Biology subjects

Aebersold, R.

Publications and source records attributed to Aebersold, R..

At least 55 records · Page 3Linked to original sources

bioRxiv2019

The polyQ expansion modulates the configuration and phosphorylation of huntingtin

The polyQ-expansion at the N-terminus of huntingtin (HTT) is the prime cause of Huntingtons disease. The recent cryo-EM structure of HTT with HAP40 provides information on the proteins prominent HEAT-repeats. Here, we present analyses of the impact of polyQ-length on the conformation of HTT by cryo-EM, the domain-interactions by cross-linking mass spectrometry and the phosphorylation of HTT. The cryo-EM analysis of normal (Q23-) and disease (Q78-) type HTTs in their apo forms shows that the structures of apo HTTs significantly differ from the structure of HTT-HAP40, and that the polyQ expansion induces global structural changes consisting of significant domain movements of the C-HEAT domain relative to the N-HEAT domain. In addition, we show that the polyQ-expansion alters the phosphorylation pattern across the full-length HTT and that the specific phosphorylation (Ser2116p) in turn affects the global structure of HTT, which influences the activity of polyQ-expanded HTT. These results provide a molecular basis for the effect of the N-terminal polyQ segment on HTT structure and activity, that may be important for the cell-selective toxicity of mutant HTT.

neuroscience↗

bioRxiv2019

Integration of transcriptome, proteome and phosphoproteome data elucidates the genetic control of molecular networks

Genomic variation affects cellular networks by altering diverse molecular layers such as RNA levels, protein abundance, and post-translational protein modifications. However, it remains unclear how these different layers are affected by genetic polymorphisms and give rise to complex physiological phenotypes. To address these questions, we generated high-quality transcriptome, proteome, and phosphoproteome data for a panel of 112 genetically diverse yeast strains. While genetic effects on transcript abundances were generally transmitted to the protein level, we found a significant uncoupling of the transcript-protein relationship for certain protein classes, such as subunits of protein complexes. The additional phosphoproteomics data suggests that the same genetic locus often affects distinct sets of genes within each of these layers. In particular, QTLs tended to affect upstream regulatory proteins at the phosphorylation layer, whereas downstream pathway targets were typically affected at the transcript and protein abundance layers. Underscoring the importance of regulatory protein phosphorylation in linking genetic to phenotypic variation is the finding that the number of protein phosphosites associated with a given genetic locus was more predictive for its influence on cellular growth traits than the number of transcripts or proteins.\n\nThis study shows how multi-layered molecular networks mediate the effects of genomic variants to more complex physiological traits and highlights the important role of protein phosphorylation in mediating these effects.

systems biology↗

bioRxiv2019

Discovery and Multi-center Verification of Prostate Cancer Protein Biomarkers using Single-shot Short Gradient Microflow SWATH and MRMHR Mass Spectrometry

We report and evaluated a microflow, single-shot, short gradient SWATH MS method intended to accelerate the discovery and verification of protein biomarkers in clinical specimens. The method uses 15-min gradient microflow-LC peptide separation, an optimized SWATH MS window configuration and OpenSWATH software for data analysis.\n\nWe applied the method to a cohort 204 of FFPE prostate tissue samples from 58 prostate cancer patients and 10 prostatic hyperplasia patients. Altogether we identified 27,976 proteotypic peptides and 4,043 SwissProt proteins from these 204 samples. Compared to a reference SWATH method with 2-hour gradient the accelerated method consumed only 27% instrument time, quantified 80% proteins and showed reduced batch effects. 3,800 proteins were quantified by both methods in two different instruments with relatively high consistency (r = 0.77). 75 proteins detected by the accelerated method with differential abundance between clinical groups were selected for further validation. A shortlist of 134 selected peptide precursors from the 75 proteins were analyzed using MRM-HR, exhibiting high quantitative consistency with the 15-min SWATH method (r = 0.89) in the same sample set. We further verified the capacity of these 75 proteins in separating benign and malignant tissues (AUC = 0.99) in an independent prostate cancer cohort (n=154).\n\nOverall our data show that the single-shot short gradient microflow-LC SWATH MS method achieved about 4-fold acceleration of data acquisition with reduced batch effect and a moderate level of protein attrition compared to a standard SWATH acquisition method. Finally, the results showed comparable ability to separate clinical groups.

