1. business and industrial
2. chemicals industry
3. plastics and polymers

686
DOI 10.1002/pmic.200700617
Proteomics 2008, 8, 686–705
REVIEW
Technologies and methods for sample pretreatment in
efficient proteome and peptidome analysis
Xiaogang Jiang1, 2, Mingliang Ye1 and Hanfa Zou1
1
National Chromatographic R&A Center, Dalian Institute of Chemical Physics,
Chinese Academy of Sciences, Dalian, China
2
Suzhou University, Suzhou, China
Although great progresses have been made in proteomics during the last decade, proteomics is
still in its infancy. Extreme complexity of proteome sample and large dynamic range of protein
abundance overwhelm the capability of all currently available analytical platforms. Sample pretreatment is a good approach to reduce the complexity of proteome sample and decrease the dynamic range. In this article, we present an overview of different technologies and methods for
sample pretreatment in efficient proteome and peptidome analysis. Methods for isolation of rare
amino acid-containing peptides, terminal peptides, PTM peptides and endogenous peptides are
reviewed. In addition, two automated sample pretreatment technologies, i.e. automated sample
injection and on-line digestion, are also covered.
Received: June 28, 2007
Revised: October 26, 2007
Accepted: November 1, 2007
Keywords:
MS / Peptidome / Sample pretreatment
1
Introduction
Proteomics, the analysis of protein components in a cell or
an organism, has experienced a rapid development in the last
decade. However, proteomic analysis is still technically challenging because of extreme complexity of proteome samples.
Besides tens of thousands of proteins coded by the genome
of many cells, there are splicing variants, PTMs, and genetic
variations among individuals. And the proteins expressed in
a cell have a large dynamic range of protein abundance
which further complicates the proteome analysis. There is
no amplification method for low abundance proteins comCorrespondence: Professor Dr. Hanfa Zou, National Chromatographic R&A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P.R. China
E-mail: [email protected]
Fax: 186-411-8437-9620
Abbreviations: CNBr, cyanogen bromide; ConA, Concanavalin A;
Cys, cysteine; His, histidine; ICAT, isotope-coded affinity tag; Met,
methionine; MW, molecular weight; PST, protein sequence tag;
RAMs, restricted access materials; SAX, strong anion exchange
chromatography; SCX, strong cation-exchange chromatography; Trp, tryptophan
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
parable to the PCR technique for amplifying DNA. Therefore, sample pretreatment is a practical way to enhance the
detection sensitivity of low abundance proteins for comprehensive proteomic analysis.
At present, there are two dominant approaches for largescale proteome analysis. The first is based on protein
separation by 2-D PAGE. Protein identification is achieved by
MS analysis of excised and digested protein spots. Until now,
2-DE is still a main-stream method for protein separation,
which allows the resolution of more than 5000 proteins
simultaneously. However, some classes of proteins such as
very acidic or basic proteins, extremely big or small proteins
and membrane proteins are difficult to be separate by 2-DE
[1]. Also, 2-DE is notoriously difficult to automate, which
limits throughput and results in greater experimental variability with manual intervention. To overcome these limitations as well as to improve the throughput of protein identification, the second approach, shotgun proteome analysis
based on the chromatographic techniques, has been developed [2]. In this approach, complex protein mixture is
digested first and then the resulting digests are analyzed by
LC-MS/MS. Thousands of proteins can be easily identified in
a single experiment by shot-gun proteomics if multi-dimensional chromatography, typically strong cation-exchange
www.proteomics-journal.com
Technology
Proteomics 2008, 8, 686–705
chromatography followed by RP chromatography (SCX-RP),
is applied for separating the peptide mixture resulted from
the digests of proteins prior to MS analysis [3, 4].
Shotgun proteomics is a high-throughput proteome
analysis approach. However, proteome sample becomes
much more complex due to the digestion of proteins, as one
protein can generate dozens of peptides. The complexity of
the proteome sample is far beyond the capacity of modern
analytical systems; the large dynamic range in protein
abundance also largely exceeds the dynamic range of all
available analytical platforms. In practice, the peptides
derived from high abundance proteins seriously suppress
the detection of peptides from low abundance proteins.
Thus direct analysis of protein digests often leads to loss of
protein information especially those of low abundance proteins. To overcome the problem of complexity as well as the
dynamic range problem, sample pretreatment is a good
approach, which can be performed either at protein level or
at peptide level. At protein level, the complexity of the sample could be reduced by pre-fractionation of proteins, and
the detection sensitivity for low abundance proteins could
be improved by removing high-abundance proteins or
enriching specific groups of interested proteins [5, 6]. At
peptide level, the complexity of the sample could also be
reduced by pre-fractionation of peptides. Furthermore, a
more effective method to reduce the complexity of a peptide
mixture is to enrich representative peptides such as peptides containing rare amino acids or terminal peptides. Isolation of PTM peptides from peptide mixture is also an
effective way to circumvent the suppression of high-abundance unmodified proteins or peptides on the analysis of
protein modification.
Here we reviewed the technologies and methods for
sample pretreatment at peptide level. As a subset of proteomics, peptidomics analyzes low molecular weight (MW)
proteins (,10 kDa) or endogenous peptides from biological
source. The methods to isolate endogenous peptides for efficient peptidome analysis were also reviewed. In addition, two
automated methods of sample processing such as sample
introduction for nanoflow LC-MS/MS system, on-line digestion with micro-enzyme-reactor were also covered in this
review.
2
Selective capture of peptides containing
rare amino acids
In shotgun proteomics, proteins in the proteome sample are
first digested by protease such as trypsin, and then the
resulting peptides are analyzed by LC-MS/MS. Enzymatic
digestion of proteins generate dozens of peptides per protein, which will result in an extremely complex peptide mixture. To reduce the complexity of the samples, multi-dimensional separation of peptides is often conducted prior to MS
analysis [7]. However, the number of peptides still overwhelms the peak capacity of current multi-dimensional
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
687
separation systems. Theoretically, one unique peptide would
be sufficient to unambiguously identify each parent protein.
As one protein can generate many peptides, there are a large
number of redundant peptides presented in the digests of
proteins. If one or a couple of representative peptides could
be isolated for each protein, the complexity of the samples for
proteome profiling would be reduced by one to two orders of
magnitudes at least. Based on the theoretical digestion of
proteins in human database, tryptic peptides containing rare
amino acids such as cysteine (Cys), methionine (Met), tryptophan (Trp),and histidine (His) account for less than 31% of
all tryptic peptides, however, they represent more than 91%
of all human proteins [8]. Thus isolation of peptides containing rare amino acids is an effective way to reduce the
complexity of proteome sample while keeping the integrity
of the proteome. However, the distribution of these rare
amino acid residues in different proteins is different, thus
the method by isolating peptides containing these residues
bias to proteins with high percentage of these residues. As
we all know, a protein contains only one N-terminal and one
C-terminal peptide after digestion. Terminal peptides
account for only about 6% of all tryptic peptides while represents 100% of proteins in the proteome [8]. Therefore, isolation of terminal peptides represents the idea approach to
reduce sample complexity. Up to now, several strategies have
been successfully developed to target and isolate peptides
containing rare amino acids (Cys, Met, Trp, His, etc.) and
terminal peptides.
2.1 Cys-containing peptides
Among these rare amino acids in peptides, Cys is one of the
earliest targets for amino-acid-based peptide selection. The
isolation of Cys-containing peptides is typically achieved by
Cys-specific tags possessing iodoacetyl or vinyl functionalities which react with the thiol group of Cys [9]. Among all
Cys-specific tags, isotope-coded affinity tag (ICAT) developed
by Aebersold and co-workers [10] probably has the highest
impact as it can not only simplify the complexity of peptide
mixture but also provide quantitative information. The ICAT
reagents included a Cys-reactive idoacetyl group, a differentially isotope coded linker region, and an affinity tag (biotin).
The proteins with Cys residues were labeled by ICAT reagent
through the Cys-reactive group. After digestion of the labeled
proteins, Cys-containing peptides were then isolated from
the digest by avidin affinity chromatography. Isolation of
Cys-containing peptides using Cys-specific affinity tags typically included two steps: the protein or peptides containing
Cys were first labeled with the tag in solution and then the
labeled peptides (after digestion if the proteins are labeled)
were isolated by affinity chromatography. To circumvent the
additional chromatographic purification step, solid-phase
capture approach has been introduced [11]. The tag with a
Cys-reactive group was anchored on solid-phase beads for the
capture of Cys-containing peptides. Similar to ICAT reagent,
the tag immobilized on solid phase also included three parts.
www.proteomics-journal.com
688
X. Jiang et al.
Besides the Cys-reactive group and isotope-coded group, a
photo-cleavage group, instead of biotin group in ICAT
reagent, was included to release the captured peptides from
beads. Cys-containing peptides were first captured by the
beads and then released by UV irradiation. Thus, simplification of complex peptide mixtures could be achieved without
avidin affinity chromatography.
In addition to use of chemical tags, chromatographic
approach could also be used to isolate Cys-containing peptides from complex peptide mixture. Wang et al. [12] described a procedure in which Cys-containing peptides from
tryptic digests of complex protein mixtures were selected by
covalent chromatography based on thiol-disulfide exchange.
Following disruption of disulfide bridges with 2,20 -dipyridyl
disulfide, all proteins were digested with trypsin and acylated
with succinic anhydride. Cys-containing peptides were then
selected from the acylated digest by disulfide interchange
with sulfhydryl groups on a thiopropyl Sepharose gel. Their
results indicated that by selecting Cys-containing peptides,
the complexity of protein digest could be reduced. Another
chromatographic approach to isolate Cys-containing peptides was diagonal chromatography which was reported by
Gevaert et al. [13]. Cys in proteins were converted to hydrophobic residues by mixed disulfide formation with Ellman’s
reagent. Proteins were subsequently digested with trypsin
and the generated peptide mixture was fractionated first by
RP-LC. Cys-containing peptides were isolated from each primary fraction by a reduction step followed by a secondary
peptide separation on the same column, and the secondary
separation was performed under identical conditions as that
of the primary separation. The reducing agent removed the
covalently attached group from the Cys side chain, making
Cys-containing peptides more hydrophilic. Thereby, such
peptides could be specifically collected during the secondary
separation. They showed that this procedure efficiently isolated Cys-containing peptides, making the sample mixture
less complex for further analysis.
By isolating Cys-containing peptides a significant number of low abundance proteins could be identified and a dynamic range for protein identification spanning several
orders of magnitude could be achieved. For example, Wang et
al. [14] reported a global proteomic approach by isolation of
cysteinyl-peptide complemented with a global enzymatic
digestion method for the characterization of the whole
mouse brain proteome. A total of 48 328 different peptides
were confidently identified (.98% confidence level), covering 7792 non-redundant proteins (approximately 34% of the
predicted mouse proteome). A total of 1564 and 1859 proteins were identified exclusively from the cysteinyl-peptide
and the global peptide samples, respectively, corresponding
to 25 and 31% improvements in proteome coverage compared to analysis of only the global peptide or cysteinyl-peptide samples. Of particular interest are the ,2000 membrane
proteins (26%) and ,1000 extracellular proteins that were
identified without any specific enrichment of membrane
fractions.
