Article pubs.acs.org/jpr
Uncovering Effects of Ex Vivo Protease Activity during Proteomics and Peptidomics Sample Extraction in Rat Brain Tissue by Oxygen-18 Labeling Christoph Stingl,† Marcus Söderquist,‡ Oskar Karlsson,§ Mats Borén,‡ and Theo M. Luider*,† †
Department of Neurology, Erasmus University Medical Center, 3000 CA Rotterdam, The Netherlands Denator AB, 413 46 Gothenburg, Sweden § Department of Pharmaceutical Biosciences, Uppsala University, 751 05 Uppsala, Sweden ‡
S Supporting Information *
ABSTRACT: In biological samples, proteins and peptides are altered by proteolytic activity. The actual ex vivo form of the peptidome or proteome analyzed, therefore, does not always reflect the natural in vivo state. Sample stabilization and sample treatment are thereby decisive for how far these two states diverge. To assess ex vivo formation of peptides, we used enzymatic incorporation of oxygen-18 water during proteolysis (PALeO approach) to label ex-vivo-formed peptides in rodent brain tissue. Rates of ex-vivo-formed peptides were determined in 25 samples that were stabilized and treated by six different protocols, whereby samples were subjected to different conditions such as temperature, urea concentration, and duration of treatment. Samples were measured by nano LC-Orbitrap-MS, and incorporation of oxygen-18 was determined by MS/MS database search and analysis of the precursor isotope pattern. Extent of ex vivo degradations was affected relevantly by the sample treatment protocol applied and stopped almost completely by heat stabilization. Determination of the formation state by oxygen18 incorporation by MS/MS database search correlated well to more elaborate analysis of the MS isotope pattern. Overall, oxygen-18 labeling in combination with shotgun data-acquisition and MS/MS database search offers an adjuvant and easily applicable tool to monitor sample quality and fidelity in peptide and neuropeptide sample preparations. KEYWORDS: peptidomics, neuropeptides, oxygen-18, sample stabilization, quality control
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INTRODUCTION When tissue is dissected and taken out of its natural environment, inherent biological processes, such as apoptosis or clotting, will continue in the ex vivo state of the tissue. These postsampling effects continue due to endogenous enzymatic activity resulting in changes to proteins and peptides. Later analysis of such a sample will show an overlap between in vivo state and ex vivo state confusing the analysis of proteins and peptides. Thus, an uncertainty is created whether some detected biomolecules are endogenously produced or formed by ex vivo degradation and results may be biased. These ex vivo alterations, if not inhibited at an early stage of the sample processing in an efficient and reproducibly way, further introduce significant variability in the proteomics analysis.1 In the field of proteomics, various methods of protease activity inhibition are knownsuch as addition of specific protease inhibitors, heating or boiling, freezing, precipitation, or changes of pH, among othersand are used dependent to the sample type and proteomics application.2,3 In the analysis of neuropeptides in brain tissue, the prevention of general protein breakdown of cytosolic proteins is of utter importance. The utilization of effective stabilization methods such as microwave radiation or conductive heat stabilization enables identification © 2014 American Chemical Society
of low-abundant neuropeptides and extends the total number of neuropeptides identified.3−6 One way to determine the time-point of protease activity, in vivo or ex vivo, utilizes the incorporated of oxygen-18 (18O) at the C-terminal carboxyl group of a peptide fragment.7,8 The mechanism underlying this protease catalyzed reaction was described in detail by Schnölzer et al.8 In brief, during proteolysis, proteases bind to their substrate whereby the peptide bond is cleaved, and subsequently, the protease− substrate intermediate is hydrolyzed and water from the surrounding solvent system is incorporated. Further, some proteases, such as trypsin or Glu-C, recognized also the cleaved fragment as pseudosubstrate and will continue to bind and hydrolyze the C-terminal carboxyl-group of the fragment peptides, whereby further water from the solvent system is incorporated. If the surrounding water contains oxygen-18, products from both reactions will result in incorporation of oxygen-18, whereby the extent of C-terminal oxygen-18 incorporation is in equilibrium with the ratio of H218O in the surrounding water. The number of incorporated oxygen-18 Received: December 12, 2013 Published: April 17, 2014 2807
dx.doi.org/10.1021/pr401232e | J. Proteome Res. 2014, 13, 2807−2817
Journal of Proteome Research
Article
