Jessica A Espino1, Christina D King2, Lisa M Jones1, Renã A S Robinson2. 1. Department of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland 21201, United States. 2. Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States.
Abstract
In vivo fast photochemical oxidation of proteins (IV-FPOP) is a hydroxyl radical protein footprinting method used to study protein structure and protein-protein interactions. Oxidatively modified proteins by IV-FPOP are analyzed by mass spectrometry (MS), and the extent of oxidation is quantified by label-free MS. Peptide oxidation changes yield useful information about protein structure, due to changes in solvent accessibility. However, the sample size necessary for animal studies requires increased sample preparation and instrument time. Here, we report the combined application of IV-FPOP and the enhanced multiplexing strategy combined precursor isotopic labeling and isobaric tagging (cPILOT) for higher-throughput analysis of oxidative modifications in C. elegans. Key differences in the performance of label-free MS and cPILOT were identified. The addition of oxygen (+16) was the most abundant modification identified among all known possible FPOP modifications. This study presents IV-FPOP coupled with enhanced multiplexing strategies such as cPILOT to increase throughput of studies seeking to examine oxidative protein modifications.
In vivo fast photochemical oxidation of proteins (IV-FPOP) is a hydroxyl radical protein footprinting method used to study protein structure and protein-protein interactions. Oxidatively modified proteins by IV-FPOP are analyzed by mass spectrometry (MS), and the extent of oxidation is quantified by label-free MS. Peptide oxidation changes yield useful information about protein structure, due to changes in solvent accessibility. However, the sample size necessary for animal studies requires increased sample preparation and instrument time. Here, we report the combined application of IV-FPOP and the enhanced multiplexing strategy combined precursor isotopic labeling and isobaric tagging (cPILOT) for higher-throughput analysis of oxidative modifications in C. elegans. Key differences in the performance of label-free MS and cPILOT were identified. The addition of oxygen (+16) was the most abundant modification identified among all known possible FPOP modifications. This study presents IV-FPOP coupled with enhanced multiplexing strategies such as cPILOT to increase throughput of studies seeking to examine oxidative protein modifications.
Proteins
are multifaceted macromolecules
found in living organisms that function as catalysts for numerous
biochemical reactions and that regulate biological processes such
as cell signaling, regulation, and structure. Structural understanding
of these interactions has been predominantly studied by X-ray crystallography,[1] nuclear magnetic resonance (NMR),[2] cryogenic electron microscopy,[3] and most recently mass spectrometry (MS).[4] MS-based methods have the advantage over other techniques of identifying
and quantifying macromolecules from complex mixtures with high sensitivity
and low detection limits (i.e., atto- to zeptomole).In recent
years, protein footprinting by MS has become increasingly
used to study protein conformation and protein–ligand interactions.[4] These methods monitor changes in protein solvent
accessible surface area (SASA) using reversible or irreversible chemical
labels, which can be detected and quantified by MS. One covalent labeling
technique, hydroxyl radical (OH) protein footprinting (HRPF),[5] irreversibly labels the side chains of solvent
accessible amino acids using OH. Although there are multiple ways
to generate OH labels (e.g., Fenton chemistry,[6] water radiolysis,[7] and electrochemistry[8]), fast photochemical oxidation of proteins (FPOP)
generates OH on the submillisecond time scale.[9] FPOP utilizes an excimer laser at 248 nm to photolyze hydrogen peroxide
(H2O2) to generate OH.[9,10]In vitro applications of this technique have identified
protein–ligand[11] and protein–protein
interaction sites[12] and regions of conformational
change.[13]FPOP is a versatile method
and has been used to study complex protein
biological systems in-cell (IC-FPOP).[14,15] FPOP is particularly
suited for in-cell protein studies because the irreversible OH label
allows for postlabeling sample handling procedures, including protein
extraction, precipitation, purification, and digestion, prior to liquid
chromatography (LC) coupled to tandem MS analysis. Recently, Espino
and Jones extended the use of FPOP for in vivo structural
analysis in Caenorhabditis elegans (C. elegans).[16] The roundworm is suitable for in vivo FPOP (IV-FPOP) studies because of its facile uptake
of H2O2 and its transparency to the laser light.[17] Due to its conserved genome with higher-ordered
species, C. elegans has been used to study molecular
and developmental biology pathways and even host–pathogen response.[18,19]C. elegans is an excellent animal model also to
study biology in the context of human diseases.IV-FPOP of C. elegans for various applications
leads to substantial analysis time and costs. For example, most protein
footprinting experiments require control conditions (e.g., no laser/H2O2 and no H2O2) to subtract
background oxidation signals. In addition, protein footprinting studies
typically require technical replication and experimental conditions,
such as ligand-free against ligand-bound or normal versus diseased.