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Proteomics 2008, 8, 686–705
2.2 Met-containing peptides
The Met-containing peptides account for only 25.5% of all
tryptic peptides, while they represent 98.9% of human proteins. This indicates that isolation of Met-containing peptides is more efficient to reduce the sample complexity than
isolation of Cys-containing peptides. However, very limited
applications are reported to isolate Met-containing peptides
probably because of the difficulty in isolation of these peptides. Only two approaches have been reported for the isolation and analysis of Met-containing peptides. The first one is
based on solid phase approach and the second one is also
based on diagonal chromatography. The solid phase
approach first used Met-specific beads to covalently attach
Met-containing peptides via bromoacetyl functional groups
to a solid support [15]. Target protein populations were firstly
digested under reduced and alkylated conditions, and resultant peptides selectively extracted via covalent attachment to
Met residues by bromoacetyl reactive groups tethered to the
surface of glass beads packed in small reaction vessels. After
conjugation, reactive beads were stringently washed to
remove nonspecifically bound peptides and then later treated
with beta-mercaptoethanol to release captured Met-containing peptides in their nascent state, without complicating affinity tags. This approach had been applied to an Escherichia
coli lysate model system and had demonstrated facility in reducing global digest complexity, enhancing sensitivity to low
protein expression levels, and improving significant quantitative capability. In the second approach using diagonal
chromatography, Met side chains on peptides were oxidized
between chromatographic runs, resulting in increased
polarity and therefore earlier RP-LC elution of the oxidized
peptides in the second dimension away from the bulk of
unmodified peptides [16].
2.3 Trp-containing peptides
For targeting Trp-containing peptides, a chemical tagging
method has been developed where Trp residues were labeled
with 2-nitrobenzenesulfenyl chloride [17]. The tagged peptides were enriched by a Sephadex column based on the
increase of hydrophobicity upon modification of Trp residues. However, many non-labeled peptides were also isolated
during isolation of tagged peptides by Sephadex column. To
improve the selectivity of the isolation, a phenyl resin, which
was generally used for hydrophobic interaction chromatography and RP-LC, was used to isolate labeled peptides[18].
This was because the 2-nitrobenzenesulfenyl-Trp moiety was
not only hydrophobic but was also aromatic, p-electron
interactions between phenyl groups of the column and the
Trp moiety of the labeled peptides were more specific.
Besides the approach by labeling target residue followed with
chromatographic purification, an interesting solid phase
approach was presented to isolate Trp-containing peptides
recently [19]. It was based on the reversible reaction of Trp
with malondialdehyde and trapping of the derivate Trp-pepwww.proteomics-journal.com
Proteomics 2008, 8, 686–705
tides on hydrazide beads via the free aldehyde group of the
modified peptides. After conjugation, the captured peptides
were recovered in their native form by specific cleavage
reactions using hydrazine or pyrrolidine. The applicability of
this Trp-specific enrichment procedure to complex biological
samples was demonstrated for total yeast cell lysate. Analysis
of the processed fraction by 1-D LC-MS/MS confirmed the
specificity of the enrichment procedure, as more than 85% of
the peptides recovered from the enrichment step contained
Trp. The reduction in sample complexity also resulted in the
identification of additional proteins in comparison to the
untreated lysate.
2.4 His-containing peptides
Instead of using chemical tag, IMAC loaded with Cu21 was
utilized to enrich His-containing peptides from complex
peptide mixtures [20–23]. It had been shown that most Hiscontaining peptides could be captured from tryptic digests
with little non-specific binding through the use of very
hydrophilic IMAC columns and imidazole as a displacer [24].
To reduce non-specific interactions of the IMAC resin with
peptides containing Cys, Trp and carboxyl groups, samples
were alkylated and acetylated before affinity capture of the
His-containing peptides by IMAC columns. Combinational
use of covalent chromatography and IMAC was applied to
enrich peptides containing both Cys and His [25], which further simplified the complexity of peptide mixture.
2.5 Terminal peptides
Each protein has only two terminals, i.e. N-terminal and Cterminal. Isolation of either N-terminal peptide or C-terminal peptide could significantly reduce the complexity of proteome sample. However, isolation of C-terminal peptides
from protein digests for proteome analysis was not reported
up to now, probably because of the difficulty in specific isolation of these peptides. In contrast, several methods for
selective isolation of N-terminal peptides from complex
mixture of digested peptides for proteomic analysis have
been reported.
Two chromatographic techniques were developed to isolate N-terminal peptides. The first one was based on diagonal
chromatography which also was reported by Gevaert et al.
[26]. In the procedure, free amino groups in proteins were
first blocked by acetylation and then digested with trypsin.
Except N-terminal peptides, new primary amino groups were
generated after digestion. After RP chromatographic fractionation of the generated peptide mixture, primary amino
groups of internal peptides were blocked using 2,4,6-trinitrobenzenesulfonic acid; this displayed a strong hydrophobic
shift and therefore segregated from the unaltered N-terminal
peptides during a second identical separation step. N-terminal peptides could thereby be specifically collected for LCMS/MS analysis. The second one was based on SCX [27]. As
N-terminally acetylated peptides lacked a positive charge at
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Technology
689
their N-terminal amino group, such peptides could be enriched in the non-binding fraction and in the early fractions
under eluting conditions of low concentration of salt. Oesterhelt et al. [27] utilized the above two chromatographic
methods for the large-scale identification of naturally N-terminal blocked peptides from prokaryotes. Combining all
data, 606 N-terminal peptides from Halobacterium salinarum
and 328 from Natronomonas pharaonis were reliably identified.
McDonald et al. [28] and Yamaguchi et al. [29] reported
two methods using the biotin-avidin technique for the isolation of N-terminal peptides of proteins, respectively. Though
biotin-avidin technique was used in both methods, the target
peptides of avidin chromatography were different. In the
first method, the internal peptides were trapped by an
immobilized avidin column, while in the second method Nterminal peptides were trapped. The schemes for both
approaches are shown in Fig. 1. In the first method (Fig. 1A),
all free amino groups on proteins were blocked by acetylation
in the beginning. Subsequently, proteolysis of proteins generated new peptides, and all but the N-terminal peptides
exposed a new free amino group that was subsequently biotinylated. These biotinylated internal peptides were removed
by recovery onto immobilized avidin, leaving behind the set
of N-terminal peptides. In contrast, a different strategy was
applied in the second method (Fig. 1B). Instead of blocking
all amino groups, only e- amino groups of lysine residues
were blocked by O-methylisourea. The left free a- amino
groups on N-terminal of protein then reacted with biotinylcysteic acid. After proteolysis, the N-terminal peptides
were enriched by avidin resins. The advantage of the first
method was that all N-terminal peptides (whether naturally
free or blocked) could be enriched. However, the second
method could not isolate N-terminal blocked proteins as
there was no free a-amino group on N-terminal of these
proteins. Recently, Mikami et al. [30] also developed a method
for selective isolation of N-terminal blocked peptides from
protein digests. The approach was based on a newly designed
isocyanate-resin, resin-NCO, which specifically reacted with
a-amino groups under weak acidic conditions. Because only
N-terminal blocked peptides had no a-amino groups, all
peptides except N-terminal blocked peptides would be captured when the protein digest was incubated with resinNCO. Thus the N-terminal blocked peptides could be recovered from the supernatant of the above solution. Obviously,
this method could also be used to isolate all N-terminal peptides if acetylation of protein was conducted before proteolysis.
Isolation of only N-terminal peptides from entire proteins is the most effective way to reduce the sample complexity in theory. However, identification of proteins by only
one peptide is often not confident enough because a decent
spectrum can not be obtained for every peptide. Furthermore, there are many variations of modifications for N-terminal blocked peptides which result in difficulty for identification of these peptides. The Protein Sequence Tag (PST)
www.proteomics-journal.com
690
X. Jiang et al.
Proteomics 2008, 8, 686–705
Figure 1. Strategies for isolation
of N-terminal peptides using biotin-avidin technique. (A): Free aand e-amino groups are acetylated before proteolysis, which is
followed by biotinylation of proteolytically exposed a-amino
groups. Subsequent subtractive
binding to immobilized streptavidin creates a preparation enriched
in those peptides that were originally derived from the N-terminus, blocked by acetylation and
therefore refractory to biotinylation. (B): All e-amino groups of a
protein are guanidinated with omethylisourea. And the Na-amino
group is specifically modified
with biotinylcysteic acid (BCA).
The derivatized protein is digested with trypsin, and the digests
are loaded into avidin resins for
the specific adsorption of the Nterminal peptide fragment modified with BCA. The symbols triangle, starburst, and cross represent an alkyl group, a guanidino
group, and BCA, respectively. Reprinted from [28, 29].
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
www.proteomics-journal.com
Proteomics 2008, 8, 686–705
technology reported by Kuhn et al. [31–33] might circumvent
this problem. It dealt with the isolation and MS/MS based
identification of one N-terminal peptide from each polypeptide fragment generated by cyanogen bromide (CNBr) cleavage of a mixture of proteins. The first step in the PST isolation process involved chemical cleavage of the protein mixture with CNBr. Then after the free primary amino groups
were blocked by amine-reactive Basic Mass Tag, the CNBr
cleavage polypeptides were further digested by trypsin,
which generated new amino groups in all of the non-N-terminal cleavage peptides. These non-N-terminal cleavage
peptides were removed by scavenger resin and the pool of
peptides that represented the N-terminal fragments from
each CNBr cleavage peptide was recovered. As the proteins
were identified by multiple peptides, the identification was
much more confident. The number of representing peptides
generated by this method for each protein depends on the
distribution of methionine. The PST process obtained up to
eight peptides per protein on average from Saccharomyces
cerevisiae and 99% of proteins had at least one peptide available per protein [32]. In that way, almost all the proteins
could be analyzed and the moderate degree of redundancy
increased confidence in protein identification. Taking advantage of the solubilization step using CNBr, the procedure
allowed the study of complex mixtures of hydrophobic proteins, particularly membrane proteins, which had been
demonstrated by analysis of a crude mitochondrial fraction
[33]. If isotope-coded Basic Mass Tag was used to block free
primary amino groups in proteins, this method could also be
applied for quantitative proteome analysis [31].
3
Specific isolation of PTM peptides
Besides the amino acid-specific and the general tagging
strategies presented above, methods specifically tailored to
isolate PTM peptides for the analysis of protein PTM have
received a great deal of attention over the past few years. Because of the low abundance of modified proteins and low
stoichiometry of the modifications, modified peptides present with large amount of unmodified peptide derived from
unmodified proteins and unmodified amino acid sequence
in the modified proteins. Shotgun proteomic analysis of
PTM proteins relies heavily on the efficiency of isolation and
enrichment of modified peptides. Phosphorylation and glycosylation are two most important PTMs of proteins, the
methods to isolate phosphorylated and glycosylated peptides
are reviewed in detail as follows.
