Evaluation of HCD- and CID-type Fragmentation Within Their Respective Detection Platforms For Murine Phosphoproteomics

Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA.
Molecular & Cellular Proteomics (Impact Factor: 6.56). 09/2011; 10(12):M111.009910. DOI: 10.1074/mcp.M111.009910
Source: PubMed
Protein phosphorylation modulates a myriad of biological functions, and its regulation is vital for proper cellular activity. Mass spectrometry is the enabling tool for phosphopeptide analysis, where recent instrumentation advances in both speed and sensitivity in linear ion trap and orbitrap technologies may yield more comprehensive phosphoproteomic analyses in less time. Protein phosphorylation analysis by MS relies on structural information derived through controlled peptide fragmentation. Compared with traditional, ion-trap-based collision-induced dissociation (CID), a more recent type of fragmentation termed HCD (higher energy collisional dissociation) provides beam type CID tandem MS with detection of fragment ions at high resolution in the orbitrap mass analyzer. Here we compared HCD to traditional CID for large-scale phosphorylation analyses of murine brain under three separate experimental conditions. These included a same-precursor analysis where CID and HCD scans were performed back-to-back, separate analyses of a phosphotyrosine peptide immunoprecipitation experiment, and separate whole phosphoproteome analyses. HCD generally provided higher search engine scores with more peptides identified, thus out-performing CID for back-to-back experiments for most metrics tested. However, for phosphotyrosine IPs and in a full phosphoproteome study of mouse brain, the greater acquisition speed of CID-only analyses provided larger data sets. We reconciled our results with those in direct contradiction from Nagaraj N, D'Souza RCJ et al. (J. Proteome Res. 9:6786, 2010). We conclude, for large-scale phosphoproteomics, CID fragmentation with rapid detection in the ion trap still produced substantially richer data sets, but the back-to-back experiments demonstrated the promise of HCD and orbitrap detection for the future.


Available from: Edward L Huttlin, Nov 18, 2015
Evaluation of HCD- and CID-type
Fragmentation Within Their Respective
Detection Platforms For Murine
Mark P. Jedrychowski‡¶, Edward L. Huttlin‡¶, Wilhelm Haas‡, Mathew E. Sowa‡,
Ramin Rad‡, and Steven P. Gygi‡§
Protein phosphorylation modulates a myriad of biological
functions, and its regulation is vital for proper cellular
activity. Mass spectrometry is the enabling tool for phos-
phopeptide analysis, where recent instrumentation ad-
vances in both speed and sensitivity in linear ion trap and
orbitrap technologies may yield more comprehensive
phosphoproteomic analyses in less time. Protein phos-
phorylation analysis by MS relies on structural information
derived through controlled peptide fragmentation. Com-
pared with traditional, ion-trap-based collision-induced
dissociation (CID), a more recent type of fragmentation
termed HCD (higher energy collisional dissociation) pro-
vides beam type CID tandem MS with detection of frag-
ment ions at high resolution in the orbitrap mass analyzer.
Here we compared HCD to traditional CID for large-scale
phosphorylation analyses of murine brain under three
separate experimental conditions. These included a
same-precursor analysis where CID and HCD scans were
performed back-to-back, separate analyses of a phos-
photyrosine peptide immunoprecipitation experiment,
and separate whole phosphoproteome analyses. HCD
generally provided higher search engine scores with more
peptides identified, thus out-performing CID for back-to-
back experiments for most metrics tested. However, for
phosphotyrosine IPs and in a full phosphoproteome study
of mouse brain, the greater acquisition speed of CID-only
analyses provided larger data sets. We reconciled our
results with those in direct contradiction from Nagaraj N,
D’Souza RCJ et al. (J. Proteome Res. 9:6786, 2010). We
conclude, for large-scale phosphoproteomics, CID frag-
mentation with rapid detection in the ion trap still pro-
duced substantially richer data sets, but the back-to-back
experiments demonstrated the promise of HCD and or-
bitrap detection for the future. Molecular & Cellular Pro-
teomics 10: 10.1074/mcp.M111.009910, 1–9, 2011.
The brain harbors specialized functions such as neural trans-
mission and memory that are contingent upon synchronized
phosphorylation events (1, 2), and the identification and char-
acterization of protein phosphorylation events is most com-
monly accomplished using mass spectrometry (3, 4). Studies
cataloging brain phosphorylation events further expand our un-
derstanding of specialized signaling events, and previous
mouse brain phosphorylation investigations, with extensive
fractionation, have sometimes yielded data sets containing
thousands of sites (5–8). The large-scale identification of phos-
phorylation sites is not only biologically important, but presents
an analytical challenge that has traditionally stretched the ca-
pabilities of mass spectrometry-based proteomics technology.
Attaining maximum depth of phosphoproteomic analysis re-
quires continual refinement and optimization of analytical meth-
ods as new technologies are introduced.
