Bio SILENCING 124 MYCN

Bio SILENCING 124 MYCN
124
BioRadiations
A Resource for Life Science Research
Differentiation
Metastasis
Proliferation
Apoptosis
MYCN
TP53
Apoptosis
SILENCING
Transcriptional Pathways of Disease
Differentiation
In this issue:
Unveiling the C1000™ Thermal Cycler’s Protocol Autowriter
ProteOn™ XPR36 Protein Interaction Array System Named Product of the Year
Optimizing Sample and Bead Volumes for Low-Abundance Protein Enrichment
Obtaining Pure Native Protein Via On-Column Cleavage in Less Than One Hour
Electrophoresis
My Tetra Is …Leakproof
The Mini-Protean® Tetra cell winged locking mechanism locks out leaks.
The Mini-PROTEAN Tetra systems for mini vertical gel electrophoresis
feature an innovative locking mechanism that eliminates leakage issues
commonly associated with gel electrophoresis. The patented* design
makes it easy to lock handcast or precast gels into the electrophoresis
module, ensuring leakproof operation and accurate experimental data.
Designed to run as many as four SDS-PAGE gels simultaneously, the
Mini-PROTEAN Tetra systems offer high throughput and a unique
design to meet all your electrophoresis needs.
Key Features
n Patented locking system to eliminate leaks
n Capacity to run up to 4 mini SDS-PAGE gels
n Easy conversion from electrophoresis cell to blotting apparatus
n Error-proof design to ensure correct polarity and orientation
Reliable and easy to use.
* U.S. patent 6,436,262.
To find your local sales office, visit www.bio-rad.com/contact/
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BioRadiations
issue 124, 2008
Denmark 45-44-52-10-00
to our readers
Finland 358-9-804-22-00
One of the greatest challenges facing researchers studying the genetic components of disease,
is discovering methodologies for silencing detrimental transcriptional pathways while preserving
those that are beneficial. At Ghent University in Belgium, researchers are working to advance
understanding how hyperactivity of the MYCN oncogene and low frequency of TP53 mutations at
diagnosis correlate to the most fatal forms of neuroblastoma. Using an optimized rt-qPCR workflow
and integrating highly specific siRNA-based techniques, these researchers have developed gene
knockdown models with more relevant silencing. Their ultimate goal is to completely unravel the
MYCN transcriptional web, enabling therapeutic methods that interfere with the oncogenetic
signaling pathways of MYCN, and leave the beneficial pathways unaltered. It is hoped that success
in these efforts will significantly reduce mortality from this very deadly form of childhood cancer.
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cover story
16Real-Time qPCR as a Tool for Evaluating RNAi-Mediated Gene Silencing
T Van Maerken,1 P Mestdagh,1 S De Clercq,2 N Yigit,1 A De Paepe,1 JC Marine,2
F Speleman,1 and J Vandesompele1
1
Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium,
2
Laboratory for Molecular Cancer Biology, Flanders Interuniversity Institute for Biotechnology
(VIB), Ghent, Belgium
departments
Spain 34-91-590-5200
2 What’s New
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6 Product Focus
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8 Tips and Techniques
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10 Dimensions
United Kingdom 44-20-8328-2000
32 New Literature
USA Toll free 1-800-4BIORAD
(1-800-424-6723)
technical reports
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13Profinity eXact™ Fusion-Tag System Performs On-Column Cleavage and Yields
Pure Native Protein From Lysate in Less Than an Hour
On the cover:
Conceptual illustration by
Joann Ma
N Oganesyan and W Strong, Bio-Rad Laboratories, Inc., Hercules, CA USA
22Simple and Rapid Optimization of Transfections Using Preset
Protocols on the Gene Pulser MXcell™ Electroporation System
J Terefe, M Pineda, E Jordan, L Ugozzoli, T Rubio, and M Collins,
Bio-Rad Laboratories, Inc., Hercules, CA USA
25Effect of PMA on Phosphorylation of Cx43: A Quantitative Evaluation Using
Blotting With Multiplex Fluorescent Detection
L Woo,1 K McDonald,1 M Pekelis,1 J Smyth,2 and R Shaw,2
1 Bio-Rad Laboratories, Inc., Hercules, CA USA,
2 University of California, San Francisco, San Francisco, CA USA
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© 2008 Bio-Rad Laboratories, Inc.
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28Applications of the ProteOn™ GLH Sensor Chip: Interactions Between
Proteins and Small Molecules
B Turner, M Tabul, and S Nimri, Bio-Rad Laboratories, Inc., Gutwirth Park,
Technion, Haifa, Israel
Legal Notices — See page 32.
BioRadiations 124
WHAT’SWHAT’S
NEW NEW
Bio-Plex® Suspension Array System: New Assays
and Updated Software
The Bio-Plex suspension array system can simultaneously measure multiple biomarkers in a single assay.
Bio-Rad introduces three new panels of immunoassays to its line of Bio-Plex Pro™ assays, and introduces
Bio-Plex Manager™ software, version 5.0.
Latest Bio-Plex Pro Assay Panels
Magnetic bead-based Bio-Plex Pro assays offer the option of using either magnetic separation or vacuum
filtration during processing.
Bio-Plex Pro human diabetes assay panel —
allows detection of 14 human diabetes and
obesity biomarkers. Available in one
12-plex panel and two singleplex kits.
Bio-Plex Pro human acute phase
assay panel — allows detection of 9 human
acute phase response biomarkers. Available
as 5-plex and 4-plex panel kits.
Bio-Plex Pro human angiogenesis assay
panel — allows detection of 9 human
angiogenesis biomarkers. Available as a
9-plex panel kit.
Available Targets
Human Diabetes Human Acute Phase
Human
Angiogenesis
Adiponectin
Adipsin
C-peptide
Ghrelin
GIP
GLP-1
Glucagon
IL-6
Insulin
Leptin
PAI-1
Resistin
TNF-a
Visfatin
a-2-macroglobulin CRP Ferritin Fibrinogen Haptoglobin
Procalcitonin
SAA
SAP
Tissue plasminogen activator Angiopoietin-2
Follistatin
G-CSF
HGF
IL-8
Leptin
PDGF-BB
PECAM-1
VEGF
Features of all kits include:
•Validation in serum, plasma, and tissue culture samples
•Premixed assays for convenience and reproducibility
• Magnetic- or vacuum-based separation
•Contain both standards and controls
• Include targets unique to the xMAP platform
Bio-Plex Manager Software,
Version 5.0
This latest software version provides:
Choose sequential data view for each
analyte or full table view for all analytes
•Tabulating and graphing functions —
visualize results and generate data
figures faster
•Statistical analysis and data
normalization functions for
normalization across different plates,
samples, or experiments
Present data in
a variety of chart
formats
•Programmable wash, preparation,
and shutdown steps for reading of
assays unattended
For available assay configurations,
complete software information,
and ordering information, go to
www.bio-rad.com/bio-plex/
BioRadiations 124
Present data by gene or by sample
© 2008 Bio-Rad Laboratories, Inc.
WHAT’S NEW
ProteoMiner™ Protein Enrichment Kits
ProteoMiner protein enrichment technology is a novel sample preparation
tool for reducing the dynamic range of protein concentrations in complex
biological samples. The presence of high-abundance proteins in biological
samples (for example, albumin and IgG in serum or plasma) makes the
detection of low-abundance proteins extremely challenging. ProteoMiner
technology overcomes this challenge by:
• Utilizing a combinatorial library of hexapeptides rather than
immunodepletion to decrease high-abundance proteins — allows use
with a variety of sample types and prevents codepletion of
low-abundance proteins
Untreated serum
Treated serum
• Enriching and concentrating low-abundance proteins that cannot be
detected through traditional methods
ProteoMiner kits enable the enrichment and detection of low-abundance
proteins for one- or two-dimensional gel electrophoresis, chromatography,
surface-enhanced laser desorption/ionization (SELDI), or another mass
spectrometry technique.
For more information, go to www.bio-rad.com/proteominer/
Ordering Information
Catalog #
163-3000
163-3001
163-3002
163-3003
Reduction of high-abundance
proteins improves detection and
resolution of proteins. Top, untreated
serum; bottom, serum treated using
the ProteoMiner protein enrichment kit.
Description
ProteoMiner Protein Enrichment Kit, 10 preps, includes 10 spin columns, wash buffer, elution reagents, collection tubes
ProteoMiner Introductory Kit, 2 preps, includes 2 spin columns, wash buffer, elution reagents, collection tubes
ProteoMiner Sequential Elution Kit, 10 preps, includes 10 spin columns, wash buffer, 4 sequential elution reagents, collection tubes
ProteoMiner Sequential Elution Reagents, includes reagents only (columns not included), to be used with 163-3000
Profinity eXact™ Fusion-Tag System
The Profinity eXact fusion-tag system is the latest complement to the Bio-Rad
line of affinity purification tools for recombinant tag purification. This integrated
set of products allows expression, detection, purification, and on-column
cleavage of fusion-tagged proteins, without the addition of protease. Cleavage
occurs in as little as 30 minutes, a significant time savings compared to
traditional methods. A highly purified, recombinant protein
containing only its native amino acid sequence is
generated in a single step and in a fraction of the
time of other methods. The result is true,
single-step purification without cleavage enzymes,
incubation times, or removal of reagents.
Ordering Information
Catalog #
156-3000
156-3001
156-3002
156-3003
156-3004
156-3005
156-3006
156-3007
156-3008
732-4646
732-4647
732-4648
Description
Profinity eXact Cloning and Expression Starter Kit
Profinity eXact pPAL7 RIC-Ready Expression Vector Kit
Profinity eXact pPAL7 Supercoiled Expression Vector Kit
BL21(DE3) Chemi-Competent Expression Cells
Profinity eXact Antibody Reagent
Profinity eXact Purification Resin, 10 ml
Profinity eXact Mini Spin Purification Starter Kit
Profinity eXact Mini Spin Columns
Profinity eXact Expression and Purification Starter Kit
Bio-Scale Mini Profinity eXact Cartridges, 2 x 1 ml Bio-Scale Mini Profinity eXact Cartridges, 4 x 1 ml
Bio-Scale Mini Profinity eXact Cartridges, 1 x 5 ml
Visit us on the Web at discover.bio-rad.com BioRadiations 124
WHAT’S NEW
1000-Series Thermal Cyclers
The new Bio-Rad 1000-series thermal cyclers offer
superior performance in a flexible and fully modular
platform. Choose the full-featured C1000™ cycler,
the basic S1000™ cycler, or a
combination of both —
there are multiple
configuration
options.
CFX96 real-time PCR
detection system
Interchangeable
Reaction Modules
Accommodate
different throughput
C1000 thermal cycler
needs with easily
S1000 thermal cycler with
with dual 48/48 fast
interchangeable reaction
96-well fast reaction module
reaction module
modules that swap in seconds
without requiring tools. The four reaction module
formats include a gradient-enabled 96-well fast module, a gradient-enabled dual 48-well fast module that
allows two independently controlled protocols to be run side by side in a single bay, a 384-well module for high
throughput, and the CFX96™ optical reaction module with five-target real-time PCR capabilities (see page 5).
Each PCR reaction module has a fully adjustable lid that supports a wide range of sealers and vessels, including
low-profile and standard-height plates.
