Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ

A modular open platform for systematic functional studies under physiological conditions

Any profound comprehension of gene function requires detailed information about the subcellular localization, molecular interactions and spatio-temporal dynamics of gene products. We developed a multifunctional integrase (MIN) tag for rapid and versatile genome engineering that serves not only as a genetic entry site for the Bxb1 integrase but also as a novel epitope tag for standardized detection and precipitation. For the systematic study of epigenetic factors, including Dnmt1, Dnmt3a, Dnmt3b, Tet1, Tet2, Tet3 and Uhrf1, we generated MIN-tagged embryonic stem cell lines and created a toolbox of prefabricated modules that can be integrated via Bxb1-mediated recombination. We used these functional modules to study protein interactions and their spatio-temporal dynamics as well as gene expression and specific mutations during cellular differentiation and in response to external stimuli. Our genome engineering strategy provides a versatile open platform for efficient generation of multiple isogenic cell lines to study gene function under physiological conditions.

The Impact II, a Very High-Resolution Quadrupole Time-of-Flight Instrument (QTOF) for Deep Shotgun Proteomics

Hybrid quadrupole time-of-flight (QTOF) mass spectrometry is one of the two major principles used in proteomics. Although based on simple fundamentals, it has over the last decades greatly evolved in terms of achievable resolution, mass accuracy, and dynamic range. The Bruker impact platform of QTOF instruments takes advantage of these developments and here we develop and evaluate the impact II for shotgun proteomics applications. Adaption of our heated liquid chromatography system achieved very narrow peptide elution peaks. The impact II is equipped with a new collision cell with both axial and radial ion ejection, more than doubling ion extraction at high tandem MS frequencies. The new reflectron and detector improve resolving power compared with the previous model up to 80%, i.e. to 40,000 at m/z 1222. We analyzed the ion current from the inlet capillary and found very high transmission (>80%) up to the collision cell. Simulation and measurement indicated 60% transfer into the flight tube. We adapted MaxQuant for QTOF data, improving absolute average mass deviations to better than 1.45 ppm. More than 4800 proteins can be identified in a single run of HeLa digest in a 90 min gradient. The workflow achieved high technical reproducibility (R2 > 0.99) and accurate fold change determination in spike-in experiments in complex mixtures. Using label-free quantification we rapidly quantified haploid against diploid yeast and characterized overall proteome differences in mouse cell lines originating from different tissues. Finally, after high pH reversed-phase fractionation we identified 9515 proteins in a triplicate measurement of HeLa peptide mixture and 11,257 proteins in single measurements of cerebellum—the highest proteome coverage reported with a QTOF instrument so far.

Characterization of the proteome of cytoplasmic lipid droplets in mouse enterocytes after a dietary fat challenge

Dietary fat absorption by the small intestine is a multistep process that regulates the uptake and delivery of essential nutrients and energy. One step of this process is the temporary storage of dietary fat in cytoplasmic lipid droplets (CLDs). The storage and mobilization of dietary fat is thought to be regulated by proteins that associate with the CLD; however, mechanistic details of this process are currently unknown. In this study we analyzed the proteome of CLDs isolated from enterocytes harvested from the small intestine of mice following a dietary fat challenge. In this analysis we identified 181 proteins associated with the CLD fraction, of which 37 are associated with known lipid related metabolic pathways. We confirmed the localization of several of these proteins on or around the CLD through confocal and electron microscopy, including perilipin 3, apolipoprotein A-IV, and acyl-CoA synthetase long-chain family member 5. The identification of the enterocyte CLD proteome provides new insight into potential regulators of CLD metabolism and the process of dietary fat absorption.

MS1 Peptide Ion Intensity Chromatograms in MS2 (SWATH) Data Independent Acquisitions. Improving Post Acquisition Analysis of Proteomic Experiments

Quantitative analysis of discovery-based proteomic workflows now relies on high-throughput large-scale methods for identification and quantitation of proteins and post-translational modifications. Advancements in label-free quantitative techniques, using either data-dependent or data-independent mass spectrometric acquisitions, have coincided with improved instrumentation featuring greater precision, increased mass accuracy, and faster scan speeds. We recently reported on a new quantitative method called MS1 Filtering (Schilling et al. (2012) Mol. Cell. Proteomics 11, 202–214) for processing data-independent MS1 ion intensity chromatograms from peptide analytes using the Skyline software platform. In contrast, data-independent acquisitions from MS2 scans, or SWATH, can quantify all fragment ion intensities when reference spectra are available. As each SWATH acquisition cycle typically contains an MS1 scan, these two independent label-free quantitative approaches can be acquired in a single experiment. Here, we have expanded the capability of Skyline to extract both MS1 and MS2 ion intensity chromatograms from a single SWATH data-independent acquisition in an Integrated Dual Scan Analysis approach. The performance of both MS1 and MS2 data was examined in simple and complex samples using standard concentration curves. Cases of interferences in MS1 and MS2 ion intensity data were assessed, as were the differentiation and quantitation of phosphopeptide isomers in MS2 scan data. In addition, we demonstrated an approach for optimization of SWATH m/z window sizes to reduce interferences using MS1 scans as a guide. Finally, a correlation analysis was performed on both MS1 and MS2 ion intensity data obtained from SWATH acquisitions on a complex mixture using a linear model that automatically removes signals containing interferences. This work demonstrates the practical advantages of properly acquiring and processing MS1 precursor data in addition to MS2 fragment ion intensity data in a data-independent acquisition (SWATH), and provides an approach to simultaneously obtain independent measurements of relative peptide abundance from a single experiment.

Phosphoproteomic Analysis of Cell-Based Resistance to BRAF Inhibitor Therapy in Melanoma

The treatment of melanoma by targeted inhibition of the mutated kinase BRAF with small molecules only temporarily suppresses metastatic disease. In the face of chemical inhibition tumor plasticity, both innate and adaptive, promotes survival through the biochemical and genetic reconfiguration of cellular pathways that can engage proliferative and migratory systems. To investigate this process, high-resolution mass spectrometry was used to characterize the phosphoproteome of this transition in vitro. A simple and accurate, label-free quantitative method was used to localize and quantitate thousands of phosphorylation events. We also correlated changes in the phosphoproteome with the proteome to more accurately determine changes in the activity of regulatory kinases determined by kinase landscape profiling. The abundance of phosphopeptides with sites that function in cytoskeletal regulation, GTP/GDP exchange, protein kinase C, IGF signaling, and melanosome maturation were highly divergent after transition to a drug resistant phenotype.

Systematic evaluation of label-free and super-SILAC quantification for proteome expression analysis

RATIONALE

Advanced implementations of mass spectrometry (MS)-based proteomics allow for comprehensive proteome expression profiling across many biological samples. The outcome of such studies critically depends on accurate and precise quantification, which has to be ensured for high-coverage proteome analysis possible on fast and sensitive mass spectrometers such as quadrupole orbitrap instruments.