Hybrid mass spectrometers are becoming increasingly
common, including quadrupole-time-of-flight instruments,
quadrupoles coupled with ion traps, and ion traps coupled
with ion cyclotron resonance cells (9–14). The hybrid linear ion
trap-orbitrap combination also enjoys widespread use. For
most bottom-up proteomic experiments, intact peptides are
initially detected in the orbitrap with high resolution and high
mass accuracy. However, MS/MS spectra are typically iso-
lated and detected in the linear ion trap by collision-induced
dissociation (CID)
because of its speed and sensitivity. For
phosphopeptide analysis, this combination is especially ubiq-
uitous (6, 15–19). Recently, new fragmentation techniques
have emerged that may complement or replace traditional
CID and include electron capture dissociation (20), electron
transfer dissociation (14), and higher energy collisional disso-
ciation (HCD) (10, 21, 22).
HCD fragmentation is available for the LTQ Orbitrap (21)
where ions are fragmented in a collision cell rather than an ion
trap and then transferred back through the C-trap for analysis
From the ‡Department of Cell Biology, Harvard Medical School,
Boston, MA 02115
Received March 24, 2011, and in revised form, August 23, 2011
Published, MCP Papers in Press, September 13, 2011, DOI
The abbreviations used are: CID, collision-induced dissociation;
HCD, higher energy collisional dissociation; SCX, strong cation ex-
change; IMAC, immobilized metal affinity chromatography; FA, formic
acid; ACN, acetonitrile; FDR false discovery rate.
Technological Innovation and Resources
© 2011 by The American Society for Biochemistry and Molecular Biology, Inc.
This paper is available on line at
Molecular & Cellular Proteomics 10.? 10.1074/mcp.M111.009910–1
Page 1
at high resolution in the orbitrap. Compared with traditional
ion trap-based collision-induced dissociation, HCD fragmen-
tation with orbitrap detection has no low-mass cutoff, high
resolution ion detection, and increased ion fragments result-
ing in higher quality MS/MS spectra. HCD also employs
higher energy dissociations than those used in ion trap CID,
enabling a wider range of fragmentation pathways. One draw-
back, however, is that spectral acquisition times are up to
twofold longer because more ions are required for Fourier
transform detection in the orbitrap compared with detection
of CID spectra in the ion trap via electron multipliers. The LTQ
Orbitrap Velos platform offers improvements to the source
region, leading to increases in ion current by 10-fold (
When coupled with a more efficient HCD collision cell this has
greatly improved the performance of HCD fragmentation,
making rapid and routine analysis possible (
Recent comparative studies of complex proteomic mixtures
aimed at determining the value of HCD with orbitrap detection
compared with CID with ion trap detection have found mixed
conclusions (
23–25). Given that it is still unclear which ap
proach is best suited for proteomics, we set out to design
several large-scale comparisons using phosphoproteomics,
which is an ideal model system both for its biological impor-
tance and because it is analytically challenging. Moreover,
phosphopeptides typically provide relatively less informative
MS/MS spectra, and localizing individual phosphorylation
sites emphasizes the quality of the spectra collected.
In order to evaluate the performance of HCD and CID
fragmentation within their respective analysis strategies, we
designed three experiments including a back-to-back analy-
sis of same-precursors, which removed the speed advantage
of CID, and two real world phosphoproteome analyses (a
brain antiphosphotyrosine peptide affinity pull-down and
large-scale brain phosphoproteome comparison). We found
that despite higher primary scores via HCD, collecting CID-
based MS/MS spectra in the ion trap was still superior, allow-
ing the detection of nearly twice as many phosphopeptides. In
light of these findings, we then compared our results with
those recently claiming that HCD (orbitrap detection) outper-
formed CID (ion trap detection) in phosphoproteomics to help
explain our divergent conclusions (
Tissue Preparation—Murine brain tissues were prepared as de-
scribed (
6). Each 10-mg aliquot of lysate was incubated overnight
with 150
g of sequencing grade trypsin (Promega, Madison, WI).
Trypsin digestion was terminated by adding trifluoroacetic acid to a
final concentration of 0.2%. The digest was desalted over a 500 mg
solid-phase extraction (SPE) cartridge (Sep-Pak; Waters, Milford,
MA) and lyophilized.
Phosphopeptide Enrichment—Phosphopeptides were enriched
from tryptic digests by strong cation exchange (SCX) chromatogra-
phy and immobilized metal affinity chromatography (IMAC) as previ-
ously described (
26). Ten SCX fractions were collected, desalted and
further enriched by IMAC. Enriched phosphopeptides were desalted
using C
StageTips (27) and re-suspended in 10
l of 5% formic acid
(FA)/5% acetonitrile (ACN), of which 4
l were analyzed by liquid
chromatography-tandem MS (LC-MS/MS) using each fragmentation
technique separately.