Multiple Configuration Options
C1000 and S1000 thermal cyclers are available in two configurations: as stand-alone units or connected via USB
cables for operation as a multi-bay cycler. The following options are available for multi-bay cycler configurations:
• Connect a C1000 thermal cycler with up to three S1000 thermal cyclers for four-bay cycling
• Add a PC with C1000 Manager™ desktop software for control of up to 32 cyclers simultaneously
Performance
The overall run time of a PCR reaction depends on protocol design, enzyme type, and the thermal capabilities
of the thermal cycler. The 1000‑series thermal cyclers deliver premium thermal performance for reproducible
results and fast run times. The time to reach target temperature, which depends on the average ramp rate
and the settling time (the time it takes to reach thermal uniformity), is the key factor determining how fast a
thermal cycler can run a given PCR protocol. Average ramp rate is a better indicator of a cycler’s capabilities
than maximum ramp rate, because the latter is generally not maintained throughout a temperature step. The
average ramp rate of 1000-series cyclers, combined with a 10 second settling time, allows fast run times while
maintaining excellent thermal accuracy and uniformity.
Ordering Information
Catalog #
Description
C1000 Thermal Cycler
185-1048
C1000 Thermal Cycler With Dual 48/48 Fast Reaction Module
185-1096
C1000 Thermal Cycler With 96-Well Fast Reaction Module
185-1384
C1000 Thermal Cycler With 384-Well Reaction Module
S1000 Thermal Cycler
S1000 Thermal Cycler With Dual 48/48 Fast Reaction Module
185-2048
185-2096
S1000 Thermal Cycler With 96-Well Fast Reaction Module
185-2384
S1000 Thermal Cycler With 384-Well Reaction Module
CFX96 Real-Time Detection System
CFX96 Real-Time PCR Detection System, includes C1000 thermal cycler chassis, CFX96 optical reaction module,
185-5096
CFX Manager software, communication cable, power cord, reagent and consumable samples, instructions
BioRadiations 124
© 2008 Bio-Rad Laboratories, Inc.
WHAT’S NEW
CFX96™ Real-Time PCR Detection System
The CFX96 optical reaction module converts a C1000™ thermal cycler into
a powerful and precise real-time PCR detection system. This six-channel
system’s solid-state optical technology (filtered LEDs and photodiodes)
maximizes fluorescent detection of dyes in specific channels, providing
precise quantitation and target discrimination. At every position and with
every scan, the optics shuttle is reproducibly centered above each well,
so the light path is always optimal and there is no need to sacrifice data
collection to normalize a passive reference. Features include:
• Data collection from all wells during acquisition — enter/edit plate
information before, during, or after the run
• Multiple data acquisition modes — tailor the run to suit your application
(including 1-color fast scan mode for SYBR® Green users)
• CFX Manager™ software ­— use advanced analysis tools for performing normalized gene expression with
multiple reference genes and individual reaction efficiencies
• Expansion capability — run up to 4 instruments from 1 computer
• E-mail notification — program software to send an e-mail with an attached data file upon run completion
Ordering Information
Catalog#
184-5096
Description
CFX96 Optical Reaction Module, includes CFX96 optics shuttle, CFX Manager software, communication cable,
reagent and consumable samples, instructions
CFX96 Real-Time PCR Detection System, includes C1000 thermal cycler chassis, CFX96 optical reaction module,
CFX Manager software, communication cable, power cord, reagent and consumable samples, instructions
185-5096
siLentMer™ Validated siRNAs With Validated qPCR Primer Pairs
Now, every siLentMer validated siRNA duplex is packaged with the validated qPCR primer pairs that were used
for the siRNA validation studies. This enables you to quickly study knockdown efficiency for your target of interest.
Examples of qPCR validation of siLentMer siRNA knockdown efficiency are shown below.
HeLa
Human Primary Fibroblasts
p53
103 DCT =3.62
91.85% knockdown
AURKA
HUVEC
DCT =4.64
95.98% knockdown
DCT =3.71
92.35% knockdown
DCT =4.26
94.79% knockdown
DCT =3.49
91.10% knockdown
102
DCT =4.60
95.88% knockdown
103
PCR base line subtracted curve fit RFU
102
0
5
10
15
20
25
30
35 40 45
0
5
10
15
20
25
30
35 40 45
0
5
10
15
20
25
30
35 40 45
Cycle
siLentMer siRNAs produce effective gene silencing with greater than 90% knockdown of multiple genes in multiple cell lines. Silencing of either
the tumor suppressor gene (TP53) or aurora kinase A gene (AURKA/STK15/BTAK) in HeLa cells, human primary fibroblasts, and human umbilical vein
endothelial cells (HUVEC) is demonstrated. The RT-qPCR traces, generated using validated qPCR primer pairs, show gene expression in cells transfected
with a nonsilencing siRNA (—), or an siRNA targeting either TP53 or AURKA mRNAs (—). All cells were transfected using siLentFect™ lipid transfection
reagent, then exposed to siRNA (HeLa, 5 nM siRNA; human primary fibroblasts and HUVEC cells, 10 nM siRNA). RNA samples were collected 24 hr
posttransfection and knockdown efficiency was measured by RT-qPCR using the coordinated validated qPCR primer pairs for the target gene.
For ordering information, go to www.bio-rad.com/rnai/
Visit us on the Web at discover.bio-rad.com BioRadiations 124
PRODUCT
PRODUCT
FOCUS
FOCUS
siLentMer™ Validated siRNAs With Validated qPCR Primer Pairs
The Bio-Rad line of siLentMer validated Dicer-substrate siRNA duplexes is continuously growing; currently available gene targets are
listed in the table below. Two duplexes per target are offered to confirm that any biological effects observed in the experiments are
specifically due to loss of the targeted gene. For more information, go to www.bio-rad.com/RNAi/
Available Gene Targets
Available Gene Targets
Catalog #
Human Gene Target
Accession #*
Reference/Housekeeping Genes
b-Actin
Cyclophilin A
GAPDH
GFP (jellyfish)
NM_001101 NM_021130 NM_002046 M62653 Duplex 1
Duplex 2
NM_000927
NM_005157
NM_001105
NM_001106
NM_020421
NM_052853
NM_004208 NM_001014431
NM_001626
NM_000038
NM_001880
NM_003600
NM_004048 NM_004324
NM_004327
NM_007294
NM_003656
NM_001223
NM_032982 NM_001225 NM_001227
NM_053056
NM_001238
NM_001786
NM_003607
NM_001798
NM_000075
NM_004935
NM_001799
NM_000389
NM_001274
NM_001278
NM_016451
NM_004379
NM_004383
NM_001904
NM_005225
NM_005228
NM_005229
NM_002037 NM_019884
NM_002093
NM_004494
NM_152696
NM_000188
NM_000875
NM_000575
Human Gene Target
Catalog #
Accession #*
Reference/Housekeeping Genes
179-0104
179-0103
179-0100
179-0106
179-0204
179-0203 179-0200
—
HPRT1 Lamin A/C Luciferase (firefly)
b-Tubulin
179-0182
179-0135
179-0164
179-0192
179-0165
179-0176
179-0151
179-0118
179-0155
179-0110
179-0130
179-0185
179-0109
179-0124
179-0126
179-0127
179-0190
179-0148
179-0140
179-0161
179-0139
179-0186
179-0194
179-0113
179-0196
179-0114
179-0117
179-0120
179-0166
179-0158
179-0189
179-0122
179-0301
179-0199
179-0152
179-0168
179-0145
179-0115
179-0131
179-0144
179-0116
179-0159
179-0300
179-0184
179-0180
179-0174
179-0195
179-0282
179-0235
179-0264
179-0292
179-0265
179-0276
179-0251
179-0218
179-0255
179-0210
179-0230
179-0285
179-0209
179-0224
179-0226
179-0227
179-0290
179-0248
179-0240
179-0261
179-0239
179-0286
179-0294
179-0213
179-0296
179-0214
179-0217
179-0220
179-0266
179-0258
179-0289
179-0222
179-0401
179-0299
179-0252
179-0268
179-0245
179-0215
179-0231
179-0244
179-0216
179-0259
179-0400
179-0284
179-0280
179-0274
179-0295
ILK
IRAK1
IRAK2
IRAK4
JAK1
LATS2
LIMK1
LIMK2
LYN
MAP2K1
MAP2K4
MAP2K5
MAP3K3
MAPK1
MAPK3
MAPK8
MAPKAPK2
MARK2
MDM2
MEN1
MET
MMP2
NF1
NFKB1 PDK1
PDK2
PDK3
PLK1
PPARA
PTK2
RAF1
RB1
RBBP8
ROCK2 RXRA
SKI
STAT1
STAT3
TEC
TGFBR2
TK1
TK2
TNFRSF1A
TP53
VEGFA
WEE1
YES1
NM_000194 NM_005572 X84846 NM_178014 Duplex 1
Duplex 2
179-0101
179-0102
179-0107
179-0105
179-0201
179-0202
—
—
179-0121
179-0160
179-0175
179-0183
179-0179
179-0198
179-0169
179-0177
179-0138
179-0125
179-0193
179-0197
179-0188
179-0153
179-0146
179-0123
179-0163
179-0142
179-0134
179-0141
179-0112
179-0149
179-0171
179-0154
179-0172
179-0156
179-0162
179-0119
179-0178
179-0128
179-0137
179-0132
179-0302
179-0167
179-0147
179-0143
179-0129
179-0157
179-0150
179-0187
179-0181
179-0191
179-0173
179-0111
179-0133
179-0170
179-0136
179-0221
179-0260
179-0275
179-0283
179-0279
179-0298
179-0269
179-0277
179-0238
179-0225
179-0293
179-0297
179-0288
179-0253
179-0246
179-0223
179-0263
179-0242
179-0234
179-0241
179-0212
179-0249
179-0271
179-0254
179-0272
179-0256
179-0262
179-0219
179-0278
179-0228
179-0237
179-0232
179-0402
179-0267
179-0247
179-0243
179-0229
179-0257
179-0250
179-0287
179-0281
179-0291
179-0273
179-0211
179-0233
179-0270
179-0236
Genes of Research Interest
Genes of Research Interest
ABCB1
ABL1
ACVR1
ACVR2B
ADCK1
ADCK2
AIFM1
AKT1
AKT2 APC
ATF2
AURKA
B2M
BAX
BCR
BRCA1
CAMK1
CASP1
CASP2
CASP4
CASP7
CCND1
CCNE1
CDC2 (CDK1)
CDC42BPA
CDK2
CDK4
CDK5
CDK7
CDKN1A
CHEK1
CHUK
COPB1
CREB1
CSK
CTNNB1
E2F1
EGFR
ELK1
FYN GSK3A
GSK3B HDGF HIPK1
HK1
IGF1R
IL1A
NM_001014794
NM_001025242
NM_001570
NM_016123
NM_002227
NM_014572
NM_002314
NM_001031801
NM_002350
NM_002755
NM_003010
NM_002757
NM_002401
NM_002745
NM_001040056
NM_002750
NM_004759
NM_004954
NM_002392
NM_000244
NM_000245
NM_004530
NM_000267
NM_003998
NM_002610
NM_002611
NM_005391
NM_005030
NM_001001928
NM_005607
NM_002880
NM_000321
NM_002894
NM_004850
NM_002957
NM_003036
NM_007315
NM_003150
NM_003215
NM_001024847
NM_003258
NM_004614
NM_001065
NM_000546
NM_001025366
NM_003390
NM_005433
* National Center for Biotechnology Information (NCBI) accession number.
