Human plasma and serum represents an important biological material for
disease diagnosis. However, the wide dynamic range in protein concentration
remains a major challenge in the development of diagnostic assays for
the very low concentration of biomarker proteins in the presence of high
abundance proteins. A practical and effective strategy is to remove 99%
of the diagnostically uninformative proteins in order to enhance the detection
of the low abundance proteins and penetrate deeper into the plasma proteome.
Among a number of plasma protein depletion techniques, the ProteoPrep
20 represents the most powerful enabling technology currently available.
1.1 Why blood plasma?
Blood plasma is not only the most studied among biological fluids,
but also the primary material for disease diagnosis. Blood plasma contains
a very high concentration of proteins, typically in the range of 60-80
mg of protein per ml. Estimates of the number of proteins in blood plasma
start from 10,000, but the actual number of distinct proteins may be several
orders of magnitude higher [1,2]. This is because each protein has a potential
for a variety of post-translational and metabolic modifications [3-6],
both in normal and diseased cells.
The global composition of proteins in the blood plasma represents the
plasma proteome. Perfusion of blood through the different organs and tissues
can result in the addition of new proteins, removal of some proteins,
or modification of existing proteins, which may vary according to specific
physiological or pathological conditions [7-14]. It is logical to expect
correlation between the proteomic profiles of
ed the number of proteins analyzed
and identified, some of the proteins found in the non-depleted serum were
not found in the depleted serum [70,109,112]. This is mostly attributed
to the so-called sponge effect, where small proteins and peptides may
bind to large proteins that normally serve as their carriers [109,112].
In reality there is no quantitative data to show how much of the non-targeted
proteins are non-specifically bound to the specifically depleted proteins,
and how much are bound to the depletion matrices. Nevertheless, these
observations raise concerns about the validity of the quantitative representation
of the whole proteome when only the protein-depleted sample is analyzed.
Therefore, for particular applications the specifically depleted bound
fraction may also be analyzed to ensure that no important proteins are
2.1 Depletion of albumin and the IgGs
Human serum albumin (HSA) and the various forms of immunoglobulins
(IgGs) represent the most abundant proteins in the serum, constituting
up to 80% of the total plasma proteins. The classical depletion strategy
for albumin involves the use of the hydrophobic dye Cibacron blue, a chlorotriazine
dye which has high affinity for albumin [104,105,113-115]. This strategy
of removing albumin is still sometimes used in proteomic analyses because
of its relatively low cost [52,116-120]. Other small molecules have been
designed (e.g. mimetic dyes) which demonstrate greater specificity than
Cibacron Blue. Another classical affinity medium is the Protein A/G [121,122],
which is used for the removal of the immunoglobulins [123,124]. As a group,
the immunoglobulins represent the second most abundant proteins in the
plasma or serum. A low cost depletion kit for simultaneous depletion of
albumin and immunoglobulins (Cat. No. PROTBA) is available which includes
both types of resins.
Comparative studies indicate that using antibody affinity ligands for
HSA and IgG result in more specific depletion compared to the traditional
Cibacron blue/Protein A or G depletion methods [71,100,106]. Because of
this demonstrated specificity, the trend is now towards the use of immunoaffinity
media for most proteomic analyses. Affinity media are made up of matrices
with covalently attached antibodies to the specific abundant proteins
[15,124-126]. An immunoaffinity media for HSA and IgG depletion is available
(Cat. No. PROTIA), conveniently packed as spin columns that are compatible
Despite the efficiency of immunoaffinity media, depletion of more proteins
besides HSA and the IgGs is necessary to enhance the detection of very
low abundance proteins that are present at the low ng/ml to pg/ml levels.
For example, it was estimated that even if 99.9% of albumin were removed,
the remaining albumin concentration would be about 50 g/ml, which is
still 50,000-fold higher concentration compared to the tumor marker prostate-
specific antigen [26,127,128]. In addition, there are still many other
highly abundant proteins that can potentially mask the analysis of the
low abundance proteins and should, therefore, be removed.
2.2 Depletion of six abundant proteins
While removing HSA and the IgGs has consistently shown improvement
in the detection of some low abundance proteins, analytical efficiency
is expected to improve even farther by increasing the number of proteins
depleted. Depletion of 6 and 12 abu
ndant proteins is expected to remove
about 85% and 90%, respectively, of the total proteins [71,100]. For example,
columns containing affinity ligands for the top six abundant proteins
have been shown to improve the visualization, detection and identification
of more low abundance proteins [38,70,73,74,99- 101,106,109,112,129-133],
when compared to depletion of only HSA and IgGs. In addition, data from
the HUPO Plasma Proteome Project clearly showed that depletion of the
most abundant proteins in serum, whether only albumin, albumin and IgGs,
or the six most abundant proteins, improved detection of some of the low
abundance proteins . However, the same report also indicated incomplete
sampling of proteins is a dominant feature. Part of the reason is likely
the limitation in the amount of sample that can be loaded for analysis,
before the remaining high abundance proteins interfere with the analysis.
