Phosphoproteomics—finally fulfilling the promise?

Lindsay D. Rogers and Leonard J. Foster*

Received 20th March 2009, Accepted 28th May 2009

First published as an Advance Article on the web 7th July 2009

DOI: 10.1039/b905580k

Networks of protein–protein and protein–metabolite interactions are commonly found in

biological systems where signals must be passed from one location or component within a cell

to another, such as from a receptor on the plasma membrane to a transcription factor in the

nucleus. Regulation of such networks, or signal transduction pathways, is often achieved by

transient, reversible modification of the components involved. Several types of post-translational

modifications of proteins are employed in signal transduction including ubiquitylation of lysines

and palmitoylation of cysteines, but by far the best appreciated and apparently the most

important involves phosphorylation of serine, threonine and tyrosine residues. Whilst protein

phosphorylation has long been recognized as functionally important, low stoichiometry has

ultimately impeded global analyses (phosphoproteomics). Recent developments in the application

of metal oxide chromatography and advanced mass spectrometric techniques have enabled

phosphoproteomics to move beyond mere proof-of-principle experiments, to the stage where it

can successfully address complex biological questions. Here we cover the development of

phosphopeptide/protein analysis by mass spectrometry and the various techniques used to enrich

phosphopeptides/proteins. We also speculate on the future of phosphoproteomic research, now

that the goal of generating global phosphoproteomic datasets has been realized.

History and current potential

Signal transduction pathways have classically been studied

with a certain degree of myopia; studies have focused on one

or a few components out of necessity since no tools were

available to allow more global approaches. As more and more

targeted tools (e.g., phospho-specific antibodies, specific point

mutations) were developed it became clear that there is a great

deal of cross-talk and redundancy in signalling pathways, but

still the complexity of these systems was generally not fully

appreciated. Initially Edman1 degradation was the method

of choice for identifying phosphorylation sites in proteins.

However, although the process can be automated,2 as a method

it suffers from low sensitivity (i.e., 10 to 100 pmol starting

material required) and low throughput (i.e., hours to days for

one peptide). With the advent of soft ionization methods, protein

and peptide mass spectrometry slowly became the method of

choice for identifying phosphorylation sites, but for many years

one still needed several picomoles of a purified protein to have a

reasonable chance of identifying phosphorylation sites that are

usually sub-stoichiometric. Thus, while one could identify one or

a few sites, phosphorylation analysis on a proteome-scale

(i.e., phosphoproteomics) was not possible. Two-dimensional

gel electrophoresis, initially using autoradiography to detect32P-labelled proteins and then using colorimetric or fluorimetric

imaging and phosphate-specific dyes, allowed the visualization

of phosphoproteomes, but determining the specific sites of

phosphorylation remained an insensitive and slow process. The

Department of Biochemistry & Molecular Biology, Centre forHigh-Throughput Biology, University of British Columbia, Vancouver,BC, Canada. E-mail: ljfoster@interchange.ubc.ca

Lindsay D. Rogers

Lindsay D. Rogers is a doctoralcandidate in Biochemistry andMolecular Biology at theUniversity of British Columbia.A graduate of QueensUniversity, she is studyinghow Salmonella bacteriasubvert host cell processes.

Leonard J. Foster

Leonard J. Foster is an Assis-tant Professor of Biochemistryand Molecular Biology atthe University of BritishColumbia in Vancouver,Canada. He is a foundingmember of the Centre forHigh-Throughput Biologyand is interested in themolecular events underlyinghost-pathogen interactions.

1122 | Mol. BioSyst., 2009, 5, 1122–1129 This journal is �c The Royal Society of Chemistry 2009

REVIEW www.rsc.org/molecularbiosystems | Molecular BioSystems

effective coupling of nano or capillary-flow high performance

liquid chromatography (HPLC) to tandem mass spectrometry

(MSn) by electrospray ionization (ESI) has made possible

the analysis of highly complex and dynamic proteomes.

The structural information provided by information rich

MSn experiments3 also provides a suitable platform for

characterization of phosphoproteins. However, five apparent

problems were facing this approach: lability of the phosphate

modification, the anionic nature of the phosphate, ion

suppression, lack of retention of phosphopeptides on reversed

phase stationary phases and phosphorylation stoichiometry.

We use the term ‘apparent problems’ because evidence now

suggests that the lability of the phosphate moiety and its

anionic nature, as well as its retention on reversed phase, are

not particularly problematic. It is also evident that poor

phosphopeptide detection is likely more a problem of

low stoichiometry between the phosphorylated and non-

phosphorylated form of proteins (inducing ion suppression

during liquid chromatography–tandem mass spectrometry

(LC-MS/MS)), as opposed to a reduced ionization efficiency

of phosphopeptides per se. While stoichiometry presents what

is likely the most significant challenge, we aim to address this

as well as the lability of the phosphate modification in

subsequent sections.

With regard to the difficulties of working with a modification

that has a reasonable chance of holding a negative charge even

under very acidic conditions (e.g., pH 2.0), this too has proven

to be less of an impediment than previously thought. Certainly

it makes some chemical sense that conventional LC-MS/MS of

tryptic peptides at low pH and in positive ion mode was

incompatible with phosphorylation analysis; the positive

charges on the peptide due to amine protonation would be

at least partially cancelled out by the negative charge on the

phosphate. It was expected that this would tend to leave only

singly-charged peptides, which are not optimal for MS/MS. It

may be that preparing phosphopeptide samples in strong acids

such as trifluoroacetic acid achieves sufficient acidification of

phosphorylated peptides, as the authors have observed no

increase in the number of phosphopeptides identified, nor the

distribution of the number of phosphorylation sites per

peptide by including singly-charged ions for MS/MS

(unpublished data).