BioRadiations 124
© 2008 Bio-Rad Laboratories, Inc.
PRODUCT FOCUS
ProteOn™ XPR36 Protein Interaction Array System
Receives 2007 Product of the Year Award
The ProteOn XPR36 protein interaction array system, a surface
plasmon resonance (SPR) biosensor, was chosen by Frost &
Sullivan as the 2007 U.S. Drug Discovery Technologies Product
of the Year. Frost & Sullivan, a global growth consulting company,
recognizes companies in a variety of regional and global markets
for outstanding achievement and superior performance in areas
such as leadership, technological innovation, customer service,
and strategic product development.
According to Frost & Sullivan analyst Shankar Sellappan,
PhD, the ProteOn XPR36 system was selected for the award
because of its unique ability to monitor multiple cellular molecular
interactions independently, which “assists in efforts to better
understand the biological mechanisms that maintain normal
cellular processes and that contribute to disease development
and progression and assists in the development of drugs.”
Factors considered by analysts in their evaluation of new
products include:
•
•
•
•
•
•
small molecule-target interactions. In addition, multiplexed
analysis using crisscross microfluidics, made possible by
XPR™ technology, enables rapid generation of large amounts
of complex data. Results are quickly ready for comparison,
seamlessly integrated, and easily categorized.
The Power of One-Shot Kinetics™
Until recently, SPR experiments for the evaluation of kinetic
rate constants could only be run sequentially. Following the
immobilization of one ligand on the sensor chip surface, a
single concentration of analyte was flowed over the ligand and
the corresponding response was measured. The surface was
then regenerated (analyte removed) to prepare the immobilized
ligand for the next concentration of analyte. This sequence was
repeated until a full analyte concentration series was collected.
The ProteOn XPR36 system uses a more powerful method,
combining multiplexed SPR technology and a unique
One-Shot Kinetics approach. Multiplexing improves the capabilities
and workflow of traditional technology by enabling multiple
quantitative protein binding experiments in parallel, so robust
kinetic analysis of an analyte concentration series can be handled
in one experiment. This one-shot approach generates a complete
kinetic profile of a biomolecular interaction — without the need for
regeneration — in one experiment, using a single sensor chip.
The ProteOn system can be used for a variety of drug discovery
and life science research applications, including protein-protein
interaction analyses, protein-drug target binding, antibody profiling,
protein-interface mapping, and protein complex assembly and
signaling cascades. This versatility and the parallel processing
workflow allow more information to be generated from each
experiment, which has the potential to accelerate understanding of
cellular processes and the development of drugs.
Significance of the product in its industry
Competitive advantage of the product in its industry
Innovation in terms of unique or revolutionary technology
Acceptance in the marketplace
Value-added services provided to customers
Number of competitors with similar product(s)
The ProteOn XPR36 Protein Interaction Array System
The ProteOn XPR36 system is a unique 6 x 6 multichannel SPR
platform that enables automated analysis of up to 36 biomolecular
interactions in one experiment. Advantages of the ProteOn
XPR36 system — high throughput, speed, kinetic response —
are multiplied for research that involves large, broad, and complex
studies, such as results from hybridoma screening and ranking
data and results from the validation and characterization of
A. Ligand immobilization
B. Injection of six
analyte concentrations C. 36 interactions
250
200
150
Response, RU
100
50
0
250
200
150
100
One-shot kinetics workflow. Up to six concentrations of analyte are
injected over six different ligand densities (single-pair kinetics) or six different
types of ligand (multiple-pair kinetics). Full kinetic results are obtained in one
injection, without the need for ligand regeneration. Reference channel and
local interspot reference subtraction methods are available.
Visit us on the Web at discover.bio-rad.com 50
0
0 2
4
6 8 10 12 14
0 2
4
6 8 10 12 14
0 2
4
6 8 10 12 14
Run time, min
BioRadiations 124
7
TIPS
TIPSAND
AND
TECHNIQUES
TECHNIQUES
Tips for Experion™ System Users: RNA Assays
28S
Intact
1 hr degradation
A
60
6,000
4,000
3,000
2,000
1,500
1,000
500
200
50
40
20
Fluorescence
RNA can be a temperamental molecule to work with and can
cause countless hours of frustration. Difficulties are generally
attributed to ubiquitous RNases — enzymes that catalyze the
hydrolysis of RNA (Figure 1). Careful and consistent laboratory
practices can help improve RNA assay results. Bio-Rad technical
support specialists have developed the following tips to help
overcome RNA assay problems when using the Experion
automated electrophoresis system.
0
–10
20
30
40
50
B
60
6,000
4,000
3,000
2,000
1,500
1,000
500
200
50
40
18S
20
lower
marker
0
–10
2 hr degradation
5 hr degradation
Fig. 1. Time course of degradation of liver carcinoma RNA. Samples of human liver
carcinoma total RNA were incubated at 90°C in TE buffer in 1 hr increments from 0 to
7 hr. Aliquots (50 ng) were then separated with the Experion RNA StdSens analysis kit.
Electropherograms of samples collected at selected time points are shown.
Analyze RNA ladder quality — first, perform a quick check
of the ladder prior to analyzing results to ensure the run
was successful and the results were unaffected by RNase
contamination. As the basis for any sizing and quantitation
that occurs on the chip, it is essential to confirm that a good
RNA ladder profile has been created. To do this, verify that
the RNA ladder pattern is correct and that all bands in the
virtual gel have been correctly labeled from 50 to 6,000 bp.
Electropherogams demonstrating good and poor ladder
profiles are shown in Figure 2.
Clean electrodes — if ladder quality is poor, clean the electrodes in
the electrophoresis station using one of the two methods outlined in
the system manual. The milder cleaning method involves using the
cleaning chips (supplied with RNA chips) to clean before and after
each run. The deep cleaning method is performed using Experion
electrode cleaner and a special lint-free swab, and should be
done: when you suspect contamination, when switching between
RNA and protein assays on the same system, as part of regular
maintenance, and prior to any critical experiment.
Minimize contaminants — separate reagents and pipets from
other general supplies, use disposable items whenever possible,
BioRadiations 124
L 1 2 3 4 5 6 7 8 9101112
60
20
30
40
Time, sec
50
60
L 1 2 3 4 5 6 7 8 91011
Fig. 2. Good and poor ladder profiles. A good ladder profile (A) shows a clearly
identified lower marker (LM) and eight peaks that gradually get smaller over time. A
poor ladder profile (B), shows poor peak resolution from the baseline, particularly for
the last two peaks (results commonly seen from a degraded ladder). Note that in the
“L” lane, the 6,000 bp marker of the ladder has not been identified.
use nuclease-free tips and tubes, use barrier tips, wear a face
mask when preparing samples and chips, and wear gloves. If
typical decontaminants do not clean surfaces effectively, use 1 M NaOH or HCl solution.
Develop standard procedures — aliquot single-use amounts
of ladder into nuclease-free tubes (one for each chip); quickly
snap-freeze aliquots on dry ice and do not reuse or refreeze
them. Use the ladder quickly after thawing; thawing for extended
periods after heating causes the ladder to renature, resulting in
broad peaks. Inadequate heating also causes broad peaks (check
the heating block if broad peaks are a recurring problem). RNA
assays are sensitive to contaminants, salts, and detergents, so
ensure samples are resuspended in DEPC-treated water (StdSens
analysis kit and HighSens analysis kit) or TE buffer (StdSens kit
only). The stain used in the Experion RNA analysis kits is sensitive
to light; if damaged, the levels of fluorescence may be diminished
and some peaks may go undetected. To protect the stain from
photobleaching, wrap the tube in aluminum foil.
Determine concentration range of the sample load — desired
ranges are: for detection only, 5–500 ng/µl (StdSens chip) and 100–5,000 pg/µl (HighSens chip), and for quantitation, 25–500 ng/µl
(StdSens chip) and 500–5,000 pg/µl (HighSens chip). When the
chip is over- or underloaded beyond the recommended ranges,
data may no longer fall within the linear range and, therefore, cannot
be accurately quantitated. To determine concentration, run a set of
serial dilutions on the chip to find the optimal range.
— Katy McGirr, PhD, senior technical support consultant, Bio-Rad Laboratories
© 2008 Bio-Rad Laboratories, Inc.
TIPS AND TECHNIQUES
C1000™ Thermal Cycler: Unveiling the Protocol Autowriter
What Is the Protocol Autowriter and How Does It
Save Time?
The protocol autowriter, a key innovation of the C1000 thermal
cycler, automatically generates a customized temperature
protocol with hot start, initial denaturation, and annealing and
extension steps based on parameters you input as well as on
standard PCR guidelines. It can create protocols that run at
standard, fast, and even ultrafast speeds. The protocol autowriter
is available on the C1000 thermal cycler and in C1000 Manager™
software, which runs on a PC.
How Does the Protocol Autowriter Work?
The protocol autowriter uses standard PCR guidelines that
automatically generate cycling protocols with initial template
denaturation and enzyme activation, followed by cycles of
denaturation, annealing, and extension, and then final extension
steps. Protocols are based on user-input parameters of target
amplicon length, enzyme type, annealing temperature, and
primer sequences. The protocol autowriter uses established
PCR standards that reference data tables to produce the final
suggested protocols. All protocols are either standard two- or
three-step methods with a final extension step.
Protocols generated by the protocol autowriter at various
speed settings (standard, fast, and ultrafast) may result in
different product yields. In generating these protocols, the
protocol autowriter may adjust the annealing temperature,
reduce the total number of protocol steps, reduce the number
of GOTO repeats, shorten hold times, or reduce the temperature
differentials between steps.
feature. Comparative reactions can even be run side-by-side on
the dual 48/48 fast reaction module. Any change to the settings
will result in a recalculation of the estimated run time, which will
allow tailoring of run settings — maximizing the productivity of the
cycler for a given experiment.
How Is the Protocol Autowriter Used?
1. Enter the amplicon length, polymerase, and primer Tm. If the
primer Tm, is unknown, select the Ta calculator (F1) to calculate
this value.
2. Select the protocol speed: standard, fast, or ultrafast.
The protocol autowriter can:
Autowrite a protocol — software will automatically suggest
a temperature protocol based on user-input experimental
parameters (amplicon length, annealing temperature, and enzyme
type). An optional Ta (annealing temperature) calculator is also
available. This suggested protocol may then be run or saved as is,
or edited and saved as a standard temperature protocol.
3. Edit, save, then run the suggested protocol.
Suggest temperature protocols with shorter run times —
once initial parameters have been entered, choose a protocol
“speed” for the total run time. The settings are standard, fast,
and ultra-fast. The faster the protocol setting, the more
chance that risk is introduced in terms of yield and successful
amplification (particularly if difficult templates are involved).
Quickly program the C1000 cycler — a three-screen wizard
permits very fast programming of new protocols and also helps
users with little knowledge of PCR to write protocols.
Provide tools to further optimize a reaction — further
optimization of reactions is possible by incorporating the gradient
Visit us on the Web at discover.bio-rad.com BioRadiations 124
TECHNICAL
DIMENSIONS
REPORT
ProteoMiner™ Protein Enrichment System:
Optimization of Sample and Bead Volumes
Introduction
Biological samples such as human plasma and serum are thought
to contain valuable information for the discovery of biomarkers.