As protein footprinting methods are further developed to study complex
protein systems in-cell and animals, the number of controls, experimental
conditions, plus the number of biological and workflow replicates
can result in as many as 24 samples for a given biological question.
Recently, IC- and IV-FPOP have been effectively demonstrated using
label-free MS. For complex mixtures, it is desirable to reduce analysis
time and variation introduced from post-labeling procedures. Here,
we coupled IV-FPOP to an enhanced multiplexing strategy termed combined
precursor isotopic labeling and isobaric tagging (cPILOT).[20] cPILOT increases the number of samples that
can be analyzed simultaneously by combining isotopic labels (i.e.,
dimethylation) with isobaric chemical reagents (i.e., tandem mass
tags (TMT), isobaric tag for relative and absolute quantitation (iTRAQ),
or N,N-dimethyl leucine (DiLeu)).[20−22] For example, the N-terminus of peptides is labeled by light or heavy
dimethylation (C2H6 or 13C22H6, respectively), while lysine residues are
labeled by TMT 6-16 plex reagents. Recent advancements in isobaric
reagents with DiLeu[23] have increased the
capabilities of cPILOT to 24 samples.[24]Here, we describe the analysis of the C. elegans proteome modified by IV-FPOP using cPILOT enhanced multiplexing.
Briefly, after IV-FPOP, proteins are extracted and digested, and peptides
are labeled by cPILOT. Labeled peptides are then analyzed using strong
cation exchange (SCX) fractionation LC-MS, MS/MS, and MS3 (Figure ). A comparison of
the evaluation of oxidatively modified proteins and peptides by label-free
quantification and cPILOT shows the latter’s capability to
reduce analysis time while also maintaining the large sample sizes
required for IV-FPOP. In addition, the coupling of FPOP with cPILOT
led to a higher reproducibility in both the identification and quantification
of oxidatively modified proteins across biological replicates. Oxidatively
modified proteins were further analyzed to evaluate site-specific
modifications and coverage with label-free and cPILOT approaches.
Figure 1
Experimental
workflow for IV-FPOP cPILOT. C. elegans (N = 20,000) is grown to its fourth larva stage
(L4). Three conditions (control, control oxidation, and FPOP) have
three biological replicates. Worms in the presence of hydrogen peroxide
are flown through a 250 μm i.d. fused silica and irradiated
using a KrF excimer at 248 nm wavelength. Each biological replicate
has two workflow replicates, resulting in 18 samples. Following oxidative
labeling, samples are lysed and digested, and peptides are further
labeled by cPILOT. Specifically, peptides (50 μg) are labeled
by either light- or heavy dimethylation at the N-terminus and isobarically
tagged by TMT 10-plex at lysine residues. Finally, peptides are analyzed
using LC-MS, MS/MS, and MS3 on an Orbitrap Fusion Lumos,
and the extent of modification of each protein of interest for every
condition is calculated.
Experimental
workflow for IV-FPOP cPILOT. C. elegans (N = 20,000) is grown to its fourth larva stage
(L4). Three conditions (control, control oxidation, and FPOP) have
three biological replicates. Worms in the presence of hydrogen peroxide
are flown through a 250 μm i.d. fused silica and irradiated
using a KrF excimer at 248 nm wavelength. Each biological replicate
has two workflow replicates, resulting in 18 samples. Following oxidative
labeling, samples are lysed and digested, and peptides are further
labeled by cPILOT. Specifically, peptides (50 μg) are labeled
by either light- or heavy dimethylation at the N-terminus and isobarically
tagged by TMT 10-plex at lysine residues. Finally, peptides are analyzed
using LC-MS, MS/MS, and MS3 on an Orbitrap Fusion Lumos,
and the extent of modification of each protein of interest for every
condition is calculated.
Experimental Procedures
IV-FPOP
Covalent labeling studies were performed as
previously described with slight modifications.[16] Each sample was prepared with approximatively 20,000 worms.