METHODS

We conducted ultra-high-performance liquid chromatography (UHPLC)/MS experiments on a Q Exactive to systematically compare label-free proteome quantification across six human cancer cell lines with quantification against a shared reference mix generated by stable isotope labeling with amino acids in cell culture (super-SILAC).

RESULTS

Single-shot experiments identified on average about 5000 proteins in the label-free compared to about 3500 in super-SILAC experiments. Label-free quantification was slightly less precise than super-SILAC in replicate measurements, verifying previous results obtained for lower proteome coverage. Due to the higher number of quantified proteins, more significant differences were detected in label-free cell line comparisons, whereas a higher percentage of quantified proteins was identified as differentially expressed in super-SILAC experiments. Additional label-free replicate analyses effectively compensated for lower precision of quantification. Finally, peptide fractionation by high pH reversed-phase chromatography prior to LC/MS analysis further increased the robustness and precision of label-free quantification in conjunction with higher proteome coverage.

CONCLUSIONS

Our results benchmark and highlight the utility of label-free proteome quantification for applications such as target and biomarker discovery on state-of-the-art UHPLC/MS workflows.

Summarization vs Peptide-Based Models in Label-Free Quantitative Proteomics: Performance, Pitfalls, and Data Analysis Guidelines

Quantitative label-free mass spectrometry is increasingly used to analyze the proteomes of complex biological samples. However, the choice of appropriate data analysis methods remains a major challenge. We therefore provide a rigorous comparison between peptide-based models and peptide-summarization-based pipelines. We show that peptide-based models outperform summarization-based pipelines in terms of sensitivity, specificity, accuracy, and precision. We also demonstrate that the predefined FDR cutoffs for the detection of differentially regulated proteins can become problematic when differentially expressed (DE) proteins are highly abundant in one or more samples. Care should therefore be taken when data are interpreted from samples with spiked-in internal controls and from samples that contain a few very highly abundant proteins. We do, however, show that specific diagnostic plots can be used for assessing differentially expressed proteins and the overall quality of the obtained fold change estimates. Finally, our study also illustrates that imputation under the "missing by low abundance" assumption is beneficial for the detection of differential expression in proteins with low abundance, but it negatively affects moderately to highly abundant proteins. Hence, imputation strategies that are commonly implemented in standard proteomics software should be used with care.

Discovery of novel candidate urinary protein biomarkers for prostate cancer in a multiethnic cohort of South African patients via label-free mass spectrometry

PURPOSE

Improvement in diagnostic accuracy of prostate cancer (PCa) progression using MS-based methods to analyze biomarkers in our African, Caucasian, and Mixed Ancestry patients can advance early detection and treatment monitoring.

EXPERIMENTAL DESIGN

MS-based proteomic analysis of pooled (N = 36) and individual samples (N = 45) of PCa, benign prostatic hyperplasia, normal healthy controls, and patients with other uropathies was used to identify differences in proteomics profile. Samples were analyzed for potential biomarkers and proteome coverage in African, Caucasian, and Mixed Ancestry PCa patients.

RESULTS

A total of 1102 and 5595 protein groups and nonredundant peptides, respectively, were identified in the pooling experiments (FDR = 0.01). Twenty potential biomarkers in PCa were identified and fold differences ± 2SD were observed in 17 proteins using intensity-based absolute quantification. Analysis of 45 individual samples yielded 1545 and 9991 protein groups and nonredundant peptides, respectively. Seventy-three (73) proteins groups, including existing putative PCa biomarkers, were found to be potential biomarkers of PCa by label-free quantification and demonstrated ethnic trends within our PCa cohort.

CONCLUSION AND CLINICAL RELEVANCE

Urinary proteomics is a promising route to PCa biomarker discovery and may serve as source of ethnic-related biomarkers of PCa.

Regulation of liver metabolism by the endosomal GTPase Rab5

The liver maintains glucose and lipid homeostasis by adapting its metabolic activity to the energy needs of the organism. Communication between hepatocytes and extracellular environment via endocytosis is key to such homeostasis. Here, we addressed the question of whether endosomes are required for gluconeogenic gene expression. We took advantage of the loss of endosomes in the mouse liver upon Rab5 silencing. Strikingly, we found hepatomegaly and severe metabolic defects such as hypoglycemia, hypercholesterolemia, hyperlipidemia, and glycogen accumulation that phenocopied those found in von Gierke's disease, a glucose-6-phosphatase (G6Pase) deficiency. G6Pase deficiency alone can account for the reduction in hepatic glucose output and glycogen accumulation as determined by mathematical modeling. Interestingly, we uncovered functional alterations in the transcription factors, which regulate G6Pase expression. Our data highlight a requirement of Rab5 and the endosomal system for the regulation of gluconeogenic gene expression that has important implications for metabolic diseases.

DNA repair. Proteomics reveals dynamic assembly of repair complexes during bypass of DNA cross-links

DNA interstrand cross-links (ICLs) block replication fork progression by inhibiting DNA strand separation. Repair of ICLs requires sequential incisions, translesion DNA synthesis, and homologous recombination, but the full set of factors involved in these transactions remains unknown. We devised a technique called chromatin mass spectrometry (CHROMASS) to study protein recruitment dynamics during perturbed DNA replication in Xenopus egg extracts. Using CHROMASS, we systematically monitored protein assembly and disassembly on ICL-containing chromatin. Among numerous prospective DNA repair factors, we identified SLF1 and SLF2, which form a complex with RAD18 and together define a pathway that suppresses genome instability by recruiting the SMC5/6 cohesion complex to DNA lesions. Our study provides a global analysis of an entire DNA repair pathway and reveals the mechanism of SMC5/6 relocalization to damaged DNA in vertebrate cells.

LC-MS/MS-based serum proteomics for identification of candidate biomarkers for hepatocellular carcinoma

Associating changes in protein levels with the onset of cancer has been widely investigated to identify clinically relevant diagnostic biomarkers. In the present study, we analyzed sera from 205 patients recruited in the United States and Egypt for biomarker discovery using label-free proteomic analysis by LC-MS/MS. We performed untargeted proteomic analysis of sera to identify candidate proteins with statistically significant differences between hepatocellular carcinoma (HCC) and patients with liver cirrhosis. We further evaluated the significance of 101 proteins in sera from the same 205 patients through targeted quantitation by MRM on a triple quadrupole mass spectrometer. This led to the identification of 21 candidate protein biomarkers that were significantly altered in both the United States and Egyptian cohorts. Among the 21 candidates, ten were previously reported as HCC-associated proteins (eight exhibiting consistent trends with our observation), whereas 11 are new candidates discovered by this study. Pathway analysis based on the significant proteins reveals upregulation of the complement and coagulation cascades pathway and downregulation of the antigen processing and presentation pathway in HCC cases versus patients with liver cirrhosis. The results of this study demonstrate the power of combining untargeted and targeted quantitation methods for a comprehensive serum proteomic analysis, to evaluate changes in protein levels and discover novel diagnostic biomarkers. All MS data have been deposited in the ProteomeXchange with identifier PXD001171 (http://proteomecentral.proteomexchange.org/dataset/PXD001171).