With regard to phosphorylated peptides not being retained

on C18 reversed phase, the favoured stationary phase for

LC-MS/MS analysis of peptides, evidence clearly indicates

that the methods used for resolving unphosphorylated

peptides are perfectly amenable to phosphopeptides as well.

Indeed, if anything phosphopeptides are likely slightly better

retained by C18 than their unphosphorylated counterparts,4

although two other studies found essentially no difference

in retention times.5,6 However, running reversed phase

LC-MS/MS under lower pH conditions (pH 1.7, 3% formic

acid) has been observed to improve the detection of poly-

phosphorylated peptides.7 The total ion chromatogram shown

in Fig. 1 compares the elution times of all peptides identified

from a complex sample (tryptic digest of mammalian cytosolic

fraction) enriched for phosphopeptides. Consistent with

previous reports, the elution patterns of phosphopeptides

and non-phosphopeptides are very similar.

With regard to poor phosphopeptide detection, for many

years it was believed that phosphopeptides are not effectively

detected because of their poor ionization efficiency. There is

still some controversy surrounding this point, with one study

suggesting that phosphopeptides ionize more or less as

efficiently as their unphosphorylated counterparts.6 A more

recent study found that by treating phosphopeptide-enriched

samples with alkaline phosphatase, the intensities of the

dephosphorylated forms of peptides were, on average, two-fold

higher than the intensities of the phosphorylated species.5 The

former study has been criticized for analysing primarily

non-tryptic peptides when virtually everyone in the field uses

trypsin to digest proteins. On the other hand, the latter study

did not take into account the likely sub-stoichiometric levels of

phosphorylation in their samples. This would have overlooked

the additive effect of having some unphosphorylated peptide

signal contributing to the signal from the newly-dephosphorylated

peptides. In any case, in the context of a complex mixture

where phosphopeptides are present only at their natural

stoichiometry, they would appear to ionize less efficiently but

the problem in such a case is the stoichiometry and thus

the dynamic range of the instrumentation rather than the

ionizability.

Lysis methods and low stoichiometry of

phosphorylated proteins

An ongoing challenge in phosphoproteomics is the low

phosphorylation signal typically observed in biological

samples. Due to the reversible nature of protein phosphorylation,

phosphatases liberated upon cell lysis can quickly and

substantially reduce the signal. In addition, large amounts of

starting material (typically milligrams) and extremely sensitive

instrumentation are required, especially as protein phos-

phorylation emerges as an important, yet rare, modification

in prokaryotes.8–10

While a similar number of kinases and phosphates are

thought to regulate tyrosine phosphorylation, many more

serine/threonine kinases exist than cognate phosphatases in

Fig. 1 Comparing elution times of phosphorylated and non-

phosphorylated peptides from a C18 reversed phase column. The

total ion chromatogram is shown, with the elution time versus

mass-to-charge ratio of all peptides detected in the sample

overlaid over top (phosphopeptides in red, non-phosphopeptides

in blue).

This journal is �c The Royal Society of Chemistry 2009 Mol. BioSyst., 2009, 5, 1122–1129 | 1123

the human genome.11 Also, kinase-substrate specificity is

typically determined by the amino acid sequence surrounding

the phosphorylated residue, while phosphatases are thought to

rely on targeting subunits to achieve specificity.12 This has

made phosphatases difficult to study and our understanding of

them lags considerably that of kinases. By far the most

common means of inhibiting phosphatases in phosphoproteomic

studies is through the use of commercially available inhibitors.

While vanadium oxides such as pervanadate and orthovanadate

are used to inhibit all protein tyrosine phosphatases (PTPs),

about 20 families of serine/threonine phosphatases have been

classified, the most common of which are protein phosphatase

1 (PP1), PP2A and PP2B. Phosphatase inhibitors such as

calyculin A are commonly used to inhibit PP1 and PP2A,

while inhibitors such as deltamethrin have been shown to

inhibit PP2B. However, in a recent study Pan et al. treated

live Hepa1-6 liver cells with pervanadate, calyculin A, and

deltamethrin and compared the abundance of individual

phosphorylated peptides to an untreated condition.9 Surprisingly,

only 27% of peptides were found to increase more than

two-fold following this treatment, suggesting that either the

phosphatases targeting many of the sites are not affected by

the inhibitors, the dephosphorylation of those sites have

absurdly slow kinetics, or almost three quarters of phos-

phorylations are near stoichiometric in growing cells (which

is not the case). Interestingly, Pan et al. also found that the

majority of pY sites were up-regulated more than two-fold

(70%), presumably due to the broad inhibition of PTPs by

pervanadate and perhaps also the low level of tyrosine phos-

phorylation in untreated cells. Only 41% of phosphothreonine

and 26% of phosphoserine sites were up-regulated two-fold

during treatment with these widely used inhibitors, which are

believed to block most phosphatase activity. Similarly, in an

analysis of the stem cell plasma membrane phosphoproteome,

Thingholm et al. found that pre-treating cells with calyculin A,

sodium pervanadate, or two phosphatase inhibitor cocktails

resulted in only a 10–40% increase in the number of

phosphoproteins identified.13 Again, inhibition with calyculin

A resulted in an 88.5% increase in the number of phospho-

tyrosine containing proteins identified. Thus, while current

inhibitor-based methods of inactivating phosphatases are

somewhat effective, especially when considering tyrosine

phosphorylation, for truly global phosphoproteomic analyses

alternative methods of phosphatase inactivation, such as heat

or chaotropic denaturation should be considered.