Phosphopeptide enrichment using TiO
was performed as de
scribed by Thingholm and coworkers (
28) using Titansphere TiO
beads (GL Sciences, Japan). Phosphopeptides were desalted using
StageTips. TiO
-enriched samples were resuspended with 12
of 5% FA/5% ACN, and 4
l were used for each LC-MS/MS analysis
for back-to-back comparison of CID and HCD fragmentation as
shown in Fig. 1 and supplemental Fig. S3.
Antibody Enrichment of Phosphotyrosine-containing Peptides—
The procedure for phosphotyrosine enrichment was adapted from the
description by Rush and coworkers (
29). Tryptic peptides (10 mg)
were dissolved in 2 ml of immunoprecipitation buffer: 50 m
NaOH, pH 7.2, 10 m
M Na
, and 50 mM NaCl. The solution was
sonicated at room temperature for 30 min and centrifuged at 4 °C for
10 min at 15,000 g to remove any insoluble debris. To the super-
natant, 50
g of pY100 anti-phosphotyrosine antibody (Cell Signaling
Technology, Danvers, MA) coupled to 50
l of protein-A Sepharose
(Amersham Biosciences/GE Healthcare, Piscataway, NJ) was added,
and the mixture was incubated overnight at 4 °C. Immune complexes
were washed three times with cold immunoprecipitation buffer and
once with water. Peptides were eluted with two volumes of 40
0.15% trifluoroacetic acid for 10 min at room temperature. They were
desalted using C
StageTips and re-suspended in 10
l of 5% FA/5%
ACN. A volume of 4
l was analyzed for each LC-MS/MS analysis by
HCD- and CID-type fragmentation.
Liquid Chromatography Electrospray Ionization Tandem Mass
Spectrometry (LC-ESI-MS/MS)—We performed LC-ESI-MS/MS on a
hybrid dual-pressure linear ion trap/orbitrap mass spectrometer (LTQ
Orbitrap Velos, Thermo Scientific, San Jose, CA) equipped with a
Famos autosampler (LC Packings, Sunnyvale, CA) and an Agilent
1200 binary HPLC pump (Agilent Technologies, Palo Alto, CA). Pep-
tide mixtures were fractionated on a 100
m I.D. microcapillary col-
umn packed first with 0.5 cm of Magic C
resin (5
m, 100 Å,
Michrom Bioresources, Auburn, CA) followed by 20 cm of Maccel
AQ resin (3
m, 200 Å, Nest Group, Southborough, MA). Separa
tion was achieved through applying a gradient from 8% ACN to 30%
ACN in 0.125% FA over an 85- or 145-min gradient at a flow rate of
300 nL/min.
The LTQ Orbitrap Velos MS was used in the data-dependent mode.
Methods using exclusively CID-fragmentation when acquiring MS/MS
spectra consisted of an orbitrap full MS scan followed by up to 20
LTQ MS/MS experiments (TOP20) on the most abundant ions de-
tected in the full MS scan. Essential MS settings were as follows: full
MS (AGC 3 10
; resolution 6 10
; m/z range 300–1500; maximum
ion time 1000 ms); MS/MS (AGC 2 10
; maximum ion time 150 ms;
minimum signal threshold 500; isolation width 2 Da; dynamic exclu-
sion time setting 30 s (10 ppm relative to the precursor ion m/z);
singly charged ions and ions for which no charge state could be
determined were excluded from selection. Normalized collision en-
ergy was set to 35%, and activation time to 20 ms.
For methods where exclusively HCD MS/MS spectra were ac-
quired an orbitrap full MS scan was followed by up to 10 HCD-
orbitrap MS/MS spectra on the most abundant ions detected in the
full MS scan. The resolution for full MS scans was set to 3 10
. The
AGC for MS/MS experiments was set to 3 10
at a maximum ion
accumulation time of 250 ms. Normalized collision energy was set to
45%, and HCD fragmentation ions were detected in the orbitrap at a
resolution setting of 7.5 10
. All other settings were as described for
the method using exclusively CID fragmentation.
For back-to-back comparisons of CID and HCD spectra (Fig. 1 and
supplemental Table S4) the five most abundant ions detected in an
orbitrap full MS spectrum were selected for MS/MS (TOP5). Each
Evaluation of HCD- and CID-type Fragmentation
10.1074/mcp.M111.009910–2 Molecular & Cellular Proteomics 10.?
Page 2
peptide ion was first selected for CID-fragmentation and then for an
HCD-experiment before the next ion was subjected to CID-MS/MS.
CID fragment ions were either detected in the LTQ ion trap or the
orbitrap. MS settings were as described above.
Experiments on an LTQ Orbitrap XL (85 min gradients, sup-
plemental Table S1) were performed using exclusively CID fragmenta-
tion in the ion trap when acquiring MS/MS spectra. Settings were
described as above except for MS/MS AGC, which was set to 5 10
and the maximum MS/MS ion accumulation time, set to 120 ms.
