Journal of the Association for Laboratory Automation

Journal of the Association for Laboratory
Automation
http://jla.sagepub.com/
Semi-Automated Sample Preparation for Plasma Proteomics
Keith Ho, Qing Xiao, Estelle M. Fach, Jeffrey D. Hulmes, Deidra Bethea, Gregory J. Opiteck, Joseph Y. Lu, Paul S. Kayne
and Stanley A. Hefta
Journal of Laboratory Automation 2004 9: 238
DOI: 10.1016/j.jala.2004.03.003
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Original Report
Semi-Automated Sample
Preparation for Plasma Proteomics
Keith Ho,1* Qing Xiao,1 Estelle M. Fach,1 Jeffrey D. Hulmes,1 Deidra Bethea,1
Gregory J. Opiteck,1 Joseph Y. Lu,2 Paul S. Kayne,2 and Stanley A. Hefta1
1
Bristol-Myers Squibb, Clinical Discovery, Clinical Discovery Technologies,
Hopewell, NJ; 2Bristol-Myers Squibb, Applied Biotechnology,
Applied Genomics, Hopewell, NJ
Keywords:
proteomics,
human plasma,
gel-free,
sample preparation,
biomaker discovery,
LC/MS
he discovery of new biomarkers will be an essential
step to enhance our ability to better diagnose and
treat human disease. The proteomics research
community has recently increased its use of human blood
(plasma/serum) as a sample source for these discoveries.
However, while blood is fairly non-invasive and readily
available as a specimen, it is not easily analyzed by liquid
chromatography (LC)/mass spectrometry (MS), because
of its complexity. Therefore, sample preparation is
a crucial step prior to the analysis of blood. This sample
preparation must also be standardized in order to gain the
most information from these valuable samples and to
ensure reproducibility. We have designed a semiautomated and highly parallel procedure for the
preparation of human plasma samples. Our process takes
the samples through eight successive steps before analysis
by LC/MS: (1) receipt, (2) reformatting, (3) filtration, (4)
depletion, (5) concentration determination and
normalization, (6) digestion, (7) extraction, and (8)
randomization, triplication, and lyophilization. These steps
utilize a number of different liquid handlers and liquid
chromatography (LC) systems. This process enhances our
ability to discover new biomarkers from human plasma.
( JALA 2004;9:238–49)
T
*Correspondence: Keith Ho, Bristol-Myers Squibb, P.O. Box 5400,
Princeton, NJ 08534-5400; Phone: +1.609.818.5339; Fax:
+1.609.818.6057; E-mail: keith.ho@bms.com
1535-5535/$30.00
Copyright
c
2004 by The Association for Laboratory Automation
doi:10.1016/j.jala.2004.03.003
238 JALA
August 2004
INTRODUCTION/BACKGROUND
Biomarker discovery has become a driving force in
proteomics during the last few years.1 These are
biological indicators that correlate with disease,
safety, or the treatment paradigm.2 The ability to
find these biological indicators is a high priority in the
biotech and pharmaceutical industries. It is thought
that monitoring the effects of drugs on patients
through changes in the level of biomarkers will
become routine and will be required for the regulatory approval process.3 Therefore, a biomarker
discovery project plan has become one of the crucial
determining factors of new drug candidates.
In a typical clinical trial (Phases I and II), the
average number of patients enrolled is between 50
and 250. In addition to this number of patients, the
presence of various time points and doses can
expand the sample set to between 250 and 1250.
Handling these samples in a standard ‘‘research
grade’’ proteomics laboratory is not an easy task. A
uniform handling process for these samples is
required for comparative analysis. Proteins are also
particularly challenging analytes to monitor during
clinical trials compared to small drug molecules, in
part because they are more easily degraded, precipitated and adsorbed.4
Recently, most biomarker discovery has been
moving toward the identification and the analysis
of human plasma proteins.5,6 There are several
advantages and disadvantages to using human
plasma from clinical trials patients for biomarker
discovery experiments. Plasma is readily available
and its collection is considerably less invasive
when compared with procedures such as biopsies.