Phosphorylation of serine, threonine and tyrosine residues

has long since been documented in eukaryotes from yeast to

humans,14,15 but only recently with the emergence of

large-scale phosphoproteomics studies has it also emerged as

an important and widespread regulatory mechanism in

prokaryotes. Reporting the first large-scale site-specific phospho-

proteomics study in bacteria, Macek et al. identified 103

unique phosphopeptides from 78 Bacillus subtilis proteins,

also observing that the distribution of phosphoserine, -threonine

and -tyrosine residues (B70 : 20 : 10) closely resembles that of

multicellular organisms.16 They also observed phosphoproteins in

all parts of the bacterial cell and among a wide variety of

metabolic and regulatory enzymes, especially those involved in

carbohydrate metabolism. The extent of serine, threonine and

tyrosine phosphorylation in B. subtilis was found to be at least

an order of magnitude less than that of mammalian cells,

phosphoproteins were found to be overrepresented in essential

genes, and the bacterial phosphorylation sites identified do not

match common target sequences for eukaryotic kinases

which suggests that many of them have evolved independently

in bacteria. In a follow-up study, similar results were

obtained in Escherichia coli, again finding no similarity to

eukaryotic kinase motifs and also limited similarity between

phosphorylation sites in B. subtilis and E. coli (20%).17

Interestingly, about twice the number of phosphorylated

proteins in B. subtilis and E. coli are conserved among other

phylogenetically distant organisms as compared to non-

phosphorylated proteins, and nine (B10%) were found to

be conserved from archaea to humans. Additional studies on

Campylobacter jejuni and Lactococcus lactus yielded similar

results, solidifying the emergence of bacterial phosphorylation

on serine, threonine, and tyrosine residues as a significant

regulatory mechanism in both prokaryotic and eukaryotic

organisms.18,19

The need for pre-fractionation and enrichment

Although it is estimated that one third of all mammalian

proteins are phosphorylated at some point, only a subset are

modified by any given stimulus.20 Furthermore, due to the

tight spatial and temporal control observed in signalling

pathways, protein phosphorylation events typically occur at

very low stoichiometry. Thus, for large-scale phosphoproteomic

analyses, enrichment of phosphorylated proteins and peptides

is indispensable and several such techniques have been

developed.

When analysing their results from a large-scale phospho-

proteomic analysis of HeLa cells stimulated with

epidermal growth factor, Olsen et al. reported that almost

half of the phosphorylation events they observed occurred on

nuclear proteins, despite the fact that only one third of all

proteins in the database were assigned as nuclear by gene

ontology.8 Alternatively mitochondrial and plasma membrane

proteins were underrepresented, suggesting that subcellular

fractionation is required for effective phosphoproteome

analysis of individual organelles, as well as for generally

improving sensitivity in whole cell phosphoproteomic

analyses.8 In addition, several chromatographic methods

and, to a lesser extent, calcium and barium precipitation and

isoelectric focusing (IEF) have also been used to enrich

phosphorylated peptides.

At pH 2.7, only lysine, arginine, histidine, and the amino

terminus of a peptide are charged and the majority of peptides

carry a charge of 2+.21 A negatively charged phosphate

moiety reduces this charge state and thus, with increasing salt

concentration, phosphopeptides elute earlier than the majority

of non-phosphorylated peptides from a strong cation-

exchange (SCX) column.10,21,22 In a study of yeast pheromone-

signalling, Gruhler et al. utilized an ammonium formate

gradient from 5 to 600 mM and retained 40% of the

eluate for analysis.22 The use of strong anion-exchange

chromatography (SAX) has also been described.23,24

Dai et al. have coupled SAX online to LC-MS/MS, eluting

1124 | Mol. BioSyst., 2009, 5, 1122–1129 This journal is �c The Royal Society of Chemistry 2009

phosphopeptides using a decreasing pH gradient onto the

reversed phase column for LC-MS/MS.25 However, acidic

peptides also bind strongly to the material and it has been

reported that phosphopeptides bind with very strong affinity

and can be difficult to remove from the resin.26

During hydrophilic interaction chromatography (HILIC),

peptides are applied to a hydrophilic stationary phase in an

organic mobile phase and separation is achieved based on

polarity using an inverse gradient from high to low organic

content.27,28 Similarly, electrostatic repulsion hydrophilic

interaction chromatography (ERLIC) employs HILIC on

a weak anion-exchange column (WAX).29 During ERLIC,

peptides are run at low pH (B2) in a mobile phase containing

high organic, and eluted with increasing salt concentration.

Contrary to HILIC, which strongly retains very acidic and

basic peptides, and WAX chromatography, which elutes basic

peptides very early, ERLIC retains basic peptides due to their

hydrophilic interaction and acidic peptides based on their

electrostatic interaction to the WAX. With increasing salt

concentration phosphopeptides elute last from an ERLIC

column with monophosphorylated peptides eluting earlier

than polyphosphorylated peptides. In a study by Gan et al.

ERLIC was compared to SCX and demonstrated to yield

three times the number of phosphopeptide identifications.30

In addition to these chromatographic methods, Zhang et al.

have reported precipitation of phosphopeptides by

co-precipitation with calcium phosphate, while Ruse et al.

have demonstrated phosphopeptide precipitation in Ba2+ and

acetone.31,32 Maccarrone et al. have shown that the

acidic nature of phosphopeptides also enables their efficient

separation by IEF, which results in the vast majority of

phosphopeptides migrating within a pH range of 3 to 6.33

Methyl-esterification of carboxyl groups has been applied to

improve separation of phosphopeptides from acidic peptides

which otherwise co-migrate to acidic regions during

focusing.34,35 However, while traditional IEF provides efficient

pre-fractionation of phosphopeptides, more modern systems

that do not rely on immobilized pH gradient strips retain the

entire sample volume and thus prevent the loss of phospho-

peptides that would otherwise migrate off the strip (even at the

lowest pH ranges available). Pre-fractionation by in solution

IEF separates phosphopeptides from a full cell lysate quite

uniformly within a pH range ofB3–6 and offers an advantage

over both traditional IPG-based IEF and chromatographic

methods by minimizing sample loss (unpublished data).