Data Analysis—After spectral data acquisition, RAW files were
converted into mzXML format and prepared for database searching
as previously described (
6). MS/MS spectra were searched using the
Sequest (version 28 revision 13) or MASCOT (version 2.3) algorithms
30, 31). Spectra were searched against a database containing se
quences of all proteins in the mouse IPI database (version 3.60,
56,738 protein entries, downloaded July 2009) and common contam-
inant sequences (e.g. human keratins and trypsin) in both forward and
reversed orientations. The following parameters were used to identify
phosphopeptides applying either search algorithm: 10 ppm precursor
mass tolerance, 0.8 Da product ion mass tolerance, fully tryptic
digestion, up to two missed cleavages, variable modifications: oxida-
tion of methionines (15.9949) and phosphorylation of serines, thre-
onines, and tyrosines (79.9663); fixed modifications: carbamidom-
ethylation of cysteine (57.0214). For all HCD spectra and the high
resolution CID spectra in supplemental Table S3, fragment ion toler-
ances were set to 0.02 Da.
The target-decoy approach was applied to control peptide and
protein level false discovery rates (FDRs) (
32). Linear discriminant
analysis (LDA) was employed to distinguish correct from incorrect
peptide identifications using the following variables: XCorr (0.8 score
minimum), Cn, precursor mass error, charge state, and solution
charge state for SCX/IMAC. The variable Cn gives the relative
difference in XCorr values for the highest scoring peptide match
found by Sequest for an MS/MS spectrum and for the next highest
scoring match with a distinct amino acid sequence without taking
post-translational modifications into account. LDA was also used to
control the FDR of data sets from Mascot searches by substituting
Mascot’s Ion Score and Delta-Ion Score for XCorr and Cn, respec-
tively. Phosphopeptides shorter than six amino acids in length were
removed and peptide spectral matches were filtered to a 1% FDR at
the peptide-level based on the number of decoy sequences in the
remaining data set. After all phosphopeptides were grouped with their
corresponding proteins, proteins were scored based on their multi-
plied peptide LDA probabilities. The sorted list was filtered based on
reversed protein hits to maximally contain 1% false positive protein
identifications. Any protein redundancy is clearly noted in each sup-
plementary peptide table.
We used the Ascore algorithm to quantify the confidence with
which each phosphorylation modification could be assigned to a
particular residue in each peptide (
33). Phosphopeptides with Ascore
values above 13 (p 0.05) were considered confidently localized to
a particular residue. To calculate the number of unique sites for each
experiment, all localized sites were counted once. Nonlocalized sites
were only counted if they could not be assigned to any localized site
32). Multiple nonlocalized sites occupying overlapping sequence
ranges were assessed as a single phosphorylation event. Therefore,
the calculated unique sites render a strict minimal estimate for all
identified phosphorylation sites.
Analysis of HCD and CID Raw Files From Mann and Coworkers
(25)—Xcalibur .RAW files acquired were downloaded from Proteome- (
34) at the hash below.
We examined all critical spectral acquisition parameters that are
embedded in the instrument method within each .RAW file. All
.RAW files were then searched by the same parameters as de-
scribed in the data analysis section of our methods. In addition,
we re-examined phosphorylation site lists that were provided
as supplemental Materials accompanying the manuscript:
pr100637q_si_002.txt, pr100637q_si_003.txt, and pr100637q_
Data Dissemination—All data are made available including all RAW
data files
Fig. 1: /sFUqXTLzCQn2oo3KKJbkut24ogzPG5uRn2hHa
Fig. 2: RqQSjWSKodoE55Ftml8pxhwujwu/V1PZMfzgHReZvC
Fig. 3: 1V7/zDAFlz1dDcmkfgiwTj8EWvmK5ycfXvbbNpRZYrtjhm5
RzA ⫽⫽
Supplemental Fig. S3: N0kSl0hRjSOIsx8tG7Hp5sLijVkQ/f3
Supplemental Table S1: POPJa9xrVWQy671CyxSseYuq
In addition, all MS/MS spectra are also made available via hyperlink
in supplementary Tables S1 to S12. An annotated list of their content
is located in the Supplementary Outline of Tables.
