A Dimethyl-Labeling-Based Strategy for Site-Specifically Quantitative

Publication Date (Web): July 10, 2018 ... Herein, we combined reductive dimethyl labeling with TOP-ABPP to develop a fast, affordable, and efficient m...
0 downloads 0 Views 2MB Size
Download PDF
Article pubs.acs.org/ac

Cite This: Anal. Chem. XXXX, XXX, XXX−XXX

A Dimethyl-Labeling-Based Strategy for Site-Specifically Quantitative Chemical Proteomics Fan Yang,†,‡ Jinjun Gao,§,‡ Jinteng Che,§ Guogeng Jia,† and Chu Wang*,†,§ †

Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering and § Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China

Downloaded via UNIV OF SOUTH DAKOTA on July 11, 2018 at 02:57:04 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

S Supporting Information *

ABSTRACT: Activity-based protein profiling (ABPP) has emerged as a powerful functional chemoproteomic strategy which enables global profiling of proteome reactivity toward bioactive small molecules in complex biological and/or pathological processes. To quantify the degree of reactivity in a site-specific manner, an isotopic tandem orthogonal proteolysis (isoTOP)-ABPP strategy has been developed; however, the high cost and long workflow associated with the synthesis of isotopically labeled cleavable tags limit its wide use. Herein, we combined reductive dimethyl labeling with TOP-ABPP to develop a fast, affordable, and efficient method, termed “rdTOP-ABPP”, for quantitative chemical proteomics with site-specific precision and triplex quantification. The rdTOPABPP method shows high accuracy and precision, good reproducibility, and better capacity for site identification and quantification and is highly compatible with many commercially available cleavable tags. We demonstrated the power of rdTOP-ABPP by profiling the target of (1S,3R)-RSL3, a canonical inducer for cell ferroptosis, and provided the first global portrait of its proteome reactivity in a quantitative and site-specific manner.

B

allow quantitative chemical proteomic profiling with sitespecific precision. Among the strategies for quantitative proteomics, dimethyl labeling is a widely used, convenient, and affordable method that is applicable to essentially any type of proteome samples.14 This chemical labeling method is based on reductive amination, where the peptide N-terminus and the ε-amino group of lysines will get isotopically labeled in a triplet manner with proper combinations of isotopomers of formaldehyde and cyanoborohydride. Previous studies have shown this method has good specificity and high accuracy in quantification of regular proteome samples.15,16 More recently, it was applied with standard ABPP to quantify at the protein level the targets of chemicals,17,18 post-translational modifications,19,20 and dynamics of glycosylation.21 Herein we combined dimethyl labeling and TOP-ABPP to develop a fast, efficient, affordable, and easily accessible strategy, called “rdTOP-ABPP”, for multiplex quantitative chemical proteomics with site-specific precision (Scheme 1). We showed that the optimized method is flexibly compatible with different types of cleavable tags. We demonstrated that the method was able to recapitulate the performance of isoTOP-ABPP in quantitative profiling of sites of modification by a representative lipid-derived electrophile, 4-hydroxy-2-

ioactive small molecules including natural products, pharmaceutical drugs, endogenous metabolites, and environmental chemicals, etc., play critical roles in shaping cell physiology and pathology.1 Chemoproteomic methods, such as “activity-based protein profiling” (ABPP), have become enabling tools for studying the bioactive-species-protein interactions on a proteome-wide scale to reveal the mechanisms underlying their biological, therapeutic, or toxicological action.2−4 Combined with a tandem orthogonal proteolysis (TOP) strategy and a pair of isotope-coded cleavable tags, an advanced version of ABPP platform named “isoTOP-ABPP” has enabled site-specific quantification of probe labeling and modification by endogenous metabolites as well as reactive drug fragments in complexed biological systems.5,6 In addition to the original isoTOP-ABPP tags that can be cleaved by TEV protease, the isotopic portions have also been incorporated into reductant, photolytic, and acid-cleavable tags.7−9 Recently, isotopically labeled iodoacetamide−alkyne probes were developed for quantitative profiling of the degree of reversible cysteine oxidation,10 which is analogous to the OxICAT strategy.11 However, in all these cases, the customized synthesis of cleavable tags or probes with isotopic labeling are often not trivial and require significant efforts to achieve desired yields. While isobaric tags for relative and absolute quantitation (iTRAQ)12 were also combined with TOP-ABPP to quantify sites of modification,13 the high costs associated with purchasing iTRAQ reagents limit their wide applications. It is therefore desirable to develop a general, affordable, and conveniently accessible approach to © XXXX American Chemical Society