The methods described above offer crude phosphopeptide

purification, and in some cases effective fractionation of

phosphopeptides themselves. However, due to their very low

abundance, additional techniques offering very high selectivity

for phosphate are often preferred or used in combination and

downstream of these methods.

For highly selective enrichment of tyrosine phosphorylated

peptides and proteins, immunoprecipitation using phospho-

tyrosine specific antibodies has proven to be a very efficient

technique.36–41 In these studies the antibody and bead

amounts are optimized for a given system to minimize non-

specific binding and to ensure complete immunoprecipitation.

However, with the exception of work done by Matsuoka et al.

to identify ATM and ATR substrates, poor specificity has

been observed for phosphoserine and phosphothreonine

antibodies.42 This, combined with the fact that only B2% of

eukaryotic phosphorylation sites have been estimated to occur

on tyrosine residues, suggests that additional purification

techniques are required for truly global analyses of phos-

phorylation signalling.8

Immobilized metal affinity chromatography (IMAC) and

metal oxide chromatography (MOC) represent two widely

used methods for the selective enrichment of phosphoserine,

-threonine and -tyrosine containing peptides. IMAC is based

on the high affinity of phosphate groups for metal ions such as

Fe3+, Zn2+, and Ga3+ 43,44 (Fig. 2a). One of the main

limitations of IMAC involves the non-specific retention of

generally acidic peptides due to the affinity of negatively

charged carboxylates for the positively charged metal ions in

the matrix (Fig. 2c). Derivatizing carboxylic acid moieties to

methyl esters has been reported to greatly reduce contamination

by acidic peptides. However sample handling and/or reaction

conditions used often facilitate the partial deamidation of

asparagine and glutamine residues and the resulting aspartate

and glutamate residues are then susceptible to methylation,

which adds a significant layer of complexity to the analysis. As

with any chemical derivatization, methyl-esterification also

decreases sensitivity due to sample loss.45–48 Alternatively,

MOC utilizes the affinity of acidified phosphoric acid for

metal oxides such as TiO2 and ZrO249 (Fig. 2a). Without

requiring chemical modification of carboxylates, MOC makes

use of dihydroxy-benzoic acid (DHB), or aliphatic hydroxyl

acids (i.e., lactic or b-hydroxypropanoic acid) to compete with

acidic but not phosphorylated peptides from the matrix

(Fig. 2b) and has been reported to yield a far higher selectivity

towards phosphorylated peptides versus carboxylates than

does IMAC.50–53 Recently, Thingholm et al. have developed

a combined approach termed ‘sequential elution from

IMAC’ (SIMAC), which first elutes monophosphorylated

and acidic peptides from an IMAC column under acidic

conditions, followed by the elution of polyphosphorylated

peptides under basic conditions.54 The monophosphorylated

peptides are separated from acidic peptides using TiO2

chromatography, the two eluates are analysed separately by

LC-MS/MS, and SIMAC has been reported to more than

double the number of phosphopeptides identified by TiO2

chromatography alone.

As mentioned, many large-scale phosphoproteomics studies

currently use a combination of one of the described crude

enrichment steps, followed by either IMAC or MOC to yield

near complete selectivity for phosphorylated peptides.8,28,30,55

We have focused primarily on phosphopeptide enrichment

techniques that do not require chemical derivatization of the

phosphate moiety itself. While several derivatization methods,

e.g., b-elimination, have been applied to phosphoproteomic

studies and are highly selective, most suffer from significant

losses during the derivatization step, which also increases

sample complexity through multiple side reactions.56,57

Therefore, we believe that chemical derivatization approaches

for enriching phosphopeptides will find limited application in

large-scale studies. However, methods such as iTRAQ

and SILAC combined with the described highly selective

This journal is �c The Royal Society of Chemistry 2009 Mol. BioSyst., 2009, 5, 1122–1129 | 1125