Furthermore, because plasma has high protein
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concentrations, it is a rich sample source. However, the two
most abundant proteins, human serum albumin (HSA) and
Immunoglobulin G (IgG),7 together account for approximately 73% of the total protein concentration in human
plasma8 making the discovery of lower abundance proteins
difficult.9 Therefore, by depleting HSA and IgG, one would
anticipate being able to detect low abundance proteins more
easily and, in turn, discover useful human plasma protein
biomarkers.
The traditional proteomics approach has been to use twodimensional polyacrylamide gel electrophoresis (2D-PAGE)
for the detection of up and down regulated proteins,
followed by mass spectrometry (MS) for their targeted
identification.10 However, the 2D-PAGE process is laborintensive and difficult to reproduce across hundreds of
samples.11,12 2D-PAGE is also limited in its dynamic range,
sensitivity and speed.13
As an alternative to 2D-PAGE, we have developed a gelfree LC/MS technology for the analysis of human plasmabased proteins.14 To ensure the reproducibility of the LC/MS
data and the integrity of the LC/MS system, the plasma
samples must be clean and easy to analyze before their
introduction to the LC/MS instrument. Therefore, this gelfree LC/MS technology relies on an 8-step sample preparation procedure in which a plasma sample is passed through
sample clean up and volume reduction prior to LC/MS
analysis. The 8 steps to this sample preparation process are
as follows: (1) receipt, (2) reformatting, (3) filtration, (4)
depletion, (5) concentration determination and normalization, (6) digestion, (7) extraction, (8) randomization,
triplication and lyophilization.
MATERIALS AND INSTRUMENTATION
Receipt
A sample tracking system called SampleTracker, which
was developed internally, is used for the receipt and input of
samples into the freezer. A ÿ70 C freezer (Ultima II, Revco,
Asheville, NC, USA) is used for sample storage.
Reformatting
Cryovials (P/N 5000_0050, Nalgene Company, Rochester,
NY, USA) are 1 ml in capacity. The liquid handler (Model
215), the custom-made cryovial rack (Rack 708), and the
custom-made refrigerated racks (Rack 714) are all from the
same manufacturer (Gilson Incorporated, Middleton, MA,
USA). The 96-well plates (P/N 40002-020, VWR, West
Chester, PA, USA) have a capacity of 2 ml per well.
Filtration
The filter plates are 10–12 lm (P/N 7700-7217) and 0.25
lm in porosity (P/N 7700-7206) and are both purchased
from the same manufacturer (Whatman, Clifton, NJ, USA).
The vacuum manifold (P/N 610, 3M, St. Paul, MN, USA)
accepts both filter plates and solid phase extraction plates.
Depletion
HSA and IgG are depleted by affinity chromatography
(HiTrap Blue HP, P/N 17-0412-01 and HiTrap Protein G HP
P/N 07-0405-01, Amersham, Piscataway, NJ, USA). An
analytical HPLC system is used (Model 1100, Agilent, Palo
Alto, CA, USA). Signals are detected and monitored at 280
nm. The autosampler (Model 215, Gilson) is purchased as
part of the HPLC system. Mobile phase A, 100 mM Tris,
10% glycerol, pH 8.0 and elution buffer B, 100 mM Tris,
10% glycerol, 500 mM NaCl, pH 2.5 are made in-house. All
the steps are controlled by software (ChemStation, CCMode,
Agilent).
Concentration, Determination, and Normalization
A 4-tip liquid handler (MultiPROBE II HT Expanded
System, P/N AMP8E00, Perkin Elmer, Boston, MA, USA)
using 1.0 ml syringes is used for sample normalization. The
dilution buffer for this step is mobile phase A (100 mM Tris
buffer, 10% glycerol, pH 8) from the previous step.
Digestion
Digestion buffers are dispensed with a 96-channel pipettor
(EDR-384S/96S, Union City, CA, USA). Samples are mixed
and incubated with a benchtop shaker (P/N 4628, Lab-Line,
Barnstead International, Dubuque, Iowa, USA). A detergent
(RapidGest SF, P/N 186002118, Waters Technologies
Corporation, Millford, MA, USA) is used to denature
proteins. Dithiothreitol (P/N D-9163), is used as a reducing
agent, and iodoacetamide (P/N I-1149), as the alkylating
agent, are both purchased from the same manufacturer
(Sigma-Aldrich, St. Louis, MA, USA). Trypsin (P/N V511X,
Promega, Madison, WI, USA) is used for digestion.