However, the plasma proteome is extremely complex and has a
wide protein dynamic range, factors that make the detection of
low-abundance proteins nearly impossible (Anderson and Anderson
2002). No single analytical method is capable of resolving all plasma
or serum proteins, and no detection method can cover more than
4 or 5 orders of magnitude. Therefore, most analytical methods
for these sample types involve the immunodepletion of highabundance proteins to reduce both the complexity and dynamic
range of samples. Although immunodepletion is effective, it also
has disadvantages and limitations: 1) the availability of antibodies
against high-abundance proteins is limited, 2) available antibodies
have a limited binding capacity, which in turn limits the amount of
protein that can be loaded, and 3) there is a high probability for
codepletion of low-abundance proteins.
To address the challenges of analyzing plasma and serum
samples, and to mitigate the limitations of immunodepletion,
Bio-Rad has developed the ProteoMiner protein enrichment
system. The ProteoMiner system utilizes an extremely diverse
combinatorial library of hexapeptides that are bound to beads.
These hexapeptides act as unique protein binders to reduce
sample complexity. Unlike immunodepletion, in which the
capacity of the bound antibodies typically limits the sample
volume to less than 100 µl, large sample volumes of 1 ml and
more can be incubated with the hexapeptide beads. Binding
of high-abundance proteins is limited by the bead capacity;
therefore, proteins in high abundance quickly saturate their
specific affinity ligands and cease binding. Excess unbound
proteins are eventually washed away. In contrast, medium- and
low-abundance proteins do not saturate their ligands and are
therefore concentrated on the beads. When eluted, the sample
is less complex, allowing detection of these medium- and lowabundance proteins by chromatography, gel electrophoresis, or
mass spectrometry techniques, such as surface-enhanced laser
desorption/ionization (SELDI).
The best results are achieved when sample and bead volumes
are optimized to ensure coverage across the proteome, to reach
an appropriate amount of saturation of ligands to reduce high-
10
BioRadiations 124
abundance proteins, and to enrich low-abundance proteins. The
recommendation is to use 1 ml of plasma or serum (or ≥50 mg of
protein) with 100 µl of beads (provided in each spin column in the
ProteoMiner protein enrichment kit). However, due to samples with
limited volume and low protein concentrations, it is often tempting
to reduce either the sample or bead volume. In this study, we
demonstrate the effects of reducing both the sample and bead
volumes in an attempt to determine the optimal experimental
conditions for the ProteoMiner protein enrichment kit.
Sample Preparation Using ProteoMiner Beads
In the ProteoMiner protein enrichment kit, beads (100 µl volume)
are stored in spin columns in a 20% ethanol, 0.5% sodium azide
solution. After centrifugation to remove the storage solution,
ProteoMiner beads were washed with deionized water followed
by phosphate buffered saline (PBS). Then 1 ml plasma (50 mg/ml) was applied to the column (10:1 sample-to-bead
ratio) and, to ensure effective binding, the sample was slowly
rotated with the ProteoMiner beads for 2 hr prior to washing with
PBS buffer to remove the unbound proteins. To elute the bound
proteins, the ProteoMiner beads were washed three times with
100 µl of acidic urea/CHAPS buffer (5% acetic acid, 8 M urea,
2% CHAPS), which is directly compatible with downstream
SELDI and two-dimensional gel electrophoresis (2DGE). This
protocol was repeated several times with different sample and
bead volumes (Table 1).
Table 1. Sample and bead volumes tested with resulting spot count data from
highlighted regions of 2-D gels (Figure 1).
Sample Volume, µl
1,000
400
500
200
Bead Volume, µl
100
100
50
50
Sample-to-Bead
Ratio
Spot Count
10:1
4:1
10:1
4:1
196
155
173
141
Yield, mg
2.02
1.70
1.26
0.62
Gel Electrophoresis and Gel Image Analysis
For 2DGE experiments, 100 µg of each eluate was loaded onto
an 11 cm ReadyStrip™ IPG strip, pH 5–8. Isoelectric focusing was
performed at 250 V for 30 min followed by 8,000 V until 45,000 V-hr were reached. After transfer onto Criterion™ 8–16%
© 2008 Bio-Rad Laboratories, Inc.
DIMENSIONS
Tris-HCl gels, the second dimension was run for 1 hr at 200 V
prior to staining with Flamingo™ fluorescent gel stain. Gels were
imaged using the Molecular Imager® PharosFX™ system and
analyzed with PDQuest™ 2-D analysis software, version 8.0.
SELDI Measurements
For this study, ProteinChip® CM10 arrays were used. The
carboxymethyl weak cation exchange arrays were equilibrated
twice with 5 µl of 100 mM sodium acetate buffer, pH 4. After
equilibration, the liquid was removed from the ProteinChip
arrays, and 0.5 µl of ProteoMiner bead-treated serum sample
was mixed with 4.5 µl of 100 mM sodium acetate buffer, pH 4.
After a 30 min incubation with shaking, each spot was washed
three times with 5 µl of binding buffer for 5 min to eliminate
unadsorbed proteins, followed by a quick rinse with deionized
water. After air-drying, ProteinChip SPA (sinapinic acid) matrix
dissolved in an acetonitrile:TFA:water mixture (49.5:0.5:50)
was added twice in 1 µl increments and allowed to air-dry.
All ProteinChip arrays were analyzed with the ProteinChip
SELDI system with an ion acceleration potential of 20 kV and
a detector voltage of 2.8 kV. Data processing steps included
baseline subtractions and external calibration using a mixture of known peptide and protein calibrants. Peak detection (S/N >3) and peak clustering were performed automatically
using ProteinChip data manager software, version 3.2.
Optimization Results
The results of the optimization experiments are shown in Figures 1 and 2.
The data demonstrate that the greatest number of proteins
were detected by both 2DGE and SELDI when 100 µl of beads
was used with 1,000 µl of sample. Decreasing the amount of
A
100 µl, 10:1 ratio
pH 5
B
50 µl, 4:1 ratio
50 µl, 10:1 ratio
100 µl, 4:1 ratio
Fig. 1. 2DGE of plasma samples treated with ProteoMiner under optimal conditions with 10:1 or 4:1 sample:bead volume ratios and 50 or 100 µl of
beads in a mini spin column. A, 10:1 sample:bead volume and 100 µl of beads using the following 2DGE conditions: 1st dimension, pH 5-8, 11-cm; 2nd
dimension, 8-16% Criterion™ precast gels, 100 µg sample, staining with Flamingo™ fluorescent gel stain. Highlighted area used for spot count (Table 1). B, Same
conditions applied to different sample:bead volume ratios; areas shown correspond to highlighted area from A.
Visit us on the Web at discover.bio-rad.com BioRadiations 124
11
DIMENSIONS
A
B
300
4:1 ratio
4:1 ratio
10:1 ratio
10:1 ratio
Signal intensity, mA
200
100
0
300
200
100
0
5,000
7,500
10,000
12,500
5,000
7,500
10,000
Molecular weight, Da
Fig. 2. ProteinChip SELDI system analysis with ProteinChip CM10 array of 4:1 and 10:1 sample-to-bead ratios for both the 50 µl (A) and 100 µl (B) bead volumes.
The 10:1 ratios produce the greatest number of peaks.
sample with a constant volume of beads reduced the number
of proteins detected. In the highlighted regions from the 2-D
gels, 196 spots were detected when 1,000 µl of sample were
added to 100 µl of beads, while only 155 spots were detected
when the volume was decreased to 400 µl. Similarly, 173 spots were detected when 50 µl of beads were loaded, while only
141 spots were detected when 200 µl were loaded. With
both protein volumes (100 and 50 µl), the greatest number of
proteins were detected when a 10:1 sample to bead volume
ratio was used.
Table 2. Sample and bead volumes tested with resulting peak count data from
SELDI runs with ProteinChip CM10 arrays.
Sample Volume, µl
Bead Volume, µl
Sample-to-Bead
Ratio
Peak Count
1,000
400
500
200
100
100
50
50
10:1
4:1
10:1
4:1
86
81
79
73
Conclusions
The ProteoMiner protein enrichment system reduces the
complexity of samples, in particular serum and plasma samples,
by decreasing the amount of high-abundance proteins and
enriching low-abundance proteins. This is achieved through
12
BioRadiations 124
a high level of diversity and representation of the hexapeptide
library, as well as an appropriate level of saturation of the ligands.
Reducing the bead volume decreases the coverage across the
proteome, which ultimately reduces the number of proteins
that can be captured. Using a smaller sample volume (lower
protein load) limits the number of high-abundance proteins
that reach saturation, thereby reducing the number of proteins
whose concentrations are decreased following treatment.
Furthermore, using less sample decreases the total protein
loaded onto the beads and therefore lowers the probability
of capturing low-abundance proteins. Hexapeptide diversity,
saturation level, and protein load all must be optimized to ensure
maximum performance of ProteoMiner system technology. For
best performance and when possible, we recommend using
1 ml of sample (50 mg/ml) with 100 µl of beads. The 2-D and
SELDI data shown here demonstrate that if sample and bead
volumes are reduced, fewer spots and peaks are detected,
thereby reducing the chance of finding a quantitative difference
in a disease versus control sample or, in other words, finding a
biomarker candidate.
Reference
Anderson NL and Anderson NG, The human plasma proteome: history, character,
and diagnostic prospects, Mol Cell Proteomics 1, 845–867 (2002)
© 2008 Bio-Rad Laboratories, Inc.
TECHNICAL
TECHNICAL
REPORT
REPORT
Profinity eXact™ Fusion-Tag System Performs On-Column Cleavage
and Yields Pure Native Protein From Lysate in Less Than an Hour
Natalia Oganesyan and William Strong, Bio-Rad Laboratories, Inc. Hercules, CA 94547 USA
Introduction
To simplify purification of recombinant proteins, including many
with unknown biochemical properties, several genetically
engineered affinity tags, or purification tags, are used. Commonly
used tags are polyhistidine (His), glutathione-S-transferase
(GST), and the antibody peptide epitope, FLAG (Arnau et al.
2006). The tag is fused to the N- or C-terminus of the protein
of interest, allowing the fusion protein to be purified to near
homogeneity in a single-step procedure using a resin with strong
binding avidity and selectivity to the tag.
Once the fusion protein has been purified, it is often necessary
to remove the tag before subsequent use in downstream
applications (Arnau et al. 2006, Waugh 2005), because the
tag may alter protein conformation (Chant et al. 2005), affect
biologically important functions (Araújo et al. 2000, Fonda et al.
2002, Goel et al. 2000), or interfere with protein crystallization
(Bucher et al. 2002, Kim et al. 2001, Smyth et al. 2003). The most
popular method to remove the tag involves building a protease
cleavage site between the tag and the target protein within the
expression vector, and cleaving the resultant fusion protein, using
purified preparations of the cognate protease specific to the
engineered site. The most frequently used processing proteases
for this purpose are tobacco etch virus (TEV) protease, thrombin,
factor Xa, and enterokinase. Although these tag-removal systems
alleviate problems associated with presence of the tag in the
final purified protein, they have several principal drawbacks:
1) the high enzyme-to-substrate ratios, the elevated temperatures
required for optimal or efficient processing, and the duration of
the reaction may affect cleavage specificity as well as stability
of the target protein (Arnau et al. 2006, Jenny et al. 2003);
2) the extended length of purification protocols due to additional
cleavage and protease-removal steps may hamper highthroughput purification approaches and result in loss of target
protein; 3) the nature of protease cleavage mechanisms often
result in generation of protein products that still contain extra
residues on their N-termini.