cancer biology↗

bioRxiv2019

Arabidopsis Proteome and the Mass Spectral Assay Library

Arabidopsis is an important model organism and the first plant with its genome sequenced. Knowledge from studying this species has either direct or indirect applications to agriculture and human health. Quantitative proteomics by data-independent acquisition (SWATH/DIA-MS) was recently developed and considered as a high-throughput targetedlike approach for accurate proteome quantitation. In this approach, a high-quality and comprehensive library is a prerequisite. Here, we generated a protein expression atlas of 10 organs of Arabidopsis and created a library consisting of 15,514 protein groups, 187,265 unique peptide sequences, and 278,278 precursors. The identified protein groups correspond to ~56.5% of the predicted proteome. Further proteogenomics analysis identified 28 novel proteins. We subsequently applied DIA-mass spectrometry using this library to quantify the effect of abscisic acid on Arabidopsis. We were able to recover 8,793 protein groups with 1,787 of them being differentially expressed which includes 65 proteins known to respond to abscisic acid stress. Mass spectrometry data are available via ProteomeXchange with identifier PXD012710 for data-dependent acquisition and PXD014032 for DIA analyses.\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@1a3f799org.highwire.dtl.DTLVardef@1d4711dorg.highwire.dtl.DTLVardef@4e3f73org.highwire.dtl.DTLVardef@127a9a4org.highwire.dtl.DTLVardef@f254bb_HPS_FORMAT_FIGEXP M_TBL C_TBL

plant biology↗

bioRxiv2019

High-throughput proteomic analysis of FFPE tissue samples facilitates tumor stratification

Formalin-fixed, paraffin-embedded (FFPE), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here we developed a pressure cycling technology (PCT)-SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PCa) and diffuse large B-cell lymphoma (DLBCL) samples. We show that the proteome patterns of FFPE PCa tissue samples and their analogous fresh frozen (FF) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PCa tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between one to 15 years in a biobank and show a high degree of the proteome pattern similarity between two types histological region of small FFPE samples, i.e. punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of certain degree of biological variations. Applying the method to two independent DLBCL cohorts we identified myeloperoxidase (MPO), a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PCa and DLBCL have been discovered.

biochemistry↗

bioRxiv2019

Parallel accumulation - serial fragmentation combined with data-independent acquisition (diaPASEF): Bottom-up proteomics with near optimal ion usage

Data independent acquisition (DIA) modes isolate and concurrently fragment populations of different precursors by cycling through segments of a predefined precursor m/z range. Although these selection windows collectively cover the entire m/z range, overall only a few percent of all incoming ions are sampled. Making use of the correlation of molecular weight and ion mobility in a trapped ion mobility device (timsTOF Pro), we here devise a novel scan mode that samples up to 100% of the peptide precursor ion current. We extend an established targeted data extraction workflow by including the ion mobility dimension for both signal extraction and scoring, thereby increasing the specificity for precursor identification. Data acquired from whole proteome digests and mixed organism samples demonstrate deep proteome coverage and a very high degree of reproducibility as well as quantitative accuracy, even from 10 ng sample amounts.

systems biology↗

bioRxiv2019

A global screen for assembly state changes of the mitotic proteome by SEC-SWATH-MS

Living systems integrate biochemical reactions that determine the functional state of each cell. Reactions are primarily mediated by proteins that have in systematic studies been treated as independent entities, disregarding their higher level organization into complexes which affects their activity and/or function and is thus of great interest for biological research. Here, we describe the implementation of an integrated technique to quantify cell state-specific changes in the physical arrangement of protein complexes, concurrently for thousands of proteins and hundreds of complexes. Applying this technique for comparison of human cells in interphase and mitosis, we provide a systematic overview of mitotic proteome reorganization. The results recall key hallmarks of mitotic complex remodeling and discover new events, such as a new model of nuclear pore complex disassembly, validated by orthogonal methods. To support the interpretation of quantitative SEC-SWATH-MS datasets, we extend the software CCprofiler and provide an interactive exploration tool, SECexplorer-cc.\n\nHighlightsO_LIQuantification of proteome assembly state changes using SEC-SWATH-MS\nC_LIO_LISystems-wide analysis of assembly state changes in the mitotic proteome\nC_LIO_LIDiscovery and validation of a novel mitotic disassembly intermediate of the nuclear pore complex\nC_LIO_LIHigher sensitivity and information content compared to thermostability-based approaches for global measurement of proteome states\nC_LIO_LISECexplorer, an online platform to browse results and investigate proteins newly implicated in cell division\nC_LI

systems biology↗

bioRxiv2019

Breast cancer classification based on proteotypes obtained by SWATH mass spectrometry

