gq-03
Technical Application Note
Depletion of Abundant Proteins
From Biological Fluids as a Tool for Biomarker Discovery: A Cerebrospinal Fluid Case Study
Analysis of the proteins detected in the FT revealed the presence of
very few peptides assigned to the proteins targeted for depletion.
By contrast, it is obvious that there was a significant gain in the
number of proteins identified in the depleted compared to the
non-depleted CSF sample. Compared to the whole CSF, 190 and 116
low-abundance (i.e. proteins not targeted to be depleted) proteins
were detected in the depleted CSF, representing an enrichment of
61.1%. 96 new proteins were identified, solely in the FT sample and
not in the undepleted sample. In addition, a significant increase
(2.6 times) in the average protein coverage was observed for proteins
identified in the depleted CSF, compared to the undepleted one. This
indicates that not only the depletion of these 12 proteins allowed
the identification of proteins undetected using the whole CSF,
but also that proteomics evidence is stronger for those that were
previously detected.
Conclusion
CSF proteomics holds great promise for the future of biomarkers
discovery. Low-abundance proteins, carrying great diagnostic
potential, are often obscured by the presence of high-abundance
proteins. By combining the depletion of the most abundant proteins
with the fractionation of the FT proteins on a short gradient 1D
SDS-PAGE that can be excised in only 15 bands per lane, (thus
reducing experimental cost), we have enabled the identification of
a significantly higher number of lower-abundance proteins from
CSF. The combination of these technologies offered by the McGill
University and Génome Québec Innovation Centre Proteomics
Platform provides an attractive strategy to the discovery of proteins
holding biological or diagnostic significance at a reasonable cost.
514 398-7211
Sylvie LaBoissière, PhD
[email protected]
514 398-2055
2799_GQ03 (03-12)
Client Management Office: [email protected]
3095_Fiche_GQ03.indd 1-2
References
[1] Bjorhall, K., Miliotis, T. and Davidsson, P. (2005)
Proteomics 5:307–317.
[2] Li, C and Lee, K H. (2004) Analytical Biochemistry
333:381-388.
[3] ProteomeLab IgY-12 High Capacity Proteome
Partitioning Kits, Standard Operating Protocol,
Beckman Coulter, PN A24341 AC, February 2007.
[4] Huang, L., Harvie, G., Feitelson, J.S., Gramatikoff,
K., Herold, D. A., Allen, D.L., Amunngama, R., Hagler,
R.A., Pisano, M.R., Zhang, W. and Xiangming, F. (2005)
Proteomics 5: 3314-3328.
[5] Kearney, R.E., Blondeau, F., McPherson, P., Bell, A.,
Servant, F., Drapeau, M., De Grandpre, S, Bergeron,
J. (2005) In: 27th Annual International Conference of the IEEE
Engineering in Medicine and Biology Society, Shanghai.
pp: 1-4.
[6] Gilchrist, A., Au, C.E., Hiding, J., Bell, A.W., Fernandez-Rodriguez,
J., Lesimple, S., Nagaya, H., Roy, L., Gosline, S.J.C., Hallett, M.,
Paiement, J., Kearney, R.E., Nilsson, T. and Bergeron, J.J.M.
(2006) Cell, 127: 1265-1281.
Depletion of Abundant Proteins
From Biological Fluids as a Tool for Biomarker Discovery: A Cerebrospinal Fluid Case Study
Introduction
The identification of protein biomarkers from biological fluids is
important to the study of many human diseases, where a measurable
change in protein concentration or structural composition can
be used to monitor disease state. Biological fluids such as serum,
plasma and cerebrospinal fluid (CSF) provide an incredible potential
source of biomarkers. Human plasma and serum are a rich source
of most of the major categories of proteins in the human body and
provide excellent biological materials for disease diagnostics. CSF
is in direct contact with the brain and the central nervous system
and represents an important medium for neurological disorders.
Approximately half of the total protein mass in plasma and serum
is albumin, and combined with 10 additional proteins it represents
85‑90% of total plasma protein mass [1]. Moreover many serum
proteins, such albumin, are also present in CSF in which they represent
60‑80% of the entire protein content [2]. The large dynamic range of
proteins within these biological fluids (over 10 orders of magnitude)
is a serious challenge for new biomarker discovery. Many potential
biomarker proteins are likely to be present at far lower concentrations
and are therefore masked by the high abundance of a few very
common proteins. This problem can be overcome by depleting
over-represented proteins to go deeper into the proteome in order
to identify putative biomarkers of disease.