Extraction
A solid phase extraction plate (P/N 6315, 3M) and
vacuum manifold (3M) is used to desalt and concentrate
the sample. A 4-tip liquid handler (MultiPROBE II HT
Expanded System, Perkin Elmer) is used for sample
handling. Washing buffer, 0.1% TFA (Trifluoroacetic acid)
and elution buffer, 90% acetonitrile in 0.1% TFA, are both
made in-house from HPLC grade reagents.
Randomization, Triplication, and Lyophilization
A small liquid handler (Model 215) and the custom-made
refrigerated racks (Rack 714) are both purchased from the
same manufacturer (Gilson). The samples are replicated into
500 ll volume 2D bar-coded vials (CAT# MTMP0301,
Micronics, Lelystad, The Netherlands). A flatbed scanner
(P/N 7400C, Hewlett-Packard, Palo Alto, CA, USA) is used
for reading the 2D barcodes.15 Samples are lyophilized in
a unit (P/N AES2010, Thermo Savant, Holbrook, NY, USA)
that is capable of holding 496-well plates.
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RESULTS AND DISCUSSION
Receipt
Human plasma samples are collected as described
elsewhere16 at various clinical trial sites. The samples are
shipped on dry-ice and delivered at our central laboratory by
overnight courier in pre-defined bar-coded cryovials with
necessary documentation. Each cryovial contains 1.0 ml of
human plasma. The barcodes are in alpha numerical format
and are used randomly in the trial clinics. Each barcode is
relayed to the central laboratory database, along with the
trial number, sample donor, demographics, disease type,
and/or treatment information (dose, time point).
Once requisitioned to our proteomics laboratory, the
samples are traced into our laboratory sample banking
system by our in-house web-based tracking system, called
SampleTracker. SampleTracker allows users to upload
sample information, which is provided in hard-copy by the
central laboratory, to the database by entering the information provided in a spreadsheet (Fig. 1). SampleTracker
also has a function for users to ‘‘batch load’’ samples to the
database. For example, if 4 different samples arrive at the
laboratory, a user can enter the information for all 4 samples
into the spreadsheet template simultaneously. The spreadsheet template is highlighted with all of the required fields,
such as ‘‘Sample Provider,’’ ‘‘Notebook #,’’ ‘‘Project,’’
‘‘Sample Receipt Date,’’ ‘‘Sample Location,’’ ‘‘Sample
Type,’’ ‘‘Disease Status.’’ These required fields provide the
minimum information necessary for SampleTracker to
generate the unique identifiers for each sample.
Samples are transferred and stored in a ÿ70 C freezer upon
receipt, and users are required to enter the sample location
within the storage freezer. Sample location is a complex
numeric field of shelves, decks, levels of deck, depths of decks,
Figure 1. A screenshot of the in-house developed sample tracking system (SampleTracker). Users can use this system as a tool to browse
samples in the sample bank and add samples to the database after sample receipts, all of which are done in the intranet setting.
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Figure 2. A Revco ÿ70 C freezer with freezer racks. Each slot
inside the freezer rack has a unique identifier which is assigned by
the level of shelves, number of decks, level of decks and depth of
decks. This unique identifier is also required by the SampleTracker
for tracking the sample location.
and location of each 1 ml sample in the freezer box (Fig. 2). A
sample placed in the second shelf from the top, third deck from
the left, first level of the deck, second deepest deck from the
front, and location number 48 in the freezer box would be
recorded as location 2-3-1-2-48 in SampleTracker.
Additional sample information can be entered into
SampleTracker. Patient demographics, such as gender, race,
age, can be also entered into the spreadsheet template.
Demographic information is sometimes blocked/blinded for
statistical and patient protection purposes, so these fields are
not required in SampleTracker. Once each sample is
uploaded into the SampleTracker database without error,
a unique SampleTracker ID is generated and linked to the
clinical trial external ID. If an error occurred, such as sample
locations, SampleTracker ID would not be generated and an
error page will prompt user to re-enter the sample information. Error monitoring is automatically done by
a system administrator or WebMaster of SampleTracker
on a monthly basis. Users also have an opportunity to review
the entered sample information on a review page before
submitting to the database to ensure the accuracy of the
information. When the samples are needed for analysis, they
are traced out and deleted by the user.