These complications can be easily avoided by using the
Profinity eXact fusion-tag purification system. The system consists
of Profinity eXact purification resin and the Profinity eXact tag,
which is a small 8 kD polypeptide expressed as a fusion to the
N-terminus of the target protein. The ligand coupled to the resin
matrix is based on the bacterial protease subtilisin BPN', which
has been extensively engineered to increase stability and to isolate
the substrate-binding and proteolytic functions of the enzyme
Visit us on the Web at discover.bio-rad.com (Abdulaev et al. 2005, Ruan et al. 2004). The incorporated
modifications allow for conventional affinity binding with high
selectivity, as well as specific and controlled triggering of the
highly active cleavage reaction. Cleavage is achieved upon the
addition of low concentrations of small anions, such as fluoride
or azide. The native recombinant protein is released without any
residual amino acids at the N-terminus, and the 8 kD Profinity
eXact tag remains bound to the modified subtilisin ligand linked to
the resin. Purification of fusion proteins is performed under native
conditions, with tag cleavage and elution of purified protein from
the column completed in about an hour.
To demonstrate the advantages of the Profinity eXact system
one-step protocol, we compared the purification process of
maltose-binding protein (MBP) fused either with GST or with
the Profinity eXact tag. To mimic the tag-removal capabilities
of the Profinity eXact system, the GST-MBP fusions were also
engineered with intervening thrombin or TEV cleavage sites.
Performance parameters tested in this study include the time
required for obtaining tag-free MBP and final yield and purity of
the purified protein.
Methods
Vectors and Purification Resins
pGEX2T vector, thrombin protease, and GSTrap HP, HiTrap
benzamidine FF, and HisTrap FF columns were purchased from
GE Healthcare. AcTEV protease was purchased from Invitrogen
Corporation. Profinity eXact pPAL7 expression vector and
Bio-Scale™ Mini Profinity eXact™ cartridges (1 ml) were from
Bio-Rad Laboratories, Inc.
Expression Vector Construction
The gene encoding MBP was amplified from pMAL vector
(Invitrogen) using iProof™ high-fidelity polymerase (Bio-Rad).
After digestion with the corresponding restriction enzymes (BamHI
and EcoRI), the fragment containing MBP was cloned into pGEX2T
vector to obtain a fusion with a thrombin cleavage site
(GST-Th-MBP). To obtain the GST-TEV-MBP fusion with AcTEV
cleavage site, the sequence encoding the thrombin cleavage site
(LVPR^GS) in the vector containing the GST-Th-MBP fusion was
replaced by the sequence ENLYFQ^G, using a QuikChange II
mutagenesis kit (Stratagene Corporation) according to
manufacturer instructions. To obtain Profinity eXact tag-MBP fusion,
an MBP-encoded PCR fragment was cloned into the Profinity
eXact pPAL7 expression vector using restriction-independent
cloning as instructed in the Profinity eXact system manual.
BioRadiations 124
13
TECHNICAL REPORT
Protein Expression and Purification
The resulting constructs were transformed into E. coli BL21(DE3)
chemi-competent expression cells (Bio-Rad), and a single clone
was grown in autoinduction media overnight at 37°C to allow
for induction and expression of the tag-MBP fusion proteins
(Studier et al. 2005). Cell lysate was prepared by sonication
of the resuspended cell pellet in the purification binding buffer
corresponding to each resin matrix: 1x PBS (140 mM NaCl,
2.7 mM KCl, 10 mM Na2PO4, 1.8 mM KH2PO4) for GSTrap
columns, and 0.1 M potassium phosphate buffer, 0.1 mM
EDTA, pH 7.2 for Bio-Scale Mini Profinity eXact cartridges. A
total of 5 ml of lysate was used for each purification. Fusion
protein purification was performed according to manufacturer
instructions in a syringe format. Sample and buffer were applied
using a syringe attached to the column. In case of GST-MBP
fusions, a slow flow rate was maintained during loading and
washing (~1 ml/min or 20 drops/min). Elution fractions, 1 ml
each, were collected in 1.5 ml tubes. Elution buffer used for the
GST gene fusion system (GE Healthcare) was 50 mM Tris-HCl,
10 mM reduced glutathione, pH 8.0. Elution buffer for the Profinity
eXact fusion-tag system was 0.1 M potassium phosphate buffer,
0.1 M potassium fluoride, 0.1 mM EDTA, pH 7.2.
Before proceeding to large-scale proteolytic cleavage of
the eluted GST-Th-MBP and GST-TEV-MBP fusion proteins,
small-scale cleavage reactions were conducted to optimize the
enzyme-to-substrate ratio for each of the two proteolytic enymes
— thrombin and AcTEV (data not shown). Thrombin cleavage
was carried out on-column. The eluate was immediately passed
through an inline HiTrap benzamidine FF column to trap the
thrombin protease, and the purified MBP was collected in the
effluent. Removal of the GST tag from the GST-TEV-MBP fusion
was achieved concurrently with buffer exchange by including a
His-tagged AcTEV protease during dialysis of the eluted fusion
protein in glutathione-free buffer (20 mM Tris-HCl, 0.5 mM EDTA,
5 mM DTT). Tag-free MBP was then obtained in the flow-through
fraction after passing the TEV cleavage reaction over a GSTrap
column to remove the released GST, immediately followed by a
HisTrap column to remove the AcTEV protease.
Preparation of tag-free MBP using the Profinity eXact
system was performed according to the standard protocol. The
proteolytic activity of the affinity matrix was activated by applying
2 column volumes (CV) of room temperature 0.1 M sodium
phosphate buffer, pH 7.2, containing 0.1 M sodium fluoride, to the
column and then incubating for 30 min to allow cleavage of the
tag from the fusion protein. Purified, tag-free MBP with a native
N-terminus was released from the column once flow resumed.
Purity and Yield Determinations
Yield of the tag-free purified MBP was estimated from each
purification using A280 absorbance and an extinction coefficient
of 1.61 mg/ml per one A280 unit. Purity was determined by SDSPAGE analysis using Criterion™ 4–20% Tris-HCl gels (Bio-Rad),
followed by staining with Bio-Safe™ Coomassie stain (Bio-Rad)
and image acquisition and analysis using a Molecular Imager®
GS-800™ calibrated densitometer (Bio-Rad) and Quantity One®
1-D analysis software (Bio-Rad).
14
BioRadiations 124
Results and Discussion
We purified MBP proteins using the GST gene fusion and
Profinity eXact fusion-tag systems, monitoring the duration
of the purification, yield, and purity of the tag-free protein.
The GE Healthcare protocol for manual purification was chosen
as the most comparable method to purify milligram quantities of
MBP across the different systems studied.
MBP Purification Using GST-Tag and Enzymatic Tag Removal
We first performed cleavage time-course studies of each enzyme
to optimize the digest conditions. A total of 0.1 mg of
GST-Th-MBP and GST-TEV-MBP was incubated with 1 U of
thrombin or 33, 16, and 8 U of TEV protease. Samples were
removed from the digest mixture at various time points and
analyzed by SDS-PAGE to estimate the yield, and extent of
digestion (for details on experimental conditions, protease
amounts, and incubation times, refer to bulletin 5652). Using
optimized cleavage conditions, preparative amounts (5 ml of
lysate containing approximately 20 mg of fusion protein) of each of
the GST-MBP fusions were processed. Fractions from each step
in the two protocols were resolved using SDS-PAGE analysis,
and results are shown in Figures 1 and 2 for thrombin and TEV
cleavage, respectively. In both cases, the final tag-free MBP
protein was found to be contaminated with GST.
MW, kD
250–
150–
100–
75–
50–
37–
25–
20–
15–
10–
GST-Th-MBP, 66 kD
MBP, 40 kD
GST, 26 kD
1 2 3 4 5 6 7
8 9 10 11 12 13 14 15 16
Fig. 1. GST-Th-MBP fusion purification and on-column cleavage with
thrombin. Lane 1, Precision Plus Protein™ unstained standards; lane 2, lysate;
lane 3, flowthrough; lane 4, wash; lanes 5–14, flow-through fractions from GSTrap
and HiTrap benzamidine FF columns containing tag-free MBP; lane 15, pooled
fractions (lanes 5–14); lane 16, bound components from GSTrap column.
MW, kD
250–
150–
100–
75–
GST-TEV-MBP, 66 kD
50–
37–
MBP, 40 kD
GST, 26 kD
25–
20–
15–
10–
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Fig. 2. GST-TEV-MBP fusion purification and cleavage with TEV
protease. After cleavage, GST and MBP mixture was passed through a
GSTrap column to bind cleaved GST. Collected flowthrough with tag-free MBP
was loaded onto a HisTrap FF column to remove His-tagged AcTEV; MBP was
collected in the flow-through fraction. Lane 1, Precision Plus Protein unstained
standards; lane 2, lysate; lane 3, flowthrough; lane 4, wash; lanes 5–6,
fractions containing GST-TEV-MBP fusion protein; lane 7, pooled fractions
(lanes 5–6); lane 8, cleaved GST-TEV-MBP fusion; lanes 9–12, purified MBP,
flow-through fractions from GSTrap column; lane 13, pooled fractions
(lanes 9–12); lane 14, MBP from flowthrough of HisTrap FF column.
© 2008 Bio-Rad Laboratories, Inc.
TECHNICAL REPORT
Table 1. Summary of MBP purification and cleavage.
Fusion
Construct
GST-MBP, thrombin
GST-MBP, TEV
Profinity eXact MBP
Cleared Lysate,
Starting Material
Purification
Steps
5 ml, 20 mg fusion protein
5 ml, 20 mg fusion protein
5 ml, 20 mg fusion protein
5
8
4
Duration of
Purification
Yield (Cleaved MBP), mg
Purity, %
19 hr
20 hr
50 min
MBP Purification Using the Profinity eXact Fusion-Tag System
Purification of MBP using the Profinity eXact system was a
one-step process. After loading 5 ml of the lysate (~20 mg of
fusion protein) onto the Profinity eXact 1 ml column, the column
was washed with 1 ml of 1 M sodium acetate in binding buffer
(0.1 M potassium phosphate buffer, pH 7.2, 0.1 mM EDTA) and
then with 15 ml of binding buffer. Washed resin was saturated
with 1 ml of the cleavage buffer (binding buffer containing 0.1 M
sodium fluoride) and the column was incubated for 30 min at
room temperature. Tag-free MBP was eluted by applying 5 ml
of cleavage buffer in 1 ml aliquots (Figure 3). The column was
regenerated by stripping the tightly bound Profinity eXact tag
(Kd <100 pM) from the resin, by decreasing the pH to below 2.0
using 3 CV of 0.1 M phosphoric acid.