Worms were kept separated from hydrogen peroxide and mixed together
prior to IV-FPOP labeling using two 5 mL syringes (SGE Analytical
Science). Each syringe was connected to a fused silica capillary (Polymicro
Technologies), 250 μm inner diameter (i.d.), and advanced by
a syringe pump (KD Scientific, Legato Model 101) at a final flow rate
of 363.26 μL*min–1. Worms were mixed in the
syringe using a VP710 tumble stirrer (V&P Scientific) with six
stir discs (VP722fF, V&P Scientific) to prevent settling. The
final peroxide concentration was 200 mM. The KrF excimer laser (GAM
Laser Inc.) at a wavelength of 248 nm was set to 50 Hz pulse frequency,
laser energy of 145 ± 1.01 mJ, pulse width of 2.46 mm, and zero
exclusion volume. Immediately after labeling, worms were collected
in a 15 mL conical tube containing the cell permeable quench solution
[20 mM N′-dimethylthiourea (DMTU) and 20 mM N-tert-butyl-α-phenylnitrone (PBN)],
in order to eliminate excess hydrogen peroxide and OH radicals, respectively.
Methionine sulfoxide reductase was inhibited by adding 1% DMSO to
the final sample. All irradiated samples were labeled in technical
duplicates and biological triplicates with an equal number of controls
(peroxide and no laser irradiation, no peroxide, and no laser irradiation).
Labeling by cPILOT
Peptides (50 μg) generated
from trypsin digestion were dissolved in 1% acetic acid (0.25 μg*μL–1). Formaldehyde/deuterated formaldehyde (Sigma-Aldrich)
(8 μL) and sodium cyanoborohydride/-deuteride (Sigma-Aldrich)
(8 μL) were added to label peptides with either light (−C2H6) or heavy (−13C22H6) dimethylation, respectively. Peptides
were reacted for 10 min (room temperature) with shaking. The reactions
were quenched with 1% ammonia (16 μL, 5 min). Dimethylated peptides
were reacidified with 5% FA, and light and heavy pairs were pooled
(Supplemental Figure S1 and Table S1),
desalted, and dried down by centrifugal evaporation. Desalted dimethylated
peptides were dissolved in 100 mM triethylammonium bicarbonate buffer,
and TMT6-plex reagents were prepared according to the manufacturer’s
protocol. TMT6 -plex reagents were added to peptides and
reacted at room temperature for 1 h with shaking. Peptides labeled
by cPILOT were quenched with 5% (w/v) hydroxylamine hydrochloride
for 15 min at room temperature and reacidified with FA. Peptides were
pooled into a single sample, dried down to remove ACN, desalted, and
dried down again by centrifugal evaporation. Peptides were then separated
by SCX fractionation.
The pooled sample containing peptides labeled by cPILOT was fractionated
by SCX according to the manufacturer’s protocol (Protea Biosciences).
Briefly, peptides (500 μg) were dissolved in buffer A and loaded
onto a preactivated spin column. Peptides were eluted from the spin
column in eight intervals (room temperature, 6 min, 4000 × g)
with increasing ammonium formate solutions (20, 40, 60, 80, 100, 150,
250, and 500 mM). Fractionated peptides were dried down by centrifugal
evaporation and dissolved in 0.1% FA in water (v/v).
Liquid Chromatography
and Mass Spectrometry Analyses
Label-Free MS Analysis
Online desalting and reversed-phase
(RP) chromatography was performed with an Acquity UPLC M-Class System
(Waters). Mobile phases A and B were 0.1% FA in water (v/v) and 0.1%
FA in ACN (v/v), respectively. Peptides (∼50 μg) were
loaded onto a commercial (Waters) trapping column (180 μm ×
20 mm) containing C18 (5 μm, 100 Å) at 15 μL*min–1 in 0.1% FA in water (v/v) for 10 min. After desalting,
samples were loaded onto an analytical column (75 μm i.d. ×
20 cm). Peptides were separated on a RP analytical column packed in-house
with C18 (Aqua, 5 μm, 125 Å, Phenomenex). The
gradient was as follows: 0–1 min, 3% B; 2–90 min 10–45%
B; 100–105 min 100% B; 106–120 min 3% B. Data-dependent
acquisition parameters were performed on an Orbitrap Fusion Lumos
mass spectrometer (Thermo Fisher) as follows: the MS survey scan in
the Orbitrap (OT, 375–1500 m/z) was 60,000
resolution; the most intense peaks within 4 s (Top Speed) were isolated
(1.2 m/z) and fragmented with high-energy collisional
dissociation (HCD) in the OT (15,000 resolution) with a normalized
collision energy (NCE) of 32%, AGC target of 5.0 × 105, dynamic exclusion of 60 s, ppm mass tolerance of 10, a maximum
IT of 35 ms, and an intensity threshold of 5.0 × 104.
