Detection of Proteoforms Using Top-Down Mass Spectrometry and Diagnostic Ions.

Characterization of protein structure modifications is an important field in mass spectrometry (MS)-based proteomics. Here, we describe a process to quickly and reliably identify a mass change in a targeted protein sequence by top-down mass spectrometry (TD MS) using electron transfer dissociation (ETD). The step-by-step procedure describes how to develop a TD MS method for data acquisition as well as the data analysis process. The described TD MS workflow utilizes diagnostic ions to characterize an unknown sample in a few hours.

Clinical method evaluation of hemoglobin S and C identification by top-down selected reaction monitoring and electron transfer dissociation.

BACKGROUND: Biological diagnosis of hemoglobin disorders is a complex process relying on the combination of several analytical techniques to identify Hb variants in a particular sample. Currently, hematology laboratories usually use high-performance liquid chromatography (HPLC), capillary electrophoresis and gel-based methods to characterize Hb variants. Co-elution and co-migration may represent major issues for precise identification of Hb variants, even for the most common ones such as Hb S and C. METHODS: We adapted a top-down selected reaction monitoring (SRM) electron transfer dissociation (ETD) mass spectrometry (MS) method to fit with a clinical laboratory environment. An automated analytical process with semi-automated data analysis compatible with a clinical practice was developed. A comparative study between a reference HPLC method and the MS assay was performed on 152 patient samples. RESULTS: The developed workflow allowed to identify with high specificity and selectivity the most common Hb variants (Hb S and Hb C). Concordance of the MS-based approach with HPLC was 71/71 (100%) for Hb S and 11/11 (100%) for Hb C. CONCLUSIONS: This top-down SRM ETD method can be used in a clinical environment to detect Hb S and Hb C.

Detection of busulfan adducts on proteins.

RATIONALE: Busulfan is a bifunctional alkyl sulfonate antineoplastic drug. This alkylating agent was described as forming covalent adducts on proteins. However, only limited data are available regarding the interaction of busulfan with proteins. Mass spectrometry and bioinformatics were used to identify busulfan adducts on human serum albumin and hemoglobin. METHODS: Albumin and hemoglobin were incubated with busulfan or control compounds, digested with trypsin and analyzed by liquid chromatography/tandem mass spectrometry (LC/MS/MS) on a Thermo Fisher LTQ Orbitrap Velos Pro. MS data were used to generate spectral libraries of non-modified peptides and an open modification search was performed to identify potential adduct mass shifts and possible modification sites. Results were confirmed by a second database search including identified mass shifts and by visual inspection of annotated tandem mass spectra of adduct-carrying peptides. RESULTS: Five structures of busulfan adducts were detected and a chemical structure could be attributed to four of them. Two were primary adducts corresponding to busulfan monoalkylation and alkylation of two amino acid residues by a single busulfan molecule. Two others corresponded to secondary adducts generated during sample processing. Adducts were mainly detected on Asp, Glu, and His residues. These findings were confirmed by subsequent database searches and experiments with synthetic peptides. CONCLUSIONS: The combination of in vitro incubation of proteins with the drug of interest or control compounds, high-resolution mass spectrometry, and open modification search allowed confirmation of the direct interaction of busulfan with proteins and characterization of the resulting adducts. Our results also showed that careful analysis of the data is required to detect experimental artifacts. Copyright © 2016 John Wiley & Sons, Ltd.

Multicenter experiment for quality control of peptide-centric LC-MS/MS analysis - A longitudinal performance assessment with nLC coupled to orbitrap MS analyzers.

Proteomic technologies based on mass spectrometry (MS) have greatly evolved in the past years, and nowadays it is possible to routinely identify thousands of peptides from complex biological samples in a single LC-MS/MS experiment. Despite the advancements in proteomic technologies, the scientific community still faces important challenges in terms of depth and reproducibility of proteomics analyses. Here, we present a multicenter study designed to evaluate long-term performance of LC-MS/MS platforms within the Spanish Proteomics Facilities Network (ProteoRed-ISCIII). The study was performed under well-established standard operating procedures, and demonstrated that it is possible to attain qualitative and quantitative reproducibility over time. Our study highlights the importance of deploying quality assessment metrics routinely in individual laboratories and in multi-laboratory studies. The mass spectrometry data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000205.This article is part of a Special Issue entitled: HUPO 2014.

Clinical protein mass spectrometry.