Received: May 31, 2018 Accepted: June 26, 2018

A

DOI: 10.1021/acs.analchem.8b02426 Anal. Chem. XXXX, XXX, XXX−XXX

Article

Analytical Chemistry

precipitated proteins were collected by centrifugation (8000 g, 5 min), washed with cold methanol three times, and resuspended in 1.2% SDS/PBS. The samples were then diluted to 0.2% SDS/PBS and incubated with 100 μL of streptavidin agarose beads (Thermo Scientific) for 4 h at 29 °C. The beads were washed with 3 × 5 mL of PBS and water sequentially and suspended in 500 μL of 6 M urea/PBS. After reduction with 10 mM dithiothreitol (DTT) at 37 °C for 30 min and alkylation with 20 mM iodoacetamide (IAA) at 35 °C for 30 min in dark, the beads were resuspended in 200 μL of 2 M urea, 1 mM CaCl2, and 2 μg of trypsin (Promega) in PBS at 37 °C with agitation overnight. On the next morning, the beads were collected by centrifugation and washed with 2 × 1 mL of PBS, 2 × 1 mL of H2O, and 2 × 1 mL of 100 mM triethylammonium bicarbonate (TEAB) buffer (Sigma) before being suspended in 100 μL of 100 mM TEAB buffer. Then 8 μL of 4% D13CDO (Sigma), DCDO (Sigma), or HCHO (Sigma) was added to the samples to be light, medium, and heavy labeled. Then 8 μL of 0.6 M NaBH3CN was added to the sample on ice to be light and medium dimethylated and NaBD 3CN to the sample to be heavy dimethylated, respectively. After being washed by 100 mM TEAB buffer twice, differently labeled samples were mixed and washed with 2 × 1 mL H2O, followed by on-beads cleavage. Test of Different Cleavable Tags. For the TEV proteasecleavable tag, the beads were first washed with 1 mL of 1× TEV buffer (140 mL water, 7.5 mL of 20× TEV buffer, and 1.5 mL of 100 μM DTT). On-beads TEV digestion was carried out by incubating the beads with 200 μL of 1× TEV buffer, and 5 μL of in-house purified Ac-TEV protease (2.5 mg/mL) in a 29 °C incubator overnight with mild agitation. After the beads were washed with H2O (2 × 200 μL), the supernatant was collected and 5% formic acid was added. The samples were desalted before LC-MS/MS analysis.5 For the photo-cleavable tag, 1 mL of methanol−H2O (7/3, vol/vol) was added to the beads, and the suspensions were transferred to thin-walled glass tubes before irradiation with UV 365 nm (5000 × 100 μJ/cm2) for 1 h on ice to release the adducted peptides. The mixtures were transferred to a LoBind tube (Eppendorf) and centrifuged to collect the cleaved peptides in liquid phase. The beads were washed with 2 × 0.5 mL of methanol−H2O (7/3, vol/vol), and the peptides solutions were combined and dried in vacuum. For acid-cleavable tags, the samples were cleaved with three sequential 30 min treatments of 2% formic acid/ H2O (300 μL) at 25 °C with rotation. The eluents from all three cleavage cycles were collected and combined. Afterward, the beads were washed with 50% acetonitrile−H2O + 1% formic acid (2 × 300 μL), and the washes were combined with the eluents to form the cleavage fraction. The cleavage fraction was concentrated using a vacuum centrifuge.22 LC-MS/MS Analysis. LC-MS/MS was performed on a QExactive plus Orbitrap mass spectrometer (Thermo Fisher Scientific) coupled with an Ultimate 3000 LC system. Mobile phase A was 0.1% FA in H2O, and mobile phase B was 0.1% FA in ACN. The flow rate was 3 μL/min for loading and 0.3 μL/min for eluting. Labeled peptide samples were loaded onto a 100 μm fused silica column packed with 15 cm × 3 μm C18 resin. Under the positive-ion mode, full-scan mass spectra were acquired over the m/z range from 350 to 1800 using the Orbitrap mass analyzer with mass resolution of 70 000. MS/ MS fragmentation is performed in a data-dependent mode, of which the 20 most intense ions are selected for MS/MS analysis at a resolution of 17 500 using collision mode of HCD.

Scheme 1. Workflow of the rdTOP-ABPP Method

nonenal (HNE). We further applied this method to profile sites of modification by (1S,3R)-RSL3, a canonical inducer for cell ferroptosis, and provided the first global portrait of its proteome reactivity with site-specific precision. The proteome samples of three different conditions were labeled with an activity-based bioorthogonal probe, conjugated by CuAAC (copper-catalyzed azide−alkyne cycloaddition) to a cleavable biotin tag and subjected to trypsin digestion. The resulting peptides with probe labeling were further isotopically derivatized by triplex reductive dimethylation, respectively. After the beads were combined and the on-beads tandem orthogonal cleavage was performed, the released adducted peptides were subjected to LC-MS/MS analysis, which allows accurate quantification of probe labeling and/or modification across the three samples.