In this study, we determined protease activity in rat brain tissue during various common sample treatments used for peptidomics and proteomics analysis. A subset of the samples used was stabilized by heat in advance to inactivate protease activity. Due to the addition of oxygen-18 water at different time-points of the processing steps, we could measure proteolytic activity in common protein analysis workflows: (a) during peptide extraction in the presence of high molar solution (8 M) of urea (pep), (b) after dilution from extraction in high molar solution of urea to low (2 M) urea concentration (low urea), (c) during isoelectric focusing like conditions in the presence of high molar solutions (8 M) of urea where samples are exposed to room temperature over a longer period of time (2D), and (d) during shotgun-digest-like conditions where samples are exposed to elevated temperatures (37 °C) at low 2 M urea concentration (shotgun). Residual enzymatic activity in the various conditions resulted in oxygen-18 incorporation in peptides created. The level and composition of oxygen-18containing peptides indicated enzymatic activity in the sample and can be used as a comparative measure to assess enzyme activity in the extracts. The shotgun condition simulates a condition of typical bottom-up proteomics experiments where usually an exogenous protease, such as trypsin, is added to digest the proteins into peptides. However, this study focuses on degradation by endogenous proteases, and thus, no exogenous proteases were added, preventing that the set of endogenous peptides (formed in vivo and ex vivo) is covered and suppressed by otherwise quantitative dominant peptides formed by exogenous added proteases (e.g., tryptic peptides). By this experimental setting we assessed enzymatic activity and determined peptide and neuropeptide profiles, cleavage patterns, and technical reproducibility, all factors that differed significantly dependent on sample stabilization and treatment conditions applied.
atoms (one or two) indicates if the interacting protease recognizes only the primary, uncleaved substrate or the cleaved pseudosubstrate. As consequence, the incorporation of oxygen18 does not indicate proteolytic cleavage per se but more generally proteolytic interaction with a substrate and, thus, can be used to monitor proteolytic activity. A C-terminus of a substrate peptide that interacts with a protease in the presence of oxygen-18 containing water, for example, during ex vivo processing or sample storage, will be labeled with oxygen-18 and can, thus, be differentiated from peptides that where formed in absence of oxygen-18 water (e.g., in vivo). Dependent on the protease and if it is catalyzing oxygen exchange of the C-terminal carboxyl, one or two oxygen-18 atoms are incorporated resulting in peptide species with a 2 or 4 u mass shift. This mechanism was utilized by Hardt and coworkers to detect and characterize endogenous protease activity in biological samples, and the method was described under the name PALeO (protease activity labeling employing oxygen-18 enriched water).9,10 This mass spectrometry compatible approach was used not only to assess protease activity in complex tissue samples but also to determine stability and degradation due to proteolysis during sample storage. Mass spectrometry (MS), often in combination with reversed-phase liquid chromatography (LC), is a state-of-theart technique for protein and peptide identification11,12 and also enables characterization of peptide modifications and use of stable isotope labeling techniques, including incorporation of oxygen-18.7,13,14 Mass spectrometric detection of oxygen-18 incorporation can thereby be determine by tandem MS (MS/ MS), whereby on the basis of a fragmentation spectra of a peptide, the corresponding peptide sequence including associated modifications can be determined. In addition, the incorporation of oxgen-18 can be detected by analysis of isotope patterns of oxygen-18/oxygen-16 pairs (or triplets), whereby also quantitative ratios between the different forms can be calculated. Both approaches have their advantages and disadvantages: MS/MS database search is a central data analysis step in shotgun proteomics experiments and a multitude of appropriate software tools to conduct MS/MS database searches are available.15,16 MS/MS spectra are typically acquired by a data-dependent shotgun proteomics method, which allows identification of a large number of peptides without any prior knowledge about the actual peptide composition of the samples. However, due to instrumental limitations, not all of the present peptide precursors MS/MS spectra can be acquired, leading to undersampling. This can potentially cause a problem in the case of overlapping isotope pattern of multiple peptide species, such as a oxygen-16/ oxygen-18 pairs, whereby the final identification of which species is identified relies on which of the isotopes is recognized as MS/MS precursor. Isotope pattern analysis on the other hand derives the presence of oxygen-18 labeled peptides from the entire isotope pattern (oxygen-16/oxygen-18 duplet) of the precursor ion (in MS1) and is, thus, independent of which isotope an MS/MS spectra was triggered. Various methods are described to deconvolute isotope patterns in regard to partial oxygen-18 incorporation,7,13,14 but these methods are not included in common proteomics data analysis tools and have to be applied in a separate, customized step. It therefore presents a valuable alternative or complement to verify the MS/MS spectra database search but also makes this approach ultimately more laborious and time-consuming to apply.