Proteomic Investigation of the Response of Enterococcus faecalis V583 when Cultivated in Urine

Enterococcus faecalis is a robust bacterium, which is able to survive in and adapt to hostile environments such as the urinary tract and bladder. In this label-free quantitative proteomic study based on MaxQuant LFQ algorithms, we identified 127 proteins present in the secretome of the clinical vancomycin-resistant isolate E. faecalis V583 and we compared proteins secreted in the initial phase of cultivation in urine with the secretome during cultivation in standard laboratory medium, 2xYT. Of the 54 identified proteins predicted to be secreted, six were exclusively found after cultivation in urine including the virulence factor EfaA ("endocarditis specific antigen") and its homologue EF0577 ("adhesion lipoprotein"). These two proteins are both involved in manganese transport, known to be an important determinant of colonization and infection, and may additionally function as adhesins. Other detected urine-specific proteins are involved in peptide transport (EF0063 and EF3106) and protease inhibition (EF3054). In addition, we found an uncharacterized protein (EF0764), which had not previously been linked to the adaptation of V583 to a urine environment, and which is unique to E. faecalis. Proteins found in both environments included a histone-like protein, EF1550, that was up-regulated during cultivation in urine and that has a homologue in streptococci (HlpA) known to be involved in bacterial adhesion to host cells. Up-regulated secreted proteins included autolysins. These results from secretome analyses are largely compatible with previously published data from transcriptomics studies. All in all, the present data indicate that transport, in particular metal transport, adhesion, cell wall remodelling and the unknown function carried out by the unique EF0764 are important for enterococcal adaptation to the urine environment. These results provide a basis for a more targeted exploration of novel proteins involved in the adaptability and pathogenicity of E. faecalis.

A Double-Barrel Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) System to Quantify 96 Interactomes per Day

The field of proteomics has evolved hand-in-hand with technological advances in LC-MS/MS systems, now enabling the analysis of very deep proteomes in a reasonable time. However, most applications do not deal with full cell or tissue proteomes but rather with restricted subproteomes relevant for the research context at hand or resulting from extensive fractionation. At the same time, investigation of many conditions or perturbations puts a strain on measurement capacity. Here, we develop a high-throughput workflow capable of dealing with large numbers of low or medium complexity samples and specifically aim at the analysis of 96-well plates in a single day (15 min per sample). We combine parallel sample processing with a modified liquid chromatography platform driving two analytical columns in tandem, which are coupled to a quadrupole Orbitrap mass spectrometer (Q Exactive HF). The modified LC platform eliminates idle time between measurements, and the high sequencing speed of the Q Exactive HF reduces required measurement time. We apply the pipeline to the yeast chromatin remodeling landscape and demonstrate quantification of 96 pull-downs of chromatin complexes in about 1 day. This is achieved with only 500 μg input material, enabling yeast cultivation in a 96-well format. Our system retrieved known complex-members and the high throughput allowed probing with many bait proteins. Even alternative complex compositions were detectable in these very short gradients. Thus, sample throughput, sensitivity and LC/MS-MS duty cycle are improved severalfold compared with established workflows. The pipeline can be extended to different types of interaction studies and to other medium complexity proteomes.

Bottom-up proteomic analysis of single HCT 116 colon carcinoma multicellular spheroids

RATIONALE

Proteomic analysis of single multicellular spheroids has not been previously reported. As three-dimensional cell cultures are an increasingly popular model system for biological research, there is interest in obtaining proteomic profiles of these samples. We investigated the proteome of single HCT 116 multicellular spheroids using protocols optimized for small sample sizes.

METHODS

Six biological replicates were analyzed via microscopy for size. Total protein content was assessed via the bicinchoninic acid assay (BCA assay). Five separate biological replicate spheroids were analyzed via mass spectrometry in technical duplicate. An ultra-performance liquid chromatography (UPLC) system coupled with an LTQ Orbitrap Velos was used for peptide separation, analysis, and identification.

RESULTS

The average diameter of six replicate HCT 116 spheroids was 940 ± 30 µm and the average total protein amount was determined to be 39 ± 4 µg. At least 1300 protein groups were identified in each single LC/MS/MS run with 10% of the material from each single spheroid loaded. Database search results showed variation between spheroid protein group identifications. Pearson correlations show that the disparity in identifications is due to random variations in spectra and protocol.

CONCLUSIONS

We detected more than 1350 protein groups in each replicate HCT 116 spheroid. While some variation was detected between replicates, differences in the number of protein groups identified were determined to be the result of random variations in mass spectra acquisition.

Secretome of Trichoderma interacting with maize roots: role in induced systemic resistance

Trichoderma virens is a biocontrol agent used in agriculture to antagonize pathogens of crop plants. In addition to direct mycoparasitism of soil-borne fungal pathogens, T. virens interacts with roots. This interaction induces systemic resistance (ISR), which reduces disease in above-ground parts of the plant. In the molecular dialog between fungus and plant leading to ISR, proteins secreted by T. virens provide signals. Only a few such proteins have been characterized previously. To study the secretome, proteins were characterized from hydroponic culture systems with T. virens alone or with maize seedlings, and combined with a bioassay for ISR in maize leaves infected by the pathogen Cochliobolus heterostrophus. The secreted protein fraction from coculture of maize roots and T. virens (Tv+M) was found to have a higher ISR activity than from T. virens grown alone (Tv). A total of 280 fungal proteins were identified, 66 showing significant differences in abundance between the two conditions: 32 were higher in Tv+M and 34 were higher in Tv. Among the 34 found in higher abundance in Tv and negatively regulated by roots were 13 SSCPs (small, secreted, cysteine rich proteins), known to be important in the molecular dialog between plants and fungi. The role of four SSCPs in ISR was studied by gene knockout. All four knockout lines showed better ISR activity than WT without affecting colonization of maize roots. Furthermore, the secreted protein fraction from each of the mutant lines showed improved ISR activity compared with WT. These SSCPs, apparently, act as negative effectors reducing the defense levels in the plant and may be important for the fine tuning of ISR by Trichoderma. The down-regulation of SSCPs in interaction with plant roots implies a revision of the current model for the Trichoderma-plant symbiosis and its induction of resistance to pathogens.

MS1-based label-free proteomics using a quadrupole orbitrap mass spectrometer

Presented is a data set for benchmarking MS1-based label-free quantitative proteomics using a quadrupole orbitrap mass spectrometer. Escherichia coli digest was spiked into a HeLa digest in four different concentrations, simulating protein expression differences in a background of an unchanged complex proteome. The data set provides a unique opportunity to evaluate the proteomic platform (instrumentation and software) in its ability to perform MS1-intensity-based label-free quantification. We show that the presented combination of informatics and instrumentation produces high precision and quantification accuracy. The data were also used to compare different quantitative protein inference methods such as iBAQ and Hi-N. The data can also be used as a resource for development and optimization of proteomics informatics tools, thus the raw data have been deposited to ProteomeXchange with identifier PXD001385.