HCD-type fragmentation, as employed on the LTQ Orbitrap
Velos, is a powerful technique for generating higher resolution
MS/MS spectra. However, the acquisition speed of HCD
MS/MS Orbitrap spectra is about half of what is found for
traditional lower resolution CID ion trap spectra. In addition,
HCD with ORBITRAP detection has lower sensitivity than
electron multiplier-based CID techniques. Despite these lim-
itations, one very useful feature of HCD is that the low mass
region is well represented in the MS/MS spectra when com-
pared with CID, allowing HCD to be combined with isobaric
tagging reagents (e.g. TMT, iTRAQ) which produce small m/z
reporter ions (
10, 35, 36). Moreover, HCD fragmentation sup
ports multiple cleavage events which may result in richer
fragmentation of phosphopeptides where the neutral loss of
phosphoric acid is unproductive and common (
37). Given the
progress toward making HCD a mainstream analysis tech-
nique and recent conflicting reports of comparisons between
HCD and CID (
10, 3840), we designed three experiments to
rigorously evaluate each technique’s performance with large-
scale phosphoproteomic data.
Comparing Same-Precursor-Ion Spectra—To compare
HCD (orbitrap detection) and CID (ion trap detection) frag-
mentation techniques for spectral differences, we designed a
back-to-back method that would equalize experimental vari-
ability because of the stochastic nature of data-dependent
LC-MS/MS analyses and account for differential rates of HCD
and CID acquisition by ensuring that identical precursors were
sequentially examined under matched experimental condi-
Evaluation of HCD- and CID-type Fragmentation
Molecular & Cellular Proteomics 10.? 10.1074/mcp.M111.009910–3
Page 3
tions. This experimental design allowed us to compare the
relative utility of HCD and CID spectra for proteomic identifi-
cations independent of their inherent disparity in acquisition
speed. Fig. 1A shows a schematic representation of the
method employed on a sample of phosphopeptides enriched
from murine brain cell lysates via titanium dioxide stationary
phase enrichment. An LC-MS/MS analysis (155-min) acquir-
ing both HCD and CID spectra sequentially on the same
precursor ions resulted in the collection of 16,640 MS/MS
spectra. All spectra were searched using Sequest (
30) and
filtered to a 1% protein FDR. More spectra (19%) and more
sites (18%) were matched by HCD than CID techniques
(Fig. 1C), and similar results were found when searched by
MASCOT (supplemental Table S2).
Using all peptides simultaneously identified, we plotted val-
ues for XCorr, Cn, and Ascore for phosphopeptides
matched by both HCD (orbitrap detection) and CID (ion trap
detection) fragmentation for 2,3, and 4 charged pep-
tides. Although XCorr is the primary score for Sequest, the
Cn value for a peptide is defined as the difference between
XCorr values for the top Sequest match and the next highest
XCorr value for a peptide with a different amino acid sequence
33). For matched spectra from doubly charged precursors,
CID overwhelmingly returned higher XCorr values, yet HCD
identified more 2 peptides overall (Fig. 1B, supp-
lemental Fig. S5). However, for 3 and 4 peptides, XCorr
values favored the HCD platform while Cn values always
favored the HCD strategy and returned higher XCorr values
(Fig. 1B, supplemental Fig. S5). Given that we saw different
XCorr trends by charge state, we profiled all phosphopeptides
identified in Fig. 1 by a multivariate analysis with respect to 49
different chemical properties in order to elucidate the etiology
of these differences (supplemental Fig. S6). Notably, there
were little or no observable differences between peptides
FIG.1. Phosphopeptide analysis by a back-to-back, alternating CID- and HCD-type fragmentation for same-precursor ions. A,
Workflow for the data-dependent scans using the hybrid LTQ Orbitrap Velos mass spectrometer. The five most abundant ions from each full
MS cycle were subjected to sequential CID (ion-trap detection) and HCD (orbitrap detection) fragmentation. A titanium dioxide-enriched sample
from 1 mg proteolyzed mouse brain was analyzed by LC-MS/MS techniques using this method. B, Scatter plot distributions of XCorr, Cn,
and Ascore values for phosphopeptides identified by both HCD (y axis) and CID (x axis) for 2,3, and 4 charged ions, showing generally
higher trends for HCD. C, Table summarizing peptide and protein identifications from this experiment. Matches to reversed (decoy) sequences
are shown in parentheses.
Evaluation of HCD- and CID-type Fragmentation
10.1074/mcp.M111.009910–4 Molecular & Cellular Proteomics 10.?
Page 4
identified by either fragmentation approach with respect to
the parameters used. This suggests that peptides identified
uniquely by one technique likely reflect stochastic differences
and do not indicate preferences for either fragmentation strat-
egy with respect to a peptide’s physical or chemical proper-
ties. Thus either platform enables comparable coverage of the
We also examined an identical mouse brain sample collect-
ing both the CID and HCD spectra in the orbitrap at high
resolution (supplemental Table S4). Each fragmentation
method identified similar numbers of phosphopeptides and
unique sites, suggesting that the improved mass accuracy of
MS/MS ions is at least partially responsible for any differences
seen in Fig. 1.