3.1 Isolation of phosphopeptides
Protein phosphorylation is one of the most important regulatory events in cells, guiding primary biological processes,
such as cell division, growth, migration, differentiation, and
intercellular communication in eukaryotes. And it has
received a great deal of attention in the scientific community
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Technology
691
for decades. Shot-gun proteomics is the dominate approach
for large-scale analysis of protein phosphorylation. In this
approach, protein mixtures containing phosphoproteins are
digested first by trypsin, and then phosphopeptides are enriched from the resulting peptide mixture for LC-MS/MS
analysis. The specificity for the isolation of phosphopeptides
is crucial as the presence of small amounts of non-phosphopeptides will still seriously suppress the ionization of phosphopeptides in MS. To improve the specificity of phosphopeptide isolation, a series of technologies, as shown in Table
1, are developed to specifically isolate phosphopeptides from
complex peptide mixture.
3.1.1 Immobilized metal affinity chromatography
IMAC was first used to isolate phosphopeptides 20 years ago,
and it is still the most widely used method [34–37]. In IMAC,
metal ions such as Fe31, Ga31 were typically immobilized to
beads, phosphopeptides were selectively captured by the
beads because of high affinity of metal ions for the phosphate moiety [38]. In recent years, new materials such as
nano-materials, monolithic materials have been adopted as
the support for IMAC. For example, Fe31 immobilized
mesoporous molecular sieves MCM-41 with particle size of
ca. 600 nm and pore size of ca. 3 nm were synthesized to
selectively trap and separate phosphopeptides from tryptic
digest of proteins [39], and Fe31 immobilized silica monolithic capillary column with id of 75 mm was prepared to
enrich phosphopeptides from minute samples [40]. However, the conventional IMAC with Fe31 lacked enough specificity. Some non-phosphorylated peptides especially acidic
peptides were also strongly bound to the adsorbents, which
resulted in serious interference for the analysis of phosphopeptides. Therefore, esterification of the acidic groups of
peptides prior to IMAC purification was conducted to
improve the enrichment specificity [41]. This approach has
been successfully applied to large-scale analysis of phosphorylation in the proteome of yeast [41], rat liver [42], and HT-29
human carcinoma cell line [43]. However, because of incomplete reactions, the esterification might also increase sample
complexity and so interfere with subsequent MS analysis.
Recently, we have developed a new IMAC adsorbents by
immobilization of Zr41 on phosphonate modified polymer
beads to improve the enrichment specificity [44]. The chelating groups for the immobilization of Zr41 in the new
adsorbents and the immobilization of Fe31 in the conventional IMAC adsorbents are shown in Fig. 2. In conventional
IMAC, metal ion like Fe31 was immobilized by use of chelating groups such as iminodiacetic acid. However, in the
new IMAC, the Zr41 was immobilized by using a phosphate
group. The adsorbent surface was first activated to covalently
link a phosphate group and then Zr41 was immobilized by
incubation with ZrOCl2 solution. Compared with conventional Fe31-IMAC, Zr41-IMAC showed higher specificity for
isolation of phosphopeptides. And the high specificity of
Zr41-IMAC adsorbent mainly resulted from strong interacwww.proteomics-journal.com
692
X. Jiang et al.
Proteomics 2008, 8, 686–705
Table 1. Summary of phosphopeptide enrichment methods
Methods
IMAC
Fe31/Ga31/Al31-IMAC
Esterification prior to IMAC
Zr41-IMAC
Metal oxide
ZrO2 /TiO2 /Al(OH)3
Ion-exchange chromatography
SCX
SAX
Chemical modification
ß-elimination
Phosphoamidate
Strength and weakness
Reference
The conventional and most popular method; using iminodiacetic acid
or nitriloacetic acid as chelating group; lacking enough specificity
due to binding very acidic peptides.
Specificity is improved, however sample complexity may be increased
because of incomplete and side reactions.
A new type of IMAC using phosphate group as chelating group;
Specificity higher than conventional IMAC.
[39, 40, 114, 115]
Specificity higher than conventional IMAC; may have steric hindrance to
bind big phosphopeptides due to the absence of space arm.
[45-47]
Able to enrich and fractionate phosphopeptides; relative low specificity;
tend to loss of multiple phosphorylated peptides due to weak interaction.
Able to enrich and fractionate phosphopeptides; relative high specificity
and recovery; low resolution for fractionation.
[48, 49]
Only limited to phosphorylated serine or threonine residue; low
specificity because the interference of O-linked glycopeptides.
Applicable to all phosphopeptides; low yield because of multi-step
derivatization.
[116]
[41]
[44]
[50, 51]
[117]
3.1.2 Metal oxide particles
Metal oxide microparticles, such as titanium oxide, TiO2,
[45], zirconium dioxide, ZrO2, [46, 47] have been proved to
have much higher selectivity for trapping phosphopeptides
than conventional IMAC beads. Similar to IMAC, the mechanism of using metal oxides for phosphopeptide isolation is
also based on the strong interaction between metal ions and
phosphopeptides. As there is no spacer arm on metal oxide
beads, one disadvantage of using metal oxide beads for
phosphopeptide enrichment, compared with IMAC, is the
presence of steric hindrance. The phosphate groups of some
large size phosphopeptides may have difficulty in accessing
the surface of metal oxide particles.
Figure 2. Schematic illustration of (A) conventional Fe31-IMAC
and (B) novel Zr41-IMAC adsorbents for binding of phosphopeptides
tion between chelating Zr41 and phosphate groups on phosphopeptides. The high specificity of Zr(41)-IMAC adsorbent
was demonstrated by effectively enriching phosphopeptides
from the digest mixture of phosphoprotein (alpha- or betacasein) and BSA with molar ratio at 1:100. It was also successfully applied for the analysis of mouse liver phosphoproteome, resulting in the identification of 153 phosphopeptides (163 phosphorylation sites) from 133 proteins in
mouse liver lysate.
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
3.1.3 Ion-exchange chromatography
Compared with unmodified peptides, phosphopeptides have
extra negatively charged groups. Thus phosphopeptides
could be enriched based on their different electrostatic interaction with stationary phase in ion-exchange chromatography. Recently, ion-exchange chromatography is applied to
simultaneously enrich and fractionate phosphopeptides.
Phosphopeptides have weak interaction with SCX because of
the phosphate groups, and so they will elute in early fractions
in SCX and thereby can be separated from non-phosphopeptides which are strongly retained on SCX [48, 49]. It was
found that the first four SCX fractions were highly enriched
www.proteomics-journal.com
Technology
Proteomics 2008, 8, 686–705
with phosphopeptides. Though some phosphopeptides
could be enriched and fractionated by SCX, this approach
was not very specific as strong acidic peptides were also
eluted in early fractions. Because some phosphopeptides,
especially those with multiple phosphate groups, have net
negative charge and will not bind on SCX column, SCX
approach will result in loss of these phosphopeptides. Using
of strong anion exchange chromatography (SAX) is another
approach to enrich and fractionate phosphopeptides. Nüshe
et al. [50] used SAX chromatography based on salt gradient as
a rough pre-fractionation approach before IMAC for the
analysis of phosphopeptides from Arabidopsis, and found the
2-D separation decreased the complexity of the phosphopeptide sample and yielded a far greater coverage of phosphorylated peptides. Dai et al. [51] applied SAX column to enrich
the phosphopeptides from the flow through of SCX column
and the bound phosphopeptides were fractionated by pH
step gradient. Recently, the performance of using SAX for
enrichment and fractionation of phosphopeptides were systematically investigated [52]. It was found that nearly only
phosphopeptides were retained on the SAX column and the
majority of non-phosphopeptides were removed. The SAX
column was further applied to enrich and fractionate phosphopeptides in tryptic digest of proteins extracted from human liver tissue adjacent to tumorous regions for large scale
phosphoproteome analysis. This resulted in the identification of hundred of phosphorylation sites from phosphoproteins. Techniques such as using IMAC and metal oxide particles were only applied to enrich phosphopeptides when
only one phosphopeptide fraction was obtained. The phosphopeptide mixture enriched from proteome samples was
still very complex. In contrast, the distinct advantage of using
ion-exchange chromatography for phosphoproteome analy-
693
sis was that it could not only enrich phosphopeptides but
also fractionated phosphopeptides. Thus it is very suitable
for large-scale phosphoproteome analysis.
3.1.4 Chip-based methods
Chip-based methods for analysis of phosphopeptides is a
rather new approach [53–55], which could decrease sample
loss, simplify analytical procedures, and finally achieve highthroughput detection by MALDI-TOF MS. Xu et al. [53] prepared porous silicon wafer with immobilized Fe31 affinity
surface to analyze phosphopeptides by MALDI-TOF MS.
Complex peptide mixtures were spotted onto the Fe31
immobilized porous silicon wafer, and non-phosphopeptides
were removed from the silicon surface by thorough washing.
After addition of matrix, the porous silicon wafer was directly
placed on the MALDI target for the analysis of the captured
phosphopeptides. The phosphopeptide enrichment and
analysis procedures were all performed on the Fe31-terminated silicon wafer, which greatly reduced the sample loss
and simplified the analysis procedure. Target purification of
phosphopeptides followed by MALDI MS analysis was also
reported by Dunn et al. [55]. Above approaches were based on
the interaction between chelated Fe31 ion and the phosphate
group in phosphopeptides. Recently, Zhou et al. [54] prepared porous silicon wafer with surface immobilized with
Zr41 for phosphopeptide analysis. Figure 3 shows the
scheme for the preparation of Zr41-terminated silicon wafer
to trap phosphopeptides for MALDI-TOF MS analysis. The
excellent selectivity of this approach was demonstrated by
analyzing phosphopeptides in the digest mixture of betacasein and BSA with molar ratio of 1:100.
Figure 3. Scheme for preparation of zirconium
phosphonate modified porous silicon (ZrP-pSi)
to trap phosphopeptides for MALDI-TOF MS
analysis. Reprinted from [54]
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
www.proteomics-journal.com
694
X. Jiang et al.
Proteomics 2008, 8, 686–705
3.2 Isolation of glycopeptides
The phosphate group is quite small and may be buried inside
of proteins. The phosphopeptide enrichment methods are
typically not applicable for enrichemnt of phosphoproteins
because of steric hindrance. However, the situation for protein glycolation is completely different. The attached carbohydrate group is much bigger and is more accessible. Thus
the methods to isolate glycopeptides are often equally effective for the isolation of glycoproteins. In practice, the
sequential use of the same method to glycoproteins and glycopeptides is often applied to improve glycopeptide enrichment specificity. This is especially true for affinity chromatography.
3.2.1 Lectin affinity chromatography
Lectin affinity chromatography has been reported numerous
times as a classic and efficient method for capturing glycoproteins as well as glycopeptides [56]. As shown in Fig. 4, a
protocol based on tandem lectin affinity chromatography
purification on the protein and peptide level has been
reported to improve the specificity for glycopeptide isolation
[57, 58]. Glycoproteins were first enriched from complex
protein mixture by a lectin affinity chromatography. The
obtained glycoproteins were then proteolyzed with trypsin
and the resulting peptide mixture was subjected to affinity
chromatography with the same lectin column to enrich glycopeptides. After deglycosylation of the glycopeptides, the
resuting peptides were subjected to LC-MS/MS analysis for
the identification of glycopeptides. Concanavalin A (ConA)
lectin chromatography has been used most widely for isolation of glycoproteins/glycopeptides with high mannose-type
and hybrid-type oligosaccharides. Kaji et al. [57] applied
ConA lectin affinity chromatography for the large-scale
identification of N-glycosylated proteins from Caenorhabditis
elegans. After the tandem enrichment step, the purified glycopeptides were treated with PNGase F (a glucosidase specifically cleaving N-linked glycans) to remove N-linked glycans.