The McGill University and Génome Québec Innovation Centre
Proteomics Platform developed a strategy to deplete the most
abundant proteins of CSF to identify lower abundance proteins.
This was done as part of a Huntingdon Disease biomarker study,
sponsored by the HighQ Foundation, and in which 6 independent
labs participated. The rationale was that the depletion of abundant
proteins would allow the detection of proteins that co-migrate with
and are masked by the highly abundant proteins. Furthermore the
removal of the most abundant proteins increases the loading capacity
of proteins present at lower concentrations on 1D SDS-PAGE and
greatly enhances their detection and identification by MS analysis.
Our depletion approach uses a recent technology: the IgY-12 High
Capacity LC2 Proteome Partitioning Kit [3] from Beckman Coulter
(Fullerton, CA, cat# A24346) combined with the HPLC system of
the Proteome Lab PF 2D from Beckman Coulter. Based on affinity
columns using avian antibody (IgY)-antigen interactions, the IgY
LC2 column is designed to remove twelve highly abundant proteins
from serum/plasma in a single step. One of the advantages of using
avian IgY antibodies is that they have high avidity and less crossreactivity with heterologous human proteins [4]. The IgY column
consists of immobilized ligands which are polyclonal antibodies
to human serum albumin (HAS), IgG, fibrinogen, transferrin, IgA,
IgM, haptoglobin, alpha-1-antitrypsin, alpha-1-acid glycoprotein
(orosomucoid), alpha-2-macroglobulin and high-density lipoprotein
(HDL) (Apo A-I and Apo A-II).
The affinity-purified anti-IgY antibodies are covalently conjugated
to microbeads.
Methods
Depletion of Highly Abundant Proteins
Twelve high-abundance proteins were depleted from a commercially
available human CSF sample (Bioreclamation Inc., Hicksville, NY).
Briefly, 500 µl of sample (~ 200 µg) was diluted 1: 2 and filtered to
remove particulates prior to depletion. The sample was manually
injected onto the IgY-12 High Capacity LC2 column and subjected
to depletion according to the supplier protocol. Flow-Through (FT)
and Bound/Eluted Fractions (EF) were collected, neutralized and
concentrated using Amicon Ultra-4 centrifugal filter units. Protein
concentration of FT and EF was determined using Micro BCA Protein
Assay Kit (Pierce). This procedure is optimized for use with very low
amounts of protein. While protein concentration of undepleted CSF
was determined using the 2-D Quant Kit (GE Healthcare) which is
resistant to interference from components such as salts, glycoproteins
and polysaccharides that were found to be present in whole CSF.
1D SDS-PAGE and Automated Band Excision
Proteins present in the FT and EF were concentrated using a
SpeedVac apparatus and 30 µg of each fraction as well as 30 µg of
undepleted CSF sample were resolved on a 2.4 cm 1D SDS-PAGE
with a 7-15% acrylamide gradient. Proteins on the gel were stained
using Coomassie Blue G (Sigma-Aldrich).
Line Roy, Nathalie Hamel, Daniel Boismenu et Sylvie LaBoissière.
McGill University and Génome Québec Innovation Centre, Montréal, QC
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McGill University and Génome Québec Innovation Centre
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www.genomequebec.mcgill.ca
740 Docteur Penfield Ave., Montréal, QC Canada H3A 0G1
T 514 398-7211 • [email protected]
12-03-19 4:14 PM
Depletion of Abundant Proteins
Depletion of Abundant Proteins
From Biological Fluids as a Tool for Biomarker Discovery: A Cerebrospinal Fluid Case Study
From Biological Fluids as a Tool for Biomarker Discovery: A Cerebrospinal Fluid Case Study
Methods (cont’d)
Results
Each lane was subjected to automated band excision, to generate 15
bands per lane. The Protein Picking Workstation ProXCISION (Perkin
Elmer) was set to excise 5 to 7 pieces per band, depending on the
width of the lane.
In-gel Tryptic Digestion
Following transfer of the gel pieces to a 96-well tray, proteins
were destained, reduced, cysteine-alkylated and in-gel digested
in an automated MassPrep Workstation (Micromass). In-gel tryptic
digestion was carried out with Sequencing Grade Modified Trypsin
(Promega) at a final concentration of 6 ng/µl and allowed to incubate
at 37 °C for 4.5 hours. Peptides were then extracted by the addition
of increasing acetonitrile concentration to a final extract of 0.54%
formic acid, 15.9% acetonitrile in 16 mM ammonium bicarbonate.