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MATERIAL AND METHODS
Animals and Tissue Collection
Female Wistar rats were obtained from Taconic (Ejby, Denmark) and housed in standard cages (59 × 38 × 20 cm) containing wood-chip bedding and nesting material. The animals were maintained on standard pellet food (R36 Labfor; Lantmännen, Kimstad, Sweden) and water ad libitum and were housed in a temperature- and humidity-controlled environment with a 12-h light/dark cycle (lights on at 6 a.m.) The Uppsala animal ethical committee approved all animal experiments, which were performed in accordance with the guidelines of the Swedish legislation on animal experimentation (Animal Welfare Act SFS1998:56) and European Union legislation (Convention ETS123 and Directive 86/609/EEC). Sample Treatment
The rats were sacrificed by decapitation, the brains were immediately removed, and the hypothalami were either instantly dissected from fresh tissue or dissected after heat stabilization of the intact brain in the groups subjected to enzyme inactivation by heat stabilization. For all solvents and buffers of subsequent extraction and dilution steps ultrapure water (Chromasolv, Fluka), oxygen-18 water (97% purity, Sigma-Aldrich), and urea (Sigma-Aldrich) were used. The starting amount of tissue was on average 23 mg (SD = 5.1 mg), and for extraction, 100 μL per 20 mg of tissue were added to normalize for variation of the initial amount of tissue. Six groups processed in different ways were created (Table 1): 2808
dx.doi.org/10.1021/pr401232e | J. Proteome Res. 2014, 13, 2807−2817
Journal of Proteome Research
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Table 1. Overview about different sample stabilization, sample treatments, and time-points of addition of oxygen-18 water of the 6 different sample groups
(6) D/shotgun: Samples from four animals were heatstabilized, snap-frozen, and further processed as the SF/shotgun samples above. These samples were prepared to determine incorporation of oxygen-18 during extraction and in the presence of 2 M urea at 37 °C for 6 h in a heat-stabilized sample, simulating a typical shotgun sample preparation. Filtrates were shipped on dry ice and stored at −80 °C until LC-MS measurement.
Snap Frozen Tissue. (1) SF/pep: Samples from four animals were snap frozen, homogenized, and extracted in 8 M urea containing 60% oxygen-18 water and were subsequently diluted to 4 M urea with 60% oxygen-18 water, centrifuged, and filtrated using a 10 kDa MW cutoff filter (Denator, Sweden) to isolate low molecular weight peptides. These samples were prepared to determine incorporation of oxygen-18 during the whole peptide extraction workflow including centrifugation. (2) SF/low urea: Samples from four animals were snap frozen, homogenized, and extracted in 8 M urea (in ordinary oxygen-16 water), further diluted to 4 M urea using oxygen-18 water in 0.25% acetic acid, centrifuged at 20 000 g for 30 min at 4 °C and filtered through a 10 kDa membrane. These samples were prepared to show incorporation of oxygen-18 during centrifugation through the 10 kDa membrane in 4 M urea. (3) SF/2D: Samples from four animals were snap frozen, homogenized, and extracted in 8 M urea containing 60% oxygen-18 water as explained above, left at room temp overnight, and afterward diluted to 4 M urea before they were centrifuged and filtered as explained above. These samples were prepared to determine ex vivo degradation in 8 M urea at room-temperature, simulating the isoelectric focusing stage of 2D-GE sample preparation. (4) SF/shotgun: Samples from four animals were snap frozen, homogenized, and extracted in 8 M urea containing 60% oxygen-18 water as explained above, diluted in 60% oxygen-18 water to 2 M urea, and incubated for 6 h at 37 °C. Subsequently samples were centrifuged and filtered as explained above. These samples were prepared to determine incorporation of oxygen-18 during extraction and in the presence of 2 M urea at 37 °C, simulating a typical shotgun sample preparation. Heat-Stabilized Tissue. (5) D/pep: Samples from five animals were heat-stabilized at 95 °C for 90 s using a Stabilizor T1 (Denator), then snap frozen and further processed as the SF/pep samples as described above. The samples were prepared to determine incorporation of oxygen-18 during the whole peptide extraction workflow in a heat-stabilized sample.