Accurate breast cancer classification is vital for patient management decisions, and better tumour classification is expected to enable more precise and eventually personalized treatment to improve patient outcomes. Here, we present a novel quantitative proteotyping approach based on SWATH mass spectrometry and establish key proteins for breast tumour classification derived from proteotype data. The study was based on 96 tissue samples representing five breast cancer subtypes according to conventional classification. Correlation of SWATH proteotype patterns indicated groups that largely recapitulate these subtypes. However, the proteotype-based classification also revealed varying degrees of heterogeneity within the conventional subtypes, with triple negative tumours being the most heterogeneous. Proteins that contributed most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2, which are associated with oestrogen receptor status, tumour grade, and HER2 status, respectively. While these three key proteins exhibited high levels of correlation between protein and transcript levels (R>0.67), general correlation did not exceed R=0.29, indicating the value of protein-level measurements of biomarkers and disease-regulated genes. Overall, our data shows how large-scale protein-level measurements by next-generation proteomics can lead to improved patient stratification for precision medicine.

cancer biology↗

bioRxiv2018

PGC1a and Exercise Adaptations in Zebrafish

Fish species display huge differences in physical activity ranging from lethargy to migration of thousands of miles, making them an interesting model to identify determinants of physical fitness. Here, we show a remarkable plasticity of zebrafish in response to exercise and induction of PGC1 (encoded by PPARGC1A), a dominant regulator of mitochondrial biogenesis. Forced expression of human PPARGC1A induces mitochondrial biogenesis, an exercise-like gene expression signature, and physical fitness comparable to wild-type animals trained in counter-current swim tunnels. Quantifying transcriptional and proteomic changes in response to exercise or PGC1, we identify conserved exercise adaptations, including a stoichiometric induction of the electron transport chain (ETC) that re-organizes into respiratory supercomplexes in both conditions. We further show that ndufa4/ndufa4l, previously assigned to complex I, associates to free and supramolecular complex IV in vivo. Thus, zebrafish is a useful and experimentally tractable vertebrate model to study exercise biology, including ETC expression and assembly.\n\nHIGHLIGHTSO_LIPGC1 reprograms zebrafish skeletal muscle to a red fiber phenotype and increases exercise performance\nC_LIO_LIZebrafish show a high molecular plasticity in response to PGC1 and exercise\nC_LIO_LISWATH-MS proteomics show a stoichiometric induction of the electron transport chain that organizes as supercomplexes in response to PGC1 and exercise\nC_LIO_LIndufa4/ndufa4l associate to free and supramolecular complex IV in vivo\nC_LI

physiology↗

bioRxiv2018

The GTPase Nog1 couples polypeptide exit tunnel quality control with ribosomal stalk assembly

Eukaryotic ribosome precursors acquire translation competence in the cytoplasm through stepwise release of bound assembly factors, and proofreading of their functional centers. In case of the large subunit precursor (pre-60S), these essential steps include eviction of placeholders Arx1 and Mrt4 that prevent premature loading of the protein-folding machinery at the polypeptide exit tunnel (PET), and the ribosomal stalk, respectively. Here, we reveal that sequential ATPase and GTPase activities license release factors Rei1 and Yvh1 recruitment to the pre-60S in order to trigger Arx1 and Mrt4 removal. Drg1-ATPase activity extracts the C-terminal tail of Nog1 from the PET, enabling Rei1 to probe PET integrity, and then catalyze Arx1 release. Subsequently, GTPase hydrolysis stimulates Nog1 removal from the pre-60S, permitting Yvh1 to mediate Mrt4 release, and initiate ribosomal stalk assembly. Thus, Nog1 couples quality control and assembly of spatially distant functional centers during ribosome formation.

biochemistry↗

bioRxiv2018

Resource misallocation as a mediator of fitness costs in antibiotic resistance.

Antimicrobial resistance poses a threat to global health and the economy. It is widely accepted that, in the absence of antibiotics, drug resistance mutations carry a fitness cost. In the case of rifampicin resistance in fast-growing bacteria, this cost stems from a reduced transcription rate of the RNA polymerase resulting in slower ribosome biosynthesis. However, this relationship does not apply in the slow-growing Mycobacterium tuberculosis, where the true mechanism of fitness cost of rifampicin resistance as well as the impact of compensatory evolution remain unknown. Here we show, using global transcriptomic and proteomic profiling of selected M. tuberculosis mutants and clinical strains, that the fitness cost of rifampicin resistance in M. tuberculosis is the result of the physiological burden caused by aberrant gene expression. We further show that the perceived burden can be increased, effectively suppressing the emergence of drug resistance.