LC-MS/MS Analysis and Bioinformatics Data Processing
Injections of digested extracts were performed using an Agilent
series 1100 Nanopump. The reverse phase separation was performed
on a PicoFrit column (New Objective) filled with C18 using a
60-min acetonitrile gradient. The separation system was coupled to
a Waters Micromass QTOF Micro mass spectrometer set to perform
tandem MS. MS/MS raw data were manipulated for the generation
of peaklists by employing the Distiller version 2.1.1.0 software with
peak picking parameters set at 30 for Signal to Noise Ratio (SNR)
and at 0.6 for Correlation Threshold (CT). The peaklisted data was
searched against the Universal Protein Resource (UniProt) database
(October 31, 2007) employing Mascot version 2.1.4.04. The search
was limited to the Homo sapiens taxonomy.
Mascot results (based on spectra assigned to tryptic peptide sequences
at the 95% confidence level) generated peptide identifications which
were then linked to the proteins to produce an initial list of protein
identifications. Because this list was quite redundant an in-house
grouping algorithm [5] was developed in order to generate a minimal
list of proteins needed to explain the peptides observed. This minimal
list of proteins is summarized on a SubGroup Count Report. Since
the redundant peptide counting approach is commonly used to
infer the relative amounts of proteins across different samples [6],
the Subgroup Count Report can be used to identify differences in
protein abundance among the different samples by comparing the
number of distinct prorated queries observed for each protein group
across different samples (NQPCT).
The migration profiles of the undepleted CSF and the EF were
very similar and clearly distinct from the FT profile (see Figure 3).
This suggests that depleting the most prominent proteins with
the IgY-12 LC2 column revealed the presence of lower abundance
proteins that were previously undetected.
Figure 2. Chromatographic profile of CSF onto the ProteomeLab IgY‑12
LC2 depletion column.
Targeted abundant proteins were captured by the IgY‑12 LC2 column, while the
remaining proteins (low-abundant proteins) flowed through the column and
were collected from the first protein peak. The second protein peak represents
the EF that was then eluted. Note that the A280 absorbance of the FT peak cannot
be directly compared to the EF peak since the flow rate changes during the run
(from 0.2 ml/min to 1 ml/min) between FT and EF peaks.
Table 1 − Protein recovery after depletion of whole CSF sample.
The recovery of proteins in the FT was determined to be ~20% while
more than 65% of the total protein content was depleted from the
starting CSF (Table 1). This indicates that the loading capacity on
1D gel has been increased by 5-fold, compared to an undepleted
CSF sample.
Figure 1. Overview of the workflow developed at the Proteomics Platform for the study of the human CSF proteome.
The removal of highly abundant proteins using the IgY-12 High Capacity LC2 column is followed by protein separation on 1D SDS-PAGE. Each lane
(whole CSF, FT and EF) is divided into 15 bands which are then individually in-gel digested with trypsin. Peptides are analyzed by mass spectrometry
and proteins identified through our bioinformatics pipeline.
3095_Fiche_GQ03.indd 3-4
Figure 3. CSF Protein Fractionation on 1D SDS-PAGE.
Thirty µg of whole CSF sample, FT and EF collected after depletion on an IgY-12
LC2 column, were resolved on a 2.4 cm 1D SDS‑PAGE with a 7-15% acrylamide
gradient. Each lane was excised in 15 bands.
Figure 4. Overview of the proteins identified by LC-MS/MS.
Peptide extracts from each digested sample were individually injected into the
mass spectrometer and protein identification carried out using Mascot. The
subgroup report generated displays the relative proportion of each protein within
each sample. This was used to create the pie charts shown above.
The twelve most abundant proteins of serum/plasma that were
targeted for depletion with the IgY-LC12 column represent roughly 60
to 80% of the total protein mass of CSF. In our study these represented
58.2% of the total CSF protein content (Figure 4).
As expected, the great majority of the EF contained proteins that
were targeted for depletion; 56.6% and 27.5% of the peptides
identified correspond to albumin and to the eleven other proteins,
respectively. A small proportion (15.9%) of really abundant proteins of
CSF, such as transthyretin, prostaglandin-H2 D-isomerase precursor,
complement component 3, cystatin-C precursor were found to bind
non-specifically to the column. However, three new proteins were
found exclusively in the EF but the proteomics evidence for them
was very weak.
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