FPOP-cPILOT MS Analysis
Online desalting and RP chromatography
was performed with a nano-UHPLC system equipped with an autosampler
(Dionex, ThermoFisher Scientific). Mobile phases A and B were 0.1%
FA in water (v/v) and 0.1% FA in ACN (v/v), respectively. Peptides
(250 ng) were loaded onto a commercial (Thermo Fisher Scientific)
trapping column (75 μm i.d. × 2 cm) containing C18 (XBridge BEH, 3 μm, 100 Å) at 2 μL*min–1 in 0.1% FA in water for 10 min. After desalting, each fraction was
loaded onto an analytical column (100 μm i.d. × 23 cm),
packed in-house with C18 (2.5 μm, 150 Å, Waters).
The gradient was as follows: 0–10 min, 10% mobile phase B;
10–30 min, 10–15% B; 30–75 min, 15–30%
B; 75–88 min, 30–60% B; 88–92 min, 60–90%
B; 92–99 min, 90% B; 99–100 min, 90–10% B; 100–120
min, 10% B. Data-dependent acquisition parameters were performed on
an Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher) as follows:
the MS survey scan in the Orbitrap (375–1500 m/z) was 120,000 resolution; the most intense peaks
within 3 s (Top Speed) were isolated (2 m/z) and fragmented with CID in the ion trap with an NCE of
35%, AGC of 1 × 104, dynamic exclusion of 20 s, ppm
mass tolerance of 10, and maximum IT of 100 ms. Directly after each
MS/MS scan, the ten most intense fragment ions (over varying m/z ranges) were selected for an additional
fragmentation (MS3) event by HCD and analyzed in the OT
(scan range: 100–400 m/z,
isolation width: 2 m/z, AGC: 5 × 104, NCE: 55%, resolution: 60,000, maximum IT: 118 ms). Other parameters
such as precursor selection range, precursor ion exclusion, and isobaric
tag loss exclusion were set as default. The targeted mass difference
node was employed. Mass differences of 8.0444 Da (heavy dimethylation
(DM) – light DM)) and 7.0381 Da (dimethyl 7-light DM) were
listed, and the partner intensity range relative to the most intense
precursor was set to 70–100%. A subsequent scan was performed
on both ions in the pair and matching charge states for ions in the
pair.
Data Analysis
RAW files were analyzed with Proteome
Discoverer v. 2.2 software (Thermo Scientific). Spectra were searched
against the Uniprot C. elegans database (07/17/2018,
26,794 sequences) to obtain sequence information. Parameters applied
to SEQUEST HT were as follows: one maximum trypsin missed cleavage,
precursor mass tolerance of 15 ppm, fragment mass tolerance of 1 Da;
static modifications were either light (+28.031 Da) or heavy (+36.028
or +35.070 Da) dimethyl on peptide N-termini and carbamidomethyl (+57.021
Da) of cysteine residues; dynamic modifications were TMT six-plex
(+229.163 Da) of lysine residues. Additionally, all known hydroxyl
radical side-chain modifications[25,26] were searched
as dynamic modifications. Raw data was searched twice to account for
light or heavy dimethylation modifications. Percolator database searching
was employed to generate medium (p < 0.05) confidence
peptide lists. Peptides with high or medium confidence were used to
identify and quantify proteins. Filters applied for peptides were
as follows: PSMs (peptide to spectral match) > 1 across biological
cohorts, peptide confidence level of medium, peptide rank of 1, peptide
deviation of 10 ppm, and S/N ≥
10. Reporter ion (m/z 126–131)
intensities had the following parameters: most confident centroid
and reporter ion mass tolerance of 30 ppm. Furthermore, reporter ion
values were normalized using internal reference scaling.[27] The extent of oxidation per peptide was calculated
as previously described[28] using the following
equationwhere reporter ion abundance (RIA) modified
is the abundance intensity of the peptide with the hydroxyl radical
modification, and RIA total is the total abundance intensity of the
same peptide with and without the hydroxyl radical modification.