Reformatting
The samples are reformatted from cryovials to 96-well
plates for ease of handling and more reproducible processing.
Once the samples are traced out from SampleTracker, they
are immediately thawed on wet ice for 1 hour, mixed by
vortexing and centrifuged at 12,000g for 10 minutes to
remove large particulates. The cryovials are then manually
uncapped and placed into a custom-made rack. In addition,
a pre-defined number of commercially available pooled
plasma samples (controls) are placed in the same rack for
tracking the accuracies of pipetting and liquid chromatography runs in the later steps. The samples and the controls
are transferred to the 96-well-plate format by the liquid
handler with clot detector and liquid sensing activated. The
plates are held in a custom-made refrigerated rack to prevent
degradation of the sample. Each sample/cryovial is divided
into two sets of 96-well plates. Therefore, the two 96-well
plates, with 450 ll of sample per well, are generated, forming
a primary plate and a secondary plate. The primary plate is
a 96-well 10–12 lm filter plate which is then carried forward
for the remaining steps of the sample preparation protocol.
The secondary plate is a 96-well deepwell plate which is
returned to the ÿ70 C freezer for future use, such as ELISA,
Western blots, protein identification, etc. The liquid handler
draws 960 ll of sample from each cryovial. The primary plate
and the secondary plate both receive 450 ll of plasma. The
remaining sample, which is 60 ll, is discarded during the
needle wash step. The time required for each sample is about
30 seconds, which includes time for needle washes. Therefore, the reformatting of 96 samples from cryovials to two
separate 96-well plates requires approximately 48 minutes.
Filtration
Samples from the primary plate are filtered immediately
after the reformatting step. The size of particulates varies
greatly in plasma, so some smaller debris still persists in the
samples even after the centrifugation to remove the larger
particulates,. During the freeze/thaw process, plasma proteins can form aggregates that could plug the auto-injector of
the HPLC system, the HPLC columns, and other automated
liquid-transfer systems.17. Therefore, the samples are filtered
after the reformatting of the samples from cryovials to 96well plates. This step is critical to maintain the integrity of
the HPLC system, and the reproducibility of the data.
During the filtration process, a 1:1 mapping is maintained for
the well positions on the 96-well plates to prevent any mix-up
of samples. Since this process should be as high throughput
as possible, traditional ‘‘spin’’ filters for individual samples
are not a viable option. The 96-well format minimizes the
time required and the errors propagated during the sample
preparation process.
A deepwell (2 ml) 10–12 lm high throughput 96-well filter
plate is used first to prevent the clogging of the 0.45 lm filter
frits in the HPLC system. Vacuum at ÿ30 inch Hg is used to
pull samples through the filter. The resulting filtered samples
are then pipetted into a deepwell (2 ml) 0.45 lm high
throughput 96-well filter plate by a hand-held 8-channel
automatic pipettor. Again, the same vacuum manifold is
used to pull samples through the filter at ÿ30 in. Hg. After
collecting the samples into a new 96-well deepwell plate from
this step, they are ready for human serum albumin (HSA)
and immunoglobulin G (IgG) depletion.
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Depletion
HSA and IgG are the two most abundant proteins in
human plasma.8 HSA accounts for about 55% and IgG
accounts for about 18% of the total protein. Therefore,
together, the HSA and IgG represent approximately 73% of
the total plasma protein profile and removal of these proteins
is thought to be important to discover lower abundance
proteins. When low abundance proteins are present with high
abundance proteins, the low abundance proteins tend to go
undetected because of ion suppression effects, limited
instrumental dynamic range, and chemical noise interference.18 Theoretically, when a depleted sample is loaded onto
LC/MS, the lower abundance proteins gain a maximum
3.7-fold increase over a non-depleted sample (Fig. 3). There
is evidence that the removal of albumin and IgG may remove
other albumin- and IgG-bound proteins as well. However,
Figure 3. A graphical illustration of the benefit of HSA and IgG depletion. The signal to noise ratio of lower abundance proteins, such as
PSA (prostate serum antigen), increases a maximum of 3.7-fold after depletion.