The resulting peptides were analyzed by LC-MS/MS which
resulted in the identification of 250 glycoproteins with the
simultaneous determination of 400 unique N-glycosylation
sites.
Besides ConA, several other kinds of lectins were also
utilized to enrich glycoproteins/glycopeptides having distinct types of carbohydrate structures as shown in Table 2. As
glycoproteins/glycopeptides could be isolated based on their
different glycan moieties through lectin specificity, the ability
of different lectins to recognize specific glycosylation motifs
was utilized to build a multi-lectin affinity platform for comprehensively capturing glycoproteins/glycopeptides of the
proteome sample. Yang et al [56] reported one of the first
large-scale glycoproteomic experiments utilizing multi-lectin
(ConA, WGA, jacalin) affinity chromatography, analyzing
human serum plasma and identifying approximately 150
different glycosylated proteins. In this approach, glycopro© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Figure 4. Tandem lectin affinity chromatography approach to
generate glycopeptides for glycoproteomics analysis.
teins were isolated by agarose-bound lectins immobilized
within the column and eluted following purification using a
solution containing simple sugars.
3.2.2 Chemical approaches
Even though lectin affinity capture is the most widely used
approach due to its ease of implementation, the binding
selectivity of lectins to specific conformations of different
carbohydrate moieties has limited the utility of lectin in
global glycoprotein analysis [59, 60]. Chemical capture
approaches, which allowed the capture of all types of glycoproteins or glycopeptides, were developed [61]. As shown in
Fig. 5, two type of chemical capture approaches based on
hydrazide chemistry were reported. The first one captured
glycoproteins and the second one captured glycopeptides.
The final products of these two approaches were the same:
the deglycosylated glycopeptides.
The glycoprotein capture strategy was initially developed
by Zhang et al. [62]. In this approach, covalent conjugation of
glycoproteins to a solid support via hydrazide chemistry was
used. Glycoprotein oxidation was carried out in order to
convert the cis-diol groups of carbohydrates to aldehydes. The
aldehyde groups reacted with the hydrazide groups immobilized on the resin, forming covalent hydrazone bonds. Thus
glycoproteins were immobilized on hydrazide beads through
the carbohydrate group. After immobilization, the resins
were subjected to thorough washing to remove non-glycosylated proteins. The immobilized glycoproteins were then
proteolyzed on the solid support. Non-glycosylated peptides
were again washed away while the glycosylated peptides
remained on the solid support. The formerly N-linked glycosylated peptides were finally released from the solid support
www.proteomics-journal.com
Technology
Proteomics 2008, 8, 686–705
695
Table 2. Different lectin for isolating glycoproteins/glycopeptides of distinct types of carbohydrate structures
Lectin type
Distinct types of carbohydrate structures
References
Concanavalin A (ConA)
Wheat germ agglutinin (WGA)
Anguilla anguilla agglutinin (AAA)
Sambucus nigra (SNA)
Aleuria aurantia lectin (AAL)
Helix pomatia agglutinin (HPA)
Peanut agglutinin (PNA)
High mannose-type and hybrid-type
N-acetyl-glucosamine and sialic acid type
Broad specificity for L-Fuc-containing glycans
a-2,6-linked sialic acid residues
Broad specificity for L-Fuc-containing glycans
N-acetylgalactosamine residues
Specific to T-antigen found commonly in O-glycans
[56, 57]
[118, 119]
[58, 120]
[58, 121]
[122, 123]
[58]
[122, 124]
Figure 5. Schematic illustrations of (A) glycoprotein capture strategy and (B) glycopeptide capture strategy for glycoproteomics analysis
using hydrazide chemistry.
using PNGaseF. This strategy was successfully applied to the
analysis of cell surface proteins and for serum proteome
profiling [63].
The glycopeptide capture strategy was reported recently
by Sun et al. [64], which was quite similar to the glycoprotein
capture strategy. As shown in Fig. 5, in this strategy the glycoproteins were first digested into peptides and the glycosylated peptides in the resulting digest were then immobilized
onto the solid support by hydrazide chemistry. Other steps
were essentially the same to that of the glycoprotein capture
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
approach. Digestion of proteins into peptides improved solubility of large membrane proteins and exposed all of the
glycosylation sites to ensure equal accessibility to external
capture reagents. Therefore, more glycopeptides should be
captured and the capture efficiency should be improved
greatly. The glycopeptide capture strategy was validated
using standard protein mixtures that resulted in close to
100% capture efficiency [64]. Using this approach, glycopeptide selectivity as high as 91% was achieved on the microsomal fraction of the ovarian-cancer cells.
www.proteomics-journal.com
696
X. Jiang et al.
3.2.3 Other approaches
Besides lectin affinity chromatography and hydrazide chemistry, different chromatographic separation techniques were
also used to enrich glycopeptides by the diverse physical and
chemical properties of glycopeptides [65–69]. Hydrophilic
interaction chromatography was applied to enrich glycopeptides because the carbohydrate group was very hydrophilic.
For example, Wada et al. [69] reported a simple method, utilizing hydrophilic binding of carbohydrate matrixes such as
cellulose and sepharose to oligosaccharides, to the isolation
of tryptic glycopeptides from some standard glycoproteins.
Both peptide and oligosaccharide structures were elucidated
by multiple-stage tandem MS (MSn) of the ions generated by
MALDI. Hagglund et al. [67] developed a novel approach to
identify N-glycosylation sites in complex biological samples
by enrichment of glycosylated peptides through hydrophilic
interaction chromatography followed by partial deglycosylation, which removed the major part of the glycan and thus
simplified the MS/MS spectra of glycopeptides.
Another interesting technique for enrichment of glycopeptides is the use of SEC [63]. An in-silico trypsin digest of
all the human protein sequences in the NCBI database, over
90% of the peptides displayed masses that were smaller than
2000 Da. Considering that the mass of the smallest N-linked
oligosaccharide was over 1200 Da, most N-linked glycopeptides should be significantly larger than the non-glycosylated
peptides. Therefore, Alvarez-Manilla et al. [65] have investigated using SEC for enrichment of glycopeptides. Analyses
performed on human serum showed that this SEC glycopeptide isolation procedure resulted in at least a three-fold
increase in the total number of glycopeptides identified by
LC-MS/MS, demonstrating that this method is an effective
tool to facilitate the identification of glycopeptides.
Besides, boronate affinity chromatography [70] and graphite chromatography [68] could also be applied to enrich
glycopeptides. Although these chromatographic techniques
do not involve multiple chromatographic steps and do not
require derivatization of glycoproteins/glycopeptides compared with affinity chromatography and hydrazide chemistry, these approaches often lack enough specificity for glycoproteomic analysis. The application of these approaches is
typically limited to analysis of simple samples where only
one or several glycoproteins are present.
4
Isolation of endogenous peptides for
peptidome analysis
Endogenous peptides play a central role in many biological
processes and some classes of such biologically active peptides, e.g. hormones, cytokines and growth factors, have been
known and studied for years. The term ‘peptidomics’ was
introduced in 2001 to define the quantitative and qualitative
analysis of endogenous peptides in biological samples [71,
72], primarily by chromatography or biochip platforms cou© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Proteomics 2008, 8, 686–705
pled with various forms of MS. The pacemakers for the
development of peptidomic technologies are modern MS
and bioinformatics. They are ideally suited for sensitive and
comprehensive peptide analysis, especially in combination
with the massive information content of today’s genomic
and transcriptomic databases.
However, the complexity and high dynamic range of biological samples make the characterization of endongenous
peptides a challenging task. To reduce the supression of
endongenous peptides by high abundance proteins, several
methodologies are currently used to enrich peptides from
biological samples.
4.1 Centrifugal ultrafiltration
Centrifugal ultrafiltration with accurate MW cutoff is the
most widely used method to extract peptides and remove
proteins with larger MWs based on a size-exclusion mechanism [73–77]. Zheng et al. [77] utilized the protocol of centrifugal ultrafiltration for identifying endogenous peptides
from serum, and the identification of over 300 unique peptides with 2 ppm or better mass accuracy per serum sample
was achieved. However, few peptides over 3000 Da were directly identified with the above approach. Therefore, Hu et al.
[78] developed a method for comprehensive peptidomic
analysis, which combined ultrafiltration with SEC chromatography pre-fractionation. The peptides in mouse liver were
first harvested by ultrafiltration with 10 kDa molecular
weight cut off, and then they were prefractionated by SEC.
The low MW peptides (MW,3000 Da) in the collected fractions were directly analyzed by LC-MS/MS which resulted in
the identification of 1181 unique peptides (from 371 proteins). The high MW peptides (MW.3000 Da) in the early
two fractions from SEC column were first digested with
trypsin and then the resulting digests were analyzed by LCMS/MS, which leaded to the identification of 123 and 127
progenitor proteins of the high MW peptides in the two
fractions, respectively. The low MW peptides were separated
from the high MW ones, which improved the sensitivity for
identification of the low MW peptides and allowed in-depth
investigation of the high MW peptides.
However, as a result of high protein content in biological
sample, the ultrafiltration time will increase sharply if a large
amount of biological sample is applied. Furthermore, other
low MW contaminants (for example, salts) will also be concentrated which may compromise the performance for peptidome analysis. Instead of using ultrafiltration, another
option is to use adsorbents carrying charged or hydrophobic
groups for peptide enrichment.
4.2 Functionalized adsorbents
Functionalized magnetic particle is one of the most widely
used adsorbents for peptide enrichment [79–82]. Recently,
Fiedler et al. [83] developed a standardized protocol for reproducible urine peptidome profiling by means of extracting
www.proteomics-journal.com
Technology
Proteomics 2008, 8, 686–705
peptides with magnetic beads with defined surface functionalities (hydrophobic interaction, cation exchange, and
metal ion affinity) followed by MALDI-TOF MS analysis, and
427 different mass signals in the urine of healthy donors
were detected. In addition to functionalized magnetic particle, conventional chromatographic packing materials such as
RP polymers were also used to enrich peptides [73, 84]. Because of high specific surface, nanoporous material [85, 86]
and nanomaterial [87, 88] are also good adsorbents for peptide enrichment. For example, Li et al. [89] described a peptidome analysis approach using multiwalled carbon nanotubes as an alternative adsorbent to capture endogenous
peptides from human plasma. In total, 374 unique peptides
were identified with high confidence by 2-D LC-MS/MS
analysis. And comparative studies showed that multiwalled
carbon nanotubes were superior to C18 and C8 silica particles for the capture of the smaller peptides.
Although the peptides can be enriched by these
adsorbents, some proteins may also be enriched which
suppress the detection of peptides. A special type of chromatographic packing materials called restricted access
materials (RAMs) [90, 91] could minimize the adsorption
of proteins. These porous packings have a bimodal surface
topochemistry and have two functions during chromatographic separation: (i) SEC, i.e. macromolecular sample
components like proteins having a MW larger than, e.g.