Label-free proteomics uncovers energy metabolism and focal adhesion regulations responsive for endometrium receptivity

The menstrual cycle of the female uterus leads to periodic changes of the endometrium. These changes are important for developing the endometrial receptivity and for achieving competency of embryo implantation. However, the molecular events underlying the endometrial receptivity process remain poorly understood. Here we applied an LC-MS-based label-free quantitative proteomic approach to compare the endometrial tissues in the midsecretory (receptive) phase with the endometrial tissues in the proliferative phase from age-matched woman (n = 6/group). The proteomes of endometrial tissues were extracted using an SDS-based detergent, digested by the filter-aided sample preparation procedures, and subsequently analyzed by nano-LC-MS/MS (Orbitrap XL) with a 4 h gradient. Reliable protein expression profiles were reproducibly obtained from the endometrial tissues in the receptive and proliferative phases. A total of 2138 protein groups were quantified under highly stringent criteria with a false discovery rate of <1% for peptide and protein groups. Among these proteins, 317 proteins had differences in expression that were statistically significant between the receptive and proliferative phases. Direct protein-protein interaction network analyses of these significantly changed proteins showed that the up-regulation of creatine kinase B-type (CKB) in the receptive phase may be related to endometrium receptivity. The interaction network also showed that proteins related to cell-cell adhesion were down-regulated. Moreover, the results from KEGG pathway analyses are consistent with the protein-protein interaction results. The proteins, including alpha-actinin (ACTN), extracellular matrix proteins, integrin alpha-V, and so on, that are involved in the focal adhesion pathway were down-regulated in the receptive phase compared with the proliferative phase, which may facilitate the implantation of the fertilized ovum. Selected proteins were validated by Western blot analysis and indirect immunofluorescence, including the up-regulation of CKB and down-regulation ACTN in the receptive phase. In summary, our proteomic analysis study shows potential for predicting the endometrial remodeling from the proliferative to the receptivity phase in women, and these results also reveal the key biological mechanisms (such as energy metabolism and focal adhesion) underlying human endometrial receptivity.

Visualization of LC-MS/MS proteomics data in MaxQuant

Modern software platforms enable the analysis of shotgun proteomics data in an automated fashion resulting in high quality identification and quantification results. Additional understanding of the underlying data can be gained with the help of advanced visualization tools that allow for easy navigation through large LC‐MS/MS datasets potentially consisting of terabytes of raw data. The updated MaxQuant version has a map navigation component that steers the users through mass and retention time‐dependent mass spectrometric signals. It can be used to monitor a peptide feature used in label‐free quantification over many LC‐MS runs and visualize it with advanced 3D graphic models. An expert annotation system aids the interpretation of the MS/MS spectra used for the identification of these peptide features.

Proteomics-based metabolic modeling reveals that fatty acid oxidation (FAO) controls endothelial cell (EC) permeability

Endothelial cells (ECs) play a key role to maintain the functionality of blood vessels. Altered EC permeability causes severe impairment in vessel stability and is a hallmark of pathologies such as cancer and thrombosis. Integrating label-free quantitative proteomics data into genome-wide metabolic modeling, we built up a model that predicts the metabolic fluxes in ECs when cultured on a tridimensional matrix and organize into a vascular-like network. We discovered how fatty acid oxidation increases when ECs are assembled into a fully formed network that can be disrupted by inhibiting CPT1A, the fatty acid oxidation rate-limiting enzyme. Acute CPT1A inhibition reduces cellular ATP levels and oxygen consumption, which are restored by replenishing the tricarboxylic acid cycle. Remarkably, global phosphoproteomic changes measured upon acute CPT1A inhibition pinpointed altered calcium signaling. Indeed, CPT1A inhibition increases intracellular calcium oscillations. Finally, inhibiting CPT1A induces hyperpermeability in vitro and leakage of blood vessel in vivo, which were restored blocking calcium influx or replenishing the tricarboxylic acid cycle. Fatty acid oxidation emerges as central regulator of endothelial functions and blood vessel stability and druggable pathway to control pathological vascular permeability.

Multiplexed, Quantitative Workflow for Sensitive Biomarker Discovery in Plasma Yields Novel Candidates for Early Myocardial Injury

We have developed a novel plasma protein analysis platform with optimized sample preparation, chromatography, and MS analysis protocols. The workflow, which utilizes chemical isobaric mass tag labeling for relative quantification of plasma proteins, achieves far greater depth of proteome detection and quantification while simultaneously having increased sample throughput than prior methods. We applied the new workflow to a time series of plasma samples from patients undergoing a therapeutic, "planned" myocardial infarction for hypertrophic cardiomyopathy, a unique human model in which each person serves as their own biologic control. Over 5300 proteins were confidently identified in our experiments with an average of 4600 proteins identified per sample (with two or more distinct peptides identified per protein) using iTRAQ four-plex labeling. Nearly 3400 proteins were quantified in common across all 16 patient samples. Compared with a previously published label-free approach, the new method quantified almost fivefold more proteins/sample and provided a six- to nine-fold increase in sample analysis throughput. Moreover, this study provides the largest high-confidence plasma proteome dataset available to date. The reliability of relative quantification was also greatly improved relative to the label-free approach, with measured iTRAQ ratios and temporal trends correlating well with results from a 23-plex immunoMRM (iMRM) assay containing a subset of the candidate proteins applied to the same patient samples. The functional importance of improved detection and quantification was reflected in a markedly expanded list of significantly regulated proteins that provided many new candidate biomarker proteins. Preliminary evaluation of plasma sample labeling with TMT six-plex and ten-plex reagents suggests that even further increases in multiplexing of plasma analysis are practically achievable without significant losses in depth of detection relative to iTRAQ four-plex. These results obtained with our novel platform provide clear demonstration of the value of using isobaric mass tag reagents in plasma-based biomarker discovery experiments.

Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues

The data-independent acquisition (DIA) approach has recently been introduced as a novel mass spectrometric method that promises to combine the high content aspect of shotgun proteomics with the reproducibility and precision of selected reaction monitoring. Here, we evaluate, whether SWATH-MS type DIA effectively translates into a better protein profiling as compared with the established shotgun proteomics.

We implemented a novel DIA method on the widely used Orbitrap platform and used retention-time-normalized (iRT) spectral libraries for targeted data extraction using Spectronaut. We call this combination hyper reaction monitoring (HRM). Using a controlled sample set, we show that HRM outperformed shotgun proteomics both in the number of consistently identified peptides across multiple measurements and quantification of differentially abundant proteins. The reproducibility of HRM in peptide detection was above 98%, resulting in quasi complete data sets compared with 49% of shotgun proteomics.

Utilizing HRM, we profiled acetaminophen (APAP)¹-treated three-dimensional human liver microtissues. An early onset of relevant proteome changes was revealed at subtoxic doses of APAP. Further, we detected and quantified for the first time human NAPQI-protein adducts that might be relevant for the toxicity of APAP. The adducts were identified on four mitochondrial oxidative stress related proteins (GATM, PARK7, PRDX6, and VDAC2) and two other proteins (ANXA2 and FTCD).