Although search algorithms such as Sequest and MASCOT
are able to identify peptide sequences with high confidence,
they often struggle to distinguish among isomeric forms of
peptides that differ only in the localization of post-transla-
tional modifications. In most cases these algorithms provide
no direct measures of confidence for localization of individual
sites of post-translational modification. The Ascore algorithm
gives a probabilistic score that reflects the relative confidence
with which each site can be assigned to a specific position on
its substrate peptide (
33). Ascore values were higher for HCD-
based spectra compared with MS/MS obtained by CID (me-
dian 39.6 versus 28.9, respectively). Example spectra are
shown in supplemental Fig. S1, and all MS/MS spectra are
available via hyperlinks in supplemental Tables S5–S8. Over-
all, this same-precursor-ion experiment allowed us to assess
differences in data quality in the absence of acquisition
speed. It is important to note that these results are based on
enforcing the same CID and HCD spectral collection rates
because of the back-to-back nature of the experiment.
Evaluating Phosphotyrosine Affinity-Enriched Samples—We
next examined the differences between HCD (orbitrap detec-
tion) and CID (ion trap detection) considering phosphoty-
rosine- (pY) containing peptides which are typically underrep-
resented in most phosphoproteomic data sets, usually
comprising only 1–2% of the total sites detected (
6). We and
others have previously used antibody immunopurifications
(IPs) to selectively enrich for pY-containing peptides (
16, 29,
41, 42), and we therefore implemented this approach to ad-
dress how well each strategy performed on these pY-en-
riched samples (Fig. 2A). A pY IP from 10 mg of proteolyzed
mouse brain lysate was split equally and subsequently ana-
lyzed using separate CID and HCD methods. In total, we
identified 845 sites (0.46% peptide FDR) by combining these
two strategies. CID analysis, however, detected 40% more
pY-containing peptides and 34% more sites than HCD (Fig.
2C). Moreover, the site overlap revealed that only 11% of all
pY sites were unique to HCD (Fig. 2B). We conclude that
larger data sets are produced from pY peptide samples by
low resolution, faster acquisition speed a CID-based strategy
than by high a resolution, slower acquisition speed HCD-
based strategy.
Evaluating the Mouse Brain Phosphoproteome—We next
performed a full phosphoproteome analysis of mouse brain
using separate CID (ion trap detection) and HCD (orbitrap
detection) analyses to address whether higher search engine
scores from HCD spectra can overcome the speed advan-
tages of traditional CID. In total, ten IMAC-enriched SCX
fractions were split in half and analyzed by HCD and CID (Fig.
3A). Within their respective strategies, CID analyses collected
2.3-fold more MS/MS spectra, matched 1.8-fold more pep-
tides, and identified 1.5-fold more sites than HCD (Fig. 3C).
Although HCD fragmentation performed better in later frac-
tions, where larger peptides and higher charge states domi-
nated, it still did not render more peptide identifications than
CID for any fraction (Fig. 3B). Moreover, the HCD results are
more representative of the numbers we accumulated from a
matched brain SCX/IMAC experiment analyzed by CID using
the previous generation LTQ Orbitrap XL mass spectrometer
FIG.2.CID- and HCD- type fragmentation for phosphotyrosine antibody-enriched peptides. A, Workflow for phosphotyrosine analysis.
B, Venn diagram of phosphotyrosine containing peptides and their overlap between CID and HCD. C, Table summarizing this experiment.
Matches to reversed (decoy) sequences are in parentheses.
Evaluation of HCD- and CID-type Fragmentation
Molecular & Cellular Proteomics 10.? 10.1074/mcp.M111.009910–5
Page 5
(supplemental Table S1) and a previously published study
using the mice from the same litter as this one (
Further examination of site and phosphoprotein overlap be-
tween CID and HCD (Figs. 3D,3E) revealed the vast majority of
sites (87%) and phosphoproteins (95%) identified were not
exclusive to HCD fragmentation. Altogether, when the two data
sets were combined, we detected 83,005 phosphopeptides
yielding 20,506 unique sites on 5101 proteins, representing the
largest brain phosphorylation data set to date. In addition, we
attempted to create a decision tree that would choose the
optimal fragmentation technique based on charge state and m/z
value as described in the literature (
40, 43). We found, irrespec
tive of the charge state and m/z value, CID would be preferred
over HCD when success probabilities were adjusted for acqui-
sition speed (supplemental Fig. S7). We conclude that tradi-
tional CID (ion trap detection) allowed much deeper coverage of
the phosphoproteome than high mass accuracy HCD spectra,
demonstrating a clear advantage to CID.
