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Ruedi Aebersold

Publications and source records attributed to Ruedi Aebersold.

At least 19 recordsLinked to original sources

AI proteomics: from protein identification to virtual cells.

Artificial intelligence (AI) is transforming scientific research, including proteomics. In this Perspective, we highlight key mass spectrometry (MS)-based proteomics areas where AI is driving innovation, ranging from protein identification to building AI virtual cells. These include improving peptide and protein identification and quantification; characterizing protein-protein interactions and protein complexes; advancing spatial and perturbation proteomics; integrating multi-omics data; and, ultimately, enabling AI virtual cells. Finally, we call for global collaboration among data producers, data consumers and other stakeholders to establish an AI-friendly ecosystem for MS-based proteomics, laying the foundation for transformative advancements in proteomics driven by AI.

Proteomics↗

Proteomic profiling of pancreatic cancer for biomarker discovery.

Pancreatic cancer is a uniformly lethal disease that is difficult to diagnose at early stage and even more difficult to cure. In recent years, there has been a substantial interest in applying proteomics technologies to identify protein biomarkers for early detection of cancer. Quantitative proteomic profiling of body fluids, tissues, or other biological samples to identify differentially expressed proteins represents a very promising approach for improving the outcome of this disease. Proteins associated with pancreatic cancer identified through proteomic profiling technologies could be useful as biomarkers for the early diagnosis, therapeutic targets, and disease response markers. In this article, we discuss recent progress and challenges for applying quantitative proteomics technologies for biomarker discovery in pancreatic cancer.

Biomarkers, Tumor↗

High throughput proteome screening for biomarker detection.

Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Current methods, while highly developed and powerful, are falling short of their goal of routinely analyzing whole proteomes mainly because the wealth of proteomic information accumulated from prior studies is not used for the planning or interpretation of present experiments. The consequence of this situation is that in every proteomic experiment the proteome is rediscovered. In this report we describe an approach for quantitative proteomics that builds on the extensive prior knowledge of proteomes and a platform for the implementation of the method. The method is based on the selection and chemical synthesis of isotopically labeled reference peptides that uniquely identify a particular protein and the addition of a panel of such peptides to the sample mixture consisting of tryptic peptides from the proteome in question. The platform consists of a peptide separation module for the generation of ordered peptide arrays from the combined peptide sample on the sample plate of a MALDI mass spectrometer, a high throughput MALDI-TOF/TOF mass spectrometer, and a suite of software tools for the selective analysis of the targeted peptides and the interpretation of the results. Applying the method to the analysis of the human blood serum proteome we demonstrate the feasibility of using mass spectrometry-based proteomics as a high throughput screening technology for the detection and quantification of targeted proteins in a complex system.

Automation↗

Increased quantitative proteome coverage with (13)C/(12)C-based, acid-cleavable isotope-coded affinity tag reagent and modified data acquisition scheme.

Quantitative protein profiling using the isotope-coded affinity tag (ICAT) method and tandem mass spectrometry (MS) enables the pair-wise comparison of protein expression levels in biological samples. A new version of the ICAT reagent with an acid-cleavable bond, which allows removal of the biotin moiety prior to MS and which utilizes (13)C substitution for (12)C in the heavy-ICAT reagent rather than (2)H (for (1)H) as in the original reagent, was investigated. We developed and validated an MS data acquisition strategy using this new reagent that results in an increased number of protein identifications per experiment, without losing the accuracy of protein quantification. This was achieved by following a single survey (precursor) ion scan and serial collision induced dissociations (CIDs) of four different precursor ions observed in the prior survey scan. This strategy is common to many high-performance liquid chromatography-electrospray ionization (HPLC-ESI)-MS shotgun proteomic strategies, but heretofore not to ICAT experiments. This advance is possible because the new ICAT reagent uses (13)C as the "heavy" element rather than (2)H, thus, eliminating the slight delay in retention time of ICAT-labeled "light" peptides on a C18-based HPLC separation that occurs with (2)H and (1)H. Analyses using this new scheme of an ICAT-labeled trypsin-digested six protein mixture as well as a tryptic digest of a total yeast lysate, indicated that about two times more proteins were identified in a single analysis, and that there was no loss in accuracy of quantification.