Our findings imply that DIA should be the preferred method for quantitative protein profiling.

Global analysis of protein N-myristoylation and exploration of N-myristoyltransferase as a drug target in the neglected human pathogen Leishmania donovani

N-Myristoyltransferase (NMT) modulates protein function through the attachment of the lipid myristate to the N terminus of target proteins, and is a promising drug target in eukaryotic parasites such as Leishmania donovani. Only a small number of NMT substrates have been characterized in Leishmania, and a global picture of N-myristoylation is lacking. Here, we use metabolic tagging with an alkyne-functionalized myristic acid mimetic in live parasites followed by downstream click chemistry and analysis to identify lipidated proteins in both the promastigote (extracellular) and amastigote (intracellular) life stages. Quantitative chemical proteomics is used to profile target engagement by NMT inhibitors, and to define the complement of N-myristoylated proteins. Our results provide new insight into the multiple pathways modulated by NMT and the pleiotropic effects of NMT inhibition. This work constitutes the first global experimental analysis of protein lipidation in Leishmania, and reveals the extent of NMT-related biology yet to be explored for this neglected human pathogen.

Optimized chemical proteomics assay for kinase inhibitor profiling

Solid supported probes have proven to be an efficient tool for chemical proteomics. The kinobeads technology features kinase inhibitors covalently attached to Sepharose for affinity enrichment of kinomes from cell or tissue lysates. This technology, combined with quantitative mass spectrometry, is of particular interest for the profiling of kinase inhibitors. It often leads to the identification of new targets for medicinal chemistry campaigns where it allows a two-in-one binding and selectivity assay. The assay can also uncover resistance mechanisms and molecular sources of toxicity. Here we report on the optimization of the kinobead assay resulting in the combination of five chemical probes and four cell lines to cover half the human kinome in a single assay (∼ 260 kinases). We show the utility and large-scale applicability of the new version of kinobeads by reprofiling the small molecule kinase inhibitors Alvocidib, Crizotinib, Dasatinib, Fasudil, Hydroxyfasudil, Nilotinib, Ibrutinib, Imatinib, and Sunitinib.

Analysis of the outer membrane proteome and secretome of Bacteroides fragilis reveals a multiplicity of secretion mechanisms

Bacteroides fragilis is a widely distributed member of the human gut microbiome and an opportunistic pathogen. Cell surface molecules produced by this organism likely play important roles in colonization, communication with other microbes, and pathogenicity, but the protein composition of the outer membrane (OM) and the mechanisms used to transport polypeptides into the extracellular space are poorly characterized. Here we used LC-MS/MS to analyze the OM proteome and secretome of B. fragilis NCTC 9343 grown under laboratory conditions. Of the 229 OM proteins that we identified, 108 are predicted to be lipoproteins, and 61 are predicted to be TonB-dependent transporters. Based on their proximity to genes encoding TonB-dependent transporters, many of the lipoprotein genes likely encode proteins involved in nutrient or small molecule uptake. Interestingly, protease accessibility and biotinylation experiments indicated that an unusually large fraction of the lipoproteins are cell-surface exposed. We also identified three proteins that are members of a novel family of autotransporters, multiple potential type I protein secretion systems, and proteins that appear to be components of a type VI secretion apparatus. The secretome consisted of lipoproteins and other proteins that might be substrates of the putative type I or type VI secretion systems. Our proteomic studies show that B. fragilis differs considerably from well-studied Gram-negative bacteria such as Escherichia coli in both the spectrum of OM proteins that it produces and the range of secretion strategies that it utilizes.

In-depth evaluation of software tools for data-independent acquisition based label-free quantification

Label-free quantification (LFQ) based on data-independent acquisition workflows currently experiences increasing popularity. Several software tools have been recently published or are commercially available. The present study focuses on the evaluation of three different software packages (Progenesis, synapter, and ISOQuant) supporting ion mobility enhanced data-independent acquisition data. In order to benchmark the LFQ performance of the different tools, we generated two hybrid proteome samples of defined quantitative composition containing tryptically digested proteomes of three different species (mouse, yeast, Escherichia coli). This model dataset simulates complex biological samples containing large numbers of both unregulated (background) proteins as well as up- and downregulated proteins with exactly known ratios between samples. We determined the number and dynamic range of quantifiable proteins and analyzed the influence of applied algorithms (retention time alignment, clustering, normalization, etc.) on quantification results. Analysis of technical reproducibility revealed median coefficients of variation of reported protein abundances below 5% for MS(E) data for Progenesis and ISOQuant. Regarding accuracy of LFQ, evaluation with synapter and ISOQuant yielded superior results compared to Progenesis. In addition, we discuss reporting formats and user friendliness of the software packages. The data generated in this study have been deposited to the ProteomeXchange Consortium with identifier PXD001240 (http://proteomecentral.proteomexchange.org/dataset/PXD001240).

Important options available--from start to finish--for translating proteomics results to clinical chemistry

In the realm of clinical chemistry, the field of clinical proteomics, that is, the application of proteomic methods for understanding mechanisms and enabling diagnosis, prediction, measurement of activity, and treatment response in disease, is first and foremost a discovery and research tool that feeds assay development downstream. Putative new assay candidates generated by proteomics discovery projects compete with well-established assays with known indications, well-described performance, and of known value in specific clinical settings. Careful attention to the many options available in the design, execution, and interpretation of clinical proteomics studies is thus necessary for translation into clinical practice. We here review and discuss important options associated with clinical proteomics endeavors stretching from the planning phases to the final use in clinical chemistry.

Deep proteomics of mouse skeletal muscle enables quantitation of protein isoforms, metabolic pathways, and transcription factors

Skeletal muscle constitutes 40% of individual body mass and plays vital roles in locomotion and whole-body metabolism. Proteomics of skeletal muscle is challenging because of highly abundant contractile proteins that interfere with detection of regulatory proteins. Using a state-of-the art MS workflow and a strategy to map identifications from the C2C12 cell line model to tissues, we identified a total of 10,218 proteins, including skeletal muscle specific transcription factors like myod1 and myogenin and circadian clock proteins. We obtain absolute abundances for proteins expressed in a muscle cell line and skeletal muscle, which should serve as a valuable resource. Quantitation of protein isoforms of glucose uptake signaling pathways and in glucose and lipid metabolic pathways provides a detailed metabolic map of the cell line compared with tissue. This revealed unexpectedly complex regulation of AMP-activated protein kinase and insulin signaling in muscle tissue at the level of enzyme isoforms.