Results and Discussion
C. elegans is
a suitable model organism to study
biologically relevant interactions as it grows quickly, has a short
lifespan, is transparent, and has an evolutionarily conserved innate
immune response. Due to noted transparency at the wavelength required
for FPOP (248 nm), C. elegans is readily labeled
by IV-FPOP. IV-FPOP results in irreversible oxidative modifications
that allow for sample homogenization, digestion, and cleanup prior
to LC-MS analysis.Espino and Jones’ extension of FPOP
for in vivo HRPF covalent labeling in C.
elegans allows for
the study of protein interactions and protein structural changes in
native environments.[16] Herein, wild-type C. elegans (L4 stage) had three conditions: 1) laser irradiated
(KrF excimer, 248 nm) in the presence of H2O2 (sample), 2) exposed to H2O2 in the absence
of laser irradiation (control oxidation), and 3) not exposed to H2O2 (control). Three biological and two technical
replicates generated a total of 18 samples for analysis. Oxidatively
modified peptides and proteins modified by IV-FPOP have been quantified
by label-free MS, traditionally. However, individually processing
18 samples can be laborious and time-consuming; therefore, cPILOT
was employed as a multiplexing strategy to increase sample throughput.
Oxidatively modified proteins were digested, and resulting peptides
were labeled by cPILOT (Figure ). Labeled peptides were separated by offline SCX and online
RP chromatography and analyzed by MS, MS/MS, and MS3. This analysis
resulted in ∼180,000 PSMs corresponding to 2,682 proteins.
Protein groups identified from light (2,334) and heavy (2,193) dimethylated
peptides (Supplemental Table S2) were similar,
with 1,844 proteins (79–84%) overlapping between these groups.
TMT labeling efficiencies of both light and heavy dimethylated peptides
were ∼98% (Supplemental Table S2), and among identified proteins, over 65% were quantified across
all 18 reporter ion channels.
Biological Replicate Reproducibility Increases
among Modified
Proteins Using cPILOT
More than 700 oxidatively modified
proteins were identified by both IV-FPOP label-free MS and IV-FPOP
cPILOT quantification. A comparison of label-free quantification versus
cPILOT demonstrated that label-free MS identified more oxidatively
modified proteins across all biological replicates; however, cPILOT
had higher reproducibility among technical and biological replicates
(Figure ). Additionally,
SCX fractionation contributed to the increased proteome depth of the
cPILOT approach. The cPILOT analysis requires MS3 on the
Fusion Lumos which increases instrument duty cycle and lowers the
number of proteins identified.[21]
Figure 2
Protein oxidation
quantification across biological and technical
replicates. (a) IV-FPOP representative biological replicate of oxidatively
modified proteins identified by label-free MS across two technical
(tech) replicates: one (yellow, N = 157) and two
(orange, N = 143). (b) IV-FPOP oxidatively modified
proteins identified by cPILOT across technical replicates one (purple, N = 565) and two (green, N = 564). Venn
diagrams of oxidatively modified proteins by IV-FPOP across three
biological replicates (BR) identified by (c) label-free MS (N = 830) and (d) cPILOT (N = 703). (e)
Venn diagram of common oxidatively modified proteins among label-free
(red, N = 48) and cPILOT (blue, N = 429).
Protein oxidation
quantification across biological and technical
replicates. (a) IV-FPOP representative biological replicate of oxidatively
modified proteins identified by label-free MS across two technical
(tech) replicates: one (yellow, N = 157) and two
(orange, N = 143). (b) IV-FPOP oxidatively modified
proteins identified by cPILOT across technical replicates one (purple, N = 565) and two (green, N = 564). Venn
diagrams of oxidatively modified proteins by IV-FPOP across three
biological replicates (BR) identified by (c) label-free MS (N = 830) and (d) cPILOT (N = 703). (e)
Venn diagram of common oxidatively modified proteins among label-free
(red, N = 48) and cPILOT (blue, N = 429).Among three biological replicates,
90, 67, and 111 (43, 12, and
40%) oxidatively modified proteins overlapped between label-free MS
technical replicates (Figure a, Supplemental Figure S2a-b),
respectively. Upon implementing cPILOT, the overlap between technical
replicates increased to 563, 431, and 416 (99, 75, and 64%) oxidatively
modified proteins, respectively (Figure b, Supplemental Figure
S2a-b). When comparing oxidatively modified proteins identified
by label-free MS and cPILOT for the same biological replicate as Figure a-b, 678 oxidatively
modified proteins were identified across both methods (Supplemental Figure S2c). Though most identifications
were unique to cPILOT, 98 proteins were in common between both approaches;
this trend was also true for the other biological replicates. Among
the proteins that overlapped, the number of oxidatively modified peptides
observed and the number of oxidatively modified residues per peptide
are greater with cPILOT in 79% of these proteins (Supplemental Table S3).Across three biological replicates,
830 oxidatively modified proteins
were identified by label-free MS (Figure c), with 177 proteins being present in at
least two biological replicates. Upon implementing cPILOT to multiplex
samples, 703 oxidatively modified proteins (Figure d) were identified with 662 proteins being
present in at least two biological replicates. Interestingly, the
number of proteins shared across at least two biological replicates
increased approximatively 4-fold with cPILOT. This is an advantage
when compared to label-free quantitation which has shown large variations
in protein oxidation due to differences in protein abundance.[16,29]In addition, quantifying 703 proteins by cPILOT is promising
as
quantitative protein information can be gleaned in future experiments
that study other conditions, such as age, disease-state, or drug treatments.