1500 Da can be directly eluted to waste in the dead volume
of such a RAM column and (ii) adsorption chromatography by RP, ion-exchange or affinity chromatography, i.e.
low MW sample components such as drugs and peptides
can be bound and extracted. RAMs, moreover, have a biocompatible outer surface tolerating frequent injections of
raw biofluids without significant loss of their mixed mode
chromatographic properties. Because of these characteristics, RAMs are especially suitable for on-line extraction of
low MW proteins and peptides respectively, as well as
depletion of abundant high MW proteins [92]. Unger et al.
[93–95] described a rather complex system for on-line
extraction and multidimensional separation of peptides in
human hemofiltrate and cell lysates applying the SPE column packed with RAMs and coupled to a conventional
separation column. Recently, a capillary SPE column
packed with RAM exhibiting SCX and size exclusion (SCX/
SEC) properties was coupled with a nano-LC-MS/MS system for peptidomic analysis of serum sample [96]. The
capillary SPE column excluded serum proteins having a
molecular mass larger than 1500 Da by SEC and simultaneously extracts peptides by SCX mechanism. After injection of 2 mL of human serum to the 1-D nanoLC-MS system, around 400 peptides could be identified. Similar to
using RAM, Tian et al. [97] attempted to use mesoporous
materials with critical pore sizes to selectively enrich peptides from human plasma but exclude other proteins by an
accurate MW cutoff like that of centrifugal ultrafiltration. It
was found that MCM-41 with a pore size of 20.5 Å was
effective for enriching peptides in human plasma with a
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
697
wide MW range from 1 to 12 kDa (Figs. 6A and C), while
repelling most other plasma proteins outside, as shown in
Figs. 6B and D. The unique pore structure of this material
made it superior for peptide enrichment when compared
to both adsorbent- and ultrafiltration-based methods.
5
Some interesting on-line sample
pretreatment approaches
5.1 Automated sample injection
Although mHPLC-MS/MS is the dominant platform for proteomic analysis, automation of sample introduction onto
analytical column without seriously compromising the
separation performance is very difficult. In typical cases,
proteomic sample size ranges from a few microliters to 100
microliters. It will take a long time for sample loading if the
samples are directly loaded onto capillary analytical column
in nanoflow HPLC. The automation could be realized by
different instrument configurations by using a short and
large id. C18 trap column coupled with a C18 analytical column for rapid sample loading. Briefly, protein digests of
large volumes are firstly loaded onto the trap column at a
high flow rate in a short time and after equilibrium the
adsorbed peptides are eluted from the trap column to the RP
analytical column. Two types of instrument configurations
have been adopted for the automated sample injection in
mHPLC-MS/MS using trap column. One is directly connecting the trap column and C18 analytical column by a nanoflow switching valve. The flow through from trap column is
directed to waste or analytical column during sample injection or separation by the switching valve [98–100]. In this
type of system, proteolytic digest without prior purification
could be directly injected and cleaned up online, which is
very attractive in comprehensive proteome analysis. But the
void volume introduced by switching valve would degrade
the separation performance greatly. The other is a vented
column system in which trap and analytical columns are directly connected via a microcross or microtee with an open/
close switching valve [101–104]. In this type of system, the
mobile phase for mHPLC separation does not pass through
the switching valve, so a regular six-port switching valve
could be used instead of using a nanoflow switching valve. In
order to minimize the void volume resulted from the microcross or microtee, Licklider et al. [102] packed the open space
of microcross with C18 particles, and Meiring et al. [103]
drilled the microtee to 0.6 mm id to fit a single micro sleeve
having a V-shaped cut as a waste outlet and the trapping and
analytical columns were butt-connected in this modified
sleeve. However, these systems largely depend on experience
and are not widely used. Another disadvantage of vented
column system is that proteolytic digests containing denaturing agents can not be loaded directly. This is because a
small portion of the sample solution will also enter the analytical column and contaminate the column during loading
www.proteomics-journal.com
698
X. Jiang et al.
Proteomics 2008, 8, 686–705
Figure 6. MALDI-TOF MS analysis of human plasma (A, B) before and (C, D) after exposure to MCM-41 by using a-cyano-4-hydroxycinnamic acid as matrix. Analysis in the MW range of (A, C) 1–15 kDa and (B, D) 10–100 kDa. Reprinted from [97].
of sample onto the trap column. So proteolytic digests must
be desalted and cleaned before the automated sample introduction.
Although the above systems enable the automated sample injection for proteome analysis by mHPLC-MS/MS, void
volume resulted from the connections between trap column
and analytical capillary column which inevitably leads to the
degradation of separation performance. As further decreasing the void volume is a technique challenge, a good solution
is to develop a void volume insensitive automated sample
injection system for mHPLC-MS/MS analysis. All above systems use C18 trap column. It was found recently that automation of sample injection using SCX trap column instead
of C18 trap column could alleviate the influence of void volume on separation [101, 105]. In this approach, protein
digest was first loaded onto a SCX trap column, the captured
peptides were then eluted onto C18 analytical column by a
high salt buffer for separation. Because the peptide sample
was retained on the entrance end of the C18 analytical column before the gradient started separation, the void volume
before the capillary column hardly affected the separation
adversely. Recently, the influence of the void volume between
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
trap column and analytical column were systematically
investigated and no obvious degradation of the proteome
analysis performance was observed even with a void volume
as large as 5 mL. Similar to using C18 trap column, the automation of the sample injection using SCX trap column could
also be realized by the two configurations, i.e. directly using
the nanoflow switching valve [105] and using the vented column configurations [101]. The schematic diagrams for these
two instrument configurations are shown in Fig. 7. The first
configuration allowed direct injection of detergent containing sample, while the second one had the advantage of overall short separation time because of its small void volume.
Besides 1-D separation, the SCX trap column systems could
also be conveniently applied for large scale proteome and
peptidome analysis of complex samples with multi-dimensional separation [89, 97, 101]. To load sample at high flow
rate, low back pressure of the trap column is preferable.
Instead of using a packed trap column, a phosphate monolithic trap column was prepared and used for automatic
sample injection in nanoLC-MS/MS system[106]. Because of
its low back pressure, sample injection at a high flow rate of
40 mL/min could be easily realized.
www.proteomics-journal.com
Proteomics 2008, 8, 686–705
Technology
699
Figure 7. Schematic diagrams
of on line sample injection systems using SCX trap column (A):
directly using the nanoflow
switching valve [105]; (B): using
the vented column [101]
5.2 On-line digestion by immobilized enzyme reactor
Usually, tryptic digestion of protein is performed either in
gel or in solution. However, these methodologies have several drawbacks, such as long digestion time (typically .5 h),
auto-proteolysis of trypsin and the difficulty for automation.
On the contrary, the trypsin immobilized on matrixes has
the advantages of high efficiency, high stability and easy to
automation [107–110]. Schriemer et al. [107, 108] demonstrated on-line, real-time tryptic digestion of proteins by a
packed immobilized trypsin cartridge, directly followed with
RP protein separation. Using test mixtures of standard proteins, peptide mass fingerprinting with high sequence coverage could be easily achieved at the 20 fmol level, with
detection limits down to 5 fmol. With the rapid development of monolithic column technologies, immobilized enzyme monolithic reactors were prepared for on-line digestion of proteins. For example, trypsin-based monolithic col© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
umn with dimension of 50 mm64.6 mm id was prepared
and applied to automated digestion of protein and protein
identification for proteome analysis [111]. However, the
large size of the reactor was not suitable for use in a nanoflow LC-MS system. Therefore, Feng et al. [112] prepared a
nanoliter trypsin microreactor, and coupled it on-line with
mRPLC-MS/MS for the analysis of the total cell lysate of
Saccharomyces cerevisiae. After database search, a total of
1578 unique peptides corresponding to 541 proteins were
identified when 590 ng yeast protein was digested by the
microreactor with an incubation time of only 1 min.
Recently, a fully automated CE-Microreactor-CE-MS/MS
system was presented for protein ananlysis [113]. In this
system, proteins were first separated by CE. A monolithic
pepsin microreactor was incorporated into the distal end of
this capillary. Peptides formed in the reactor were transferred to a second capillary, where they were separated by
CE and characterized by MS.
www.proteomics-journal.com
700
6
X. Jiang et al.
Conclusion and perspective
As there are a lot of redundant peptides presented in a peptide mixture, isolation of a subset of interested peptides
represented an efficient approach to simplify the complexity
of proteome analysis. Therefore, the key to this approach is
to significantly reduce the sample complexity and meanwhile keep the integrity of the proteome. At present, isolation
of rare amino acid-containing peptides, especially Cys-containing peptides, has already been proved to be an effective
method to reduce sample complexity. However, the disadvantage for isolation of rare amino acid-containing peptides is that the distribution of these rare amino acid residues
among different proteins is not even. Therefore, some proteins have many representative peptides while others have a
few or even no representative peptides, proteome analysis by
this approach bias to proteins with high percentage of this
type of rare amino acid residues. In contrast, terminal peptides are the most evenly distributed peptides as every protein has one N-terminal peptide and one C-terminal peptide.
Reducing the sample complexity by isolating terminal peptides has drawn strong attention since Gevaert et al. [26]
published the first paper in 2003 on isolation of N-terminal
peptides for proteome analysis. Up to now, several approaches were developed to isolate N-terminal peptides. It should
be mentioned that identification of protein by only one peptide is not always successful. This happens because the peptide may not be the right size for MS/MS analysis or the
peptide has some unknown modifications. To solve this
problem, PST technology reported by Kuhn et al. [24–26] is
an alternative way. However, it also depends on the distribution of Met-residues among proteins. An ideal approach to
reduce the sample complexity for proteome analysis may be
to isolate both N-terminal and C-terminal peptides. However,
there is still a long way to go before this approach is applicable. The specificity for isolation of N-terminal peptides
should be improved and an effective method to isolate C-terminal peptides should be developed.
Phosphoproteome analysis depends heavily on LC-MS/
MS analysis of phosphopeptides. Because of low stoichiometry of protein phosphorylation, phosphopeptides always
co-exist with huge amounts of non-phosphopeptides which
seriously depress the detection of phosphopeptides. To specifically isolate phosphopeptides is still one of the key issues
for phosphoproteome analysis. Use of metal oxide particles
such as ZrO2 and TiO2 has already proved to be more specific
than conventional IMAC with Fe31. If Zr41 or Ti41 is immobilized onto chromatographic support via space arm, the
resulting new IMAC may have higher performance for isolation of phosphopeptides than corresponding metal oxides
because the steric hindrance will be reduced. We already
demonstrated that the new IMAC with Zr41 had excellent
specificity for isolation of phosphopeptides [44]. Also, the
new IMAC with Ti41 has been under investigation in our lab
and the preliminary results are promising. The affinity
chromatography with immobilized Zr41 or Ti41 might
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Proteomics 2008, 8, 686–705
become a new generation of high performance IMAC for
specific isolation of phosphopeptides. As the phosphopeptide mixture enriched by the majority of currently available
phosphopeptide enrichment methods is still very complex,
fractionation of phosphopeptides prior to LC-MS/MS analysis is beneficial for large scale phosphoproteome analysis.