Carbon↗

Advances in protein complex analysis using mass spectrometry.

Proteins often function as components of larger complexes to perform a specific function, and formation of these complexes may be regulated. For example, intracellular signalling events often require transient and/or regulated protein-protein interactions for propagation, and protein binding to a specific DNA sequence, RNA molecule or metabolite is often regulated to modulate a particular cellular function. Thus, characterizing protein complexes can offer important insights into protein function. This review describes recent important advances in mass spectrometry (MS)-based techniques for the analysis of protein complexes. Following brief descriptions of how proteins are identified using MS, and general protein complex purification approaches, we address two of the most important issues in these types of studies: specificity and background protein contaminants. Two basic strategies for increasing specificity and decreasing background are presented: whereas (1) tandem affinity purification (TAP) of tagged proteins of interest can dramatically improve the signal-to-noise ratio via the generation of cleaner samples, (2) stable isotopic labelling of proteins may be used to discriminate between contaminants and bona fide binding partners using quantitative MS techniques. Examples, as well as advantages and disadvantages of each approach, are presented.

Animals↗

High throughput quantitative analysis of serum proteins using glycopeptide capture and liquid chromatography mass spectrometry.

It is expected that the composition of the serum proteome can provide valuable information about the state of the human body in health and disease and that this information can be extracted via quantitative proteomic measurements. Suitable proteomic techniques need to be sensitive, reproducible, and robust to detect potential biomarkers below the level of highly expressed proteins, generate data sets that are comparable between experiments and laboratories, and have high throughput to support statistical studies. Here we report a method for high throughput quantitative analysis of serum proteins. It consists of the selective isolation of peptides that are N-linked glycosylated in the intact protein, the analysis of these now deglycosylated peptides by liquid chromatography electrospray ionization mass spectrometry, and the comparative analysis of the resulting patterns. By focusing selectively on a few formerly N-linked glycopeptides per serum protein, the complexity of the analyte sample is significantly reduced and the sensitivity and throughput of serum proteome analysis are increased compared with the analysis of total tryptic peptides from unfractionated samples. We provide data that document the performance of the method and show that sera from untreated normal mice and genetically identical mice with carcinogen-induced skin cancer can be unambiguously discriminated using unsupervised clustering of the resulting peptide patterns. We further identify, by tandem mass spectrometry, some of the peptides that were consistently elevated in cancer mice compared with their control littermates.

Animals↗

Quantitative mass spectrometry reveals a role for the GTPase Rho1p in actin organization on the peroxisome membrane.

We have combined classical subcellular fractionation with large-scale quantitative mass spectrometry to identify proteins that enrich specifically with peroxisomes of Saccharomyces cerevisiae. In two complementary experiments, isotope-coded affinity tags and tandem mass spectrometry were used to quantify the relative enrichment of proteins during the purification of peroxisomes. Mathematical modeling of the data from 306 quantified proteins led to a prioritized list of 70 candidates whose enrichment scores indicated a high likelihood of them being peroxisomal. Among these proteins, eight novel peroxisome-associated proteins were identified. The top novel peroxisomal candidate was the small GTPase Rho1p. Although Rho1p has been shown to be tethered to membranes of the secretory pathway, we show that it is specifically recruited to peroxisomes upon their induction in a process dependent on its interaction with the peroxisome membrane protein Pex25p. Rho1p regulates the assembly state of actin on the peroxisome membrane, thereby controlling peroxisome membrane dynamics and biogenesis.

Actins↗

Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometry.