Interestingly, our findings directly contradict the results re-
cently reported by Mann and coworkers (
25) who performed a
similar large-scale phosphoproteomic analysis from HeLa
cells (also using 10 fractions) to evaluate HCD- and CID-type
fragmentation. In contrast to our data, their study reported
that HCD with orbitrap detection identified more phosphory-
lation sites than traditional CID (16,559 versus 11,893). We
initially questioned whether this large difference could be
attributed to the search algorithm used (Sequest and
MASCOT, respectively). However, when comparing MASCOT
and Sequest for our back-to-back experiment (Fig. 1), we
found only small differences in algorithm performance (supp-
lemental Table S2). Therefore, to determine the key differ-
ences between our respective studies (especially in light of
the highly similar methods used for the collection of both data
sets), we downloaded the .RAW files provided by the authors
on Tranche (
32). Importantly, these files contain not only the
raw MS data from the experiments, but also include the actual
methods and instrument settings used for data acquisition.
Among these parameters was a significant difference be-
tween the reported and actual settings for the exclusion
width mass tolerance for the CID analyses. As shown in
FIG.3. Full phosphoproteome analysis of mouse brain by CID- and HCD-type fragmentation. A, Workflow for phosphoproteomic
analysis. Brain phosphopeptides were enriched with the SCX-IMAC approach (
26), and ten fractions were analyzed by separate 85-min CID
and HCD runs. B, Phosphopeptides identified in SCX fractions. C, Summary of these studies. Matches to reversed (decoy) sequences are in
parentheses. D, E, Venn diagrams of site and phosphoprotein overlaps between CID and HCD experiments.
Evaluation of HCD- and CID-type Fragmentation
10.1074/mcp.M111.009910–6 Molecular & Cellular Proteomics 10.?
Page 6
supplemental Fig. S3, the exclusion mass width window after
selecting a peak for MS/MS was set to 10 ppm for all HCD
files but to 5 and 10 m/z for all CID files (10 ppm was
reported for both in the manuscript). Thus, a CID-specific, 15
m/z (instead of 20 ppm) window was blocked from re-analysis
for every MS/MS that was acquired for up to 1 min (a 750-fold
difference in window size at m/z 1000). Since hundreds of
MS/MS spectra can be collected per minute, this difference
likely resulted in the majority of ions present in the spectrum
being unavailable for selection by the software. Hints of this
problem were apparent in the data as the authors noted that
their cycle times were extremely inefficient, stating that “… in
particular, the instrument only performed 10 or more CID
scans in 1% of the cases and in most cases only fragmented
none or one precursor ion” (Page 6792). This led to a dramatic
decrease in the number of MS/MS events triggered for CID
fragmentation and is likely the main reason why HCD outper-
formed CID in their hands. Fig. 4 contains the number of
MS/MS spectra acquired per cycle in our experiments. The
vast majority (90%) of cycles with MS/MS scans contained
the full limit of MS/MS scans.
For completeness, we searched the MS/MS spectra from
the .RAW files provided by Mann and coworkers (
25) (includ
ing MASCOT searches as well as the Ascore algorithm to
localize sites). Here we again encountered an apparent dis-
crepancy from the published results. Their report claimed
16,559 sites detected in a data set containing 10 HCD anal-
yses. However, our re-analysis assigned only 8910 sites
(55% of their value) in those same runs (suppleme-
ntal Tables S3, S9). We then attempted to reconcile our re-
sults with their supplementary tables. Unfortunately, there
was not enough information shared to fully evaluate the dif-
ference in site counting. For example, two pieces of informa-
tion were missing: (1) the total number of phosphopeptides
identified by HCD analysis, and (2) a list of the sequences of
these identified phosphopeptides. One of their supplementary
tables contains 16,559 entries to represent the sites deter-
mined in one replicate of their analysis. However, many en-
tries cite the same singly phosphorylated peptide from the
same scan and the same file and then assign several sites to
it (supplemental Figs. S4A, 4B). Based on these data, we can
confirm that over-counting occurred, but we have no way to
determine its actual extent without the complete list of phos-
phopeptides identified. To address this issue, we have pro-
vided all data for this reanalysis in supplemental Table S9 in
the hope that this can be resolved at a later date.
In conclusion, we evaluated CID (ion trap detection) versus
HCD (orbitrap detection) for phosphopeptide analysis in a full
phosphoproteome setting. Using a same-precursor analysis
(Fig. 1), HCD demonstrated superior Cn and Ascore values
and identified more phosphopeptides. However, CID was
greatly favored for pY IP samples and for the comprehensive
analysis of the mouse brain phosphoproteome. At this point,
the speed benefits of CID (ion trap detection) outweigh the
higher search engine scores from high resolution HCD for in
depth phosphoproteomics, despite a previous report in the
literature (
25). Nevertheless, HCD’s true experimental benefit
may lie in the realm of multiplexed mass spectrometry anal-
yses using isobaric tags such as TMT or iTRAQ where its
ability to measure low m/z products is clearly superior to
CID-based methods. Finally, newer and faster orbitrap-based
HCD analyses have been reported which may negate the
speed advantage for CID with ion trap detection (
Acknowledgments—We would like to thank Deepak Kolippakkam
for help with the bioinformatics aspects of this manuscript. We also
thank John Rush of Cell Signaling Technology for pY antibody
method help.