Bifunctional fatty acid chemical reporter for analyzing S-palmitoylated membrane protein-protein interactions in mammalian cells

Studying the functions of S-palmitoylated proteins in cells can be challenging due to the membrane targeting property and dynamic nature of protein S-palmitoylation. New strategies are therefore needed to specifically capture S-palmitoylated protein complexes in cellular membranes for dissecting their functions in vivo. Here we present a bifunctional fatty acid chemical reporter, x-alk-16, which contains an alkyne and a diazirine, for metabolic labeling of S-palmitoylated proteins and photo-cross-linking of their involved protein complexes in mammalian cells. We demonstrate that x-alk-16 can be metabolically incorporated into known S-palmitoylated proteins such as H-Ras and IFITM3, a potent antiviral protein, and induce covalent cross-linking of IFITM3 oligomerization as well as its specific interactions with other membrane proteins upon in-cell photoactivation. Moreover, integration of x-alk-16-induced photo-cross-linking with label-free quantitative proteomics allows identification of new IFITM3 interacting proteins.

Global quantitative proteomics reveals novel factors in the ecdysone signaling pathway in Drosophila melanogaster

The ecdysone signaling pathway plays a major role in various developmental transitions in insects. Recent advances in the understanding of ecdysone action have relied to a large extent on the application of molecular genetic tools in Drosophila. Here, we used a comprehensive quantitative SILAC MS-based approach to study the global, dynamic proteome of a Drosophila cell line to investigate how hormonal signals are transduced into specific cellular responses. Global proteome data after ecdysone treatment after various time points were then integrated with transcriptome data. We observed a substantial overlap in terms of affected targets between the dynamic proteome and transcriptome, although there were some clear differences in timing effects. Also, downregulation of several specific mRNAs did not always correlate with downregulation of their corresponding protein counterparts, and in some cases there was no correlation between transcriptome and proteome dynamics whatsoever. In addition, we performed a comprehensive interactome analysis of EcR, the major target of ecdysone. Proteins copurified with EcR include factors involved in transcription, chromatin remodeling, ecdysone signaling, ecdysone biosynthesis, and other signaling pathways. Novel ecdysone-responsive proteins identified in this study might link previously unknown proteins to the ecdysone signaling pathway and might be novel targets for developmental studies. To our knowledge, this is the first time that ecdysone signaling is studied by global quantitative proteomics. All MS data have been deposited in the ProteomeXchange with identifier PXD001455 (http://proteomecentral.proteomexchange.org/dataset/PXD001455).

Proteomic analysis of the response to cell cycle arrests in human myeloid leukemia cells

Previously, we analyzed protein abundance changes across a 'minimally perturbed' cell cycle by using centrifugal elutriation to differentially enrich distinct cell cycle phases in human NB4 cells (Ly et al., 2014). In this study, we compare data from elutriated cells with NB4 cells arrested at comparable phases using serum starvation, hydroxyurea, or RO-3306. While elutriated and arrested cells have similar patterns of DNA content and cyclin expression, a large fraction of the proteome changes detected in arrested cells are found to reflect arrest-specific responses (i.e., starvation, DNA damage, CDK1 inhibition), rather than physiological cell cycle regulation. For example, we show most cells arrested in G2 by CDK1 inhibition express abnormally high levels of replication and origin licensing factors and are likely poised for genome re-replication. The protein data are available in the Encyclopedia of Proteome Dynamics (

Extracellular peptidases of the cereal pathogen Fusarium graminearum

The plant pathogenic fungus Fusarium graminearum (Fgr) creates economic and health risks in cereals agriculture. Fgr causes head blight (or scab) of wheat and stalk rot of corn, reducing yield, degrading grain quality, and polluting downstream food products with mycotoxins. Fungal plant pathogens must secrete proteases to access nutrition and to breakdown the structural protein component of the plant cell wall. Research into the proteolytic activity of Fgr is hindered by the complex nature of the suite of proteases secreted. We used a systems biology approach comprising genome analysis, transcriptomics and label-free quantitative proteomics to characterize the peptidases deployed by Fgr during growth. A combined analysis of published microarray transcriptome datasets revealed seven transcriptional groupings of peptidases based on in vitro growth, in planta growth, and sporulation behaviors. A high resolution mass spectrometry-based proteomics analysis defined the extracellular proteases secreted by F. graminearum. A meta-classification based on sequence characters and transcriptional/translational activity in planta and in vitro provides a platform to develop control strategies that target Fgr peptidases.

Evolutionary acquisition of cysteines determines FOXO paralog-specific redox signaling

Reduction-oxidation (redox) signaling, the translation of an oxidative intracellular environment into a cellular response, is mediated by the reversible oxidation of specific cysteine thiols. The latter can result in disulfide formation between protein hetero- or homodimers that alter protein function until the local cellular redox environment has returned to the basal state. We have previously shown that this mechanism promotes the nuclear localization and activity of the Forkhead Box O4 (FOXO4) transcription factor.

AIMS

In this study, we sought to investigate whether redox signaling differentially controls the human FOXO3 and FOXO4 paralogs.

RESULTS

We present evidence that FOXO3 and FOXO4 have acquired paralog-specific cysteines throughout vertebrate evolution. Using a proteome-wide screen, we identified previously unknown redox-dependent FOXO3 interaction partners. The nuclear import receptors Importin-7 (IPO7) and Importin-8 (IPO8) form a disulfide-dependent heterodimer with FOXO3, which is required for its reactive oxygen species-induced nuclear translocation. FOXO4 does not interact with IPO7 or IPO8.

INNOVATION AND CONCLUSION

IPO7 and IPO8 control the nuclear import of FOXO3, but not FOXO4, in a redox-sensitive and disulfide-dependent manner. Our findings suggest that evolutionary acquisition of cysteines has contributed to regulatory divergence of FOXO paralogs, and that phylogenetic analysis can aid in the identification of cysteines involved in redox signaling.

The effector repertoire of Fusarium oxysporum determines the tomato xylem proteome composition following infection

Plant pathogens secrete small proteins, of which some are effectors that promote infection. During colonization of the tomato xylem vessels the fungus Fusarium oxysporum f.sp. lycopersici (Fol) secretes small proteins that are referred to as SIX (Secreted In Xylem) proteins. Of these, Six1 (Avr3), Six3 (Avr2), Six5, and Six6 are required for full virulence, denoting them as effectors. To investigate their activities in the plant, the xylem sap proteome of plants inoculated with Fol wild-type or either AVR2, AVR3, SIX2, SIX5, or SIX6 knockout strains was analyzed with nano-Liquid Chromatography-Mass Spectrometry (nLC-MSMS). Compared to mock-inoculated sap 12 additional plant proteins appeared while 45 proteins were no longer detectable in the xylem sap of Fol-infected plants. Of the 285 proteins found in both uninfected and infected plants the abundance of 258 proteins changed significantly following infection. The xylem sap proteome of plants infected with four Fol effector knockout strains differed significantly from plants infected with wild-type Fol, while that of the SIX2-knockout inoculated plants remained unchanged. Besides an altered abundance of a core set of 24 differentially accumulated proteins (DAPs), each of the four effector knockout strains affected specifically the abundance of a subset of DAPs. Hence, Fol effectors have both unique and shared effects on the composition of the tomato xylem sap proteome.