■

EXPERIMENTAL SECTION Cell Culture. HT1080 and MDA-MB-231 cells were maintained in DMEM (Gibco, Life), and K562 cells were in RPMI 1640 medium (Gibco, Life) supplemented with 5% FBS (Premium, South America) and antibiotics (100 IU/mL penicillin and 100 μg/mL streptomycin) at 37 °C under 5% CO2 atmosphere. Fluorescence Gel Imaging. HT1080 cells were grown to 80% confluence and harvested by scraping and centrifugation at 1400g. The cells were washed twice in PBS buffer and frozen at −80 °C. Upon use, frozen cell pellets were resuspended in PBS buffer containing 0.1% TritonX-100 and lysed by sonication. The lysates were centrifuged at 100 000g for 30 min to remove cell debris. The concentrations of cell lysate were determined with a Pierce BCA protein assay kit (Thermo Fisher Scientific) and normalized to 2 mg/mL. The lysate was incubated with DMSO, (1R,3R)-RSL3, or (1S,3R)-RSL3 at indicated concentrations for 1 h at 25 °C and treated with 100 μM IA-alkyne probe for another 1 h. The proteomes were reacted with 1 mM CuSO4, 100 μM tris(benzyltriazolylmethyl)amine (TBTA), 1 mM TCEP, and 100 μM rhodamin-N3 for 1 h and then boiled using 5× SDSPAGE loading buffer at 95 °C for 5 min. The samples were analyzed by 10% SDS-PAGE gels and imaged by a rhodamine channel on a ChemiDoc MP (Bio-Rad). The gels were then stained by Coomassie staining (CBB) as loading control. rdTOP-ABPP Labeling. Each treated cell lysate (2 mg/ mL) was incubated with 100 μM probe for 1 h at 25 °C and reacted with 1 mM CuSO4, 100 μM TBTA ligand, 1 mM TCEP, and 100 μM biotin cleavable tag for another 1 h. The B

DOI: 10.1021/acs.analchem.8b02426 Anal. Chem. XXXX, XXX, XXX−XXX

Article

Analytical Chemistry

Figure 1. Optimization of the condition of dimethyl labeling in rdTOP-ABPP. (A) The scheme of introducing reductive dimethylation in rdTOPABPP. Pos. 1: before orthogonal proteolysis; pos. 2: after orthogonal proteolysis and before desalting; pos. 3: after desalting. (B) Optimization of the position for performing reductive dimethylation. (C) Optimization of the concentration of dimethyl labeling reagent (shown as NaBH3CN). HCHO is 2.2 equiv to NaBH3CN. (D) Optimization of the labeling time. In parts B−D, the number of probe-adducted peptides identified by each rdTOP-ABPP condition was normalized to that identified by standard TOP-ABPP. (E) Comparison of the numbers of probe-adducted peptides identified by the optimized rdTOP-ABPP and the standard TOP-ABPP. (F) Percentage of peptides identified with reductive dimethylation. (G) Comparison of the number of identified peptides by the optimized rdTOP-ABPP using the TEV protease- and photo- and acid-cleavable tags, respectively. Error bars in B, C, D, and G represent mean ± SD.

■

RESULTS AND DISCUSSION Development of rdTOP-ABPP Method. While it seems conceptually straightforward to combine dimethyl labeling with the well-established TOP-ABPP workflow, key experimental conditions need to be carefully investigated and optimized, including where to introduce the dimethyl labeling, and the concentration and incubation time of dimethyl labeling. We followed the original TOP-ABPP workflow with a cysteine-reactive iodoacetamide alkyne (IA-alkyne) probe (Figure S1) and a cleavable biotin tag (TEV protease-cleavable tag)5 to optimize our method. Because dimethyl labeling should be introduced at the peptide level, we tested the incorporation of dimethyl labeling at three possible positions after trypsin digestion, including (1) before orthogonal proteolysis, (2) after orthogonal proteolysis and before desalting, and (3) after desalting (Figure 1A). The results showed that dimethyl labeling on beads before orthogonal proteolysis at position 1 yielded the highest number of identified probe-adducted peptides, whereas a lower number of peptides identified when the dimethyl labeling was performed at positions 2 and 3, most likely due to the relatively low activity of TEV protease in TEAB buffer and the extra step in the desalting operation (Figure 1B). Considering that introducing isotopic labeling at early steps will also help minimize variation of quantitation, we finally chose to perform dimethyl labeling on beads between the trypsin digestion and the orthogonal proteolysis. We further optimized the concentration of dimethyl labeling reagents, including NaBH3CN and HCHO (Figure 1C) and the length of time