Quantitative protein analysis is routinely performed in clinical chemistry laboratories for diagnosis, therapeutic monitoring, and prognosis. Today, protein assays are mostly performed either with non-specific detection methods or immunoassays. Mass spectrometry (MS) is a very specific analytical method potentially very well suited for clinical laboratories. Its unique advantage relies in the high specificity of the detection. Any protein sequence variant, the presence of a post-translational modification or degradation will differ in mass and structure, and these differences will appear in the mass spectrum of the protein. On the other hand, protein MS is a relatively young technique, demanding specialized personnel and expensive instrumentation. Many scientists and opinion leaders predict MS to replace immunoassays for routine protein analysis, but there are only few protein MS applications routinely used in clinical chemistry laboratories today. The present review consists of a didactical introduction summarizing the pros and cons of MS assays compared to immunoassays, the different instrumentations, and various MS protein assays that have been proposed and/or are used in clinical laboratories. An important distinction is made between full length protein analysis (top-down method) and peptide analysis after enzymatic digestion of the proteins (bottom-up method) and its implication for the protein assay. The document ends with an outlook on what type of analyses could be used in the future, and for what type of applications MS has a clear advantage compared to immunoassays.

Identification of hemoglobin variants by top-down mass spectrometry using selected diagnostic product ions.

Hemoglobin disorder diagnosis is a complex procedure combining several analytical steps. Due to the lack of specificity of the currently used protein analysis methods, the identification of uncommon hemoglobin variants (proteoforms) can become a hard task to accomplish. The aim of this work was to develop a mass spectrometry-based approach to quickly identify mutated protein sequences within globin chain variants. To reach this goal, a top-down electron transfer dissociation mass spectrometry method was developed for hemoglobin ß chain analysis. A diagnostic product ion list was established with a color code strategy allowing to quickly and specifically localize a mutation in the hemoglobin ß chain sequence. The method was applied to the analysis of rare hemoglobin ß chain variants and an (A)γ-ß fusion protein. The results showed that the developed data analysis process allows fast and reliable interpretation of top-down electron transfer dissociation mass spectra by nonexpert users in the clinical area.

Repeated exposure to Ochratoxin A generates a neuroinflammatory response, characterized by neurodegenerative M1 microglial phenotype.

Neurotoxic effects of the environmentally abundant mycotoxin Ochratoxin A (OTA) were studied in histotypic 3D rat brain cell cultures, comprising all brain cell types. Cultures were exposed to nanomolar OTA concentrations and samples were collected 48h after a single exposure, or after 10 days of repeated administration. OTA-induced changes in gene- and protein expression, as well as alterations in cell morphology were assessed. Forty-eight-hour OTA exposure resulted in a disruption of the neuronal cytoskeleton and reduced expression of several oligodendrocyte-specific markers indicative of demyelination. Astrocyte disturbances were revealed by a decrease in two astrocytic proteins involved in regulation of inflammatory responses, metallothioneins I and II. Repeated OTA administration induced a neuroinflammatory response, as visualized by an increase of isolectin B4 labelled cells, increased expression of pro-inflammatory cytokines, and detection of macrophagic ED1/CD68 positive cells, as well as an upregulation of neurodegenerative M1 microglial phenotype markers. Partial recovery from OTA-induced deleterious effects on oligodendrocytes and astrocytes was achieved by co-treatment with sonic hedgehog (SHH). In addition, metallothionein I and II co-treatment partially restored OTA-induced effects on oligodendrocytes after 48h, and modulated microglial reactivity after 10 days. These results suggest that OTA-exposure affects Shh-signalling, which in turn may influence both oligodendrocytes and astrocytes. Furthermore, the primarily astrocytic proteins MTI/MTII may affect microglial activation. Thus the neuroinflammatory response appears to be downstream of OTA-induced effects on demyelination, axonal instabilities and astrocytes disturbances. In conclusion, repeated OTA-exposure induced a secondary neuroinflammatory response characterized by neurodegenerative M1 microglial activation and pro-inflammatory response that could exacerbate the neurodegenerative process.

Immediate and delayed effects of subchronic Paraquat exposure during an early differentiation stage in 3D-rat brain cell cultures.