Ligand-independent EPHA2 signaling drives the adoption of a targeted therapy-mediated metastatic melanoma phenotype

Many patients with BRAF inhibitor resistance can develop disease at new sites, suggesting that drug-induced selection pressure drives metastasis. Here, we used mass spectrometry-based phosphoproteomic screening to uncover ligand-independent EPHA2 signaling as an adaptation to BRAF inhibitor therapy that led to the adoption of a metastatic phenotype. The EPHA2-mediated invasion was AKT-dependent and readily reversible upon removal of the drug as well as through PI3K and AKT inhibition. In xenograft models, BRAF inhibition led to the development of EPHA2-positive metastases. A retrospective analysis of patients with melanoma on BRAF inhibitor therapy showed that 68% of those failing therapy develop metastases at new disease sites, compared with 35% of patients on dacarbazine. Further IHC staining of melanoma specimens taken from patients on BRAF inhibitor therapy as well as metastatic samples taken from patients failing therapy showed increased EPHA2 staining. We suggest that inhibition of ligand-independent EPHA2 signaling may limit metastases associated with BRAF inhibitor therapy.

SIGNIFICANCE

This study provides evidence that BRAF inhibition promotes the adoption of a reversible, therapy-driven metastatic phenotype in melanoma. The cotargeting of ligand-independent EPHA2 signaling and BRAF may be one strategy to prevent the development of therapy-mediated disease at new sites.

A systems-wide screen identifies substrates of the SCFβTrCP ubiquitin ligase

Cellular proteins are degraded by the ubiquitin-proteasome system (UPS) in a precise and timely fashion. Such precision is conferred by the high substrate specificity of ubiquitin ligases. Identification of substrates of ubiquitin ligases is crucial not only to unravel the molecular mechanisms by which the UPS controls protein degradation but also for drug discovery purposes because many established UPS substrates are implicated in disease. We developed a combined bioinformatics and affinity purification-mass spectrometry (AP-MS) workflow for the system-wide identification of substrates of SCF(βTrCP), a member of the SCF family of ubiquitin ligases. These ubiquitin ligases are characterized by a multisubunit architecture typically consisting of the invariable subunits Rbx1, Cul1, and Skp1 and one of 69 F-box proteins. The F-box protein of this member of the family is βTrCP. SCF(βTrCP) binds, through the WD40 repeats of βTrCP, to the DpSGXX(X)pS diphosphorylated motif in its substrates. We recovered 27 previously reported SCF(βTrCP) substrates, of which 22 were verified by two independent statistical protocols, thereby confirming the reliability of this approach. In addition to known substrates, we identified 221 proteins that contained the DpSGXX(X)pS motif and also interacted specifically with the WD40 repeats of βTrCP. Thus, with SCF(βTrCP), as the example, we showed that integration of structural information, AP-MS, and degron motif mining constitutes an effective method to screen for substrates of ubiquitin ligases.

Overexpression of Q-rich prion-like proteins suppresses polyQ cytotoxicity and alters the polyQ interactome

Expansion of a poly-glutamine (polyQ) repeat in a group of functionally unrelated proteins is the cause of several inherited neurodegenerative disorders, including Huntington's disease. The polyQ length-dependent aggregation and toxicity of these disease proteins can be reproduced in Saccharomyces cerevisiae. This system allowed us to screen for genes that when overexpressed reduce the toxic effects of an N-terminal fragment of mutant huntingtin with 103 Q. Surprisingly, among the identified suppressors were three proteins with Q-rich, prion-like domains (PrDs): glycine threonine serine repeat protein (Gts1p), nuclear polyadenylated RNA-binding protein 3, and minichromosome maintenance protein 1. Overexpression of the PrD of Gts1p, containing an imperfect 28 residue glutamine-alanine repeat, was sufficient for suppression of toxicity. Association with this discontinuous polyQ domain did not prevent 103Q aggregation, but altered the physical properties of the aggregates, most likely early in the assembly pathway, as reflected in their increased SDS solubility. Molecular simulations suggested that Gts1p arrests the aggregation of polyQ molecules at the level of nonfibrillar species, acting as a cap that destabilizes intermediates on path to form large fibrils. Quantitative proteomic analysis of polyQ interactors showed that expression of Gts1p reduced the interaction between polyQ and other prion-like proteins, and enhanced the association of molecular chaperones with the aggregates. These findings demonstrate that short, Q-rich peptides are able to shield the interactive surfaces of toxic forms of polyQ proteins and direct them into nontoxic aggregates.

E-cadherin interactome complexity and robustness resolved by quantitative proteomics

E-cadherin-mediated cell-cell adhesion and signaling plays an essential role in development and maintenance of healthy epithelial tissues. Adhesiveness mediated by E-cadherin is conferred by its extracellular cadherin domains and is regulated by an assembly of intracellular adaptors and enzymes associated with its cytoplasmic tail. We used proximity biotinylation and quantitative proteomics to identify 561 proteins in the vicinity of the cytoplasmic tail of E-cadherin. In addition, we used proteomics to identify proteins associated with E-cadherin-containing adhesion plaques from a cell-glass interface, which enabled the assignment of cellular localization to putative E-cadherin-interacting proteins. Moreover, by tagging identified proteins with GFP (green fluorescent protein), we determined the subcellular localization of 83 putative E-cadherin-proximal proteins and identified 24 proteins that were previously uncharacterized as part of adherens junctions. We constructed and characterized a comprehensive E-cadherin interaction network of 79 published and 394 previously uncharacterized proteins using a structure-informed database of protein-protein interactions. Finally, we found that calcium chelation, which disrupts the interaction of the extracellular E-cadherin domains, did not disrupt most intracellular protein interactions with E-cadherin, suggesting that the E-cadherin intracellular interactome is predominantly independent of cell-cell adhesion.

Cell-type-resolved quantitative proteomics of murine liver

Mass spectrometry (MS)-based proteomics provides a powerful approach to globally investigate the biological function of individual cell types in mammalian organs. Here, we applied this technology to the in-depth analysis of purified hepatic cell types from mouse. We quantified 11,520 proteins, making this the most comprehensive proteomic resource of any organ to date. Global protein copy number determination demonstrated that a large proportion of the hepatocyte proteome is dedicated to fatty acid and xenobiotic metabolism. We identified as-yet-unknown components of the TGF-β signaling pathway and extracellular matrix in hepatic stellate cells, uncovering their regulative role in liver physiology. Moreover, our high-resolution proteomic data set enabled us to compare the distinct functional roles of hepatic cell types in cholesterol flux, cellular trafficking, and growth factor receptor signaling. This study provides a comprehensive resource for liver biology and biomedicine.