Since the IV-FPOP reaction and the time of laser irradiation occur
very quickly (<30 s), significant changes in peptide oxidation
are mostly due to rapid natural occurring structural differences.Most importantly, the number of common oxidatively modified proteins
increased approximatively 9-fold from 48 to 429 proteins from using
label-free to cPILOT quantitative strategies, respectively (Figure c–d). This
greatly increases the potential number of proteins that can be compared
in future analyses. Among all biological replicates and between both
quantification strategies, 36 proteins (Figure e) were identified. When assessing the coefficient
of variation (CV) of 36 unique proteins common across both approaches,
cPILOT had a 2-fold less CV, on average, in comparison to label free
(data not shown). However, for most of these proteins,
single or few peptides were oxidatively modified and used to calculate
the CV across biological replicates. Greater numbers of peptides would
generally give more measurements, resulting in lower CVs.
Multiplexing
by cPILOT Increases Biological Reproducibility
in IV-FPOP Oxidatively Modified Peptides
The extent of oxidation
of the tubulin beta chain protein was evaluated as previously described.[28,30] Eleven oxidatively modified peptides for tubulin beta chain were
identified by label-free MS (Figure a), with no peptides being present in all three biological
replicates. In contrast, six oxidatively modified peptides were identified
with cPILOT; four of which were observed in all biological replicates
(Figure b).
Figure 3
Protein oxidation
for tubulin beta chain. Calculated ln(PF) for
tubulin beta chain oxidatively modified peptides identified by (a)
label-free MS (N = 11) and (b) cPILOT (N = 6) across three biological replicates. SASA calculated values
using the Homo sapiens tubulin beta chain cryo-EM
structure (PDB: 5N5N(31)) are displayed on top of each bar.
(c) Oxidatively modified peptides identified by label-free MS only
(red), cPILOT only (blue), and both methods only (yellow) mapped on
the cryo-EM structure of the human tubulin beta chain. CID-MS/MS spectra
of the tubulin beta chain peptide 325–336 showing b- and y-ions
for (d) light and (e) heavy dimethylation plus a +16 FPOP modification
for residue M330 and isobaric-tag. HCD-MS3 spectra generated
from the 10 most intense fragment ions (SPS-10) of the (f) light and
(g) heavy CID-MS/MS ion.
Protein oxidation
for tubulin beta chain. Calculated ln(PF) for
tubulin beta chain oxidatively modified peptides identified by (a)
label-free MS (N = 11) and (b) cPILOT (N = 6) across three biological replicates. SASA calculated values
using the Homo sapiens tubulin beta chain cryo-EM
structure (PDB: 5N5N(31)) are displayed on top of each bar.
(c) Oxidatively modified peptides identified by label-free MS only
(red), cPILOT only (blue), and both methods only (yellow) mapped on
the cryo-EM structure of the human tubulin beta chain. CID-MS/MS spectra
of the tubulin beta chain peptide 325–336 showing b- and y-ions
for (d) light and (e) heavy dimethylation plus a +16 FPOP modification
for residue M330 and isobaric-tag. HCD-MS3 spectra generated
from the 10 most intense fragment ions (SPS-10) of the (f) light and
(g) heavy CID-MS/MS ion.Oxidation coverage was
higher for tubulin beta chain from label-free
MS (33%) in comparison to cPILOT (19%); however, peptides quantified
in cPILOT were more reproducible in their detection across biological
replicates. Oxidatively modified peptides identified by label-free
MS (red), cPILOT (blue), or both methods (yellow) are mapped on the
human tubulin beta chain cryo-EM structure (PDB: 5N5N(31)) (Figure c). Both approaches identified ∼30% of the protein sequence,
with contributions from each method.An example, MS/MS spectrum
of peptide 325EVDEQMLSVQNK336, shows a +16 modification at M330 for both light (Figure d) and heavy (Figure e) labeled peptides.