Mass Spectrometric Measurement
Samples were measured with a nano liquid chromatography (LC) system (Ultimate 3000, Thermo Fisher Scientific/Dionex, Amsterdam, The Netherlands) coupled online to a hybrid linear ion trap/Orbitrap mass spectrometer (LTQ-Orbitrap-XL, Thermo Fisher Scientific, Bremen, Germany). Sample volumes of 2 to 10 μL of the samples (Supporting Information Table 1) were loaded onto a trap column (PepMap C18, 300 μm ID × 5 mm length, 5 μm particle size, 100 Å pore size Thermo Fisher Scientific/Dionex) and washed and desalted for 10 min using 0.1% TFA (in water) as loading solvent. Then, the trap column was switched online with the analytical column (PepMap C18, 75 μm ID × 250 mm, 3 μm particle and 100 Å pore size; Dionex), and peptides were eluted with the following binary gradient: starting with 100% solvent A, then from 0% to 25% solvent B in 60 min and from 25% to 50% solvent B in an additional 30 min, where solvent A consisted of 2% acetonitrile and 0.1% formic acid (rest water), and solvent B consisted of 80% acetonitrile and 0.08% formic acid (rest water). All LC solvents were purchased from Biosolve, Valkenswaard, The Netherlands. Column flow rate was set to 300 nL/min. For electrospray ionization (ESI), we used a chip-based nanospray source (Triversa NanoMate, Advion, Ithaca, NY, U. S. A.) equipped with a 3 μm nozzle chip and applying a spray voltage of 1.7 kV. For MS detection, a data-dependent acquisition method was used: high-resolution survey scan from 400−1800 m/z was detected in the Orbitrap (target of automatic gain control = 106, resolution = 30 000 at 400 m/z, lock mass set to 445.120 m/z [protonated (Si(CH3)2O)6]). On the basis of this full scan, the five most intensive ions were consecutively isolated (isolation width of 2 m/z, and AGC target set to 104 ions) and fragmented by collisionally activated dissociation (CAD, applying 35% normalized collision energy) and were subsequently detected in the ion trap. Precursor masses within 2809
dx.doi.org/10.1021/pr401232e | J. Proteome Res. 2014, 13, 2807−2817
Journal of Proteome Research
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a tolerance range of ±5 ppm that were selected once for MS/ MS were excluded for MS/MS fragmentation for 3 min or until the precursor intensity fell below a S/N of 1.5 for more than 10 scans (early expiration). Monoisotopic precursor selection was activated, and precursors with unknown charge states were excluded from MS/MS triggering events. Orbitrap full scan spectra and ion trap MS/MS fragmentation spectra were acquired partially simultaneously.