* This work was supported in part by a grant from the National
Institutes of Health to SPG (HG3456).
S This article contains supplemental Tables S1 to S12
and Figs. S1 to S7.
§ To whom correspondence should be addressed: Department of
Cell Biology, Harvard Medical School, Boston, Massachusetts 02115.
These authors contributed equally to the work.
FIG.4.Cycle depth (A) and validation rate (B) for the CID and
HCD methods. The data from Fig. 3 were analyzed for cycle depth by
computing the number of MS/MS spectra triggered from each full MS
scan across all ten SCX runs. A TOP10 and TOP20 method were used
for HCD and CID analyses, respectively. When MS/MS were trig-
gered, the vast majority of cycles contained either 10 or 20 MS/MS
events, correspondingly. HCD spectra had higher validation rates at
all MS/MS positions within a cycle. Fraction valid denotes the fraction
containing phosphopeptides at the 1% FDR.
Evaluation of HCD- and CID-type Fragmentation
Molecular & Cellular Proteomics 10.? 10.1074/mcp.M111.009910–7
Page 7
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  • Source
    • "The data generated from these two instruments were not compared because of only one measurement per instrument. Instead, the data were combined since the CID and HCD fragmentations are based on different mechanisms [31] and used to generate complementary data for comparison of fractionation and enrichment approaches. Utilizing SDS-PAGE, the proteins were separated evenly in the lane based on the molecular weight. "
    [Show abstract] [Hide abstract] ABSTRACT: Phosphorylation of proteins is important for controlling cellular signaling and cell cycle regulatory events. The process is reversible and phosphoproteins normally constitute a minor part of the global proteome in a cell. Thus, sample preparation techniques tailored for phosphoproteome studies are continuously invented and evaluated. This paper aims at evaluating the performances of the most popular techniques for phospho-enrichments in sub-proteome analysis, such as viral proteomes expressed in human cells during infection. A two-species sample of Adenovirus type 2 infected human cells was used, and in-solution digestion, strong cation exchange (SCX), and electrostatic repulsion hydrophilic interaction chromatography (ERLIC) fractionation, and subsequent enrichment by TiO2, were compared with SDS-PAGE fractionation and in-gel digestion. Evaluation was focused on phosphopeptide detection in the sub-proteome. The results showed that the SCX+TiO2 or ERLIC+TiO2 combinations had the highest enrichment efficiencies, but SDS-PAGE fractionation and in-gel digestion resulted in the highest number of identified proteins and phosphopeptides. Furthermore, the study demonstrates the usefulness of applying as many orthogonal techniques as possible in deep phosphoproteome analysis, since the overlap between approaches was low. Graphical Abstract The phosphoproteome originating from Adenovirus type 2 infected cells was investigated with different phosphopeptide-selective techniques
    Full-text · Article · Jan 2016 · Analytical and Bioanalytical Chemistry
  • Source
    • "Techniques such as neutral loss scanning, precursor ion scanning, and multi-stage activation (MSA) have been successfully applied to the routine identification of protein phosphorylation from complex biological samples678. New fragmentation methods including HCD, ECD, and ETD have also been utilized for protein phosphorylation analysis, which has allowed better fragmentation of the phosphorylated peptides, improved assignment of phosphorylation sites, and increased the sensitivity of MS-based protein phosphorylation analysis91011. One of the breakthroughs in the field of proteomics has been the development of a vast array of quantitative methods. "
    [Show abstract] [Hide abstract] ABSTRACT: Isobaric tagging reagents have become an invaluable tool for multiplexed quantitative proteomic analysis. These reagents can label multiple, distinct peptide samples from virtually any source material (e.g., tissue, cell line, purified proteins), allowing users the opportunity to assess changes in peptide abundances across many different time points or experimental conditions. Here, we describe the application of isobaric peptide labeling, specifically 8plex isobaric tags for relative and absolute quantitation (8plex iTRAQ), for quantitative phosphoproteomic analysis of cultured cells or tissue suspensions. For this particular protocol, labeled samples are pooled, fractionated by strong cation exchange chromatography, enriched for phosphopeptides, and analyzed by tandem mass spectrometry (LC-MS/MS) for both peptide identification and quantitation.
    Full-text · Chapter · Jan 2016
  • Source
    • "The vast majority of peptide identifications are accomplished with fragmentation followed by protein database searches of the resulting fragments. Electron capture dissociation (ECD) [23], electron transfer dissociation (ETD) [24,25], higher energy collisional dissociation (HCD) [26,27], collision-induced dissociation (CID) [9,28,29], and a host of other fragmentation methods are available303132, each with recommended applications [33]. Furthermore, mass spectrometry methods are often customized within software. "
    [Show abstract] [Hide abstract] ABSTRACT: Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.
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