A crucial aim upon the completion of the human genome is the verification and functional annotation of all predicted genes and their protein products. Here we describe the mapping of peptides derived from accurate interpretations of protein tandem mass spectrometry (MS) data to eukaryotic genomes and the generation of an expandable resource for integration of data from many diverse proteomics experiments. Furthermore, we demonstrate that peptide identifications obtained from high-throughput proteomics can be integrated on a large scale with the human genome. This resource could serve as an expandable repository for MS-derived proteome information.

Amino Acid Sequence↗

N-acetylation and ubiquitin-independent proteasomal degradation of p21(Cip1).

Expression of the CDK inhibitor p21(Cip1) is tightly regulated by signals that control cell division. p21 is an unstable protein that is degraded by the proteasome; however, the pathway that leads to proteasomal degradation of p21 has proven to be enigmatic. An important issue is whether proteasomal degradation of p21 occurs independently of ubiquitylation or, alternatively, whether ubiquitylation on its N terminus is crucial. We resolve this uncertainty by showing that endogenous cellular p21 is completely acetylated at its amino terminus and is therefore not a substrate for N-ubiquitylation. We further show that inactivation of essential components of the ubiquitylation machinery does not directly impact endogenous p21 degradation. Our results underscore the importance of N-acetylation in restricting N-ubiquitylation and show, in particular, that ubiquitylation of endogenous p21 either at internal lysines or on the N terminus is unlikely to control its degradation by the proteasome.

Acetylation↗

An SMC-domain protein in fission yeast links telomeres to the meiotic centrosome.

Abnormal centrosomal structures similar to those occurring in human cancers are induced in fission yeast by overexpression of the pericentrin homolog Pcp1p. Analysis of abnormal Pcp1p-containing structures with quantitative mass spectrometry and isotope-coded affinity tags identified a coiled-coil, structural maintenance of chromosomes (SMC) domain protein. This protein, termed Ccq1p (coiled-coil protein quantitatively enriched), localizes with Taz1p to telomeres in normal vegetative cells. Fluorescence resonance energy transfer (FRET) measurements indicate that Ccq1p also interacts with centrosomal Pcp1p in mating pheromone-stimulated cells containing centrosomally clustered telomeres. We provide evidence that the Ccq1p-Pcp1p interaction, while essential for meiosis, is deleterious when forced to occur during vegetative growth. Cells lacking one ccq1 allele exhibit a loss-of-function phenotype including abnormally long cell length, chromosome segregation failure, telomeric shortening, and defective telomeric clustering during meiotic prophase. Our data indicate a mechanism underlying meiotic chromosomal bouquet formation and suggest a recruitment model for supernumerary centrosome toxicity.

Alleles↗

Proteomic analysis identifies that 14-3-3zeta interacts with beta-catenin and facilitates its activation by Akt.

beta-Catenin is a central effector of Wnt signaling in embryonic and stem cell development and in tumorigenesis. Here, through a mass spectrometric analysis of a beta-catenin protein complex, we identified 12 proteins as putative beta-catenin interactors. We show that one of them, 14-3-3zeta, enhances beta-catenin-dependent transcription by maintaining a high level of beta-catenin protein in the cytoplasm. More importantly, 14-3-3zeta facilitates activation of beta-catenin by the survival kinase Akt and colocalizes with activated Akt in intestinal stem cells. We propose that Akt phosphorylates beta-catenin, which results in 14-3-3zeta binding and stabilization of beta-catenin, and these interactions may be involved in stem cell development.

14-3-3 Proteins↗

Quantitative proteomic analysis of metabolic regulation by copper ions in Methylococcus capsulatus (Bath).

Copper ions switch the oxidation of methane by soluble methane monooxygenase to particulate methane monooxygenase in Methylococcus capsulatus (Bath). Toward understanding the change in cellular metabolism related to this transcriptional and metabolic switch, we have undertaken genomic sequencing and quantitative comparative analysis of the proteome in M. capsulatus (Bath) grown under different copper-to-biomass ratios by cleavable isotope-coded affinity tag technology. Of the 682 proteins identified, the expressions of 60 proteins were stimulated by at least 2-fold by copper ions; 68 proteins were down-regulated by 2-fold or more. The 60 proteins overexpressed included the methane and carbohydrate metabolic enzymes, while the 68 proteins suppressed were mainly responsible for cellular signaling processes, indicating a role of copper ions in the expression of the genes associated with the metabolism of the organism downstream of methane oxidation. The study has also provided a complete map of the C1 metabolism pathways in this methanotroph and clarified the interrelationships between them.