An affinity column designed to remove the 12 most abundant proteins is
also available, but experimental data on this product is yet to emerge.
2.3 Depletion of 20 abundant proteins
It has been suggested that removal of 18 to 22 of the most abundant
proteins is desirable in order to effect an overall depletion of 98 to
99 percent of the total proteins [100,134]. A new affinity column with
high binding capacity has been developed. The ProteoPrep 20
Plasma Immunodepletion Kit (PROT20)
is the only commercially available product that contains immunoaffinity
ligands designed to remove 20 of the abundant proteins (Table 1) in human
plasma or serum . This novel technology is the most power
currently available, and has demonstrated the ability to deplete more
proteins to visualize low copy number proteins in plasma samples and subsequently
identify them by mass spectrometry .
For convenience, the ProteoPrep 20 Plasma Immunodepletion Kit (PROT20)
is supplied as a complete kit containing 3 spin columns and the necessary
reagents and consumable supplies. The kit also includes protocols that
have been optimized for specific applications. Carefully controlled tests
 indicated that each spin column removed the 20 high abundance proteins
with an average depletion of 99.6% when 10 x 8 l plasma depletions were
concentrated and depleted twice. This depletion enabled a 38-fold and
a 3-fold increase, respectively, in the load of low abundance proteins
compared to the sample without depletion and depletion of just 6 proteins.
This enrichment consequently enabled the identification of several low
abundance proteins that could not be detected either in the non-depleted
serum nor the 6-protein depleted serum. Finally, the spin columns have
high economic value because they are re-usable for at least 100 times.
Ordering information for PROT20 and companion reagents/consumables is
shown in Table 2.
As indicated previously, protein depletion can be considered an initial
dimension in orthogonal protein separation, the purpose of which is to
separate the highly abundant proteins from the low abundance proteins.
Since the flow through from ProteoPrep 20 spin column (low abundance proteins)
and the fraction derived from the proteins bound to the affinity media
(high abundance proteins) are both in solution phase, they are amenable
to subsequent protein separation steps. A variety of possible combinations
of orthogonal protein separation techniques are shown in the workflow
(Figure 1), depending on the application and instrumentation available
to the researcher. Finally, the different fractions from the different
multi-dimensional separation techniques are subjected to trypsin digestion
and analyzed by LC-mass spectrometry. Multi-dimensional analysis and mass
spectrometry will be discussed separately elsewhere.
Figure 1. Typical workflow for protein depletion using ProteoPrep
20 Plasma Immunodepletion Kit (PROT20), leading to multidimensional separation,
mass spectrometry, and protein identification. The different separation
techniques are enclosed in a dotted box to indicate that any combination
of these techniques can be used in an orthogonal manner. Abbreviations
used: HPLC, High Performance Liquid Chromatography; RP, Reversed Phase;
IE, Ion Exchange; SEC, Size Exclusion; AC, Affinity Chromatography; SDS-PAGE,
SDS-Polyacrylamide Electrophoresis; CZE, Capillary Zone Electrophoresis;
CIEF, Capillary Isoelectric Focusing; CGE, Capillary Gel Electrophoresis.
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When blood is coagulated and centrifuged, a translucent liquid called
serum separates as a top layer. The coagulated portion is presumed to
be mostly fibrin and other proteins involved in the coagulation process.
The serum still contains a very high concentration of proteins. While
both plasma and serum have been extensively used for diagnostic purposes,
there is an increasing trend towards the use of blood plasma for proteomic
profiling to ensure that important proteins are not trapped and lost into
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and testis are now being explored . While
the usefulness of these alternative biological fluids or tissues has not
yet been clearly established, it is very conceivable that their profiles
will complement or supplement those obtained from blood plasma or serum
1.2 Why proteomics?
There are two important biomolecular disciplines used in identifying
disease- associated biomarkers: genomics and proteomics. In the genomics
approach, genes that are associated with specific diseases or physiological
processes are identified and studied. The Human Genome Project (HGP) led
to the successful sequencing of the human genome [30,31], which resulted
in the identification of about 20,000 25,000 genes in the human body
. In various diseased states the expression of specific genes may
either be enhanced (turned on) or suppressed (turned off). Thus, the levels
of mRNA generated from the relative expression of these genes have been
thought to correlate to specific diseased states.