242 JALA
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the increase in sensitivity of 3.7-fold outweighs the potential
loss of other proteins. The increased signal to noise can make
it easier to detect lower abundance proteins. Similarly, the
peptides are easier to integrate than the non-depleted samples
because of the increased signal to noise ratios.
There is a variety of depletion methods available. The
price ranges from very expensive, such as antibody-based
Sepharose,19 to cheaper method, such as Cibacron Blue
F3GA Sepharose and Protein G Sepharose. Sepharosecoupled antibodies are used for affinity chromatography
because of their perceived higher specificity.20 However, the
antibody-based purification approach is expensive. For a 3.7fold increase in signal to noise level, a research facility would
spend an estimated $3,000 in materials per sample (Fig. 4a).
Also, there is a reduction of binding capacity of the
antibody-coupled Sepharose over time after several
Figure 4. (A) The cost of using antibody for the depletion of HSA and IgG per sample is illustrated. Each milliliter of Sepharose requires
a minimum of 5–10 milligram of antibody. However, the efficiency of 1 ml of antibody coupled sepharose only has a capacity of 2 mg of
HSA. Therefore, for a 200 ll of plasma sample, 4.4 ml of sepharose is needed for a total cost of $3,000 per sample. (B) The cost of using
Cibacron blue and Protein G for the depletion of HSA and IgG per sample is illustrated. The efficiency of 1 ml of Cibacron Blue and Protein
G Sepharose has a capacity of 20 mg of HSA and 25 mg of IgG. Therefore, for a 200 ll of plasma sample, only 1 ml of each Sepharose is
needed for a total cost of $95 per sample.
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washings, elutions, and regeneration. Therefore, the cost of
using antibody-coupled Sepharose for the depletion of high
abundant proteins would increase. In addition, large lot-tolot variations of antibodies and low binding capacity are also
disadvantageous. A typical anti-HSA antibody coupled
Sepharose has a capacity of 2 mg/ml. This results in a large
dilution of the samples.
The combination of Cibacron Blue and Protein G presents
an alternative method for the depletion of HSA and IgG.
They are both commercially available as pre-packed HPLC
columns. Therefore, methods which use these materials can
be easily scaled-up and automated on a HPLC system.
Cibacron Blue and Protein G are widely accepted in the
industry21–23 for their inexpensive material price, durability
and reproducibility. The combination of Cibacron Blue and
Protein G columns can deplete more than 100200 ll
samples of plasma. Each Cibacron Blue column has a binding
capacity of 20 mg of human albumin per 1 ml of gel; a Protein
G column has a binding capacity of 25 mg of IgG per 1 ml of
gel. Depleting human plasma by this method is more than 30
times less expensive than using the traditional antibodycoupled Sepharose method (Fig. 4b) and much less
susceptible to lot-to-lot variations. Furthermore, samples
are diluted only 22 fold in Cibacron Blue and Protein G
depletion, instead of 55-fold in antibody-coupled Sepharose
depletion. For all of these reasons, we opt for using the
Cibacron Blue and Protein G method.
The depletion step is straightforward. Cibacron Blue and
Protein G columns are placed in-line of an HPLC system.
The 96-well plate from the previous filtration step is placed in
a custom refrigerated rack on a liquid handler. The
temperature of the rack is set to 40 C to prevent evaporation
of buffer and degradation of plasma proteins. The flow rate
on the HPLC is set to 0.5 ml/min during the binding step and
1.0 ml/min during the washing and elution steps. To reduce
the non-specific and protein-protein binding of other
proteins in the plasma to the affinity columns, 10% glycerol
and 100 mM Tris are added to the mobile phase. The
depleted samples are collected into a new deepwell 96-well
plate with 1:1 well mapping. The combined effect of high salt
and low pH in the elution buffer displaces the HSA and IgG
through changes in their conformation. Columns are
regenerated and equilibrated at the end of each 30-minute
run by a 10-minute flush of 100% mobile phase A. A one
dimensional gel shows the efficacy of the depletion columns
(Fig. 5). The time required is 40 minutes per sample;
therefore, a run of 96 samples takes 64 hours or 2.7 days.
