in yeast, we found a contact site, marked by Vam6/Vps39, between vacuoles (the yeast lysosomal compartment) and mitochondria, named vCLAMP (vacuole and mitochondria patch). vCLAMP is enriched with ion and amino-acid transporters and has a role in lipid relay between the endomembrane system and mitochondria. Critically, we show that mitochondria are dependent on having one of two contact sites, ERMES or vCLAMP. The absence of one causes expansion of the other, and elimination of both is lethal. Identification of vCLAMP adds to our ability to understand the complexity of interorganellar crosstalk.
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•A membrane contact site exists between mitochondria and vacuoles (yeast lysosomes)•Mitochondrial contact sites with the ER and with vacuoles are coregulated•Mitochondria require at least one contact site with the endomembrane system•Loss of both mitochondrial contact sites impairs phospholipid transport
Organelle communication is instrumental in coordinating cellular function and can be achieved by creation of membrane contact sites (MCSs). Elbaz-Alon et al. uncover MCSs in yeast between vacuoles (the yeast lysosomes) and mitochondria. These vacuole and mitochondria patches (vCLAMPs) are coregulated with ER/mitochondria MCSs for efficient transfer of phospholipids.
While the number and identity of proteins expressed in a single human cell type is currently unknown, this fundamental question can be addressed by advanced mass spectrometry (MS)‐based proteomics. ...Online liquid chromatography coupled to high‐resolution MS and MS/MS yielded 166 420 peptides with unique amino‐acid sequence from HeLa cells. These peptides identified 10 255 different human proteins encoded by 9207 human genes, providing a lower limit on the proteome in this cancer cell line. Deep transcriptome sequencing revealed transcripts for nearly all detected proteins. We calculate copy numbers for the expressed proteins and show that the abundances of >90% of them are within a factor 60 of the median protein expression level. Comparisons of the proteome and the transcriptome, and analysis of protein complex databases and GO categories, suggest that we achieved deep coverage of the functional transcriptome and the proteome of a single cell type.
More than 10 000 proteins were identified by high‐resolution mass spectrometry in a human cancer cell line. The data cover most of the functional proteome as judged by RNA‐seq data and it reveals the expression range of different protein classes.
Tumor-associated macrophages (TAMs) promote tumor development, invasion, and dissemination by various mechanisms. In this study, using an orthotopic colorectal cancer (CRC) model, we found that ...monocyte-derived TAMs advance tumor development by the remodeling of its extracellular matrix (ECM) composition and structure. Unbiased transcriptomic and proteomic analyses of (a) TAM-abundant and -deficient tumor tissues and (b) sorted tumor-associated and -resident colonic macrophage subpopulations defined a distinct TAM-induced ECM molecular signature composed of an ensemble of matricellular proteins and remodeling enzymes they provide to the tumor microenvironment. Remarkably, many of these ECM proteins are specifically increased in human CRC versus healthy colon. Specifically, we demonstrate that although differentiating into TAMs, monocytes up-regulate matrix-remodeling programs associated with the synthesis and assembly of collagenous ECM, specifically collagen types I, VI, and XIV. This finding was further established by advanced imaging showing that TAMs instruct the deposition, cross-linking, and linearization of collagen fibers during tumor development, especially at areas of tumor invasiveness. Finally, we show that cancer-associated fibroblasts are significantly outnumbered by TAMs in this model and that their expression of collagen XIV and I is reduced by TAM deficiency. Here, we outline a novel TAM protumoral function associated with building of the collagenous ECM niche.
The translation machinery and the genes it decodes co-evolved to achieve production throughput and accuracy. Nonetheless, translation errors are frequent, and they affect physiology and protein ...evolution. Mapping translation errors in proteomes and understanding their causes is hindered by lack of a proteome-wide experimental methodology. We present the first methodology for systematic detection and quantification of errors in entire proteomes. Following proteome mass spectrometry, we identify, in E. coli and yeast, peptides whose mass indicates specific amino acid substitutions. Most substitutions result from codon-anticodon mispairing. Errors occur at sites that evolve rapidly and that minimally affect energetic stability, indicating selection for high translation fidelity. Ribosome density data show that errors occur at sites where ribosome velocity is higher, demonstrating a trade-off between speed and accuracy. Treating bacteria with an aminoglycoside antibiotic or deprivation of specific amino acids resulted in particular patterns of errors. These results reveal a mechanistic and evolutionary basis for translation fidelity.
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•A new methodology to detect and quantify most translation errors in proteomes•Most amino acid substitutions result from mis-pairing between codons and anti-codons•Proteins’ error rates are reduced at conserved and highly expressed proteins•Translation speed is negatively correlated with error rates
Errors in translation are common, occurring almost once per protein. Mordret et al. have developed a methodology to detect and quantify translation errors and applied it to bacteria and yeast. Errors appear to be programmed, reduced in highly expressed proteins and conserved protein sites. Codon identity and ribosome speed participate in governing a protein translation fidelity code.
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