Other important parameters: isolation window, 2.0 m/z units; default charge, 2+; normalized collision energy, 28%; maximum IT, 50 ms; dynamic exclusion, 20.0 s. Data Processing. The MS/MS spectra were extracted from the raw file using RAW Xtractor into an ms2 format and were searched using the ProLuCID algorithm23 using a reverse concatenated, nonredundant variant of the Human UniProt database (release-2012_11). Cysteine carbamidomethylation (+57.0215 Da), N-terminus dimethyl labeling, and lysine residue dimethyl labeling were chosen as static modifications with tag masses of +28.03130 Da (light), + 32.05641 Da (medium), and +36.07567 Da (heavy), respectively. Variable modifications on cysteines are set at 464.28596 Da (for TEV protease-cleavable tag), 180.1375 Da (for photocleavable tag) or 322.23688 Da (for acid-cleavable tag). Peptides were required to have at least one cognate tryptic end. ProLuCID data was filtered through DTASelect (version 2.0)24 to achieve a peptide false-positive rate below 1%. Quantification of light/ medium/heavy ratios (rdTOP-ABPP ratios, R) was performed using an in-house software CIMAGE written in the R programming language that utilizes routines from the opensource XCMS package for MS data analysis to read in raw chromatographic data in the mzXML format. On the basis of duplex quantification for isoTOP-ABPP data analysis as described previously,5 an additional algorithm was developed to enable triplex quantification of light to heavy (L:H), light to medium (L:M), and heavy to medium (H:M) ratios at the same time. C

DOI: 10.1021/acs.analchem.8b02426 Anal. Chem. XXXX, XXX, XXX−XXX

Article

Analytical Chemistry for the dimethyl labeling reaction (Figure 1D). The results showed that the labeling reached saturation with 48 mM of NaBH3CN and was completed within 2 h. Under these optimized conditions, more probe-adducted peptides were identified by rdTOP-ABPP than that by the standard TOPABPP experiment (Figure 1E) with a labeling efficiency of 99.7% (Figure 1F). The improvement is consistent with previous studies showing that dimethylation induces a stronger response of labeled peptides in electrospray ionization (ESI) and increases the peptide hydrophobicity to enhance the performance of reverse phase high performance liquid chromatography (RP-HPLC).25,26 Because isotopic labeling is introduced by dimethylation, this new method is in principle compatible with any type of cleavable azide−biotin tags, many of which are commercially available. We next compared the performance of three commonly used cleavable tags in rdTOP-ABPP, including the TEV tag for the original TOP-ABPP application, the photocleavable tag for profiling of cysteine oxidation,27 and the acid-cleavable tag for quantitative glycoproteomic applications.22 The results showed that the acid-cleavable tag yielded the most probe-adducted peptide identifications (Figure 1G). These results collectively demonstrated that by introducing isotopic labeling with reductive dimethylation, the method is highly compatible with different types of cleavable azide− biotin enrichment tags. Thus, rdTOP-ABPP provides an efficient and affordable alternative strategy for site-specific quantitative chemical proteomics without the trouble of complicated and lengthy chemical synthesis of cleavable tags containing an inherent isotope-coded signature. Evaluation of Quantitation Accuracy of rdTOP-ABPP. We next evaluated accuracy and dynamic range of the rdTOPABPP method for quantifying sites of probe labeling. K562 proteomes were first labeled by 100 μM of IA-alkyne, and after conjugation with the TEV protease-cleavable tag by CuAAC, probe-labeled proteins were affinity enriched by streptavidin beads and digested on beads by trypsin. The beads were split into one of the five defined portions (5:1, 2:1, 1:1, 1:2, 1:5) and labeled by medium and light dimethyl labeling reagents, respectively. The labeled beads were recombined and subjected to an orthogonal digestion by TEV protease to release probe-adducted peptides for LC-MS/MS analysis (Figure S2). Quantification of the probe-adducted peptides by light and medium dimethylation showed that the median ratio measured from each of the five samples closely matched the expected value with the calculated R2 very close to 1. Moreover, the standard deviations of quantified ratios from each sample ranged from 0.11 to 0.34, demonstrating the high accuracy and large dynamic range of the rdTOP-ABPP workflow (Figure 2A). To further verify the ability of triplex quantification of rdTOP-ABPP, we treated three equal aliquots of the streptavidin beads with enriched peptides by light, medium, and heavy dimethyl labeling reagents, respectively, and mixed all of them together before TEV protease digestion and LC-MS/MS analysis. The median ratio of heavy/medium, light/medium, and light/heavy were 1.07, 1.00, and 0.93, respectively, and the standard deviations of quantification were all below 0.3 (Figure 2B). Application of rdTOP-ABPP in Profiling HNE-Reactive Cysteines in Proteomes. To further validate the quantitation capacity of rdTOP-ABPP, we also applied the new method to analyze the modification of cysteines in proteomes by HNE, which is a major product of lipid peroxidation under oxidative