Xenobiotic exposure is a risk factor in the etiology of neurodegenerative disease. It was recently hypothesized that restricted exposure during brain development could predispose for a neurodegenerative disease later in life. As neuroinflammation contributes to progressive neurodegeneration, it is suspected that neurodevelopmental xenobiotic exposure could elicit a neuroinflammatory process, which over time may assume a detrimental character. We investigated the neurotoxic effects of paraquat (PQ) in three-dimensional whole rat brain cell cultures, exposed during an early differentiation stage, comparing immediate effects-directly post exposure-with long-term effects, 20 days after interrupted PQ-administration. Adverse effects and neuroinflammatory responses were assessed by measuring changes in gene- and protein-expression as well as by determining cell morphology changes. Differentiating neural cultures were highly susceptible to PQ and showed neuronal damage and strong astrogliosis. After the 20-day washout period, neurons partially recovered, whereas astrogliosis persisted, and was accompanied by microglial activation of a neurodegenerative phenotype. Our data shows that immediate and long-term effects of subchronic PQ-exposure differ. Also, PQ-exposure during this window of extensive neuronal differentiation led to a delayed microglial activation, of a character that could promote further pro-inflammatory signals that enable prolonged inflammation, thereby fueling further neurodegeneration.

Applications of mass spectrometry for quantitative protein analysis in formalin-fixed paraffin-embedded tissues.

Proteomic analysis of tissues has advanced in recent years as instruments and methodologies have evolved. The ability to retrieve peptides from formalin-fixed paraffin-embedded tissues followed by shotgun or targeted proteomic analysis is offering new opportunities in biomedical research. In particular, access to large collections of clinically annotated samples should enable the detailed analysis of pathologically relevant tissues in a manner previously considered unfeasible. In this paper, we review the current status of proteomic analysis of formalin-fixed paraffin-embedded tissues with a particular focus on targeted approaches and the potential for this technique to be used in clinical research and clinical diagnosis. We also discuss the limitations and perspectives of the technique, particularly with regard to application in clinical diagnosis and drug discovery.

Proteomic approach to investigate pathogenicity and metabolism of methicillin-resistant Staphylococcus aureus.

Over the last two decades, numerous genomes of pathogenic bacteria have been fully sequenced and annotated, while others are continuously being sequenced. To date, the sequences of more than 8,500 whole bacterial genomes are publicly available for research purposes. These efforts in high-throughput sequencing simultaneously to progresses in methods allowing to study whole transcriptome and proteome of bacteria provide the basis of comprehensive understanding of metabolism, adaptability to environment, regulation, resistance pathways, or pathogenicity mechanisms of bacterial pathogens. Staphylococcus aureus is a Gram-positive human pathogen causing a wide variety of infections ranging from benign skin infection to life-threatening diseases. Furthermore, the spreading of multidrug-resistant isolates requiring the use of last barrier drugs has resulted in a particular attention of the medical and scientific community to this pathogen. We describe here proteomic methods to prepare, identify, and analyze protein fractions, which allow studying Staphylococcus aureus on the organism level. Besides evaluation of the whole bacterial transcriptome, this approach might contribute to the development of rapid diagnostic tests and to the identification of new drug targets to improve public health.

Translation of pre-spliced RNAs in the nuclear compartment generates peptides for the MHC class I pathway.

The scanning of maturing mRNAs by ribosomes plays a key role in the mRNA quality control process. When ribosomes first engage with the newly synthesized mRNA, and if peptides are produced, is unclear, however. Here we show that ribosomal scanning of prespliced mRNAs occurs in the nuclear compartment, and that this event produces peptide substrates for the MHC class I pathway. Inserting antigenic peptide sequences in introns that are spliced out before the mRNAs exit the nuclear compartment results in an equal amount of antigenic peptide products as when the peptides are encoded from the main open reading frame (ORF). Taken together with the detection of intron-encoded nascent peptides and RPS6/RPL7-carrying complexes in the perinucleolar compartment, these results show that peptides are produced by a translation event occurring before mRNA splicing. This suggests that ribosomes occupy and scan mRNAs early in the mRNA maturation process, and suggests a physiological role for nuclear mRNA translation, and also helps explain how the immune system tolerates peptides derived from tissue-specific mRNA splice variants.

Clustering and filtering tandem mass spectra acquired in data-independent mode.

Data-independent mass spectrometry activates all ion species isolated within a given mass-to-charge window (m/z) regardless of their abundance. This acquisition strategy overcomes the traditional data-dependent ion selection boosting data reproducibility and sensitivity. However, several tandem mass (MS/MS) spectra of the same precursor ion are acquired during chromatographic elution resulting in large data redundancy. Also, the significant number of chimeric spectra and the absence of accurate precursor ion masses hamper peptide identification. Here, we describe an algorithm to preprocess data-independent MS/MS spectra by filtering out noise peaks and clustering the spectra according to both the chromatographic elution profiles and the spectral similarity. In addition, we developed an approach to estimate the m/z value of precursor ions from clustered MS/MS spectra in order to improve database search performance. Data acquired using a small 3 m/z units precursor mass window and multiple injections to cover a m/z range of 400-1400 was processed with our algorithm. It showed an improvement in the number of both peptide and protein identifications by 8% while reducing the number of submitted spectra by 18% and the number of peaks by 55%. We conclude that our clustering method is a valid approach for data analysis of these data-independent fragmentation spectra. The software including the source code is available for the scientific community.