However, there are still questions about the correlation between the
expression levels of mRNAs and the corresponding changes in expression
levels of proteins expressed, whether in human tissues [12,33,34] or in
yeast cells [35,36]. In addition, one gene may express multiple proteins
[35,37], with multiple biological functions. Finally, the proteins expressed
from the genes may undergo a variety of post-translational modifications
[4,5], as well as isoforms , some of which may be important in disease
processes. For example, human plasma has been shown to contain 22 different
forms of &alpha -1-antitrypsin . In many cases, the processes that
regulate post-translational protein modifications are ind
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of the low molecular weight human serum proteome. Mol Cell Proteomics
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Kappel WK, Scott GB: Immunoaffinity depletion of 20 high abundance
human plasma proteins. Removal of approximately 97% of total plasma protein
improves identification of low abundance proteins. Origins
back to top
gene function. Thus, despite the abundance of scientific data, diagnostic
approaches based on genomic studies are still limited and are not always
practical for clinical use.
The obvious alternative is the proteomics approach since, as the final
form of the gene product, proteins are most directly related with biological
function. The proteome is also more responsive to physiological and diseased
states, as well as external stimuli. The dynamic nature of the proteome,
as opposed to the static nature of the genome, makes the proteome a real
time indicator of physiological processes. The proteomes of normal and
diseased states are quantitatively compared, and biomarker proteins are
then identified based on their relative abundance or structural form
(i.e. PTM state) [7,8,10,11,40-56]. Once identified, these biomarker
proteins are utilized for developing diagnostic tools, and the processes
that regulate their expression, processing and functions can be used as
therapeutic targets for drug candidates. Proteomic analyses have been
used to investigate potential biomarkers for such diseases as cancer [7,8,22,40-52,56-65],
hemophilia , osteoarthritis , and cardiovascular diseases .
The major goal of plasma and serum proteomics is to obtain the most reliable
information possible for diagnostic and therapeutic purposes. This requires
the establishment of accurate and comprehensive baseline data of the serum
proteome, including as many of the low abundance proteins as possible,
against which subsequent data from a variety of serum samples can be compared.
A baseline profile includes both the identification and quantitation
of different proteins. Such a baseline would permit better detection o
significant changes in biomarker levels as a result of specific physiological
conditions or disease, as well as indicate whether the condition warrants
further investigation. Highly sensitive and accurate biomarkers are very
important in detecting the early onset of diseases, since these biomarker
proteins are usually present at very low concentrations.
Although simple in principle, obtaining reliable baseline information
is extremely difficult in practice [2,66]. Major issues include variability
in sample collection and handling [66-69], a lack of standardized protocols
and instrumentation [64,70-74], and differences in handling, processing
and interpreting the data [68,75-79]. The recognition of the enormity
of the problem and potential benefits of success has brought international
cooperation and coordination within the research community, [e.g. Human
Proteome Organisation (HUPO)]. HUPO was organized in an attempt to provide
a comprehensive analysis of the proteins of human plasma and serum, annotate
the entire human proteome, and make the data publicly accessible. An initial
set of data generated from the Plasma Proteome Project (PPP) of HUPO identified
9504 proteins with one or more peptides, and 3020 proteins with two or
more peptides and were taken to represent their Core Dataset . A similar
database has annotated gene products encoded by 3778 distinct genes .
Current data from HUPO and elsewhere have successfully mapped 6342 peptides
to EnsEMBL 29.35b genome build . As more sensitive procedures are
developed, the number of proteins identified will likely increase. However,
the present results indicate that the number of proteins identified is
still below the predicted number of protei
ns present in the plasma or
Proteomics is certainly a promising approach to revolutionize clinical
diagnostics, improve prognosis, and lead to potentially life-saving medical
treatments. However, it is very likely that genomics and proteomics will
complement each other in establishing the most comprehensive approach
to biomarker discovery and identification of therapeutic targets that
will ultimately find clinical applications in the bedside.
1.3 The analytical challenge: Detecting the low abundance proteins
The presence of a large number of proteins in blood plasma makes human
plasma an excellent material for discovering biomarkers for potential
clinical diagnostics and therapeutics. However, it also represents a tremendous
analytical challenge because the estimated dynamic range of protein concentrations
in human serum may be up to 12 orders of magnitude [83-86]. Albumin, the
most abundant protein, constitutes over half of the plasma proteins and
is present at 30-50 mg/ml concentration. In contrast, most of the potential
biomarkers are secreted into the blood stream at very low copy number
[11,26,86-89], especially in the early onset of diseases [7,8,40,85,88].