Normalization
To ensure the efficacy of the tryptic digestion of the
proteins for each sample on the 96-well plate, all samples
must have the same total protein and sample volume. If the
concentrations of the samples vary, the digestion efficiency
might vary proportionally. As a result, samples would not be
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Figure 5. This one-dimensional gel shows the efficiency of the
depletion process. Clearly, HSA and IgG (both heavy and light
chains) are depleted. Elution step shows the bound materials.
comparable across a plate. Therefore, each sample must be
normalized to the same amount of total protein in the same
total volume.
There are three steps in this normalization process. First,
the concentrations of the depleted samples are each obtained.
The Area under the curves (AUCs) are obtained from the
chromatograms of each depletion based on the 280 nm
absorbance peak of the proteins. Second, the values of the
AUCs from the first peak/depleted peak are calculated by
the HPLC software system (built-in auto-integration). Third,
the value of the AUC from the depleted peak is plotted
against a standard curve previously generated with serial
dilutions of a pooled plasma and the concentration of the
peak is calculated.
Samples are next normalized by a liquid handler. The
protein concentration data are input to the liquid handler
system software via an EXCEL macro. Each probe of the
liquid handler draws the appropriate volumes directed by the
macro values, so that each new well will have a total load of
1.5 mg total protein. Each sample is then mixed with various
volumes of dilution buffer and dispensed into a new 96deepwell plate in order to achieve a final well volume of 1 ml.
Thus, the final concentration of each sample is 1.5 mg/ml.
The normalization step reduces the variation in concentration from sample to sample. As a result of normalization,
the coefficients of variation for total protein concentration in
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Figure 6. (A) Protein concentrations before and after Normalization are plotted on a graph for 27 different depleted samples. CV before
normalization is larger than 6.781%. CV after normalization is less than 2.654%. (B) A table listing the values of average, standard deviation
and coefficient of variation for the data before and after normalization.
each well drop from 6.781% to 2.654% (Fig. 6a and b) as
measured by flow injection assay. The time required for normalization is 40 seconds per sample. Since the liquid handling system can manipulate four samples simultaneously, the
normalization of 96 samples requires 16 minutes.
Digestion
Peptide samples, when lyophilized, are more stable for
both short and long term storage than intact protein samples.
Peptides are also easier to separate and ionize. Further,
peptide spectra do not develop envelops of peaks, such as the
ones found in intact protein spectra. Therefore, the plasma
proteins are proteolyzed prior to LC/MS analysis. A 96channel pipettor is used to ensure the consistency of the
reagents added to each well for the digestion process. The
pipettor accommodates 296-deepwell plates and it provides
a 10–300 ll module to accurately aspirate and dispense the
buffers. Moreover, independent disposable tips are used to
prevent cross contamination between experiments. The
plates retain their 1:1 well mapping from the previous
processing steps.
The standard procedure is to denature, reduce, alkylate
and digest the proteins. A mild detergent (RapiGest SF) is
used to solublize and unfold the plasma proteins. The
detergent slightly dilutes the volume of each sample. For
a standard 1 ml of normalized sample, 100 ll of a stock
solution of 10% (w/v) detergent is used, which give a final
detergent concentration of 1%. The reduction of the disulfide
bonds is performed by adding 20 ll of 500 mM of
dithiothreitol to each well and mixing the contents by
pipetting five times into the same well. The plate is then
incubated at 50 C for 30 minutes with gentle shaking. The
alkylating step is performed by adding 40 ll of 500 mM of
iodoacetamide to each well and mixing the contents by
pipetting five times into the same well. The plate is then
incubated at 25 C for 10 minutes with gentle shaking. The
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August 2004 245
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protein is next digested with sequencing grade trypsin by
adding 28.30 ll of trypsin (0.53 mg/ml) to each well, so that
the enzyme to substrate ratio is 1:100. The plate is incubated
at 37 C for 16 hours with gentle shaking. After digestion, the
pipettor adds 60 ll of 500 mM HCl into each well to stop the
reaction. The resulting plate is either taken to solid phase
extraction (SPE) or to a ÿ80 C freezer for later processing.