STAT6 promotes bi-directional modulation of PKM2 in liver and adipose inflammatory cells in rosiglitazone-treated mice.

STAT6 interacts with PPARγ to elicit macrophage polarization towards an anti-inflammatory, insulin-sensitizing phenotype. Mice deficient in STAT6 display liver lipid accumulation (hepatosteatosis). Rosiglitazone (RSG), a PPARγ agonist, ameliorates hepatosteatosis and enhances insulin sensitivity. To elucidate the role of STAT6 in PPARγ action on hepatosteatosis we compared liver proteomes of RSG-treated wild type and STAT6-deficient mice and we identified pyruvate kinase M2 (PKM2), a glycolysis and proliferation-regulating enzyme that displayed STAT6-dependent expression. RSG induced PKM2 within inflammatory cells in liver but suppressed its expression in adipose tissue. RSG diminished hepatosteatosis and oxidative stress, enhanced fat accumulation and improved insulin sensitivity in STAT6-deficient mice. Our data reveal a complex interaction between STAT6 and PPARγ in the regulation of liver and adipose tissue lipid depot distribution and design STAT6 as a novel link between inflammatory cell metabolism and adipocyte and hepatocyte function.

Quantitative mass spectrometry analysis of intact hemoglobin A2 by precursor ion isolation and detection.

Precise and accurate quantification of proteins is essential in clinical laboratories. Here, we present a mass spectrometry (MS)-based method for the quantification of intact proteins in an ion trap mass spectrometer. The developed method is based on the isolation and detection of precursor ions for the quantification of the corresponding signals. The method was applied for the quantification of hemoglobin (Hb) A2, a marker used for the diagnosis of a ß-thalassemia trait. The α and δ globin chains, corresponding to total Hb and HbA2, respectively, were isolated in the ion trap at specific charge states and ejected without activation. Areas of the corresponding isolated precursor ions were used to calculate the δ to α ratio. Three series of quantifications were performed on 7 different days. The standard curve fitted linearly (R(2) = 0.9982) and allowed quantification of HbA2 over a concentration range from 3% to 18% of total Hb. Analytical imprecision ranged from 3.5% to 5.3%, which is enough to determine if the HbA2 level is below 3.5% or above 3.7%. In conclusion, our method reaches precision requirements that would be acceptable for the quantitative measurement of diagnostic proteins, such as HbA2, in clinical laboratories.

Development of a fluorescent monoclonal antibody-based assay to measure the allosteric effects of synthetic peptides on self-oligomerization of AGR2 protein.

Many regulatory proteins are homo-oligomeric and designing assays that measure self-assembly will provide novel approaches to study protein allostery and screen for novel small molecule modulators of protein interactions. We present an assay to begin to define the biochemical determinants that regulate dimerization of the cancer-associated oncoprotein AGR2. A two site-sandwich microtiter assay ((2S) MTA) was designed using a DyLight800-labeled monoclonal antibody that binds to an epitope in AGR2 to screen for synthetic self-peptides that might regulate dimer stability. Peptides derived from the intrinsically disordered N-terminal region of AGR2 increase in trans oligomer stability as defined using the (2S) MTA assay. A DSS-crosslinking assay that traps the AGR2 dimer through K95-K95 adducts confirmed that Δ45-AGR2 was a more stable dimer using denaturing gel electrophoresis. A titration of wt-AGR2, Δ45-AGR2 (more stable dimer), and monomeric AGR2(E60A) revealed that Δ45-AGR2 was more active in binding to Reptin than either wt-AGR2 or the AGR2(E60A) mutant. Our data have defined a functional role for the AGR2 dimer in the binding to its most well characterized interacting protein, Reptin. The ability to regulate AGR2 oligomerization in trans opens the possibility for developing small molecules that regulate its' biochemical activity as potential cancer therapeutics. The data also highlight the utility of this oligomerization assay to screen chemical libraries for ligands that could regulate AGR2 dimer stability and its' oncogenic potential.

Intact protein profiling in breast cancer biomarker discovery: protein identification issue and the solutions based on 3D protein separation, bottom-up and top-down mass spectrometry.