Table 1 summarizes data for the purification experiments. In
all the parameters used to gauge the success of purification, the
Profinity eXact system performed better than the GST system
coupled to either thrombin or TEV cleavage. The use of the Profinity
eXact tag and purification resin resulted in nearly 2-fold higher MBP
protein yields, when starting from a fixed amount of fusion protein
2.0
2.7
5.0
96.4
96.6
98.0
Concentration of Final Purified Protein, mg/ml
0.16
0.39
0.90
and carrying it through the process to a tag-free form. The lower
yields with protocols using GST tags are presumably due to the
additional purification steps and possible system sensitivities to the
flow rate, which were hard to control in the syringe format. Purity
of MBP proteins using the Profinity eXact system was higher than
the GST-based purifications, with no visible contaminants in SDSPAGE analysis using a 3 μg sample load. The product was not
appreciably contaminated with the affinity tag or bacterial proteins
even at a 10 µg load, as illustrated in Figure 4.
Conclusions
With the Profinity eXact fusion-tag system, fewer steps are
required to reach the tag-free form of the target protein, and the
duration of the purification process is considerably reduced
from nearly a day to less than 1 hr. The use of the Profinity
eXact system also results in the eluted tag-free protein in a
more concentrated form. Unlike the thrombin and TEV cleavage
systems that leave terminal GS and G residues, respectively, MBP
purified with the Profinity eXact system is in its native form and is
amenable to direct use in downstream applications.
References
MW,kD
250–
Abdulaev NG et al., Bacterial expression and one-step purification of an isotopelabeled heterotrimeric G-protein a-subunit, J Biomol NMR 32, 31–40 (2005)
150–
100–
75–
Profinity eXact
MBP fusion,
48 kD
MBP, 40 kD
50–
37–
25–
20–
15–
10–
Profinity eXact tag,
8 kD
1
2
3
4
5
6
7
8
9
10
11
12
Fig. 3. MBP purification using Profinity eXact tag. Lane 1, Precision Plus
Protein unstained standards; lane 2, lysate; lane 3, flowthrough; lane 4, wash;
lanes 5–11, tag-free MBP in elution fractions; lane 12, Profinity eXact tag
(~8 kD), stripped from the column using 0.1 M phosphoric acid.
Araújo A et al., Influence of the histidine tail on the structure and activity of
recombinant chlorocatechol 1,2-dioxygenase, Biochem Biophys Res
Commun 272, 480–484 (2000)
Arnau J et al., Current strategies for the use of affinity tags and tag removal for the
purification of recombinant proteins, Protein Expr Purif 48, 1–13 (2006)
Bucher MH et al., Differential effects of short affinity tags on the crystallization of
Pyrococcus furiosus maltodextrin-binding protein, Acta Crystallogr D Biol Crystallogr
58, 392–397 (2002)
Chant A et al., Attachment of a histidine tag to the minimal zinc finger protein of the
Aspergillus nidulans gene regulatory protein AreA causes a conformational change
at the DNA-binding site, Protein Expr Purif 39, 152–159 (2005)
Fonda I et al., Attachment of histidine tags to recombinant tumor necrosis factoralpha drastically changes its properties, ScientificWorldJournal 2, 1312–1325 (2002)
Goel A et al., Relative position of the hexahistidine tag effects binding properties of
a tumor-associated single-chain Fv construct, Biochim Biophys Acta 1523, 13–20
(2000)
MW, kD
250–
150–
Jenny RJ et al., A critical review of the methods for cleavage of fusion proteins with
thrombin and factor Xa, Protein Expr Purif 31, 1–11 (2003)
100–
75–
50–
37–
MBP, 40 kD
25–
20–
15–
10–
Kim KM et al., Post-translational modification of the N-terminal His tag interferes
with the crystallization of the wild-type and mutant SH3 domains from chicken src
tyrosine kinase, Acta Crystallogr D Biol Crystallogr 57, 759–762 (2001)
Ruan B et al., Engineering subtilisin into a fluoride-triggered processing protease
useful for one-step protein purification, Biochemistry 43, 14539–14546 (2004)
1 2 3
4 5
Fig. 4. Purity analysis of isolated MBP using GST fusion and enzymatic
tag removal or eXact tag fusion and one-step on-column tag removal.
Lane 1, Precision Plus Protein unstained standards; lanes 2–5, MBP protein
purified using different methods; lane 2, purified as GST-fusion, tag cleaved
with thrombin; lane 3, purified as GST-fusion, tag cleaved with AcTEV; lane
4–5, purified as eXact-tag fusion; lanes 2–4 contained 3 μg sample protein per
lane; lane 5 contained 10 μg sample protein per lane.
Visit us on the Web at discover.bio-rad.com Smyth DR et al., Crystal structures of fusion proteins with large-affinity tags,
Protein Sci 12, 1313–1322 (2003)
Studier FW, Protein production by auto-induction in high-density shaking cultures,
Protein Expr Purif 41, 207–234 (2005)
Waugh DS, Making the most of affinity tags, Trends Biotechnol 23, 316–320 (2005)
For an expanded version of this article, request bulletin 5652.
BioRadiations 124
15
MYCN
TP53
Real-Time qPCR as a Tool
for Evaluating RNAi-Mediated Gene Silencing
Real-time quantitative PCR (rt-qPCR) is the method of choice for accurate, sensitive,
and specific quantitation of nucleic acid sequences. Applications of this technology
are numerous, both in molecular diagnostics and in virtually all fields of life sciences,
including gene expression profiling, measurement of DNA copy number alterations,
genotyping, mutation detection, pathogen detection, measurement of viral load,
disease monitoring, and assessment of drug response. Several ingredients are
essential to the successful and reliable completion of an rt-qPCR assay, such as
careful primer design and evaluation, template preparation, the use of a robust
normalization strategy, and accurate data analysis. This article describes how
rt-qPCR can be implemented as a tool to monitor silencing efficiency and
functional effects of RNA interference (RNAi)-mediated gene knockdown, using
examples from our research on neuroblastoma. For detailed information on the
experiments that contributed to this research, including instruments, reagents,
and procedures, request bulletin 5692.
Authors: Tom Van Maerken, Pieter Mestdagh, Sarah De Clercq, Filip Pattyn, Nurten Yigit,
Anne De Paepe, Jean-Christophe Marine, Frank Speleman, and Jo Vandesompele
cover story
Visit us on the Web at discover.bio-rad.com
With the focus of his research in neuroblastoma,
a very deadly form of childhood cancer, Professor
Jo Vandesompele often gets asked if he meets
the children behind the research. His answer:
“No, we see a tube.” In fact, most researchers
spend countless hours with analytical tools,
but little time, if any, interacting with people
affected by disease. That’s why the scientists that
comprise Vandesompele’s lab at Ghent University
in Belgium are introducing a pilot program, where parents of children who
have died or are suffering from neuroblastoma will be invited to speak to
researchers about their experiences.
“Most of us don’t maintain a sense of what we’re doing research for,”
says Vandesompele. “A sample is brought from a hospital lab. We begin
extracting molecules and conducting procedures that have nothing to do
with the child the sample came from, a child who might be dying. There’s
a disconnect there that shouldn’t be.” The parent program is meant to
bridge this disconnect.
The idea sprang from travels to international conferences, where
parents involved in disease-related support groups occasionally give
talks. Vandesompele’s colleagues realized that in terms of motivating
progress toward a cure, even the world’s best scientists can’t match the
words of a parent whose child has died. And it’s not just that parents have
heartbreaking tales to tell. It’s also that they have a passion for raising
money to support research, and that they’re truly interested in what’s
happening in the field.
“Yes, we’re doing science,” says Vandesompele, “but being connected
to the human aspects of research can motivate scientists to be much more
precise, closer to perfect in what we are doing. Passion brings us to a level
unattainable based on intellectual skills alone.”
Soon, at least in Belgium, researchers will begin to be able to match a
name and a face to a test tube.
integrity, electrophoresis and PCR-based methods are available
(Fleige and Pfaffl 2006, Nolan et al. 2006). Figure 1 shows
an electropherogram of high-quality RNA assessed using the
Experion™ automated electrophoresis system. Sharp peaks at
18S and 28S and no nonspecific peaks are desired results when
determining whether or not RNA samples are intact.
45
40
35
30
25
20
15
10
0
20
30
28S
5
18S
From Experimental Design to Analysis of an rt-qPCR Assay
Purity and integrity of the template are critical factors to the
success of an rt-qPCR assay. Several commercial kits are
available for producing clean RNA samples. Contaminants
should be avoided or removed, as they can greatly influence
the reverse-transcription step or the actual PCR. The presence
of PCR inhibitors can be determined by a variety of methods,
including the simple and fast PCR-based SPUD assay (Nolan et
al. 2006). An oligonucleotide target sequence with no homology
to human DNA is spiked into human RNA samples and a
water control at a known concentration. rt-qPCR quantitation
of the oligonucleotide template in both the RNA samples and
the (negative) water control is indicative of possible enzymatic
inhibitors present in the RNA extract. For assessment of RNA
The Many Faces of Disease
Fluorescence
Neuroblastoma and the MYCN and TP53 Cancer Genes
Neuroblastoma is a childhood cancer derived from precursor
cells of the adrenosympathetic system, arising in the adrenal
medulla or in sympathetic ganglia. Although a relatively rare form
of cancer, neuroblastoma is among the most fatal of childhood
diseases. Indicators of mortality include age at diagnosis (the
outcome for children with neuroblastoma is most favorable when
diagnosed before the age of one year, even when the disease
has metastasized), tumor stage, and level of MYCN protein
activity (the most fatal clinicogenetic subtype of neuroblastoma
is characterized by amplification of the MYCN oncogenic
transcription factor) (Vandesompele et al. 2005). The mechanisms
by which this transcription factor exerts its oncogenic activity and
confers an unfavorable prognosis are poorly understood.
Another intriguing feature of neuroblastoma is the remarkably
low frequency of TP53 mutations at diagnosis (Tweddle et al.
2003). Previous studies have shown that reactivation of the
p53 pathway by the selective small-molecule MDM2 antagonist
nutlin-3 constitutes a promising novel therapeutic approach
for neuroblastoma (Van Maerken et al. 2006). To gain insight
into the mechanism of action of these two pivotal genes in
neuroblastoma pathogenesis and to create model systems for
future exploration of targeted therapeutics in relationship to
MYCN and TP53 status, RNAi was used as an experimental
tool for suppressing the expression of these genes. Because
neuroblastomas are notoriously difficult to transfect, we
introduced an siRNA model with accurate detection of silencing
efficiency and the resulting effects. In particular, for study of
MYCN function, this model is believed to be more relevant,
because traditional systems with forced overexpression of this
gene in single-copy cells seem to lack the proper cellular context
to mimic endogeneous amplification and hyperactivity. Our final
goal is to disentangle MYCN’s transcriptional web, in order to
interfere with its oncogenic signaling pathways, while leaving the
beneficial pathways unaltered.
40
50
Time, sec
60
Fig. 1. Electropherogram generated using the Experion system depicting
high-quality RNA sample.