enrichment techniques are becoming the gold standard for

functional phosphoproteomics research.8,37,40,55

LC-MS/MS methods for phosphoproteomics

The dogma in the mass spectrometry field for several years was

that collision-induced dissociation (CID) is ineffective for

phosphopeptide analysis as neutral loss of phosphoric acid

(H3PO4, from pS and pT) would occur before backbone

cleavage, giving insufficient backbone fragmentation for

effective identification of the peptide58 (Fig. 3a). Electron

capture dissociation (ECD) and infrared multiphoton

dissociation (IRMPD) were recognized to minimize such

neutral losses but were, and still are, too slow for HPLC

timescales and were restricted to Fourier transform-ion

cyclotron resonance (FT-ICR) instruments. Methods such

as MS3 and MultiStage Activation have been employed to

impose additional activation events on pre-selected neutral

loss peaks.21,59 They differ in the sense that during MS3 the

peak selected for additional fragmentation is isolated prior to

activation and results in an entirely new set of product ions

(Fig. 3b), while during MultiStage Activation the second

isolation step is eliminated and the spectra contain product

ions from both activation events, making it a pseudo-MS3

approach (Fig. 3c). MultiStage Activation also enables higher

MSn activations in cases where multiply phosphorylated

peptides undergo sequential neutral losses. Following MS3

or MultiStage Activation, phosphoserine and -threonine sites

are recognized by the presence of fragment ions containing

dehydroalanine and dehydrobutyric acid, respectively, while

phosphotyrosine residues are rarely observed to undergo the

described neutral loss.60

However, the advantages of using neutral loss-driven MS3

and pseudo-MS3 scans in phosphoproteomics are somewhat

controversial. Recently, Villen et al. have shown that

MS3-based schemes did not result in an overall increase in

the number of phosphopeptides identified and offered only

a very minor advantage in phosphosite localization.61

They attribute this to the fact that MS3 based schemes are

approximately 20% slower, generally hold only 15% of the ion

intensity of MS2 spectra, and rarely produce more informative

ions than normalMS2 CIDwhen highmass-accuracy instruments

are used. Conversely, Ulintz et al. observed that, using an

LTQ-FT, both MultiStage Activation and MS2 outperform

MS3 methodologies, MultiStage Activation resulted in a 6%

increase in the number of unique phosphopeptides identified,

and all three methods performed equally well in localizing

phosphorylation sites.62 Overall it appears that while pseudo-MS3

scans may generate slightly richer spectra than MS2 and MS3

scans, mass spectrometers with high mass accuracy and

increased ion capacity are capable of producing much richer

MS2 scans for phosphoproteomic analyses than was originally

realized. In addition, MS3-based scans can complicate analysis

and cause ambiguity in phosphosite localization. For example,

Kruger et al. reported that the neutral loss of methanesulfonic

acid from methionine and phosphoric acid from threonine,

both yield dehydrobutyric acid. This can impose false positives

from MS3 scans where fragment ions containing dehydrobutyric

acid are used to localize phosphothreonine sites in instances of

methionine and threonine isomerism.63

Similarly, Palumbo et al. have shown that, contrary to the

b-elimination reaction that was believed to explain the

neutral loss of phosphoric acid from phosphoserine and

phosphothreonine-containing peptides, the neutral loss occurs

Fig. 2 Diagram of IMAC and TiO2 enrichment methods. (A) The co-ordination of IMAC and TiO2 resin with a phosphorylated peptide is

shown. (B) The co-ordination of TiO2 resin with DHB (middle) and lactic acid (right) is shown. (C) The co-ordination of IMAC and TiO2 with a

peptide containing an acidic residue (carboxyl group) is shown. Peptides are represented by a red wave line.

1126 | Mol. BioSyst., 2009, 5, 1122–1129 This journal is �c The Royal Society of Chemistry 2009

through a SN2 charge-directed mechanism that can result in

the sequential neutral loss of metaphosphoric acid and water

from two different residues in a peptide.64 In this case,

localizing a phosphorylation site based on the presence of

dehydroalanine or dehydrobutyric acid may mislocalize the

site. Palumbo et al. also observed that during the relatively

long activation times required for CID in ion trap mass

spectrometers, almost half of the peptides they analyzed had

transferred a phosphate group to a previously unmodified site

during activation. This was observed to increase with proton

mobility and at lower charge states, and also to be dependent

on the relatively long activation times employed for CID in an

ion trap MS. Thus to minimize such artefacts, peptides should

be activated in either a quadrupole, or using alternative

fragmentation methods such as electron capture dissociation

(ECD) or electron transfer dissociation (ETD), both of

which allow fragmentation along the peptide backbone while

maintaining the phosphate intact.65,66

Phosphopeptide/protein databases

As the last four years have seen an exponential increase in the

number of identified phosphorylation sites, several groups

have expended enormous efforts to curate and compile these

data into on-line resources. Much of the high quality data,

including some high-content data, are curated in UniProt,67

which is probably the best way to make the data available to

the wider biological community since it is used outside

the high-throughput disciplines. In addition, more specific

compendiums are available (Table 1) and each provides

specific types of tools (e.g., predictors, network/pathway

viewers) and/or information (e.g., analytical context in which

peptides were identified, quantitative profiles of phosphorylation

dynamics after agonist stimulation). The overlap in phospho-

peptide information stored in some of these databases is very

high so we expect to see many of these efforts combining forces

in a few years, as was seen with the protein interaction

network databases between 2004 and 2007. Several hurdles

face such an effort to reduce redundancy, however, as each

database has different standards for data reliability regarding

peptide identification and phosphosite localization.

Major challenges

Here we have attempted to summarize where the field of

phosphoproteomics is and how it has developed to this point.

Our view of the field is that MOC is very quickly beginning to

dominate all other approaches for enriching phosphopeptides.

The effectiveness of MOC is enhanced greatly by pre-

fractionation approaches and it is not yet clear if one of these

approaches is vastly better than the others. In the future,

confidence in site localization needs to be better addressed,

especially as phenomena such as the transfer of a phosphate

during CID and the sequential loss of metaphosphoric acid

Fig. 3 Schematic of MS2, MS3 and MultiStage Activation for phosphoproteomics. (A) During MS2 a phosphopeptide is selected for CID and

isolated (1A). The resulting fragments consist either of primarily y- and b-ions (2A) or a dominant neutral loss peak corresponding to the loss of

phosphoric acid (�98 Da) (3A). (B) DuringMS3 a phosphopeptide is selected for CID and isolated (1B). If a dominant neutral loss peak is detected

(�98 Da) (2B), the neutral loss peak is re-isolated (3B) and an additional round of CID yields fragment ions from the neutral loss peak (4B).

(C) During MultiStage Activation a peptide is selected for CID and isolated (1C). If a dominant neutral loss peak is detected (�98 Da) (2C) the

neutral loss peak is re-activated by CID (2C) yielding a product ion spectra containing fragment ions from both collision events. Red and blue bars

represent parent ions and fragment ions from the first and second fragmentation events, respectively.