Reporter ion intensities were present for light (Figure f) and heavy (Figure g) labeled peptides in all
IV-FPOP conditions (sample, control oxidation, control) and biological
replicates. Similarly, for the actin protein, multiple oxidatively
modified peptides were identified in both label-free MS and cPILOT
(Supplemental Figure S3). Notably, 12 oxidatively
modified peptides were identified using label-free MS (Supplemental Figure 3a), while three peptides
were identified with cPILOT (Supplemental Figure
S3b). MS/MS spectra of peptide 41HQGVMVGMGQK51 displayed differences in fragmentation patterns between
HCD-MS/MS (label-free MS) (Supplemental Figure
S3c) and CID-MS/MS (cPILOT) (Supplemental
Figure S3d). HCD-MS/MS yielded a more disperse range of fragments
and the identification of oxidatively modified residues M41, V46,
and M48, whereas CID-MS/MS resulted in less fragments and the sole
identification of M48. The identification of oxidative modifications
by CID has been shown to be limited in peptides containing Met and
His.[32,33] Additionally, this suggests HCD-MS/MS and
HCD-MS3 could improve identifications of cPILOT for IV-FPOP
oxidatively modified proteins.Peptides identified by FPOP-cPILOT
were fragmented by CID, resulting
in the identification of residues with oxidative modifications. Conversely,
the label-free MS analysis used HCD fragmentation, which herein resulted
in a wider range of oxidative modifications. For the cPILOT acquisition,
it was more suitable to not use HCD fragmentation for peptide identification,
as the time required to obtain HCD data for both peptide identification
(MS/MS) and quantification (MS3) would greatly increase
the duty cycle. This would have resulted in a reduction of the number
of peptides identified. In addition, the use of HCD-MS/MS may have
reduced the accuracy of reporter ion intensities obtained.[34,35] Using CID fragmentation is beneficial in this application of IV-FPOP,
as an additional fragmentation cycle is being employed to obtain quantitative
information.Owing to the fragmentation differences between
label-free MS and
cPILOT data generated herein, known OH amino acid modifications[25] for all oxidatively modified peptides (N = 1005, 703 proteins) were compared. These modifications
are found on most amino acids in which MS/MS spectra provide the location
of these modifications. Peptides identified from label-free MS (Figure a, top) and cPILOT
(Figure b, top) were
mostly oxidatively modified by the addition of an oxygen atom, leading
to a +16 modification. This modification occurred at M330 in the peptide 325EVDEQMLSVQNK336. This
is promising, as the major modification (+16) was identified in both
quantification strategies. Many other OH modifications were present
in the label-free MS data, in comparison to that from cPILOT, with
the exception of +32 modifications, which were higher in cPILOT data.
Less abundant OH modifications to His (+5 and −10 Da mass shifts)
residues were observed with cPILOT. We note that the use of different
MS/MS fragmentation methods for label-free and cPILOT could contribute
to the overall differences in fragmentation patterns and intensities
of fragment peaks as shown (Figure .)
Figure 4
Oxidative mass shift modifications and body systems identified
by IV-FPOP. (a) Oxidative mass shift modifications observed by HCD-MS/MS
fragmentation (top) and body systems (bottom) identified by IV-FPOP
label-free MS. (b) Oxidative mass shift modifications observed by
CID-MS/MS fragmentation (top) and body systems (bottom) identified
IV-FPOP-cPILOT.
Oxidative mass shift modifications and body systems identified
by IV-FPOP. (a) Oxidative mass shift modifications observed by HCD-MS/MS
fragmentation (top) and body systems (bottom) identified by IV-FPOP
label-free MS. (b) Oxidative mass shift modifications observed by
CID-MS/MS fragmentation (top) and body systems (bottom) identified
IV-FPOP-cPILOT.Next, oxidatively modified proteins
were matched to their primary
gene and localized to relevant systems using the online Gene Search
tool by The Genome BC C. elegans Gene Expression
Consortium.[36] The percentage of proteins
identified in both label-free MS (Figure a, bottom) and cPILOT (Figure b, bottom) were very similar across nervous,
muscle, epithelial, and reproductive body systems. This demonstrates
that cPILOT probes oxidation in similar body systems as label-free;
however, it extends the number of proteins observed in each of these
bodily systems, providing more insight into the biological implications
of readily accessible oxidatively modified proteins. Additionally,
the epithelial system is the most outer-part system of C.