BioRadiations 124
17
cover story
rt-qPCR for Assessment of siRNA Silencing Efficiency:
Anti-MYCN siLentMer™ siRNA Duplexes
Human IMR-32 neuroblastoma cells were transfected with
different anti-MYCN siLentMer siRNA duplexes or a nonspecific
control siRNA, and the MYCN transcript level was determined
48 hours posttransfection by rt-qPCR. Our results indicate the
importance of primer location for evaluation of siRNA silencing
efficiency, in agreement with a previous independent report
(Shepard et al. 2005). The target mRNA sequence is cleaved
18
BioRadiations 124 A
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101
0
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200
-d(RFU)/dT
150
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50
0
C
60
65
70
75
80
Temperature, °C
85
90
95
34
PCR efficiency 98.6 ± 0.4%
32
30
Cq
To control for inevitable experimental variation due to factors
such as the amount and quality of starting material, enzymatic
efficiencies, and overall cellular transcriptional activity, use of
a reliable normalization strategy in which these factors are
taken into account is necessary. In principle, internal reference
genes offer the best way to deal with the multiple sources of
variables that might exist between different samples. A truly
accurate normalization can only be achieved when multiple
reference genes are utilized, as use of a single reference gene
results in relatively large errors in a considerable proportion of
the sample set (Vandesompele et al. 2002). Care should be
taken when selecting the genes to be used for normalizing the
expression levels since no universal set of always-applicable
reference genes exists. Different sample origins and experimental
manipulations might require another set of genes to be used as
reference genes. The selection and validation of reference genes
can be done using the geNorm algorithm (see sidebar), which
determines the most stable genes from a set of tested candidate
reference genes in a given sample panel and calculates a
normalization factor (Vandesompele et al. 2002).
Bioinformatics-based quality assessment of newly designed
rt-qPCR primers can considerably improve the likelihood of
obtaining specific and efficient primers. A number of quality
control parameters have been integrated in Ghent University’s
RTPrimerDB in silico assay evaluation pipeline (Pattyn et al.
2006). This pipeline allows a streamlined evaluation of candidate
primer pairs, with automated BLAST specificity search, prediction
of putative secondary structures of the amplicon, indication of
which transcript variants of the gene of interest will be amplified,
and search for known SNPs in the primer annealing regions.
This in silico evaluation, however, does not preclude the need
for experimental validation after synthesis of the primers. Ideally,
experimental evaluation addresses specificity, efficiency, and
dynamic range of the assay using a broad dilution series of
template (Figure 2).
Processing and analysis of the raw rt-qPCR data represent a
multistep computational process of averaging replicate
CT values, normalization, and proper error propagation
along the entire calculation track. This process might prove
cumbersome and deserves equal attention as the previous
steps in order to get accurate and reliable results. This final
procedure has been automated and streamlined in Biogazelle’s
qBasePlus software (www.biogazelle.com, see sidebar), a
dedicated program for the management and analysis of
rt-qPCR data (Hellemans et al. 2007).
28
26
24
22
0
1
10 log starting quantity
10
100
Fig. 2. Experimental validation of newly designed rt-qPCR primers. A, PCR
efficiency and dynamic range of the rt-qPCR assay was tested using a 4-fold serial
dilution of six points of reverse transcribed human qPCR reference total RNA (64 ng
down to 62.5 pg) and TP53_P2 primers; B, specificity of the TP53_P2 primers was
assessed by generating a melting curve of the PCR product; C, standard curve
and PCR efficiency estimation (including the error) according to the qBasePlus
software. Cq, quantitation cycle value generated in RDML software (see sidebar).
by the RNA-induced silencing complex (RISC) near the center
of the region complementary to the guiding siRNA (Elbashir
et al. 2001). Complete nucleolytic degradation of the resulting
fragments is not always guaranteed, which might result in
underestimation of siRNA silencing efficiency if primers are used
that do not span the siRNA target sequence, as observed for
this gene (Figure 3).
© 2008 Bio-Rad Laboratories, Inc.
Programming Progress
The year 2000 is a milestone that symbolizes
movement toward the height of progress, particularly
in science and technology. But back in 2000,
Professor Jo Vandesompele (then a doctorate student
beginning what would become a career devoted to
the study of the genetics of neuroblastoma at Ghent
University in Belgium) was attempting to conduct
sophisticated analysis of genetic research results with
rudimentary tools. “In 2000,” says Vandesompele,
“evaluating candidate reference genes with respect to their expression stability
was impossible.” Moreover, the concept of accurate normalization using multiple
reference genes did not exist. “The problem of housekeeping gene variability was
significantly underestimated at that time,” he explains. In addition, he remembers
calculating qPCR analyses by hand with Excel software, “a slow and error-prone
process that required insight into mathematics and various quantitation models.”
With no other solutions available, Vandesompele and colleagues set out
to develop the first of many software, web, and database tools that continue
to help drive progress in genetic research — not just in their lab, but in labs
across the world. Launched in 2002, geNorm software is a tool used for the
identification of stably expressed reference genes (http://medgen.ugent.
be/genorm/). This launch was quickly followed by development of RTPrimerDB
in 2003, a real-time PCR primer and probe database containing published and
validated assays, as well as an integrated in silico PCR assay evaluation pipeline
(http://medgen.ugent.be/rtprimerdb/).
In 2004, Jan Hellemans, a PhD student in the University’s Center for
Medical Genetics laboratory, began automating the arduous mathematical
computations associated with qPCR analysis by programming a few simple
macros in Excel. These initial macros evolved into the qBase 1.0 qPCR data
analysis software package (http://medgen.ugent.be/qbase/). Since then,
several thousand copies have been downloaded and used worldwide. In
2007, the Excel version began being phased out by qBasePlus, a professional
Java-based application that runs 20 times faster and is more intuitive than the
original platform. All current versions of these programs are available at no
charge, and even this latest tool developed by Biogazelle, a Ghent University
spin-off company, will offer both free and reasonably priced licensing packages.
That these programs have revolutionized the synthesis of real-time PCR data
is unquestionable. What is surprising, at least to Vandesompele, is that “what
were once just tools to measure gene expression levels in scarce tumor biopsies
from children with neuroblastoma in our laboratory, have now grown in scope to
form an independent research line.”
And while researchers in this lab continue to try to find new ways to combat
neuroblastoma, so will they continue to discover tools to aid achievement of
reliable and meaningful results through bioinformatics. Future plans include
establishment of an international consortium to finalize a standard exchange
format for real-time PCR data (coined RDML, previews of this effort can be seen
at www.rdml.org). In addition, they are developing a web-based primer design
portal that will enable researchers to design high-quality assays in a highthroughput environment.
IMR-32 Cells
A
siRNA 1
P1
coding
P2
UTR
P
P3
PCR amplicon
P4
siRNA 1
siRNA 2
P5
siRNA 2
Relative mRNA expression of TP53
120 B
TP53_P1 primers
TP53_P2 primers
100 80 60 40 20 0-
Primers
P1
P2
P3
P4
P5
0-
Silencing, %
20 -
40 -
60 -
80 -
100 -
Fig. 3. Importance of primer location for rt-qPCR assessment of siRNA
silencing efficiency. A, schematic representation of the MYCN mRNA
structure with location of siRNA targeted sequences and primer binding sites;
B, percentage silencing of MYCN gene expression measured by five different
primer pairs (P1–P5) in IMR-32 cells 48 hr posttransfection with anti-MYCN
siLentMer siRNA duplexes (siRNA 1 or siRNA 2), compared to cells transfected
with a nonspecific control siRNA.
Visit us on the Web at discover.bio-rad.com
NGP Cells
140 Relative mRNA expression of TP53
TP53_P1 primers
TP53_P2 primers
120 100 80 60 40 20 0LV-m-p53 infection
LV-h-p53 infection
Fig. 4. Assessment of shRNA-mediated TP53 knockdown efficiency by
rt-qPCR. IMR-32 and NGP cells were infected with a lentivirus carrying an shRNA
construct specific for either the human TP53 gene (LV-h-p53) or the murine Trp53
gene (LV-m-p53) as a control. Efficiency of TP53 gene silencing was evaluated by
rt-qPCR using two different primer pairs (TP53_P1 and TP53_P2). Bars indicate
mRNA expression levels of TP53 relative to the respective LV-m-p53 cells; error
bars depict standard error of the mean (duplicated PCR reactions for TP53 and
three reference genes).
BioRadiations 124
19
cover story
Use of a high-performance real-time qPCR system is important to accurately
measure the effectivity of your siRNA knockdown. The CFX96™ real-time
PCR detection system (used in the experiments discussed in this article)
builds on the power and flexibility of the C1000™ thermal cycler, adding an
easy-to-install interchangeable reaction module to create an exceptional
real-time PCR system.
The system’s thermal performance combined with an innovative optical design
ensure accurate, reliable data. The powerful yet intuitive software accelerates
every step of your real-time PCR research, shortening the time between getting
started and getting great results.
The CFX96 system’s solid-state optical technology (six filtered LEDs and six
filtered photodiodes) provides sensitive detection for precise quantitation
and target discrimination. Scanning just above the sample plate, the optics
shuttle individually illuminates and reads fluorescence from each well with
high sensitivity and no crosstalk. The optical system always collects data from
all wells during data acquisition, so you can enter or edit well information on
your own schedule.
With the CFX96 system, you can:
• Be up and running fast — quick
installation and factory-calibrated
optics let you set up the system
in seconds
• Perform more experiments — fast
thermal cycling produces results in
<30 minutes
• Save research time — thermal
gradient feature lets you optimize
reactions in a single experiment
• Minimize sample and reagent
usage — reliable results are
obtained with sample volumes as
low as 10 µl
• Analyze results when and where
you want — software can send
e-mail notification with
attached data file when
the run is finished
Six-channel
optics shuttle of
the CFX96 system.
20
BioRadiations 124 • Trust your results — Security
Edition software integrates
the CFX96 system with good
laboratory practice (GLP)
standards for data collection and
analysis
• Expand your throughput when
you need to — up to 4 instruments
can be controlled by a single
computer
Relative mRNA expression
12
10
8
6
4
2
0
0
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16
Nutlin-3, µM
shRNA construct LV-h-p53
IMR-32
Cell type
0
8
16
LV-m-p53
IMR-32
0
8
16
LV-h-p53
NGP
0
8
16
LV-m-p53
NGP
0
8
16
LV-m-p53
IMR-32
0
8
16
LV-h-p53
NGP
0
8
16
LV-m-p53
NGP
8
16
LV-h-p53
NGP
0
8
16
LV-m-p53
NGP
8
16
LV-h-p53
NGP
0
8
16
LV-m-p53
NGP
B. MDM2 expression
Relative mRNA expression
8
7
6
5
4
3
2
1
0
0
8
16
Nutlin-3, µM
shRNA construct LV-h-p53
IMR-32
Cell type
C. TP53 expression (using TP53_P1 primers)
1.20
Relative mRNA expression
Designed for the Way You Want to Work
A. BBC3 (PUMA) expression
1.00
0.80
0.60
0.40
0.20
0.00
0
8
16
Nutlin-3, µM
shRNA construct LV-h-p53
IMR-32
Cell type
0
8
16
LV-m-p53
IMR-32
0
D. TP53 expression (using TP53_P2 primers)
1.20
Relative mRNA expression
rt-qPCR for Monitoring of shRNA Silencing Efficiency
and Functional Effects: Lentiviral-Mediated shRNA
Knockdown of TP53
For generation of stable TP53 knockdown variants of
neuroblastoma cell lines with wild-type p53, we infected IMR32 and NGP cells with a lentiviral vector encoding an shRNA
directed specifically against human TP53 (LV-h-p53) or against
the murine Trp53 gene (LV-m-p53, negative control). rt-qPCR
analysis with two different primer pairs demonstrated that
expression of TP53 was reduced by 81–87% in IMR-32-LV-h-p53
cells and by 92–94% in NGP-LV-h-p53 cells compared to the
respective LV-m-p53 controls (Figure 4). Functionality of the TP53
knockdown variants was validated by rt-qPCR and cell viability
analysis after treatment of the cells with nutlin-3, a small-molecule
compound that selectively disrupts the interaction between p53
and its negative regulator MDM2, resulting in stabilization and
1.00
0.80
0.60
0.40
0.20
0.00
0
8
16
Nutlin-3, µM
shRNA construct LV-h-p53
IMR-32
Cell type
0
8
16
LV-m-p53
IMR-32
0
Fig. 5. Functional validation of shRNA-mediated TP53 knockdown through
rt-qPCR analysis of transcript levels of p53-regulated genes after nutlin-3
treatment. IMR-32 and NGP cells were infected with a lentiviral vector encoding
an shRNA directed specifically against either the human TP53 gene (LV-h-p53)
or the murine Trp53 gene (LV-m-p53). Cells were treated with 0, 8, or 16 µM
nutlin-3 for 24 hr, and expression of BBC3 (PUMA) (A), and MDM2 (B),
p53-regulated genes, and TP53 was determined by rt-qPCR. Two different
primer pairs (TP53_P1 and TP53_P2) were used for quantitation of TP53
transcript levels (C,D). Bars indicate mRNA expression levels relative to the
respective vehicle-treated (0 µM nutlin-3) LV-m-p53 infected cells, mean of two
different rt-qPCR measurements; error bars show standard error of the mean.