This journal is �c The Royal Society of Chemistry 2009 Mol. BioSyst., 2009, 5, 1122–1129 | 1127

and water from different sites are reported. We also hope to

see these techniques move out of proof-of-principle studies

and begin to be widely applied to address real biological

questions, but this will only come by incorporating a

quantitative dimension into experiments.8 Metabolic labelling

strategies are likely to be favoured over chemical introduction

of stable isotopes or label-free approaches for quantitative

phosphoproteomics for at least two reasons: (1) chemical

derivatization invariably results in some sample loss and the

scale required for successful measurement of phosphoproteomes

is already big enough, (2) spectral counting approaches are not

appropriate in cases where proteins may be identified by only

one or two peptides, as in phosphoproteomics. Nonetheless,

these technologies exist and are mature enough now to be used

for quantitative or functional phosphoproteomics. Many

scientists who still practice the ‘one lab, one protein’ approach

to molecular biology take a dim view of ‘omics approaches’

and until more effective methods for validating a phospho-

proteomic dataset become available, such views will

persist. Reviewers will still ask proteomics researchers to

‘validate’ their findings by western blot or other equally

out-dated methods, so better tools than antibodies need to be

developed for follow-up studies to phosphoproteome analyses. A

perfect example is the ease with which one can quickly and

effectively screen thousands of different genes through the use

of siRNA in Drosophila or Caenorhabditis elegans.74 Since

whole genome RNAi screens in mammalian systems remain

very challenging, combining the discovery of regulated phos-

phorylation sites by quantitative phosphoproteomics with

highly-multiplexed multiple reaction monitoring assays for

determining stoichiometry and for tracking the levels of sites

across a wide range of conditions represents a very attractive goal

for the field to strive for in the next five years.

Acknowledgements

The authors thank the other members of the Cell Biology

Proteomics (CBP) group in the Centre for High-Throughput

Biology for fruitful discussions and advice, particularly

Robert Parker, Anders Kristensen and Nikolay Stoynov.

Phosphoproteomic research in the CBP is supported by the

Canadian Institutes of Health Research (CIHR), the Canadian

Foundation for Innovation, the British Columbia (BC)

Knowledge Development Fund and the Michael Smith

Foundation through the BC Proteomics Network (BCPN).

LJF is the Canada Research Chair in Organelle Proteomics

and a Michael Smith Foundation Scholar. LDR is supported

by a CIHR PGS-D award.

References

1 P. Edman, Acta Chem., Scand., 1950, 4, 283–293.2 H. D. Niall, Methods Enzymol., 1973, 27, 942–1010.3 R. Aebersold and M. Mann, Nature, 2003, 422, 198–207.4 Y. Ishihama, F. Y. Wei, K. Aoshima, T. Sato, J. Kuromitsu andY. Oda, J. Proteome Res., 2007, 6, 1139–1144.

5 M. Marcantonio, M. Trost, M. Courcelles, M. Desjardins andP. Thibault, Mol. Cell. Proteomics, 2008, 7, 645–660.

6 H. Steen, J. A. Jebanathirajah, J. Rush, N. Morrice andM. W. Kirschner, Mol. Cell. Proteomics, 2006, 5, 172–181.

Table 1 Publicly accessible phosphopeptide databases

Name, URL DescriptionaProteins/peptidesb Notesc Ref.

Phospho.ELM,http://phospho.elm.eu.org/

Experimentally-verifiedeukaryotic phosphorylation sites

4110/18 252 2166 pY, 13 320 pS, 2766 pTsites

68

PhosphoPOINT,http://kinase.bioinformatics.tw/

Comprehensive humaninteractome and phosphoproteindatabase

4195 Integrates phosphoproteins,kinases and their protein–protein interaction networks

69

Phosida,http://www.phosida.com/

Management, structural andevolutionary investigation, andprediction of phosphosites

6518/15 648 Contains information oftemporal regulation ofphosphosites by variousstimuli

70

PhosPhAt,http://phosphat.mpimp-golm.mpg.de/

Arabidopsis thaliana andplant-specific phosphorylationsite predictor

6282peptides

Experimental and analyticalcontext information. pSerprediction algorithm

71

P3DB, http://www.p3db.org/ Resource of proteinphosphorylation data frommultiple plants

8554/11 491 General to all plants 72

PhosphoNET,http://www.phosphonet.ca/

Human Phospho-SiteKnowledgebase

5374/26 052 Functional and regulatoryinformation included. Links toUniProt and otherphospho databases

Corporated

PhosphoPep,http://www.phosphopep.org/

Project to support systemsbiology signalling research inmodel organisms

Various Specific foci on Saccharomycescerevisiae, Drosophilamelanogaster, C. elegans,Homo sapiens. Tools forbrowsing pathways

73

PhosphoSitePlus,http://www.phosphosite.org/

Protein modification resource 9888/64 934 Links to literature andMS/MS records. Additionalmodifications included

Corporated

a The stated purpose of the given database, often taken directly from the on-line information. b The reported number of phosphoproteins and

phosphopeptides, where it is explicitly stated. c Unique features of the given database. d Databases developed by corporations, not presented in a

peer-reviewed publication.

1128 | Mol. BioSyst., 2009, 5, 1122–1129 This journal is �c The Royal Society of Chemistry 2009

7 H. Choi, H. S. Lee and Z. Y. Park,Anal. Chem., 2008, 80, 3007–3015.8 J. V. Olsen, B. Blagoev, F. Gnad, B. Macek, C. Kumar,P. Mortensen and M. Mann, Cell (Cambridge, Mass.), 2006,127, 635–648.