Figure 2. Quantification accuracy of rdTOP-ABPP. Measured quantitative ratios of identified peptides are shown for (A) the 5:1, 2:1, 1:1, 1:2, 1:5 ratios of medium and light dimethyl labeling and (B) the 1:1:1 ratios of triplex (heavy, medium, and light) dimethyl labeling. Box plots denote the median (line), the 25th and 75th percentile (box), and the 10th and 90th percentile (whiskers).

stress (Figure S1).20 Previously, a competitive isoTOP-ABPP workflow was developed to quantify HNE-reactive cysteines in proteomes with isotopically labeled TEV protease-cleavable tag.28 We envision that such an experiment will serve as a perfect reference to evaluate the performance of rdTOP-ABPP where the isotopic labeling was introduced by the reductive dimethylation. More specifically, we repeated the competitive isoTOP-ABPP experiments with 10 μM and 50 μM HNE as in vitro competing compounds, respectively (Figure 3A). Limited by the duplex quantification capacity of isoTOP-ABPP, each dose of HNE had to be applied separately, and its competition on the IA-alkyne probe labeling was individually compared to the control group treated with DMSO. To demonstrate the dose-dependent competition by HNE, the quantification data from the two independent LC-MS/MS runs (DMSO vs 10 μM HNE; DMSO vs 50 μM HNE) needed to be cross-checked with each other, and only the overlapping sites were kept which results in significant loss in proteome coverage due to the stochastic nature of data-dependent acquisition in LC-MS/ MS. In this regard, rdTOP-ABPP shows unique advantage by allowing triplex quantification of IA-alkyne probe labeling on proteomes treated with DMSO, 10 μM and 50 μM of HNE simultaneously in a single LC-MS/MS run. As shown in Figure 3B, rdTOP-ABPP with triplex quantification in a single run could quantify slightly more cysteine sites with dose-dependent HNE labeling than those by the two competitive isoTOPABPP experiments combined, and more importantly, the two methods showed substantial overlap in identifying HNEreactive cysteines in proteomes. For example, most of the HNE-hyperreactive cysteines identified from the competitive isoTOP-ABPP experiments were also accurately quantified by rdTOP-ABPP, including C1101 of reticulon-4 (RTN4), C44 of elongation factor 2 (EEF2) and C44 of ketosamine-3kinasein (FN3KRP) (Figure 3C).28 rdTOP-ABPP also quantified two other HNE-hyperreactive cysteines, C282 of HMOX2 and C210 of VDAC2, both of which were identified in a recent study using an aniline-based probe.20 (Table S1). Furthermore, quantitative ratios measured by competitive D

DOI: 10.1021/acs.analchem.8b02426 Anal. Chem. XXXX, XXX, XXX−XXX

Article

Analytical Chemistry

approaches correlate very well with each other with a fitted slope line close to 1 and R2 of 0.9 for each concentration of HNE (Figure S3). These results collectively demonstrated that rdTOP-ABPP was able to reproduce the performance of competitive isoTOP-ABPP with higher quantification capacity (from duplex to triplex) and much reduced analytical instrument time and reagent cost. Profiling of RLS3-Reactive Cysteines in Proteomes by rdTOP-ABPP. In addition to quantitative profiling of sitespecific modification by a given reactive ligand of interest in a dose-dependent manner, the triplex labeling of rdTOP-ABPP should also allow head-to-head comparison of target engagement between two highly related compounds but with dramatically different bioactivity. This will enable identification of specific targets of the bioactive compound with both the inactive counterpart and solvent as negative controls. Herein we chose to apply rdTOP-ABPP to profile cysteine targets of RSL3, which is a potent inducer of ferroptosis, a recently annotated form of cell death driven by elevated level of intracellular reactive oxygen species (ROS) (Figure S4).29,30 It has been shown that only the (1S,3R) diastereomer of this small molecule could induce ferroptosis, while the closely related (1R,3R) diastereomer is at least 200-fold less active.31 Using a fluorescein-derivatized (1S,3R)-RSL3 probe, Stockwell and co-workers identified glutathione peroxidase 4 (GPX4) as the main target of RSL3 and later confirmed biochemically that (1S,3R)-RSL3 covalently modifies the active-site selenocysteine to impair its catalytic activity and induce accumulation of phospholipid hydroperoxide. Despite the promiscuous reactivity of the chloroacetamide group in RSL3 (marked with asterisks and red color, Figure S4), its proteome-wide reactivity toward other functional cysteines or selenocysteines have not been thoroughly explored with site-specific precision. We therefore set out to apply rdTOP-ABPP to distinguish the sensitive cysteine sites of the active (1S,3R)-RSL3 from the inactive (1R,3R)-RSL3 by comparing their competition with the IA-alkyne probe labeling (Figure 4A). First, we monitored