Proteomics profiling of intact proteins based on MALDI-TOF MS and derived platforms has been used in cancer biomarker discovery studies. This approach suffers from a number of limitations such as low resolution, low sensitivity, and that no knowledge is available on the identity of the respective proteins in the discovery mode. Nevertheless, it remains the most high-throughput, untargeted mode of clinical proteomics studies to date. Here we compare key protein separation and MS techniques available for protein biomarker identification in this type of studies and define reasons of uncertainty in protein peak identity. As a result of critical data analysis, we consider 3D protein separation and identification workflows as optimal procedures. Subsequently, we present a new protocol based on 3D LC-MS/MS with top-down at high resolution that enabled the identification of HNRNP A2/B1 intact peptide as correlating with the estrogen receptor expression in breast cancer tissues. Additional development of this general concept toward next generation, top-down based protein profiling at high resolution is discussed.

EasyProt--an easy-to-use graphical platform for proteomics data analysis.

High throughput protein identification and quantification analysis based on mass spectrometry are fundamental steps in most proteomics projects. Here, we present EasyProt (available at http://easyprot.unige.ch), a new platform for mass spectrometry data processing, protein identification, quantification and unexpected post-translational modification characterization. EasyProt provides a fully integrated graphical experience to perform a large part of the proteomic data analysis workflow. Our goal was to develop a software platform that would fulfill the needs of scientists in the field, while emphasizing ease-of-use for non-bioinformatician users. Protein identification is based on OLAV scoring schemes and protein quantification is implemented for both, isobaric labeling and label-free methods. Additional features are available, such as peak list processing, isotopic correction, spectra filtering, charge-state deconvolution and spectra merging. To illustrate the EasyProt platform, we present two identification and quantification workflows based on isobaric tagging and label-free methods.

Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application.

Proteomics studies typically aim to exhaustively detect peptides/proteins in a given biological sample. Over the past decade, the number of publications using proteomics methodologies has exploded. This was made possible due to the availability of high-quality genomic data and many technological advances in the fields of microfluidics and mass spectrometry. Proteomics in biomedical research was initially used in 'functional' studies for the identification of proteins involved in pathophysiological processes, complexes and networks. Improved sensitivity of instrumentation facilitated the analysis of even more complex sample types, including human biological fluids. It is at that point the field of clinical proteomics was born, and its fundamental aim was the discovery and (ideally) validation of biomarkers for the diagnosis, prognosis, or therapeutic monitoring of disease. Eventually, it was recognized that the technologies used in clinical proteomics studies [particularly liquid chromatography-tandem mass spectrometry (LC-MS/MS)] could represent an alternative to classical immunochemical assays. Prior to deploying MS in the measurement of peptides/proteins in the clinical laboratory, it seems likely that traditional proteomics workflows and data management systems will need to adapt to the clinical environment and meet in vitro diagnostic (IVD) regulatory constraints. This defines a new field, as reviewed in this article, that we have termed quantitative Clinical Chemistry Proteomics (qCCP).

Electron transfer dissociation mass spectrometry of hemoglobin on clinical samples.

A mass spectrometry-based assay combining the specificity of selected reaction monitoring and the protein ion activation capabilities of electron transfer dissociation was developed and employed for the rapid identification of hemoglobin variants from whole blood without previous proteolytic cleavage. The analysis was performed in a robust ion trap mass spectrometer operating at nominal mass accuracy and resolution. Subtle differences in globin sequences, resulting with mass shifts of about one Da, can be unambiguously identified. These results suggest that mass spectrometry analysis of entire proteins using electron transfer dissociation can be employed on clinical samples in a workflow compatible with diagnostic applications.

An improved method for the construction of decoy peptide MS/MS spectra suitable for the accurate estimation of false discovery rates.

The relevance of libraries of annotated MS/MS spectra is growing with the amount of proteomic data generated in high-throughput experiments. These reference libraries provide a fast and accurate way to identify newly acquired MS/MS spectra. In the context of multiple hypotheses testing, the control of the number of false-positive identifications expected in the final result list by means of the calculation of the false discovery rate (FDR). In a classical sequence search where experimental MS/MS spectra are compared with the theoretical peptide spectra calculated from a sequence database, the FDR is estimated by searching randomized or decoy sequence databases. Despite on-going discussion on how exactly the FDR has to be calculated, this method is widely accepted in the proteomic community. Recently, similar approaches to control the FDR of spectrum library searches were discussed. We present in this paper a detailed analysis of the similarity between spectra of distinct peptides to set the basis of our own solution for decoy library creation (DeLiberator). It differs from the previously published results in some key points, mainly in implementing new methods that prevent decoy spectra from being too similar to the original library spectra while keeping important features of real MS/MS spectra. Using different proteomic data sets and library creation methods, we evaluate our approach and compare it with alternative methods.