Bacterial Proteins↗

System-based proteomic analysis of the interferon response in human liver cells.

BACKGROUND: Interferons (IFNs) play a critical role in the host antiviral defense and are an essential component of current therapies against hepatitis C virus (HCV), a major cause of liver disease worldwide. To examine liver-specific responses to IFN and begin to elucidate the mechanisms of IFN inhibition of virus replication, we performed a global quantitative proteomic analysis in a human hepatoma cell line (Huh7) in the presence and absence of IFN treatment using the isotope-coded affinity tag (ICAT) method and tandem mass spectrometry (MS/MS). RESULTS: In three subcellular fractions from the Huh7 cells treated with IFN (400 IU/ml, 16 h) or mock-treated, we identified more than 1,364 proteins at a threshold that corresponds to less than 5% false-positive error rate. Among these, 54 were induced by IFN and 24 were repressed by more than two-fold, respectively. These IFN-regulated proteins represented multiple cellular functions including antiviral defense, immune response, cell metabolism, signal transduction, cell growth and cellular organization. To analyze this proteomics dataset, we utilized several systems-biology data-mining tools, including Gene Ontology via the GoMiner program and the Cytoscape bioinformatics platform. CONCLUSIONS: Integration of the quantitative proteomics with global protein interaction data using the Cytoscape platform led to the identification of several novel and liver-specific key regulatory components of the IFN response, which may be important in regulating the interplay between HCV, interferon and the host response to virus infection.

Cell Line, Tumor↗

A dataset of human liver proteins identified by protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry.

Proteins from human liver carcinoma Huh7 cells, representing transformed liver cells, and cultured primary human fetal hepatocytes (HFH) and human HH4 hepatocytes, representing nontransformed liver cells, were extracted and processed for proteome analysis. Proteins from stimulated cells (interferon-alpha treatment for the Huh7 and HFH cells and induction of hepatitis C virus [HCV] proteins for the HH4 cells) and corresponding control cells were labeled with light and heavy cleavable ICAT reagents, respectively. The labeled samples were combined, trypsinized, and subject to cation-exchange and avidin-affinity chromatographies. The resulting cysteine-containing peptides were analyzed by microcapillary LC-MS/MS. The MS/MS spectra were initially analyzed by searching the human International Protein Index database using the SEQUEST software (1). Subsequently, new statistical algorithms were applied to the collective SEQUEST search results of each experiment. First, the PeptideProphet software (2) was applied to discriminate true assignments of MS/MS spectra to peptide sequences from false assignments, to assign a probability value for each identified peptide, and to compute the sensitivity and error rate for the assignment of spectra to sequences in each experiment. Second, the ProteinProphet software (3) was used to infer the protein identifications and to compute probabilities that a protein had been correctly identified, based on the available peptide sequence evidence. The resulting protein lists were filtered by a ProteinProphet probability score p > or = 0.5, which corresponded to an error rate of less than 5%. A total of 1,296, 1,430, and 1,476 proteins or related protein groups were identified in three subdatasets from the Huh7, HFH, and HH4 cells, respectively. In total, these subdatasets contained 2,486 unique protein identifications from human liver cells. An increase of the threshold to p > or = 0.9 (corresponding to an error rate of less than 1%) resulted in 2,159 unique protein identifications (1,146, 1,235, and 1,318 for the Huh7, HFH, and HH4 cells, respectively).

Algorithms↗

Absolute quantification of specific proteins in complex mixtures using visible isotope-coded affinity tags.