Figure 3. Comparison of isoTOP-ABPP and rdTOP-ABPP by quantifying target sites of HNE. (A) Schematic workflow for profiling HNE target using competitive version of isoTOP-ABPP and rdTOPABPP where triplex quantification can be realized by a single LC-MS/ MS run. (B) Venn diagram showing the numbers of quantified peptides in rdTOP-ABPP and TOP-ABPP in HNE target profiling. (C) Recapitulation of known HNE-hyperreactive cysteines by rdTOP-ABPP.

isoTOP-ABPP and rdTOP-ABPP were compared side-by-side, and the results showed that the performance of the two

Figure 4. Profiling of target cysteines of (1S,3R)-RSL3 in proteome by rdTOP-ABPP. (A) The schematic workflow for profiling the target sites of (1S,3R)-RSL3. (B) Competition of IA-alkyne labeling by (1S,3R)-RSL3 and (1R,3R)-RSL3 using in-gel fluorescence. (C) Venn diagram showing the number of high-confidence target sites of (1S,3R)-RSL3 from three replicates. (D) rdTOP-ABPP ratio distributions of targets modified by (1S,3R)-RSL3 but not (1R,3R)-RSL3. Raw extracted ion chromatographic peaks of C47 of VDAC2 which is an outstanding target of (1S,3R)RSL3 are shown on right. E

DOI: 10.1021/acs.analchem.8b02426 Anal. Chem. XXXX, XXX, XXX−XXX

Article

Analytical Chemistry Table 1. Summary of Outstanding Target Cysteines by (1S,3R)-RSL3 Quantified by rdTOP-ABPP Uniprot

protein

site(s)

R(1R,3R)‑RSL3

R(1S,3R)‑RSL3

function of identified site(s)

ref

P45880 Q9BQB6 Q53GQ0 P12236

VDAC2 VKORC1 HSD17B12 SLC25A6

C47 C43, C51 C166 C257

1.08 0.99 1.10 1.06

15.00 8.22 5.77 5.68

distinct reactivity toward some lactones electron transfer unannotated elevated mitochondrial ROS and decreased MMP

13 32 − 18

proteome samples. The method is also compatible with a large suite of cleavable enrichment tags, many of which are commercially available and therefore saves the trouble for expensive and demanding synthesis of isotopically coded enrichment tags. We optimized the workflow so that it operates quantitatively with high accuracy, wide dynamic range, and good reproducibility. We showed that the triplex quantification allows profiling of modification sites by bioactive compounds in a dose-dependent manner within a single LCMS/MS run, and the feature can also be implemented to determine target specificity between closely related ligands. We applied rdTOP-ABPP to provide the first global landscape of RSL3-reactive cysteines in proteomes and identified C47 of VDAC2 and a few other cysteines as outstanding targets of this ferroptosis inducer. We believe that, with its great affordability and general applicability, rdTOP-ABPP will become another valuable chemoproteomic tool to discover and characterize of protein−ligand interactions and protein post-translational modifications in complex biological systems.

the competition by these diastereomers using in-gel fluorescence, and the results showed that loss of IA-alkyne labeling only occurred in the presence of (1S,3R)-RSL3 but not the (1R,3R)-RSL3, indicating that the active diastereomer has a higher reactivity toward cysteines in proteomes (Figure 4B). We next performed the triplex rdTOP-ABPP experiment and identified by mass spectrometry those cysteines that are only sensitive to modification by (1S,3R)-RSL3. More specifically, lysates of HT1080 cells were first treated with DMSO, 100 μM of (1S,3R)-RSL3, or (1R,3R)-RSL3, respectively, and subsequently labeled by the IA-alkyne probe. The three samples were then prepared by the described rdTOP-ABPP workflow with the DMSO-, (1S,3R)-RSL3-, and (1R,3R)-RSL3-treated samples being labeled by light, medium, and heavy dimethylation reagents, respectively (Figure 4A). After LC-MS/MS analysis and triplex quantification by CIMAGE, we defined (1S,3R)-RSL3-sensitive cysteines as those with both the low light/heavy ratio (0.8 ≤ R(1R,3R)‑RSL3 ≤ 1.25) and the high light/medium ratio (R > R(1R,3R)‑RSL3). In total, we identified 106 unique cysteines across three biological replicates (Figure 4C, Table S1). We also specifically searched for selenocysteine-containing peptides in the LC-MS/MS data and unfortunately did not identify any positive hit including that from GPX4, which could probably be explained by the low abundance of these functionally important redox-regulating proteins in HT1080 cells.31 Among all the (1S,3R)-RSL3sensitive cysteines, C47 of VDAC2 was ranked as the top candidate, which showed an outstanding competition ratio only with the active form of RSL3 (R = 15) but not with the inactive counterpart (R = 1.25) (Figure 4D, Table 1). Furthermore, other cysteines of VDAC2 did not show any obvious competition by both RSL3 diastereomers, suggesting C47 of VDAC2 is a specific site of modification by (1S,3R)RSL3 (Figure S5). VDAC2 is a voltage-dependent anionselective channel protein located on the outer membrane of mitochondria. It was previously identified as one of the major targets of erastin, another potent inducer of ferroptosis29 and more recently discovered as the substrate of protein carbonylation during ferroptosis.20 Our rdTOP-ABPP profiling found a novel cysteine in VDAC2 as the direct target of (1S,3R)RSL3 and suggested the protein might be playing an important role in mediating ferroptosis induced by RSL3 in addition to the established GPX4 route. In addition to C47 of VDAC2, we also quantified a few other cysteines with outstanding competition ratios, suggesting that these sites are also targeted by (1S,3R)-RSL3 (Figure 4D, Table 1). It will be intriguing to test the functional implication of these cysteines with ferroptosis in future.