Although phosphopeptides could be fractionated by SAX or
SCX, their performance is far from ideal. High resolution
techniques for fractionation of phosphopeptides need to be
developed for comprehensive phosphoproteome analysis.
Glycoproteomics analysis also relies on analysis of glycopeptides. Up to now, using lectin affinity chromatography
and hydrazide beads are the two most effective approaches to
isolate glycopeptides. Both approaches have its strengths and
weaknesses. Lectin affinity chromatography approach keeps
the carbohydrate moiety intact which makes characterization
of the carbohydrate moiety possible. However, the carbohydrate moiety will be destroyed during chemical reaction with
the hydrazide chemistry approach. The advantage of hydrazide chemistry approach is its extremely high specificity as
the glycopeptide selectivity as high as 91% could be achieved
[64]. But the specificity for lectin affinity chromatography
was relative poor even when a tandem purification approach
was applied. Hydrazide chemistry approach can capture all
types of glycopeptides and so can be applied to analyze all
types of glycosylation in theory. However, majority of applications are limited in analysis of N-linked glycosylation because of the formally N-linked glycosylated peptides could be
easily cleaved from the beads by PNGaseF. In order to analyze other types of glycosylation by hydrazide chemistry
approach, the methods to specifically cleave the corresponding peptides from the beads should be developed.
For peptidome analysis, one of the key challenges is to
isolate endogenous peptides from biologic sample where
huge amounts of protein are presented. As the only difference between peptide and protein is the size, it is preferable
to use size based separation approach to isolate endogenous
peptides. RAMs have a bimodal surface topochemistry and
have functions of both SEC and adsorption chromatography,
thus it is a good approach for isolation of peptides. Application of new materials such as mesoporous materials with
critical pore sizes for selectively enriching peptides but
exclude other proteins by an accurate MW cutoff represents a
new trend to isolate peptides [97]. Similar to RAM, to further
improve peptide isolation efficiency, derivatization of inner
surface and outer surface of these materials with different
functionary groups is required. The inner surface should be
derivatized with stationary phase such as RP, ion-exchange,
etc. to bind peptides while the outer surface should be derivatized with hydrophilic groups to minimize the non-specific
adsorption of proteins.
Although sample pretreatment technologies have made
big progress in the last decade, more improvements are
required to further overcome the complexity and dynamic
range problem for proteomics analysis. For selective enrichment of a subset of interested peptides, specificity should be
www.proteomics-journal.com
Proteomics 2008, 8, 686–705
improved to enrich the target peptides. This field will still be
a vital part of proteomics, which is available to reduce proteome complexity substantially and simplify peptide identification. Moreover, development of high efficient and automated platforms, including protein digestion, desalting of
sample, introduction of sample, etc, is urgently needed for
proteomic analysis. With the development of new sample
pretreatment methods, proteome analysis could mine
deeper and more insights for biological and medical research
in the future.
Financial supports from the National Natural Sciences
Foundation of China (20735004, 20675081), the China State
Key Basic Research Program Grant (2005CB522701), the
China High Technology Research Program Grant
(2006AA02A309), and the Knowledge Innovation program of
CAS (KJCX2.YW.HO9, KSCX2-YW-R-079) and the Knowledge
Innovation program of DICP to H.Z. and National Natural
Sciences Foundation of China (No. 20605022, 90713017) to
M.Y. are gratefully acknowledged.
The authors have declared no conflict of interest.
7
References
[1] Rabilloud, T., Two-dimensional gel electrophoresis in proteomics: Old, old fashioned, but it still climbs up the mountains. Proteomics 2002, 2, 3–10.
[2] Steen, H., Mann, M., The ABC’s (and XYZ’s) of peptide sequencing. Nat. Rev. Mol. Cell Biol. 2004, 5, 699–711.
[3] Washburn, M. P., Wolters, D., Yates, J. R., 3rd, Large-scale
analysis of the yeast proteome by multidimensional protein
identification technology. Nat. Biotechnol. 2001, 19, 242–
247.
[4] Link, A. J., Eng, J., Schieltz, D. M., Carmack, E. et al., Direct
analysis of protein complexes using mass spectrometry.
Nat. Biotechnol., 1999, 17, 676–682.
[5] Azarkan, M., Huet, J., Baeyens-Volant, D., Looze, Y. et al.,
Affinity chromatography: a useful tool in proteomics studies. J. Chromatogr. B 2007, 849, 81–90.
Technology
701
[11] Zhou, H., Ranish, J. A., Watts, J. D., Aebersold, R., Quantitative proteome analysis by solid-phase isotope tagging and
mass spectrometry. Nat. Biotechnol. 2002, 20, 512–515.
[12] Wang, S., Regnier, F. E., Proteomics based on selecting and
quantifying cysteine containing peptides by covalent chromatography. J. Chromatogr. A 2001, 924, 345–357.
[13] Gevaert, K., Ghesquiere, B., Staes, A., Martens, L. et al.,
Reversible labeling of cysteine-containing peptides allows
their specific chromatographic isolation for non-gel proteome studies. Proteomics 2004, 4, 897–908.
[14] Wang, H., Qian, W. J., Chin, M. H., Petyuk, V. A. et al., Characterization of the mouse brain proteome using global proteomic analysis complemented with cysteinyl-peptide
enrichment. J. Proteome Res. 2006, 5, 361–369.
[15] Weinberger, S. R., Viner, R. I., Ho, P., Tagless extractionretentate chromatography: a new global protein digestion
strategy for monitoring differential protein expression.
Electrophoresis 2002, 23, 3182–3192.
[16] Gevaert, K., Van Damme, J., Goethals, M., Thomas, G. R. et
al., Chromatographic isolation of methionine-containing
peptides for gel-free proteome analysis: identification of
more than 800 Escherichia coli proteins. Mol. Cell. Proteomics 2002, 1, 896–903.
[17] Kuyama, H., Watanabe, M., Toda, C., Ando, E. et al., An
approach to quantitative proteome analysis by labeling
tryptophan residues. Rapid Commun. Mass Spectrom. 2003,
17, 1642–1650.
[18] Matsuo, E., Toda, C., Watanabe, M., Lida, T. et al., Improved
2-nitrobenzenesulfenyl method: Optimization of the protocol and improved enrichment for labeled peptides. Rapid
Commun. Mass Spectrom. 2006, 20, 31–38.
[19] Foettinger, A., Leitner, A., Lindner, W., Selective enrichment
of tryptophan-containing peptides from protein digests
employing a reversible derivatization with malondialdehyde
and solid-phase capture on hydrazide beads. J. Proteome
Res. 2007, 6, 3827–3834.
[20] Ji, J., Chakraborty, A., Geng, M., Zhang, X. et al., Strategy for
qualitative and quantitative analysis in proteomics based on
signature peptides. J. Chromatogr. B 2000, 745, 197–210.
[21] Ren, D., Penner, N. A., Slentz, B. E., Inerowicz, H. D. et al.,
Contributions of commercial sorbents to the selectivity in
immobilized metal affinity chromatography with Cu(II). J.
Chromatogr. A 2004, 1031, 87–92.
[6] Lescuyer, P., Hochstrasser, D. F., Sanchez, J. C., Comprehensive proteome analysis by chromatographic protein prefractionation. Electrophoresis 2004, 25, 1125–1135.
[22] Ren, D., Penner, N. A., Slentz, B. E., Mirzaei, H. et al., Evaluating immobilized metal affinity chromatography for the
selection of histidine-containing peptides in comparative
proteomics. J. Proteome Res. 2003, 2, 321–329.
[7] Ye, M., Jiang, X., Feng, S., Tian, R. et al., Advances in chromatographic techniques and methods in shotgun proteome
analysis. Trac-Trend. Anal.Chem. 2007, 26, 80–84.
[23] Ren, D., Penner, N. A., Slentz, B. E., Regnier, F. E., Histidinerich peptide selection and quantification in targeted proteomics. J. Proteome Res. 2004, 3, 37–45.
[8] Zhang, H., Yan, W., Aebersold, R., Chemical probes and tandem mass spectrometry: a strategy for the quantitative
analysis of proteomes and subproteomes. Curr. Opin. Chem.
Biol. 2004, 8, 66–75.
[24] Noubhani, A. M., Dieryck, W., Bakalara, N., Latxague, L. et
al., Evaluation of chromatographic recycling for imidazole
used in the chromatographic purification of His-tag recombinant proteins. J. Chromatogr. B 2003, 790, 153–159.
[9] Leitner, A., Lindner, W., Current chemical tagging strategies
for proteome analysis by mass spectrometry. J. Chromatogr. B 2004, 813, 1–26.
[25] Wang, S., Zhang, X., Regnier, F. E., Quantitative proteomics
strategy involving the selection of peptides containing both
cysteine and histidine from tryptic digests of cell lysates. J.
Chromatogr. A 2002, 949, 153–162.
[10] Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F. et al., Quantitative analysis of complex protein mixtures using isotopecoded affinity tags. Nat. Biotechnol. 1999, 17, 994–999.
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
[26] Gevaert, K., Goethals, M., Martens, L., Van Damme, J. et al.,
Exploring proteomes and analyzing protein processing by
www.proteomics-journal.com
702
X. Jiang et al.
mass spectrometric identification of sorted N-terminal peptides. Nat. Biotechnol. 2003, 21, 566–569.
[27] Aivaliotis, M., Gevaert, K., Falb, M., Tebbe, A. et al., Largescale identification of N-terminal peptides in the halophilic
archaea Halobacterium salinarum and Natronomonas pharaonis. J. Proteome Res. 2007, 6, 2195–2204.
Proteomics 2008, 8, 686–705
[42] Moser, K., White, F. M., Phosphoproteomic analysis of rat
liver by high capacity IMAC and LC-MS/MS. J. Proteome
Res. 2006, 5, 98–104.
[43] Kim, J. E., Tannenbaum, S. R., White, F. M., Global phosphoproteome of HT-29 human colon adenocarcinoma cells.
J. Proteome Res. 2005, 4, 1339–1346.
[28] McDonald, L., Robertson, D. H., Hurst, J. L., Beynon, R. J.,
Positional proteomics: selective recovery and analysis of Nterminal proteolytic peptides. Nat. Methods 2005, 2, 955–
957.
[44] Feng, S., Ye, M., Zhou, H., Jiang, X. et al., Immobilized zirconium ion affinity chromatography for specific enrichment
of phosphopeptides in phosphoproteome analysis. Mol.
Cell. Proteomics 2007, 6, 1656–1665.
[29] Yamaguchi, M., Nakazawa, T., Kuyama, H., Obama, T. et al.,
High-throughput method for N-terminal sequencing of proteins by MALDI mass spectrometry. Anal. Chem. 2005, 77,
645–651.
[45] Cantin, G. T., Shock, T. R., Park, S. K., Madhani, H. D. et al.,
Optimizing TiO(2)-based phosphopeptide enrichment for
automated multidimensional liquid chromatography coupled to tandem mass spectrometry. Anal. Chem. 2007, 79,
4666–4673.
[30] Mikami, T., Takao, T., Selective isolation of N-blocked peptides by isocyanate-coupled resin. Anal. Chem. 2007, 79,
7910–7915.