The identification of proteins in complex mixtures is most useful when quantitative information is also obtained. We describe a new type of protein tagging reagent called the visible isotope-coded affinity tag (VICAT) which allows the absolute amount of a target protein or proteins to be quantified in a complex biological sample such as a eukaryotic cell lysate. VICAT reagents tag thiol groups of cysteines or thioacetylated amino groups and introduce into the tryptic peptide a biotin affinity handle, a visible moiety for tracking the chromatographic location of the target peptide by a method other than mass spectrometry, a photocleavable linker for removing a portion of the tag, and an isotope tag for distinguishing sample and internal standard peptides. We demonstrate the use of VICAT reagents together with isoelectric focusing of peptides on an immobilized gel strip followed by combined micro-liquid chromatography/electrospray ionization mass spectrometry operating in selected reaction monitoring mode to determine the absolute abundance of a specific protein, human group V phospholipase A(2), in eukaryotic cell lysates. It is found that human lung macrophages contain 66 fmol of this protein per 100 microg of cell protein. Western blot analysis of human group V phospholipase A(2) in macrophages gave inconclusive data. VICAT reagents should be useful for numerous applications including the analysis of candidate disease markers in complex mixtures such as serum.

Amino Acid Sequence↗

Integrated genomic and proteomic analyses of gene expression in Mammalian cells.

Using DNA microarrays together with quantitative proteomic techniques (ICAT reagents, two-dimensional DIGE, and MS), we evaluated the correlation of mRNA and protein levels in two hematopoietic cell lines representing distinct stages of myeloid differentiation, as well as in the livers of mice treated for different periods of time with three different peroxisome proliferative activated receptor agonists. We observe that the differential expression of mRNA (up or down) can capture at most 40% of the variation of protein expression. Although the overall pattern of protein expression is similar to that of mRNA expression, the incongruent expression between mRNAs and proteins emphasize the importance of posttranscriptional regulatory mechanisms in cellular development or perturbation that can be unveiled only through integrated analyses of both proteins and mRNAs.

Animals↗

A tool to visualize and evaluate data obtained by liquid chromatography-electrospray ionization-mass spectrometry.

We present a software tool for visualizing data obtained from analyzing complex peptide mixtures by liquid chromatography (LC) electrospray ionization (ESI) mass spectrometry (MS). The data are represented as a two-dimensional density plot. For experiments employing collision-induced dissociation (CID), links are embedded in the image to the CID spectra and the corresponding peptide sequences that are represented by the respective feature. The image provides an intuitive method to evaluate sample quality and the performance of an LC-ESI-MS system and can be used to optimize experimental conditions. Local patterns of the image can also be used to identify chemical contaminants and specific peptide features. Therefore, this software tool may have broad application in MS-based proteomics.

Chromatography, Liquid↗

Identification of TFB5, a new component of general transcription and DNA repair factor IIH.

We previously described the use of quantitative proteomics to study macromolecular complexes. Applying the method to analyze a yeast RNA polymerase II preinitiation complex, we identified a new 8-kDa protein, encoded by the uncharacterized open reading frame YDR079c-a, as a potential new component of the preinitiation complex. Here we show that YDR079c-a is a bona fide component of polymerase II preinitiation complexes and investigate its role in transcription. YDR079c-a is recruited to promoters both in vivo and in vitro and is required for efficient transcription in vitro and for normal induction of GAL genes. In addition, YDR079c-a is a core component of general transcription and DNA repair factor IIH and is required for efficient recruitment of TFIIH to a promoter. Yeast lacking YDR079c-a grow slowly, and, like strains carrying mutations in core TFIIH subunits, are sensitive to ultraviolet radiation. YDR079c-a is conserved throughout evolution, and mutations in the human ortholog account for a DNA repair-deficient form of the tricothiodystrophy disorder called TTD-A(2). The identification of a new, evolutionarily conserved, core TFIIH subunit is essential for our understanding of TFIIH function in transcription, DNA repair and human disease.

DNA Polymerase II↗