■

ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.analchem.8b02426. Figures S1−5 and NMR data of (1R,3R)-RSL3 (PDF) Target sites of HNE and (1S,3R)-RSL3 (Table S1) (XLSX)

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Chu Wang: 0000-0002-6925-1268 Author Contributions ‡

These authors contributed equally

Author Contributions

C.W. and F.Y. conceived of the project. F.Y. and G.J. performed the chemoproteomic and biological experiments. J.G. developed the computational software for triplex quantification. J.C. synthesized (1R,3R)-RSL3 compound. F.Y. and C.W. analyzed data and wrote the manuscript. F.Y. and J.G. contributed equally to this work. Notes

The authors declare no competing financial interest.

■

■

ACKNOWLEDGMENTS We thank the Computing Platform of the Center for Life Science for supporting the proteomic data analysis. This work was supported by Ministry of Science and Technology of China (2016YFA0501500), National Science Foundation of China (21778004, 21521003, and 81490741), and a “1000 Talents Plan” Young Investigator Award (C.W.).

CONCLUSIONS In summary, we have developed an efficient and affordable chemical proteomic method with site-specific precision and triplex quantification. rdTOP-ABPP takes advantages of the easily accessible and inexpensive isotopic labeling by reductive dimethylation that can be generally applicable to any type of F

DOI: 10.1021/acs.analchem.8b02426 Anal. Chem. XXXX, XXX, XXX−XXX

Article

Analytical Chemistry

■

A. F.; Clish, C. B.; Brown, L. M.; Girotti, A. W.; Cornish, V. W.; Schreiber, S. L.; Stockwell, B. R. Cell 2014, 156, 317−331. (32) Schulman, S.; Wang, B.; Li, W.; Rapoport, T. A. Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 15027−15032.