9 C. Pan, F. Gnad, J. V. Olsen and M. Mann, Proteomics, 2008, 8,4534–4546.

10 K. Mann, J. V. Olsen, B. Macek, F. Gnad and M. Mann,Proteomics, 2007, 7, 106–115.

11 A. Alonso, J. Sasin, N. Bottini, I. Friedberg, I. Friedberg,A. Osterman, A. Godzik, T. Hunter, J. Dixon and T. Mustelin,Cell (Cambridge, Mass.), 2004, 117, 699–711.

12 A. Remenyi, M. C. Good and W. A. Lim, Curr. Opin. Struct. Biol.,2006, 16, 676–685.

13 T. E. Thingholm, M. R. Larsen, C. R. Ingrell, M. Kassem andO. N. Jensen, J. Proteome Res., 2008, 7, 3304–3313.

14 S. Barik, Subcell. Biochem., 1996, 26, 115–164.15 C. S. Rubin and O. M. Rosen, Annu. Rev. Biochem., 1975, 44,

831–887.16 B. Macek, I. Mijakovic, J. V. Olsen, F. Gnad, C. Kumar,

P. R. Jensen and M. Mann, Mol. Cell. Proteomics, 2007, 6,697–707.

17 B. Macek, F. Gnad, B. Soufi, C. Kumar, J. V. Olsen, I. Mijakovicand M. Mann, Mol. Cell. Proteomics, 2008, 7, 299–307.

18 S. Voisin, D. C. Watson, L. Tessier, W. Ding, S. Foote, S. Bhatia,J. F. Kelly and N. M. Young, Proteomics, 2007, 7, 4338–4348.

19 B. Soufi, F. Gnad, P. R. Jensen, D. Petranovic, M. Mann,I. Mijakovic and B. Macek, Proteomics, 2008, 8, 3486–3493.

20 P. Cohen, Eur. J. Biochem., 2001, 268, 5001–5010.21 S. A. Beausoleil, M. Jedrychowski, D. Schwartz, J. E. Elias,

J. Villen, J. Li, M. A. Cohn, L. C. Cantley and S. P. Gygi,Proc. Natl. Acad. Sci. U. S. A., 2004, 101, 12130–12135.

22 A. Gruhler, J. V. Olsen, S. Mohammed, P. Mortensen,N. J. Faergeman, M. Mann and O. N. Jensen, Mol. Cell.Proteomics, 2005, 4, 310–327.

23 T. S. Nuhse, A. Stensballe, O. N. Jensen and S. C. Peck, Mol. Cell.Proteomics, 2003, 2, 1234–1243.

24 G. Han, M. Ye, H. Zhou, X. Jiang, S. Feng, R. Tian, D. Wan,H. Zou and J. Gu, Proteomics, 2008, 8, 1346–1361.

25 J. Dai, L. S. Wang, Y. B. Wu, Q. H. Sheng, J. R. Wu, C. H. Shiehand R. Zeng, J. Proteome Res., 2009, 8, 133–141.

26 T. E. Thingholm, O. N. Jensen and M. R. Larsen, Proteomics,2009, 9, 1451–1468.

27 A. J. Alpert, J. Chromatogr., 1990, 499, 177–196.28 D. E. McNulty and R. S. Annan, Mol. Cell. Proteomics, 2008, 7,

971–980.29 A. J. Alpert, Anal. Chem., 2008, 80, 62–76.30 C. S. Gan, T. Guo, H. Zhang, S. K. Lim and S. K. Sze, J. Proteome

Res., 2008, 7, 4869–4877.31 X. Zhang, J. Ye, O. N. Jensen and P. Roepstorff, Mol. Cell.

Proteomics, 2007, 6, 2032–2042.32 C. I. Ruse, D. B. McClatchy, B. Lu, D. Cociorva, A. Motoyama,

S. K. Park and J. R. Yates, 3rd, J. Proteome Res., 2008, 7,2140–2150.

33 G. Maccarrone, N. Kolb, L. Teplytska, I. Birg, R. Zollinger,F. Holsboer and C. W. Turck, Electrophoresis, 2006, 27,4585–4595.

34 C. W. Hung, D. Kubler and W. D. Lehmann, Electrophoresis,2007, 28, 2044–2052.

35 C. F. Xu, H. Wang, D. Li, X. P. Kong and T. A. Neubert, Anal.Chem., 2007, 79, 2007–2014.

36 B. Blagoev, S. E. Ong, I. Kratchmarova and M. Mann,Nat. Biotechnol., 2004, 22, 1139–1145.

37 M. Kruger, I. Kratchmarova, B. Blagoev, Y. H. Tseng, C. R. Kahnand M. Mann, Proc. Natl. Acad. Sci. U. S. A., 2008, 105,2451–2456.

38 S. Hanke and M. Mann, Mol. Cell. Proteomics, 2008, 8, 519–534.39 J. Rush, A. Moritz, K. A. Lee, A. Guo, V. L. Goss, E. J. Spek,

H. Zhang, X. M. Zha, R. D. Polakiewicz and M. J. Comb,Nat. Biotechnol., 2005, 23, 94–101.

40 Y. Zhang, A. Wolf-Yadlin, P. L. Ross, D. J. Pappin, J. Rush,D. A. Lauffenburger and F. M. White, Mol. Cell. Proteomics,2005, 4, 1240–1250.

41 M. Oyama, H. Kozuka-Hata, S. Tasaki, K. Semba, S. Hattori,S. Sugano, J. Inoue and T. Yamamoto, Mol. Cell. Proteomics,2009, 8, 226–231.