This part of the process requires 30 seconds for each
pipetting step plus 16 hours of incubation time, for a total
of 18 hours per plate.
Extraction
The digested plasma samples must be desalted and
concentrated prior to LC/MS analysis. This ensures LC/
MS reproducibility and allows for smaller injection volumes,
which increases throughput. A C18-based solid phase
extraction plate in a 96-well format is used to reduce the
sample handling error and to maintain the 1:1 well mapping.
The extraction step uses the same instrumentation as in
the previous steps. Samples and buffers are both pipetted
into the SPE plate by a 4-channel liquid handler. The plate is
used with the same vacuum manifold as in the previously
described sample filtration step. The resulting extracted
products maintain 1:1 well mapping.
This SPE process requires a series of four steps and each is
performed by a liquid handler. First, the SPE plate is washed
with 250 ll of 90% acetonitrile (ACN) in 0.1% TFA, then
equilibrated with 250 ll 0.1% TFA. Second, the samples are
diluted 1:1 with 0.1% TFA and are loaded onto the 96-well
SPE plate using the liquid handler. The total volume of
sample loaded onto the SPE plate is 2 ml of the 0.60 mg/ml
sample. Third, following binding of peptides to the
stationary phase, the wells are washed 2500 ll using
0.1% TFA. Fourth, the samples are eluted 2300 ll using
90% ACN in 0.1% TFA. This buffer is volatile, mass
spectrometer compatible, and easily evaporated by lyophilization. The final elution volume is 600 ll and the final
concentration is 0.65 mg/ml after elution, which was
determined by flow injection assay (data not shown).
Analysis by RPLC/UV shows an average recovery of 50%
(by area) in the SPE process and the product profile is
unchanged (Fig. 7a and b). The quantity of un-retained
species, such as salts, buffers, detergent fragments), are
reduced. The processing time for an entire 96-well plate is 30
minutes.
Randomization, Triplication, and Lyophilization
A randomization and triplication step is included before
LC/MS (Fig. 8) to account for any statistical errors during
LC/MS data acquisition. This serves to blind operators from
the identification of the samples in the LC/MS facility and
eliminates ‘‘sample sequence’’ errors, such as falling sensitivity as a function of mass spectrometer fouling. Lyophilization also promotes more stable sample storage.
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Figure 7. (A) RPLC-UV (C18 column) of the tryptic digest
samples before SPE. Four different concentrations are loaded and
the corresponding chromatograms are overlaid. Note the first
major peak is the salt front. (B) RPLC-UV (C18 column) separation
of the tryptic digested samples after SPE. The same 4 overlaid
chromatograms as in (A) are shown. Note the salt front from the
starting material is removed and washed away by the SPE matrix.
Also, the number of peaks between the starting material and the
SPE samples are similar. The estimated concentration before and
after the SPE step is done by the addition of the AUC’s (area under
curves) of all the peaks in the chromatogram. The estimated
material lost during this SPE step is 50%.
Randomization and triplication are performed computationally by a spreadsheet macro and mechanically by a liquid
handler. The macro is written to randomize the well numbers
and this information is exported to the liquid handler
software. By following this sample table, the liquid handler
aspirates 500 ll of sample and dispenses 150 ll into each of
three randomized locations. The receiving plates contain
factory pre-labeled 500 ll 2D bar-coded vials. Custom
refrigerated racks are used to minimize the evaporation of
the samples, which are in 90% acetonitrile buffer from the
SPE steps. The plates with the 2D bar-coded vials are
scanned as described elsewhere.24 Locations of the randomized samples are recorded and saved in a laboratory
information management system.
The randomized samples are lyophilized immediately
following randomization. This prevents inconsistencies and
degradation of peptides before LC/MS. There are three main
reasons for the lyophilzation of the samples. First, samples
may not be stable in solution during storage. Second,
acetonitrile is a volatile reagent that may evaporate inconsistently across plate wells over time. Third, 150 ll of
sample is too large for the autosampler in the LC/MS
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Original Report
Figure 8. A schematic view of the triplication and randomization
step. After the SPE step, an autosampler is used to triplicate and
randomize the samples. It redistributes the samples to 396-well
plates. Randomization is performed by a macro on an EXCEL
spreadsheet.
analysis. By drying a larger volume and resuspending the
samples in a smaller volume, throughput and sample
concentration are both increased.