pairwise compared (in total, 300 comparisons), whereby comparison of protein sets was based on their accession number and comparison of peptide sets on the unique peptide sequences. (b) Principle component analysis (PCA) and hierarchical cluster analysis (HCA) of protein profiles: protein profiles were thereby defined as a list of all proteins identified and their corresponding protein spectral count abundance. For the following analysis, protein abundances were 2log transformed and normalized. PCA and HCA (by average linkage and Pearson distance) and generation of clustered heat-maps were conducted using the statistical software package R,20 library “gplots”. (c) Motif cleavage frequency: for each identified peptide the C-terminal and N-terminal P1−P1′ motifs (two amino acid motif, using the nomenclature according Schechter and Berger21) were extracted and counted as a cleaved motif. Then, the occurrences of these motifs within all peptides sequenced were determined and counted as noncleaved motif. The cleavage specificity for each motif was calculated as the ratio of cleaved motifs to the total motif occurrence (sum of noncleaved and cleaved motifs), ranging from 0−100%, where 0% indicates that the regarding motif is not cleaved and 100% indicated complete cleavage of that motif. For subsequent principal component analysis (PCA) and hierarchical cluster analysis (HCA), we extracted two sets of motifs: (a) all motifs that occurred in all samples at least once (n = 302) and (b) all in vivo and ex-vivo-formed C-terminal motifs of SF/2D and SF/ shotgun samples (n = 94). Neuropeptide Identification. A set of neuropeptides was compiled as follows: First, a list of rat neuropeptide precursors (gene names) was derived from the SwePep database22 (UniProt release 49.0, February 2006), an Internet neuropeptide repository (neuropeptides.nl; status, August 8, 2013),23 and from a review about mouse brain peptide from Fricker et al;4 for peptides where no protein or gene identifiers were available, we derived the gene names by matching the given peptide sequences against precursor sequences of Uniprot protein database (version July 2013). Then the corresponding rat accessions were derived from the Uniprot database, yielding a list of 410 rat proteins. In a second step, the Uniprot sequence annotations (features) related to molecule processing were queried (www.uniprot.org) for these proteins, and a set of neuropeptides was created of all sequence segments that are defined as “peptide”. For example, Protachykinin-1 (P06767) had six different “peptide” sequence annotations: Substance P (58−68); Neuropeptide K (72−107); Neuropeptide gamma, first part (72−73); Neuropeptide gamma, second part (89− 107); Neurokinin A (98−107); and C-terminal-flanking peptide (111−126). The list of potential neuropeptides created contained 244 distinct peptides from 110 corresponding proteins. For further computations, we aggregated and merged overlapping peptides to “super sequences” and, finally, aligned all identified peptides against these sequences, including the count of how many times per sample preparation group these peptides were identified, the relative intensity of the peptide precursor (relative to the most abundant peak of the sample), and the ex vivo/in vivo formation state. Isotope Pattern Analysis. Incubation took place at estimated equimolar amounts of oxygen-16 water and oxygen-18 water and the presence of mixed population of both in vivo and ex-vivo-formed peptides were possible. Therefore, we expected incomplete and variable incorporation of oxygen-18, yielding duplets or triplets of unlabeled and labeled peptides having a mass difference of about 2 u or 4 u, respectively. This
Data Analysis
Protein and Peptide Identification. For peptide and protein identification, we used the database search engine Mascot (version 2.3.01, Matrix Science, London, U. K.) and subsequently combined these results using Scaffold (version 4.3., Proteome Software Inc., Portland, OR, U. S. A.). MS/MS spectra were extracted from raw data files and converted into mgf files using extract_msn (part of Xcalibur version 2.0.7, Thermo Fisher Scientific Inc.) and were used for searching against the rat subset of the Uniprot-Swissprot database (version July 2013, 7870 rat sequence entries) whereby following parameters were applied: taxonomy Rattus norvegicus; unspecific enzyme cleavage; variable modification: C-terminal oxygen-18 incorporation (+2.001 u), N-terminal acetylation (+42.011 u), pyro-Glu formation on N-terminal glutamine (−17.027 u), C-terminal amidation (−0.985 u), and methionine oxidation (+15.995 u). We used a peptide tolerance of 10 ppm and a fragment tolerance 0.5 u. To combine results from individual Mascot searches, applying scoring of hits (local false discovery rates, LFDR), and protein grouping, we used Scaffold.17−19 Filter criteria were set to ≤1% LFDR and a minimum of 2 peptides per protein was required. Protein and peptide identifications matching these criteria were exported for further external calculations to a spreadsheet containing detailed information about the protein and peptide hits (Scaffold spectrum report). Protein abundances were calculated on the basis of spectral counts computed by Scaffold (Scaffold’s quantitative values). Proteins with significant abundance difference between the various groups were determined by an ANOVA (function of Scaffold). Result table containing the abundances of all proteins and of all proteins with significant different abundances (ANOVA p value