42 S. Matsuoka, B. A. Ballif, A. Smogorzewska, E. R. McDonald,3rd, K. E. Hurov, J. Luo, C. E. Bakalarski, Z. Zhao, N. Solimini,Y. Lerenthal, Y. Shiloh, S. P. Gygi and S. J. Elledge, Science, 2007,316, 1160–1166.

43 L. Andersson and J. Porath, Anal. Biochem., 1986, 154,250–254.

44 P. Scanff, M. Yvon and J. P. Pelissier, J. Chromatogr., 1991, 539,425–432.

45 J. A. Karty and J. P. Reilly, Anal. Chem., 2005, 77, 4673–4676.46 R. J. Seward, D. H. Perlman, E. A. Berg, J. Hu and C. E. Costello,

in 52nd ASMS Conference on Mass Spectrometry and Allied Topics,American Society for Mass Spectrometry, Nashville, USA, 2004,p. A042056.

47 R. J. Seward, P. D. von Haller, R. Aebersold and B. T. Huber,Mol. Immunol., 2003, 39, 983–993.

48 S. B. Ficarro, M. L. McCleland, P. T. Stukenberg, D. J. Burke,M. M. Ross, J. Shabanowitz, D. F. Hunt and F. M. White,Nat. Biotechnol., 2002, 20, 301–305.

49 M. W. Pinkse, P. M. Uitto, M. J. Hilhorst, B. Ooms andA. J. Heck, Anal. Chem., 2004, 76, 3935–3943.

50 M. R. Larsen, T. E. Thingholm, O. N. Jensen, P. Roepstorff andT. J. Jorgensen, Mol. Cell. Proteomics, 2005, 4, 873–886.

51 N. Sugiyama, T. Masuda, K. Shinoda, A. Nakamura, M. Tomitaand Y. Ishihama, Mol. Cell. Proteomics, 2007, 6, 1103–1109.

52 H. K. Kweon and K. Hakansson, Anal. Chem., 2006, 78,1743–1749.

53 Y. Kyono, N. Sugiyama, K. Imami, M. Tomita and Y. Ishihama,J. Proteome Res., 2008, 7, 4585–4593.

54 T. E. Thingholm, O. N. Jensen, P. J. Robinson and M. R. Larsen,Mol. Cell. Proteomics, 2008, 7, 661–671.

55 N. Dephoure, C. Zhou, J. Villen, S. A. Beausoleil,C. E. Bakalarski, S. J. Elledge and S. P. Gygi, Proc. Natl. Acad.Sci. U. S. A., 2008, 105, 10762–10767.

56 D. T. McLachlin and B. T. Chait, Anal. Chem., 2003, 75,6826–6836.

57 Z. A. Knight, B. Schilling, R. H. Row, D. M. Kenski,B. W. Gibson and K. M. Shokat, Nat. Biotechnol., 2003, 21,1047–1054.

58 J. P. DeGnore and J. Qin, J. Am. Soc. Mass Spectrom., 1998, 9,1175–1188.

59 M. J. Schroeder, J. Shabanowitz, J. C. Schwartz, D. F. Hunt andJ. J. Coon, Anal. Chem., 2004, 76, 3590–3598.

60 H. Steen, B. Kuster, M. Fernandez, A. Pandey and M. Mann,J. Biol. Chem., 2002, 277, 1031–1039.

61 J. Villen, S. A. Beausoleil and S. P. Gygi, Proteomics, 2008, 8,4444–4452.

62 P. J. Ulintz, A. K. Yocum, B. Bodenmiller, R. Aebersold,P. C. Andrews and A. I. Nesvizhskii, J. Proteome Res., 2009, 8,887–899.

63 R. Kruger, C.-W. Hung, M. Edelson-Averbukh andW. D. Lehmann, Rapid Commun. Mass Spectrom., 2005, 19,1709–1716.

64 A. M. Palumbo and G. E. Reid, Anal. Chem., 2008, 80, 9735–9747.65 H. Molina, D. M. Horn, N. Tang, S. Mathivanan and A. Pandey,

Proc. Natl. Acad. Sci. U. S. A., 2007, 104, 2199–2204.66 A. Stensballe, O. N. Jensen, J. V. Olsen, K. F. Haselmann and

R. A. Zubarev, Rapid Commun. Mass Spectrom., 2000, 14,1793–1800.

67 UniProt Team, Nucleic Acids Res., 2009, 37, D169–D174.68 F. Diella, C. M. Gould, C. Chica, A. Via and T. J. Gibson,

Nucleic Acids Res., 2008, 36, D240–D244.69 C. Y. Yang, C. H. Chang, Y. L. Yu, T. C. Lin, S. A. Lee,

C. C. Yen, J. M. Yang, J. M. Lai, Y. R. Hong, T. L. Tseng,K. M. Chao and C. Y. Huang, Bioinformatics, 2008, 24, i14–i20.

70 F. Gnad, S. Ren, J. Cox, J. V. Olsen, B. Macek, M. Oroshi andM. Mann, GenomeBiology, 2007, 8, R250.

71 J. L. Heazlewood, P. Durek, J. Hummel, J. Selbig, W. Weckwerth,D. Walther and W. X. Schulze, Nucleic Acids Res., 2008, 36,D1015–D1021.

72 J. Gao, G. K. Agrawal, J. J. Thelen and D. Xu, Nucleic Acids Res.,2009, 37, D960–D962.

73 B. Bodenmiller, D. Campbell, B. Gerrits, H. Lam, M. Jovanovic,P. Picotti, R. Schlapbach and R. Aebersold,Nat. Biotechnol., 2008,26, 1339–1340.

74 G. J. Hannon, Nature, 2002, 418, 244–251.

This journal is �c The Royal Society of Chemistry 2009 Mol. BioSyst., 2009, 5, 1122–1129 | 1129