The samples are lyophilized without heat for 16 hours to
remove both the ACN and TFA buffer. After the samples are
dried, they are transferred to a ÿ80 C freezer and logged into
SampleTracker. This system informs the LC/MS laboratory
personnel that the samples are ready for analysis.
Data generated from samples prepared using this process
showed good reproducibility. Two samples were analyzed by
LC/MS. These were pooled human plasma samples taken
through the entire process. Plotting the data from duplicate
experiments (Fig. 9a and b) showed R2 values of 0.9883.
Note that the high CV’s (CV>0.5) is due to the artificial
noises generated by the LC/MS and can be neglected.
CONCLUSION
The automated sample preparation procedure described here
is a semi-automated and highly parallel procedure for sample
preparation in a industrial proteomics laboratory. As shown
in the LC/MS data, the sample preparation procedure
generated highly reproducible data. Data quality is similar
to that of commercially available Affymetrix microarray
chips.25,26 There appears to be no reason why this system
could not be used for the profiling of human plasma.
Although this semi-automated process is certainly expensive (Fig. 10) compared to manual processing, the investment
will eventually be returned due to the more effective use of
time of the researchers, and a reduction of ‘‘re-run’’ samples
because of sample handling errors. Since all data points, such
as chromatograms and concentration data files, are readily
Figure 9. (A) A histogram demonstrating the reproducibility of
two samples that are prepared by this sample preparation step. Yaxis is the number of unique masses matched between the two
samples. X-axis is the CV. The range of CV from 0.1 to 0.3
represents 60% of the data. Note that the high CV’s (CV > 0.5) is
due to the artificial noises generated by the LC/MS and can be
neglected. (B) The reproducibility of the sample preparation
process is demonstrated here in a x-y plot by EXCEL. Two
samples are prepared by this sample preparation step and are
analyzed by LC/MS. The intensities of the peaks is recorded. An
x-y plot is generated by plotting the matched intensities of both
runs. The resulting data points showed R2 of 0.9883 at CV valued
at less than or equal to 0.3%.
available and stored, they are easily input and exported into
any laboratory information management system (LIMS).
This sample preparation process was designed only for
human plasma samples in order to facilitate biomarker
discoveries. It would be feasible to develop a similar process
for other non-plasma proteomics projects. Examples may
include urine, cell culture or biopsy samples, all of which
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August 2004 247
Original Report
Figure 10. The cost of this sample preparation is demonstrated here in a pie chart. The total cost per sample is $1,882.17. This cost
includes labor, instrumentation, supplies and materials.
have different biological and physical properties, and
therefore present their own unique challenges.
by high performance liquid chromatography. J. Pharm. Biomed. Anal.
2002, 28(3–4), 645–651.
5. Reynolds, M. A.; et al. Early biomarkers of stroke. Clin. Chem. 2003,
49(10), 1733–1739.
6. Amacher, D. E. A toxicologist’s guide to biomarkers of hepatic response.
ACKNOWLEDGMENTS
The authors thank William Neil (Discovery Chemistry—BMS) for the
development of the 2D bar-coding system. Also, thanks to Peter McDonald,
Al Wang, Rahul Karnik (Global Informatics- BMS) for their IT design and
support on the SampleTracker. In addition, thanks to Michael Thibeault
(Discovery Technology - BMS) and Norbert Wodke (Gilson) for their
continued support on the custom designs on the HPLC and liquid handler
Hum. Exp. Toxicol. 2002, 21(5), 253–262.
7. Wu, S. L.; et al. Targeted proteomics of low-level proteins in human
plasma by LC/MSn: using human growth hormone as a model system.
J. Proteome. Res. 2002, 1(5), 459–465.
8. Putnam, F. W. The Plasma Proteins—Structure, Function, and Genetic
Control, 2nd ed, Putnam, F. W., Eds., Vol. 1, Academic: New York,
1975; p 481.
systems.
9. Anderson, N. L.; Anderson, N. G. The human plasma proteome: history,
character, and diagnostic prospects. Mol. Cell. Proteomics 2002, 1(11),
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