A "proteomic ruler" for protein copy number and concentration estimation without spike-in standards

Absolute protein quantification using mass spectrometry (MS)-based proteomics delivers protein concentrations or copy numbers per cell. Existing methodologies typically require a combination of isotope-labeled spike-in references, cell counting, and protein concentration measurements. Here we present a novel method that delivers similar quantitative results directly from deep eukaryotic proteome datasets without any additional experimental steps. We show that the MS signal of histones can be used as a "proteomic ruler" because it is proportional to the amount of DNA in the sample, which in turn depends on the number of cells. As a result, our proteomic ruler approach adds an absolute scale to the MS readout and allows estimation of the copy numbers of individual proteins per cell. We compare our protein quantifications with values derived via the use of stable isotope labeling by amino acids in cell culture and protein epitope signature tags in a method that combines spike-in protein fragment standards with precise isotope label quantification. The proteomic ruler approach yields quantitative readouts that are in remarkably good agreement with results from the precision method. We attribute this surprising result to the fact that the proteomic ruler approach omits error-prone steps such as cell counting or protein concentration measurements. The proteomic ruler approach is readily applicable to any deep eukaryotic proteome dataset-even in retrospective analysis-and we demonstrate its usefulness with a series of mouse organ proteomes.

Super-SILAC: current trends and future perspectives

Stable isotope labeling with amino acids in cell culture (SILAC) has risen as a powerful quantification technique in mass spectrometry (MS)-based proteomics in classical and modified forms. Previously, SILAC was limited to cultured cells because of the requirement of active protein synthesis; however, in recent years, it was expanded to model organisms and tissue samples. Specifically, the super-SILAC technique uses a mixture of SILAC-labeled cells as a spike-in standard for accurate quantification of unlabeled samples, thereby enabling quantification of human tissue samples. Here, we highlight the recent developments in super-SILAC and its application to the study of clinical samples, secretomes, post-translational modifications and organelle proteomes. Finally, we propose super-SILAC as a robust and accurate method that can be commercialized and applied to basic and clinical research.

Proteome sequencing goes deep

Advances in mass spectrometry (MS) have transformed the scope and impact of protein characterization efforts. Identifying hundreds of proteins from rather simple biological matrices, such as yeast, was a daunting task just a few decades ago. Now, expression of more than half of the estimated ∼20,000 human protein coding genes can be confirmed in record time and from minute sample quantities. Access to proteomic information at such unprecedented depths has been fueled by strides in every stage of the shotgun proteomics workflow-from sample processing to data analysis-and promises to revolutionize our understanding of the causes and consequences of proteome variation.

Accurate protein complex retrieval by affinity enrichment mass spectrometry (AE-MS) rather than affinity purification mass spectrometry (AP-MS)

Protein–protein interactions are fundamental to the understanding of biological processes. Affinity purification coupled to mass spectrometry (AP-MS) is one of the most promising methods for their investigation. Previously, complexes were purified as much as possible, frequently followed by identification of individual gel bands. However, todays mass spectrometers are highly sensitive, and powerful quantitative proteomics strategies are available to distinguish true interactors from background binders. Here we describe a high performance affinity enrichment-mass spectrometry method for investigating protein–protein interactions, in which no attempt at purifying complexes to homogeneity is made. Instead, we developed analysis methods that take advantage of specific enrichment of interactors in the context of a large amount of unspecific background binders. We perform single-step affinity enrichment of endogenously expressed GFP-tagged proteins and their interactors in budding yeast, followed by single-run, intensity-based label-free quantitative LC-MS/MS analysis. Each pull-down contains around 2000 background binders, which are reinterpreted from troubling contaminants to crucial elements in a novel data analysis strategy. First the background serves for accurate normalization. Second, interacting proteins are not identified by comparison to a single untagged control strain, but instead to the other tagged strains. Third, potential interactors are further validated by their intensity profiles across all samples. We demonstrate the power of our AE-MS method using several well-known and challenging yeast complexes of various abundances. AE-MS is not only highly efficient and robust, but also cost effective, broadly applicable, and can be performed in any laboratory with access to high-resolution mass spectrometers.

ICan: an optimized ion-current-based quantification procedure with enhanced quantitative accuracy and sensitivity in biomarker discovery

The rapidly expanding availability of high-resolution mass spectrometry has substantially enhanced the ion-current-based relative quantification techniques. Despite the increasing interest in ion-current-based methods, quantitative sensitivity, accuracy, and false discovery rate remain the major concerns; consequently, comprehensive evaluation and development in these regards are urgently needed. Here we describe an integrated, new procedure for data normalization and protein ratio estimation, termed ICan, for improved ion-current-based analysis of data generated by high-resolution mass spectrometry (MS). ICan achieved significantly better accuracy and precision, and lower false-positive rate for discovering altered proteins, over current popular pipelines. A spiked-in experiment was used to evaluate the performance of ICan to detect small changes. In this study E. coli extracts were spiked with moderate-abundance proteins from human plasma (MAP, enriched by IgY14-SuperMix procedure) at two different levels to set a small change of 1.5-fold. Forty-five (92%, with an average ratio of 1.71 ± 0.13) of 49 identified MAP protein (i.e., the true positives) and none of the reference proteins (1.0-fold) were determined as significantly altered proteins, with cutoff thresholds of ≥1.3-fold change and p ≤ 0.05. This is the first study to evaluate and prove competitive performance of the ion-current-based approach for assigning significance to proteins with small changes. By comparison, other methods showed remarkably inferior performance. ICan can be broadly applicable to reliable and sensitive proteomic survey of multiple biological samples with the use of high-resolution MS. Moreover, many key features evaluated and optimized here such as normalization, protein ratio determination, and statistical analyses are also valuable for data analysis by isotope-labeling methods.

The growing landscape of lysine acetylation links metabolism and cell signalling

Lysine acetylation is a conserved protein post-translational modification that links acetyl-coenzyme A metabolism and cellular signalling. Recent advances in the identification and quantification of lysine acetylation by mass spectrometry have increased our understanding of lysine acetylation, implicating it in many biological processes through the regulation of protein interactions, activity and localization. In addition, proteins are frequently modified by other types of acylations, such as formylation, butyrylation, propionylation, succinylation, malonylation, myristoylation, glutarylation and crotonylation. The intricate link between lysine acylation and cellular metabolism has been clarified by the occurrence of several such metabolite-sensitive acylations and their selective removal by sirtuin deacylases. These emerging findings point to new functions for different lysine acylations and deacylating enzymes and also highlight the mechanisms by which acetylation regulates various cellular processes.

Copy number analysis of the murine platelet proteome spanning the complete abundance range

Knowledge of the identity and quantity of expressed proteins of a cell type is a prerequisite for a complete understanding of its molecular functions. Mass-spectrometry-based proteomics has allowed the identification of the entire protein complement of yeast and the close-to-complete set of proteins expressed in mammalian cell lines. Using recent technological advances, we here characterized the proteome of murine platelets, key actors in mediating hemostasis and thrombosis. We accurately measured the absolute protein concentrations of 13 platelet proteins using SILAC-protein epitope signature tags and used them as reference points to estimate the copy numbers of all proteins of the platelet proteome. To distinguish contaminants such as plasma or erythrocyte proteins from true platelet proteins, we monitored protein abundance profiles across multiple purification steps. In total, we absolutely quantified 4,400 platelet proteins, with estimated copy numbers ranging from less than 10 to about a million per cell. Stoichiometries derived from our data correspond well with previous studies. Our study provides a close-to-complete reference map of platelet proteins that will be useful to the community, for instance, for interpreting mouse models of human platelet diseases.