For example, the cytokines and the prostate specific antigen (PSA) are
present in the low pg/ml levels. Based on this wide dynamic range, quantitation
of all proteins simultaneously in a single assay is enormously difficult.
The more abundant proteins will certainly mask the detection of the very
low abundance proteins.
The analytical challenge is further increased when we consider that the
very low concentrations of potential biomarker proteins in raw samples
are beyond the detection limit of most analytical instrume
nts . For
example, while mass spectrometry (MS) represents the most sophisticated
and sensitive analytical tool currently available, the current dynamic
range of detection is only about 103 when analyzed in a single
spectrum. Even when MS is combined with an on-line separation such as
HPLC, enhancement of the dynamic range will only be in the 104
to 106 ranges.
Innovations in both sample preparation and protein analysis are therefore
necessary to push the analytical capabilities towards the required 1012
dynamic range. In sample preparation, depletion of the abundant, mostly
high molecular weight proteins is a necessity to enable loading of a much
higher amount of the low copy and/or low molecular weight proteins for
analysis. This strategy has been shown to effect a general enhancement
of the intensity of the low abundance proteins, as discussed in greater
detail in Section 2.
Innovations in protein analysis consist of a large group of multidimensional
separation technologies that are applied orthogonally to fractionate the
proteins and peptides prior to mass spectrometric analysis. These multidimensional
technologies for protein and peptide separation vary in principle and
instrumentation, and include such techniques as electrophoresis (1D-PAGE,
2D-PAGE, capillary, free-flow, etc.), chromatography (reversed-phase,
ion exchange, size exclusion, affinity, etc), ultrafiltration, solvent
precipitation, and other less common fractionation techniques. Traditionally,
each orthogonal separation technique is a separate process step. However,
a significant innovation was developed and termed Multi-Dimensional Protein
Identification Technology (MuDPIT), wh
ere two separation techniques are
achieved in a single column packed with two different separation matrices
. Typically MudPIT uses a strong cation exchange and a reversed phase
resin in single column that can be interfaced directly with the mass spectrometer.
This technology allows a higher level of automation in sample handling,
analysis and data processing.
Different combinations of these multidimensional separation technologies
are used in both top down and bottom up proteomic analysis. In the
top down approach  a mixture of proteins in a sample are separated
into individual spots or fractions using different separation techniques,
and the individual proteins are then analyzed by mass spectrometry to
establish their identity. This is accomplished by determining the mass
of the whole protein ion and then fragmenting the ionized protein to yield
relatively large segments whose masses can then be deconvoluted and compared
against known proteins in protein databases. On the other hand, the bottom
up approach can be performed by using either of two strategies: In one
strategy, samples containing a mixture of different proteins are subjected
to multidimensional separation techniques and the individual protein spots
or fractions are digested with trypsin to yield peptide fragments. With
or without another separation step, the tryptic peptides are analyzed
by mass spectrometry to establish their identify, either based on their
peptide mass fingerprints or by further mass fragmentation to obtain
sequence information. Recently, most bottom up proteomics employ the
shotgun strategy [91,93- 99] where, without prior separation, entire
samples containing a mixture of a large number of different proteins,
such as plasma or serum, are proteolytically digested into peptides. The
peptides in the tryptic digest are then separated by multidimensional
separation techniques and then analyzed by mass spectrometry to establish
the identities of the proteins present in the sample. In other words,
the top down approach utilizes the mass spectral information from the
whole protein for identification, while in the bottom up approach the
mass spectral data of the peptides are used to identify their source proteins.
In both top down and bottom up proteomics, the combination of protein
depletion and multidimensional separation technologies offer significant
enhancement in sensitivity for low abundance proteins by removing the
masking effect of the highly abundant proteins, thereby enabling deeper
penetration into the plasma proteomes.
2. PROTEIN DEPLETION
Since protein depletion is becoming a common choice as the first
dimension in orthogonal protein separation strategies, this subject will
be emphasized in this review. Depletion of plasma proteins can be accomplished
using different strategies, but the final goal is to separate the high
abundance, non-diagnostic proteins from the low abundance proteins.
In the past, the fractions containing the most abundant proteins were
presumed to be diagnostically unimportant and usually not analyzed. However,
recent proteomic analyses indicate that other proteins may be concomitantly
removed during depletion due to non-specific binding to the depleted proteins
[26,70,73,74,100-111]. For example, comparative experiments between non-depleted
serum and serum depleted of the six most abundant proteins have shown
that while depletion significantly increasPage: All 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 Related biology technology :1
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