REFERENCES

(1) Rix, U.; Superti-Furga, G. Nat. Chem. Biol. 2009, 5, 616−624. (2) Cravatt, B. F.; Wright, A. T.; Kozarich, J. W. Annu. Rev. Biochem. 2008, 77, 383−414. (3) Wang, C.; Chen, N. Huaxue Xuebao 2015, 73, 657−668. (4) Meier, J. L.; Schnermann, M. J. Mol. Pharmaceutics 2018, 15, 703−704. (5) Weerapana, E.; Wang, C.; Simon, G. M.; Richter, F.; Khare, S.; Dillon, M. B.; Bachovchin, D. A.; Mowen, K.; Baker, D.; Cravatt, B. F. Nature 2010, 468, 790−795. (6) Backus, K. M.; Correia, B. E.; Lum, K. M.; Forli, S.; Horning, B. D.; González-Páez, G. E.; Chatterjee, S.; Lanning, B. R.; Teijaro, J. R.; Olson, A. J.; Wolan, D. W.; Cravatt, B. F. Nature 2016, 534, 570−574. (7) Szychowski, J.; Mahdavi, A.; Hodas, J. J.; Bagert, J. D.; Ngo, J. T.; Landgraf, P.; Dieterich, D. C.; Schuman, E. M.; Tirrell, D. A. J. Am. Chem. Soc. 2010, 132, 18351−18360. (8) Yang, Y. Y.; Grammel, M.; Raghavan, A. S.; Charron, G.; Hang, H. C. Chem. Biol. 2010, 17, 1212−1222. (9) Qian, Y.; Martell, J.; Pace, N. J.; Ballard, T. E.; Johnson, D. S.; Weerapana, E. ChemBioChem 2013, 14, 1410−1414. (10) Abo, M.; Li, C.; Weerapana, E. Mol. Pharmaceutics 2018, 15, 743−749. (11) Leichert, L. I.; Gehrke, F.; Gudiseva, H. V.; Blackwell, T.; Ilbert, M.; Walker, A. K.; Strahler, J. R.; Andrews, P. C.; Jakob, U. Proc. Natl. Acad. Sci. U. S. A. 2008, 105, 8197−8202. (12) Zieske, L. R. J. Exp. Bot. 2006, 57, 1501−1508. (13) Tian, C.; Sun, R.; Liu, K.; Fu, L.; Liu, X.; Zhou, W.; Yang, Y.; Yang, J. Cell Chem. Biol. 2017, 24, 1416−1427.e5. (14) Hsu, J. L.; Huang, S. Y.; Chow, N. H.; Chen, S. H. Anal. Chem. 2003, 75, 6843−6852. (15) Boersema, P. J.; Raijmakers, R.; Lemeer, S.; Mohammed, S.; Heck, A. J. Nat. Protoc. 2009, 4, 484−494. (16) Hsu, J. L.; Chen, S. H. Philos. Trans. R. Soc., A 2016, 374, 20150364. (17) Counihan, J. L.; Ford, B.; Nomura, D. K. Curr. Opin. Chem. Biol. 2016, 30, 68−76. (18) Ye, Z.; Zhang, X.; Zhu, Y.; Song, T.; Chen, X.; Lei, X.; Wang, C. Mol. Pharmaceutics 2018, 15, 2413−2422. (19) Chen, Y.; Cong, Y.; Quan, B.; Lan, T.; Chu, X.; Ye, Z.; Hou, X.; Wang, C. Redox Biol. 2017, 12, 712−718. (20) Chen, Y.; Liu, Y.; Lan, T.; Qin, W.; Zhu, Y.; Qin, K.; Gao, J.; Wang, H.; Hou, X.; Chen, N.; Friedmann Angeli, J. P.; Conrad, M.; Wang, C. J. Am. Chem. Soc. 2018, 140, 4712−4720. (21) Khidekel, N.; Ficarro, S. B.; Clark, P. M.; Bryan, M. C.; Swaney, D. L.; Rexach, J. E.; Sun, Y. E.; Coon, J. J.; Peters, E. C.; HsiehWilson, L. C. Nat. Chem. Biol. 2007, 3, 339−348. (22) Woo, C. M.; Iavarone, A. T.; Spiciarich, D. R.; Palaniappan, K. K.; Bertozzi, C. R. Nat. Methods 2015, 12, 561−567. (23) Xu, T.; Park, S. K.; Venable, J. D.; Wohlschlegel, J. A.; Diedrich, J. K.; Cociorva, D.; Lu, B.; Liao, L.; Hewel, J.; Han, X.; Wong, C. C. L.; Fonslow, B.; Delahunty, C.; Gao, Y.; Shah, H.; Yates, J. R., 3rd J. Proteomics 2015, 129, 16−24. (24) Tabb, D. L.; McDonald, W. H.; Yates, J. R., 3rd J. Proteome Res. 2002, 1, 21−26. (25) Kulevich, S. E.; Frey, B. L.; Kreitinger, G.; Smith, L. M. Anal. Chem. 2010, 82, 10135−10142. (26) Cho, K. C.; Kang, J. W.; Choi, Y.; Kim, T. W.; Kim, K. P. J. Mass Spectrom. 2016, 51, 105−110. (27) Yang, J.; Tallman, K. A.; Porter, N. A.; Liebler, D. C. Anal. Chem. 2015, 87, 2535−2541. (28) Wang, C.; Weerapana, E.; Blewett, M. M.; Cravatt, B. F. Nat. Methods 2014, 11, 79−85. (29) Yagoda, N.; von Rechenberg, M.; Zaganjor, E.; Bauer, A. J.; Yang, W. S.; Fridman, D. J.; Wolpaw, A. J.; Smukste, I.; Peltier, J. M.; Boniface, J. J.; Smith, R.; Lessnick, S. L.; Sahasrabudhe, S.; Stockwell, B. R. Nature 2007, 447, 864−868. (30) Dixon, S. J.; Stockwell, B. R. Nat. Chem. Biol. 2014, 10, 9−17. (31) Yang, W. S.; SriRamaratnam, R.; Welsch, M. E.; Shimada, K.; Skouta, R.; Viswanathan, V. S.; Cheah, J. H.; Clemons, P. A.; Shamji, G

DOI: 10.1021/acs.analchem.8b02426 Anal. Chem. XXXX, XXX, XXX−XXX