microbiology↗

bioRxiv2018

Cross-linking/Mass Spectrometry: A Community-Wide, Comparative Study Towards Establishing Best Practice Guidelines

The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has largely increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats that are generally accepted in the field and that have shown to lead to high-quality results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. From the results obtained, common protocols will be established. Our study serves as basis for establishing best practice guidelines in the field for conducting cross-linking experiments, performing data analysis, and reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results.

biochemistry↗

bioRxiv2018

Ultra-sensitive proteome profiling of FACS-isolated cell populations by data-independent acquisition-MS: Application to human hematopoietic stem and progenitor cells

Physiological processes in multicellular organisms depend on the function and interactions of a multitude of specialized cell types operating in context. Fluorescence-activated cell sorting (FACS) provides a powerful tool to determine the cell type composition of complex mixtures and to purify highly homogeneous cell populations using a small number of differentially expressed marker proteins. These populations can be further characterized, e.g. by phenotypic or molecular analyses.\n\nWe describe an ultra-sensitive mass spectrometric method for the robust quantitative and reproducible proteomic analysis of cohorts of FACS-isolated cell samples. It uses a minimum of post-sorting sample processing steps prior to data-independent acquisition MS on a current generation Orbitrap hybrid mass spectrometer. The method provides highly accurate and reproducible quantitative proteome profiles across the cohort with an average coefficient of variance <15% from as little as 150 ng of total peptide mass. We quantified the proteome of 25,000 sorted human hematopoietic stem/multipotent progenitor cell and three committed progenitor cell subpopulations (common myeloid progenitors, megakaryocyte-erythrocyte progenitors and granulocyte-macrophage progenitors) isolated from five healthy donors. On average, 5,851 protein groups were identified per sample. After stringent filtering, a subset of 4,131 protein groups ([≥]2 peptides) was used for differential comparison across the 20 samples, defining unique proteomic signatures for each cell type tested. A comparison of proteomic and transcriptomic profiles of the four cell types indicated hematopoietic stem/multipotent progenitor cell-specific divergent regulation of biochemical processes that are essential for maintaining stemness and were detected at the proteome rather than the transcriptome level.\n\nThe technology supports the generation of extensive and accurate quantitative proteomic profiles from low numbers of FACS-purified cells providing new information about the biochemical state of the analyzed cell types that is essential for basic and translational research.

systems biology↗

bioRxiv2018

Complex-centric proteome profiling by SEC-SWATH-MS

Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance.\n\nIn this paper we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation. The method consists of size exclusion chromatography (SEC) to fractionate native protein complexes, SWATH/DIA mass spectrometry to precisely quantify the proteins in each SEC fraction and the computational framework CCprofiler to detect and quantify protein complexes by error-controlled, complex-centric analysis using prior information from generic protein interaction maps.\n\nOur analysis of the HEK293 cell line proteome delineates 462 complexes composed of 2127 protein subunits. The technique identifies novel subcomplexes and assembly intermediates of central regulatory complexes while assessing the quantitative subunit distribution across them. We make the toolset CCprofiler freely accessible, and provide a web platform, SECexplorer, for custom exploration of the HEK293 proteome modularity.\n\nHighlightsO_LIIntroduction of the concept of complex-centric proteome profiling\nC_LIO_LIDevelopment of CCprofiler, a software framework for complex-centric data analysis\nC_LIO_LIDetection and quantification of subunit distribution of 462 distinct protein complexes containing 2127 proteins from a SEC-SWATH-MS dataset of HEK293 cells, and identification of novel complex variants such as assembly intermediates\nC_LIO_LIStatistical target-decoy model to estimate accurate false discovery rates for complexes quantified by complex-centric analysis\nC_LIO_LISECexplorer, an online platform to support custom complex-centric exploration of SEC-SWATH-MS datasets.\nC_LI

systems biology↗

bioRxiv2018

Genomic, Proteomic and Phenotypic Heterogeneity in HeLa Cells across Laboratories: Implications for Reproducibility of Research Results