[46] Kweon, H. K., Hakansson, K., Selective zirconium dioxidebased enrichment of phosphorylated peptides for mass
spectrometric analysis. Anal. Chem. 2006, 78, 1743–1749.
[31] Kuhn, K., Prinz, T., Schafer, J., Baumann, C. et al., Protein
sequence tags: A novel solution for comparative proteomics. Proteomics 2005, 5, 2364–2368.
[47] Zhou, H., Tian, R., Ye, M., Xu, S. et al., Highly specific
enrichment of phosphopeptides by zirconium dioxide
nanoparticles for phosphoproteome analysis. Electrophoresis 2007, 28, 2201–2215.
[32] Kuhn, K., Thompson, A., Prinz, T., Muller, J. et al., Isolation of
N-terminal protein sequence tags from cyanogen bromide
cleaved proteins as a novel approach to investigate hydrophobic proteins. J. Proteome Res. 2003, 2, 598–609.
[33] Prinz, T., Muller, J., Kuhn, K., Schafer, J. et al., Characterization of low abundant membrane proteins using the protein
sequence tag technology. J. Proteome Res. 2004, 3, 1073–
1081.
[48] Beausoleil, S. A., Jedrychowski, M., Schwartz, D., Elias, J. E.
et al., Large-scale characterization of HeLa cell nuclear
phosphoproteins. Proc. Natl. Acad. Sci. USA 2004, 101,
12130–12135.
[49] Ballif, B. A., Villen, J., Beausoleil, S. A., Schwartz, D. et al.,
Phosphoproteomic analysis of the developing mouse brain.
Mol. Cell. Proteomics 2004, 3, 1093–1101.
[34] Feuerstein, I., Morandell, S., Stecher, G., Huck, C. W. et al.,
Phosphoproteomic analysis using immobilized metal ion
affinity chromatography on the basis of cellulose powder.
Proteomics 2005, 5, 46–54.
[50] Nuhse, T. S., Stensballe, A., Jensen, O. N., Peck, S. C., Largescale analysis of in vivo phosphorylated membrane proteins
by immobilized metal ion affinity chromatography and
mass spectrometry. Mol. Cell. Proteomics 2003, 2, 1234–
1243.
[35] Jin, W. H., Dai, J., Zhou, H., Xia, Q. C. et al., Phosphoproteome analysis of mouse liver using immobilized metal affinity purification and linear ion trap mass spectrometry.
Rapid Commun. Mass Spectrom. 2004, 18, 2169–2176.
[51] Dai, J., Jin, W. H., Sheng, Q. H., Shieh, C. H. et al., Protein
phosphorylation and expression profiling by Yin-yang multidimensional liquid chromatography (Yin-yang MDLC)
mass spectrometry. J. Proteome Res. 2007, 6, 250–262.
[36] Lee, J., Xu, Y., Chen, Y., Sprung, R. et al., Mitochondrial
phosphoproteome revealed by an improved IMAC method
and MS/MS/MS. Mol. Cell. Proteomics 2007, 6, 669–676.
[52] Han, G. H., Ye, M. L., Zhou, H. J., Jiang, X. N. et al., Large
scale phosphoproteome analysis of human liver tissue by
enrichment and fractionation of phosphopeptides with
strong anion exchange chromatography. Proteomics 2008,
in press.
[37] Wagner, V., Gessner, G., Heiland, I., Kaminski, M. et al.,
Analysis of the phosphoproteome of Chlamydomonas reinhardtii provides new insights into various cellular pathways.
Eukaryot. Cell 2006, 5, 457–468.
[38] Nuhse, T. S., Peck, S. C., Peptide-based phosphoproteomics
with immobilized metal ion chromatography. Methods Mol.
Biol. 2006, 323, 431–436.
[39] Pan, C., Ye, M., Liu, Y., Feng, S. et al., Enrichment of phosphopeptides by Fe31-immobilized mesoporous nanoparticles of MCM-41 for MALDI and nano-LC-MS/MS analysis. J. Proteome Res. 2006, 5, 3114–3124.
[40] Feng, S., Pan, C., Jiang, X., Xu, S. et al., Fe31 immobilized
metal affinity chromatography with silica monolithic capillary column for phosphoproteome analysis. Proteomics
2007, 7, 351–360.
[41] Ficarro, S. B., McCleland, M. L., Stukenberg, P. T., Burke, D. J.
et al., Phosphoproteome analysis by mass spectrometry and
its application to Saccharomyces cerevisiae. Nat. Biotechnol. 2002, 20, 301–305.
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
[53] Xu, S., Zhou, H., Pan, C., Fu, Y. et al., Iminodiacetic acid
derivatized porous silicon as a matrix support for sample
pretreatment and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis. Rapid Commun. Mass Spectrom. 2006, 20, 1769–1775.
[54] Zhou, H., Xu, S., Ye, M., Feng, S. et al., Zirconium phosphonate-modified porous silicon for highly specific capture of
phosphopeptides and MALDI-TOF MS analysis. J. Proteome
Res. 2006, 5, 2431–2437.
[55] Dunn, J. D., Watson, J. T., Bruening, M. L., Detection of
phosphopeptides using Fe(III)-nitrilotriacetate complexes
immobilized on a MALDI plate. Anal. Chem. 2006, 78, 1574–
1580.
[56] Yang, Z., Hancock, W. S., Chew, T. R., Bonilla, L., A study of
glycoproteins in human serum and plasma reference
standards (HUPO) using multilectin affinity chromatography coupled with RPLC-MS/MS. Proteomics 2005, 5, 3353–
3366.
www.proteomics-journal.com
Proteomics 2008, 8, 686–705
Technology
703
[57] Kaji, H., Saito, H., Yamauchi, Y., Shinkawa, T. et al., Lectin
affinity capture, isotope-coded tagging and mass spectrometry to identify N-linked glycoproteins. Nat. Biotechnol.
2003, 21, 667–672.
[73] Aristoteli, L. P., Molloy, M. P., Baker, M. S., Evaluation of endogenous plasma peptide extraction methods for mass
spectrometric biomarker discovery. J. Proteome Res. 2007,
6, 571–581.
[58] Drake, R. R., Schwegler, E. E., Malik, G., Diaz, J. et al., Lectin
capture strategies combined with mass spectrometry for the
discovery of serum glycoprotein biomarkers. Mol. Cell. Proteomics 2006, 5, 1957–1967.
[74] Johnson, K. L., Mason, C. J., Muddiman, D. C., Eckel, J. E.,
Analysis of the low molecular weight fraction of serum by
LC-dual ESI-FT-ICR mass spectrometry: precision of retention time, mass, and ion abundance. Anal. Chem. 2004, 76,
5097–5103.
[59] Lis, H., Sharon, N., Lectins: Carbohydrate-specific proteins
that mediate cellular recognition. Chem. Rev. 1998, 98, 637–
674.
[60] Nilsson, C. L., Lectins: Proteins that interpret the sugar code.
Anal. Chem. 2003, 75, 348A–353A.
[61] Bond, M. R., Kohler, J. J., Chemical methods for glycoprotein discovery. Curr. Opin. Chem. Biol. 2007, 11, 52–58.
[62] Zhang, H., Li, X. J., Martin, D. B., Aebersold, R., Identification
and quantification of N-linked glycoproteins using hydrazide chemistry, stable isotope labeling and mass spectrometry. Nat. Biotechnol. 2003, 21, 660–666.
[75] Tirumalai, R. S., Chan, K. C., Prieto, D. A., Issaq, H. J. et al.,
Characterization of the low molecular weight human serum
proteome. Mol. Cell. Proteomics 2003, 2, 1096–1103.
[76] Yuan, X., Desiderio, D. M., Human cerebrospinal fluid peptidomics. J. Mass Spectrom. 2005, 40, 176–181.
[77] Zheng, X., Baker, H., Hancock, W. S., Analysis of the low
molecular weight serum peptidome using ultrafiltration and
a hybrid ion trap-Fourier transform mass spectrometer. J.
Chromatogr. A 2006, 1120, 173–184.
[63] Zhang, H., Liu, A. Y., Loriaux, P., Wollscheid, B. et al., Mass
spectrometric detection of tissue proteins in plasma. Mol.
Cell. Proteomics, 2007, 6, 64–71.
[78] Hu, L., Li, X., Jiang, X., Zhou, H. et al., Comprehensive peptidome analysis of mouse livers by size exclusion chromatography prefractionation and nanoLC-MS/MS identification. J. Proteome Res. 2007, 6, 801–808.
[64] Sun, B., Ranish, J. A., Utleg, A. G., White, J. T. et al., Shotgun
glycopeptide capture approach coupled with mass spectrometry for comprehensive glycoproteomics. Mol. Cell.
Proteomics 2007, 6, 141–149.
[79] Hsieh, S. Y., Chen, R. K., Pan, Y. H., Lee, H. L., Systematical
evaluation of the effects of sample collection procedures on
low-molecular-weight serum/plasma proteome profiling.
Proteomics 2006, 6, 3189–3198.
[65] Alvarez-Manilla, G., Atwood, J., 3rd, Guo, Y., Warren, N. L. et
al., Tools for glycoproteomic analysis: size exclusion chromatography facilitates identification of tryptic glycopeptides
with N-linked glycosylation sites. J. Proteome Res. 2006, 5,
701–708.
[80] Villanueva, J., Lawlor, K., Toledo-Crow, R., Tempst, P., Automated serum peptide profiling. Nat. Protoc. 2006, 1, 880–
891.
[66] An, H. J., Peavy, T. R., Hedrick, J. L., Lebrilla, C. B., Determination of N-glycosylation sites and site heterogeneity in
glycoproteins. Anal. Chem. 2003, 75, 5628–5637.
[67] Hagglund, P., Bunkenborg, J., Elortza, F., Jensen, O. N. et al.,
A new strategy for identification of N-glycosylated proteins
and unambiguous assignment of their glycosylation sites
using HILIC enrichment and partial deglycosylation. J. Proteome Res. 2004, 3, 556–566.
[68] Larsen, M. R., Hojrup, P., Roepstorff, P., Characterization of
gel-separated glycoproteins using two-step proteolytic
digestion combined with sequential microcolumns and
mass spectrometry. Mol. Cell. Proteomics 2005, 4, 107–119.
[69] Wada, Y., Tajiri, M., Yoshida, S., Hydrophilic affinity isolation
and MALDI multiple-stage tandem mass spectrometry of
glycopeptides for glycoproteomics. Anal. Chem. 2004, 76,
6560–6565.
[70] Zhang, Q., Tang, N., Brock, J., Mottaz, H. et al., Enrichment
and analysis of nonenzymatically glycated peptides: boronate affinity chromatography coupled with electron-transfer dissociation mass spectrometry J. Proteome Res. 2007,
6, 2323–2330.
[71] Verhaert, P., Uttenweiler-Joseph, S., de Vries, M., Loboda, A.
et al., Matrix-assisted laser desorption/ionization quadrupole time-of-flight mass spectrometry: an elegant tool for
peptidomics. Proteomics 2001, 1, 118–131.
[72] Schulz-Knappe, P., Zucht, H. D., Heine, G., Jurgens, M. et al.,
Peptidomics: he comprehensive analysis of peptides in
complex biological mixtures. Comb. Chem. High Throughput Screen. 2001, 4, 207–217.