elegans and has 13% of oxidatively modified proteins, which
is intuitive given it is the first contact for the laser to target
proteins. However, the FPOP strategy is able to probe deeper into
the organism and study oxidation as demonstrated from reproductive,
nervous, and muscle systems also being observed.Some factors
that should be considered when using enhanced multiplexing
include the additional steps added to the sample workflow, data acquisition,
and processing. Multiplexing strategies require a chemical labeling
step. For cPILOT, two chemical labeling steps are necessary for dimethylation
and TMT. Next, offline fractionation is performed to ensure proteome
depth. Critical to the detection of multiple samples and quantitatively
for cPILOT is the inclusion of HCD-MS3 to achieve accurate
reporter ion information.[34] The MS3 increases the instrument duty cycle; however, the overall
gradient times are similar to the label-free approach. Generally,
the time spent for label-free for this study from sample preparation
to MS acquisition is 20 h, and for cPILOT it is 22 h. The additional
time for cPILOT is not attributed to the multiplexing but more so
to the incorporation of fractionation, which arguably could have improved
the coverage in the label-free approach also but would have been over
12 days longer than that from cPILOT for 18 samples.The MS
time between both approaches was kept at 120 min. Once raw
data is acquired, files are searched to obtain peptide and protein
identifications/quantifications. Searching label-free versus cPILOT
quantified data entails including all possible FPOP oxidative modifications,
along with the specified quantification strategy. The time required
to search 18 files as opposed to two files (one file per dimethylation
modification) will also increase the overall time necessary to complete
label-free experiments. In terms of quantification, ideally, resulting
data would contain quantitative information from all channels; however,
reporter ion intensities may be missing. To decrease the number of
channels with missing reporter ion intensities, SPS has been employed.
The collection of multiple fragment ions increases the intensities
of reporter ions, thus increasing the probability of having quantitative
information in all channels. As seen in the recent work of King and
Robinson, using SPS-MS3, in addition to the targeted mass
difference strategy, increased both the percentage of light and heavy
dimethylation pair detections and peptide quantifications.[37] Previous analyses[21] have shown that using Lys-C results in longer peptides, thus reducing
ionization and detection. Hence, trypsin was employed, resulting in
∼80% of K-terminated peptides (Supplemental
Table S2) available for TMT labeling and subsequent detection.
In short, more peptides were detected and quantified.Overall,
the complexity of this data set must be considered. Quantification
information is obtained when 1. both light and heavy dimethylation
pairs are detected and 2. reporter ion intensities are above the searching
threshold. The experimental design may result in missing channels
as peptides not oxidatively modified by FPOP or control oxidation
would not be present. This may contribute to missing channels within
the data set.
Conclusions
Here, we demonstrated
the power of sample multiplexing for quantification
of IV-FPOP modifications by using cPILOT.[20,21] Peptide oxidation levels were quantified across three biological
replicates, thus increasing sample reproducibility among technical
and biological replicates. Moreover, within a single experiment control,
sample and background conditions that typically are performed in independent
label-free MS analyses were probed simultaneously with cPILOT. Enhanced
multiplexing has been demonstrated as a valuable technique to reduce
sample preparation time while increasing sample throughput for IV-FPOP.
Despite trade-offs with throughput and protein depth, the quantification,
multiplexing, and reproducibility of cPILOT informed of robust changes
to protein oxidation for C. elegans.
Authors: R Srikanth; Jonathan Wilson; Juma D Bridgewater; Jason R Numbers; Jihyeon Lim; Mark R Olbris; Ali Kettani; Richard W Vachet Journal: J Am Soc Mass Spectrom Date: 2007-05-23 Impact factor: 3.109
Authors: Rebecca Hunt-Newbury; Ryan Viveiros; Robert Johnsen; Allan Mah; Dina Anastas; Lily Fang; Erin Halfnight; David Lee; John Lin; Adam Lorch; Sheldon McKay; H Mark Okada; Jie Pan; Ana K Schulz; Domena Tu; Kim Wong; Z Zhao; Andrey Alexeyenko; Thomas Burglin; Eric Sonnhammer; Ralf Schnabel; Steven J Jones; Marco A Marra; David L Baillie; Donald G Moerman Journal: PLoS Biol Date: 2007-09 Impact factor: 8.029