The independent reproduction of research results is a cornerstone of experimental research, yet it is beset by numerous challenges, including the quality and veracity of reagents and materials. Much of life science research depends on life materials, including human tissue culture cells. In this study we aimed at determining the degree of variability in the molecular makeup and the ensuing phenotypic consequences in commonly used human tissue culture cells. We collected 14 stock HeLa aliquots from 13 different laboratories across the globe, cultured them in uniform conditions and profiled the genome-wide copy numbers, mRNAs, proteins and protein turnover rates via genomic techniques and SWATH mass spectrometry, respectively. We also phenotyped each cell line with respect to the ability of transfected Let7 mimics to modulate Salmonella infection.\n\nWe discovered significant heterogeneity between HeLa variants, especially between lines of the CCL2 and Kyoto variety. We also observed progressive divergence within a specific cell line over 50 successive passages. From the aggregate multi-omic datasets we quantified the response of the cells to genomic variability across the transcriptome and proteome. We discovered organelle-specific proteome remodeling and buffering of protein abundance by protein complex stoichiometry, mediated by the adaptation of protein turnover rates. By associating quantitative proteotype and phenotype measurements we identified protein patterns that explained the varying response of the different cell lines to Salmonella infection.\n\nAltogether the results indicate a striking degree of genomic variability, the rapid evolution of genomic variability in culture and its complex translation into distinctive expressed molecular and phenotypic patterns. The results have broad implications for the interpretation and reproducibility of research results obtained from HeLa cells and provide important basis for a general discussion of the value and requirements for communicating research results obtained from human tissue culture cells.

systems biology↗

bioRxiv2018

MLL1 minimal catalytic complex is a dynamic conformational ensemble susceptible to pharmacological allosteric disruption

Histone H3K4 methylation is an epigenetic mark associated with actively transcribed genes. This modification is catalyzed by the mixed lineage leukaemia (MLL) family of histone methyltransferases including MLL1, MLL2, MLL3, MLL4, SET1A and SET1B. Catalytic activity of MLL proteins is dependent on interactions with additional conserved proteins but the structural basis for subunit assembly and the mechanism of regulation is not well understood. We used a hybrid methods approach to study the assembly and biochemical function of the minimally active MLL1 complex (MLL1, WDR5 and RbBP5). A combination of small angle X-ray scattering (SAXS), cross-linking mass spectrometry (XL-MS), NMR spectroscopy, and computational modeling were used to generate a dynamic ensemble model in which subunits are assembled via multiple weak interaction sites. We identified a new interaction site between the MLL1 SET domain and the WD40 repeat domain of RbBP5, and demonstrate the susceptibility of the catalytic function of the complex to disruption of individual interaction sites.

biophysics↗

bioRxiv2018

Identification of protein abundance changes in biopsy-level hepatocellular carcinoma tissues using PCT-SWATH

In this study, we optimized the pressure-cycling technology (PCT) and SWATH mass spectrometry workflow to analyze biopsy-level tissue samples (2 mg wet weight) from 19 hepatocellular carcinoma (HCC) patients. Using OpenSWATH and pan-human spectral library, we quantified 11,787 proteotypic peptides from 2,579 SwissProt proteins in 76 HCC tissue samples within about 9 working days (from receiving tissue to SWATH data). The coefficient of variation (CV) of peptide yield using PCT was 32.9%, and the R2 of peptide quantification was 0.9729. We identified protein changes in malignant tissues compared to matched control samples in HCC patients, and further stratified patient samples into groups with high -fetoprotein (AFP) expression or HBV infection. In aggregate, the data identified 23 upregulated pathways and 13 ones. We observed enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues. 16 proteins of high documented relevance to HCC are highlighted in our data. We also identified changes of virus-infection-related proteins including PKM, CTPS1 and ALDOB in the HBV+ HCC subcohort. In conclusion, we demonstrate the practicality of performing proteomic analysis of biopsy-level tissue samples with PCT-SWATH methodology with moderate effort and within a relatively short timeframe.

systems biology↗

bioRxiv2018

Rapid proteotyping reveals cancer biology and drug response determinants in the NCI-60 cells

We describe the rapid and reproducible acquisition of quantitative proteome maps for the NCI-60 cancer cell lines and their use to reveal cancer biology and drug response determinants. Proteome datasets for the 60 cell lines were acquired in duplicate within 30 working days using pressure cycling technology and SWATH mass spectrometry. We consistently quantified 3,171 proteotypic proteins annotated in the SwissProt database across all cell lines, generating a data matrix with 0.1% missing values, allowing analyses of protein complexes and pathway activities across all the cancer cells. Systematic and integrative analysis of the genetic variation, mRNA expression and proteomic data of the NCI-60 cancer cell lines uncovered complementarity between different types of molecular data in the prediction of the response to 240 drugs. We additionally identified novel proteomic drug response determinants for clinically relevant chemotherapeutic and targeted therapies. We anticipate that this study represents a significant advance toward the translational application of proteotypes, which reveal biological insights that are easily missed in the absence of proteomic data.

systems biology↗