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
[81] Villanueva, J., Philip, J., Chaparro, C. A., Li, Y. et al., Correcting common errors in identifying cancer-specific serum
peptide signatures. J. Proteome Res. 2005, 4, 1060–1072.
[82] Villanueva, J., Philip, J., Entenberg, D., Chaparro, C. A. et al.,
Serum peptide profiling by magnetic particle-assisted,
automated sample processing and MALDI-TOF mass spectrometry. Anal. Chem. 2004, 76, 1560–1570.
[83] Fiedler, G. M., Baumann, S., Leichtle, A., Oltmann, A. et al.,
Standardized peptidome profiling of human urine by magnetic bead separation and matrix-assisted laser desorption/
ionization time-of-flight mass spectrometry. Clin. Chem.
2007, 53, 421–428.
[84] Koomen, J. M., Li, D., Xiao, L. C., Liu, T. C. et al., Direct tandem mass spectrometry reveals limitations in protein profiling experiments for plasma biomarker discovery. J. Proteome Res. 2005, 4, 972–981.
[85] Gaspari, M., Ming-Cheng Cheng, M., Terracciano, R., Liu, X.
et al., Nanoporous surfaces as harvesting agents for mass
spectrometric analysis of peptides in human plasma. J.
Proteome Res. 2006, 5, 1261–1266.
[86] Terracciano, R., Gaspari, M., Testa, F., Pasqua, L. et al.,
Selective binding and enrichment for low-molecular weight
biomarker molecules in human plasma after exposure to
nanoporous silica particles. Proteomics 2006, 6, 3243–3250.
[87] Jia, W., Chen, X., Lu, H., Yang, P., CaCO3-poly(methyl
methacrylate) nanoparticles for fast enrichment of lowabundance peptides followed by CaCO3-core removal for
MALDI-TOF MS analysis. Angew. Chem. Int. Ed. Engl. 2006,
45, 3345–3349.
[88] Zhang, Y., Wang, X., Shan, W., Wu, B. et al., Enrichment of
low-abundance peptides and proteins on zeolite nanocrys-
www.proteomics-journal.com
704
X. Jiang et al.
Proteomics 2008, 8, 686–705
tals for direct MALDI-TOF MS analysis. Angew. Chem. Int.
Ed. Engl. 2005, 44, 615–617.
to peptide and protein analysis. J. Sep. Sci. 2002, 25, 557–
568.
[89] Li, X., Xu, S., Pan, C., Zhou, H. et al., Enrichment of peptides
from plasma for peptidome analysis using multiwalled
carbon nanotubes. J. Sep. Sci. 2007, 30, 930–943.
[104] Yi, E. C., Lee, H., Aebersold, R., Goodlett, D. R., A microcapillary trap cartridge-microcapillary high-performance
liquid chromatography electrospray ionization emitter device capable of peptide tandem mass spectrometry at the
attomole level on an ion trap mass spectrometer with
automated routine operation. Rapid Commun. Mass Spectrom. 2003, 17, 2093–2098.
[90] Desilets, C. P., Rounds, M. A., Regnier, F. E., Semipermeable-surface reversed-phase media for high-performance
liquid chromatography. J. Chromatogr. 1991, 544, 25–39.
[91] Hagestam, I., Pinkerton, T., Internal surface reversed-phase
silica supports for liquid chromatography. Anal. Chem.
1985, 57.
[92] Boos, K., Grimm, C., High-performance liquid chromatography integrated solid-phase extraction in bioanalysis
using restricted access precolumn packings. Trac-Trend.
Anal. Chem. 1999, 18, 175–180.
[93] Machtejevas, E., Andrecht, S., Lubda, D., Unger, K. K.,
Monolithic silica columns of various format in automated
sample clean-up/multidimensional liquid chromatography/mass spectrometry for peptidomics. J. Chromatogr. A
2007, 1144, 97–101.
[94] Machtejevas, E., John, H., Wagner, K., Standker, L. et al.,
Automated multi-dimensional liquid chromatography:
sample preparation and identification of peptides from human blood filtrate. J. Chromatogr. B 2004, 803, 121–130.
[95] Wagner, K., Miliotis, T., Marko-Varga, G., Bischoff, R. et al.,
An automated on-line multidimensional HPLC system for
protein and peptide mapping with integrated sample
preparation. Anal. Chem. 2002, 74, 809–820.
[96] Hu, L., Ye, M., Boos, K., Jiang, X. et al., Fully automated
serum peptidome analysis by coupling a novel bifunctional
capillary trap column with nanoLC-MS. In preparation.
[97] Tian, R., Zhang, H., Ye, M., Jiang, X. et al., Selective extraction of peptides from human plasma by highly ordered
mesoporous silica particles for peptidome analysis.
Angew. Chem. Int. Ed. Engl. 2007, 46, 962–965.
[98] Devreese, B., Vanrobaeys, F., Van Beeumen, J., Automated
nanoflow liquid chromatography/tandem mass spectrometric identification of proteins from Shewanella putrefaciens separated by two-dimensional polyacrylamide gel
electrophoresis. Rapid Commun. Mass Spectrom. 2001, 15,
50–56.
[99] Masuda, J., Maynard, D. A., Nishimura, M., Uedac, T. et al.,
Fully automated micro- and nanoscale one- or two-dimensional high-performance liquid chromatography system
for liquid chromatography-mass spectrometry compatible
with non-volatile salts for ion exchange chromatography.
J. Chromatogr. A 2005, 1063, 57–69.
[100] Mitulovic, G., Stingl, C., Smoluch, M., Swart, R. et al.,
Automated, on-line two-dimensional nano liquid chromatography tandem mass spectrometry for rapid analysis of
complex protein digests. Proteomics 2004, 4, 2545–2557.
[101] Jiang, X., Feng, S., Tian, R., Han, G. et al., Automation of
nanoflow liquid chromatography-tandem mass spectrometry for proteome analysis by using a strong cation
exchange trap column. Proteomics 2007, 7, 528–539.
[102] Licklider, L. J., Thoreen, C. C., Peng, J. M., Gygi, S. P.,
Automation of nanoscale microcapillary liquid chromatography-tandem mass spectromentry with a vented column. Anal. Chem. 2002, 74, 3076–3083.
[103] Meiring, H. D., van der Heeft, E., ten Hove, G. J., de Jong,
A., Nanoscale LC-MS(n): Technical design and applications
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
[105] Wang, F., Jiang, X., Feng, S., Tian, R. et al., Automated
injection of uncleaned samples using ten-port switching
valve and stronge cation exchange trap column for proteome analysis. J. Chromatogr. A 2007, 1171, 56–62.
[106] Wang, F., Dong, J., Jiang, X., Ye, M. et al., Capillary trap
column with strong cation-exchange monolith for automated shotgun proteome analysis. Anal. Chem. 2007, 79,
6599–6606.
[107] Slysz, G. W., Lewis, D. F., Schriemer, D. C., Detection and
identification of sub-nanogram levels of protein in a
nanoLC-trypsin-MS system. J. Proteome Res. 2006, 5,
1959–1966.
[108] Slysz, G. W., Schriemer, D. C., Blending protein separation
and peptide analysis through real-time proteolytic digestion. Anal. Chem. 2005, 77, 1572–1579.
[109] Ye, M., Hu, S., Schoenherr, R. M., Dovichi, N. J., On-line
protein digestion and peptide mapping by capillary electrophoresis with post-column labeling for laser-induced
fluorescence detection. Electrophoresis 2004, 25, 1319–
1326.
[110] Duan, J., Liang, Z., Yang, C., Zhang, J. et al., Rapid protein
identification using monolithic enzymatic microreactor
and LC-ESI-MS/MS. Proteomics 2006, 6, 412–419.
[111] Calleri, E., Temporini, C., Perani, E., De Palma, A. et al.,
Trypsin-based monolithic bioreactor coupled on-line with
LC/MS/MS system for protein digestion and variant identification in standard solutions and serum samples. J. Proteome Res. 2005, 4, 481–490.
[112] Feng, S., Ye, M., Jiang, X., Jin, W. et al., Coupling the
immobilized trypsin microreactor of monolithic capillary
with muRPLC-MS/MS for shotgun proteome analysis. J.
Proteome Res. 2006, 5, 422–428.
[113] Schoenherr, R. M., Ye, M., Vannatta, M., Dovichi, N. J., CEmicroreactor-CE-MS/MS for protein analysis. Anal. Chem.
2007, 79, 2230–2238.
[114] Neville, D. C., Rozanas, C. R., Price, E. M., Gruis, D. B. et al.,
Evidence for phosphorylation of serine 753 in CFTR using a
novel metal-ion affinity resin and matrix-assisted laser desorption mass spectrometry. Protein Sci. 1997, 6, 2436–
2445.
[115] Posewitz, M. C., Tempst, P., Immobilized gallium(III) affinity
chromatography of phosphopeptides. Anal. Chem. 1999,
71, 2883–2892.
[116] Oda, Y., Nagasu, T., Chait, B. T., Enrichment analysis of
phosphorylated proteins as a tool for probing the phosphoproteome. Nat. Biotechnol. 2001, 19, 379–382.
[117] Zhou, H. L., Watts, J. D., Aebersold, R., A systematic
approach to the analysis of protein phosphorylation. Nat.
Biotechnol. 2001, 19, 375–378.
[118] Guo, L., Eisenman, J. R., Mahimkar, R. M., Peschon, J. J. et
al., A proteomic approach for the identification of cell-sur-
www.proteomics-journal.com
Proteomics 2008, 8, 686–705
face proteins shed by metalloproteases. Mol. Cell. Proteomics 2002, 1, 30–36.
[119] Vosseller, K., Trinidad, J. C., Chalkley, R. J., Specht, C. G. et
al., O-linked N-acetylglucosamine proteomics of postsynaptic density preparations using lectin weak affinity
chromatography and mass spectrometry. Mol. Cell. Proteomics 2006, 5, 923–934.
[120] Wu, A. M., Wu, J. H., Singh, T., Liu, J. H. et al., Lectinochemical studies on the affinity of Anguilla anguilla agglutinin for mammalian glycotopes. Life Sci. 2004, 75, 1085–
1103.
[121] Shibuya, N., Goldstein, I. J., Broekaert, W. F., NsimbaLubaki, M. et al., Fractionation of sialylated oligosaccha-
© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Technology
705
rides, glycopeptides, and glycoproteins on immobilized
elderberry (Sambucus nigra L.) bark lectin. Arch. Biochem.
Biophys. 1987, 254, 1–8.
[122] Morelle, W., Canis, K., Chirat, F., Faid, V. et al., The use of
mass spectrometry for the proteomic analysis of glycosylation. Proteomics 2006, 6, 3993–4015.
[123] Kochibe, N., Furukawa, K., Purification and properties of a
novel fucose-specific hemagglutinin of Aleuria aurantia.
Biochemistry 1980, 19, 2841–2846.
[124] Neurohr, K. J., Young, N. M., Mantsch, H. H., Determination
of the carbohydrate-binding properties of peanut agglutinin by ultraviolet difference spectroscopy. J. Biol. Chem.
1980, 255, 9205–9209.
www.proteomics-journal.com