© 2008 Bio-Rad Laboratories, Inc.
cover story
A. Uninfected IMR-32 cells
B. IMR-32 cells infected with LV-h-p53
80
60
40
20
1
10
Nutlin-3, µM
20
1
10
Nutlin-3, µM
80
60
40
20
1
10
Nutlin-3, µM
100
40
20
1
10
Nutlin-3, µM
100
F. NGP cells infected with LV-m-p53
100
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60
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0
80
60
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100
Cell viability, %
Cell viability, %
40
E. NGP cells infected with LV-h-p53
100
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60
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100
D. Uninfected NGP cells
80
Cell viability, %
0
100
Cell viability, %
100
Cell viability, %
Cell viability, %
100
C. IMR-32 cells infected with LV-m-p53
1
10
Nutlin-3, µM
100
80
60
40
20
0
1
10
Nutlin-3, µM
100
Fig. 6. Functional validation of shRNA-mediated TP53 knockdown through cell viability analysis after treatment of IMR-32 and NGP cells with nutlin-3.
Effect of nutlin-3 on viability of uninfected cells (A, D), LV-h-p53 infected cells (B, E) and LV-m-p53 infected cells (C, F). Exponentially growing cells were exposed to
0–32 µM of nutlin-3 for 24 (—), 48 (—), and 72 (—) hr, and the percentage cell viability with respect to vehicle-treated cells was determined. Error bars indicate standard
deviation of mean cell viability values of three independent experiments.
accumulation of the p53 protein and activation of the p53 pathway
(Vassilev et al. 2004). Transactivation of p53 target genes such
as BBC3 (PUMA) and MDM2 by nutlin-3 and nutlin-3 induced
downregulation of TP53 mRNA level, a consequence of the ability
of the p53 protein to negatively regulate its own transcriptional
expression after accumulation (Hudson et al. 1995), were largely
prevented by lentiviral-mediated expression of shRNA against
human TP53 (Figure 5). At the cellular level, silencing of human
TP53 severely attenuated the nutlin-3 induced reduction in cell
viability observed in nontransduced parental cells, in contrast to
control infection with LV-m-p53 (Figure 6). These results firmly
demonstrate potent and selective impairment of p53 function in
IMR-32-LV-h-p53 and NGP-LV-h-p53 cells.
Conclusions
rt-qPCR analysis provides a convenient and reliable method for
evaluation of knockdown efficiency and functional consequences
of RNAi-mediated gene silencing. Successful application of
this monitoring tool requires careful attention to be given to all
different steps in the rt-qPCR workflow, including primer design
and evaluation, template preparation, normalization strategy, and
data analysis, as discussed in this article.
Similar studies will be conducted in the future to evaluate
results achieved using additional cell lines and varying
combinations of multiple siLentMer duplexes, durations of effect,
and concentrations of active siLentMer duplexes.
References
Elbashir SM et al., RNA interference is mediated by 21- and 22-nucleotide RNAs,
Genes Dev 15, 188–200 (2001)
Fleige S and Pfaffl MW, RNA integrity and the effect on the real-time qRT-PCR
performance, Mol Aspects Med 27, 126–139 (2006)
Hellemans J et al., qBase relative quantification framework and software for
management and automated analysis of real-time quantitative PCR data, Genome
Biol 8, R19 (2007)
Hudson JM et al., Wild-type p53 regulates its own transcription in a cell-type
specific manner, DNA Cell Biol 14, 759–766 (1995)
Nolan T et al., Quantification of mRNA using real-time RT-PCR, Nat Protoc 1,
1559–1582 (2006)
Nolan T et al., SPUD: a quantitative PCR assay for the detection of inhibitors in
nucleic acid preparations, Anal Biochem 351, 308–310 (2006)
Pattyn F et al., RTPrimerDB: the real-time PCR primer and probe database, major
update 2006, Nucleic Acids Res 34, D684–D688 (2006)
Shepard AR et al., Importance of quantitative PCR primer location for short
interfering RNA efficacy determination, Anal Biochem 344, 287–288 (2005)
Tweddle DA et al., The p53 pathway and its inactivation in neuroblastoma, Cancer
Lett 197, 93–98 (2003)
Vandesompele J et al., Unequivocal delineation of clinicogenetic subgroups and
development of a new model for improved outcome prediction in neuroblastoma,
J Clin Oncol 23, 2280–2299 (2005)
Vandesompele J et al., Accurate normalization of real-time quantitative RT-PCR
data by geometric averaging of multiple internal control genes, Genome Biol 3,
RESEARCH0034 (2002)
Van Maerken T et al., Small-molecule MDM2 antagonists as a new therapy
concept for neuroblastoma, Cancer Res 66, 9646–9655 (2006)
Vassilev LT et al., In vivo activation of the p53 pathway by small-molecule
antagonists of MDM2, Science 303, 844–848 (2004)
Grant support: the Fund for Scientific Research – Flanders (FWO) grants
011F4004 (T. Van Maerken, Research Assistant), G.1.5.243.05 (J. Vandesompele)
and G.0185.04; GOA grant 12051203; grants from the Belgian Foundation
against Cancer (S. De Clercq), the Ghent Childhood Cancer Fund, and the Ghent
University Research grant (B.O.F.) 01D31406 (P. Mestdagh).
Contact information: Jo Vandesompele, Center for Medical Genetics, Ghent
University Hospital, MRB, De Pintelaan 185, 9000 Ghent, Belgium. Phone: 32-9332-5187; Fax: 32-9-332-6549; E-mail: [email protected]
Visit us on the Web at discover.bio-rad.com
BioRadiations 124
21
TECHNICAL REPORT
Simple and Rapid Optimization of Transfections Using Preset
Protocols on the Gene Pulser MXcell™ Electroporation System
Joseph Terefe, Maxinne Pineda, Elizabeth Jordan, Luis Ugozzoli, Teresa Rubio, and Michelle Collins, Bio-Rad Laboratories, Inc., Hercules, CA 94547 USA
Introduction
The ability to modulate gene expression is essential to achieving
a better understanding of gene function. The transfer of
exogenous nucleic acids, such as plasmids or siRNAs, into
mammalian cells is an important tool for the study and analysis
of gene function, expression, regulation, and mutation, and has
advanced basic cellular research, drug target identification, and
validation. Electroporation is a well-established gene transfer
method and an effective means of transferring nucleic acids
into cells. Finding optimal transfection conditions is crucial in
a gene transfer experiment to obtain the highest transfection
efficiency with maximum cell viability. There are many parameters
that affect the efficiency of electroporation, including waveform
(exponential or square-wave), voltage, capacitance, resistance,
pulse duration, and number of pulses.
The Gene Pulser MXcell electroporation system and Gene Pulser® electroporation buffer were designed to address
the need for attaining the highest transfection efficiency and cell
viability in mammalian cells. The Gene Pulser MXcell system is
an open platform that provides the flexibility for creating specific
protocols and varying parameters, including the unique option
of providing both square and exponential waveforms in the
same instrument. Preset and gradient protocols allow easy
optimization of all parameters. Preset protocols are defined
for whole or partial (mini protocol) plates, depending on cell
availability. A preset protocol decision tree is shown in Figure 1.
Here, we demonstrate using Gene Pulser electroporation
buffer with preset protocols to achieve maximum transfection
efficiency and cell viability.
Existing Protocol
New Protocol
Quick confirmation that protocol is
optimal; known waveform
New cell line or cell type,
no electroporation information;
unknown waveform
Cell
number
limiting
<5 x 106
Opt mini
96-well/
Exp
Opt mini
96-well/
Sqr
Cell
number
nonlimiting
>5 x 106
Opt mini
96-well/
Sqr, NP, D
96-well/
Exp,
Vgrad,
Cgrad
96-well/
Sqr,
Vgrad,
Dgrad
Multiple
cell lines
Uniform
96-, 24or 12-well/
Exp, Sqr
Opt mini
96-well/
Exp
Cell
number
limiting
<5 x 106
Cell
number
nonlimiting
>5 x 106
Opt mini
96-well/
Exp, Sqr
Opt 96-,
24-, 12-well/
Exp, Sqr
Opt mini
96-well/Sqr
Opt mini
96-well/
Sqr, NP, D
Optimized
Protocol
Fig. 1. Gene Pulser MXcell system preset protocol decision tree.
22
BioRadiations 124
96-well/
Exp,
Vgrad,
Cgrad
96-well/
Sqr, Vgrad,
Dgrad
Methods
Cell Lines, Plasmids, and siRNAs
Cells were obtained from American Type Culture Collection
(ATCC). HeLa cells (#CCL-2) were cultured in Dulbecco’s modified
Eagle’s medium containing 1 mM sodium pyruvate, 0.1 mM
nonessential amino acids, and 10% fetal bovine serum (FBS).
CHO-K1 cells (#CCL-61) were cultured in Ham’s F-12K medium
supplemented with 10% FBS.
For optimization of siRNA delivery, fluorescently labeled
siLentMer™ Dicer-substrate siRNA duplexes, targeting the
glyceraldehyde-3-phosphate dehydrogenase gene (GAPDH) or negative controls, were used. Negative control and luciferase-specific siRNAs were also used. For the optimization
of plasmid delivery, a plasmid DNA expressing the luciferase
gene (pCMVi-Luc) was used.
Electroporation
Cells were used at a density of 1 x 106 cells/ml, unless indicated
otherwise. Electroporation was performed in either 96- or 24-well
electroporation plates. After harvesting by trypsinization, cells
were washed with phosphate buffered saline (PBS), counted,
and the appropriate number of cells per experiment was
aliquoted. Before electroporation, cells were resuspended in
Gene Pulser electroporation buffer, and plasmid DNA (10 μg/ml)
or siLentMer siRNA (100 nM) was added to the mix. Then, the
cells were transferred to electroporation plates (96- or 24-well)
and pulsed with the Gene Pulser MXcell electroporation system.
Electroporated cells were transferred to tissue culture plates
containing the appropriate growth medium and incubated at
37°C for 24 hr. Prior to harvesting, cell viability was assessed
by visual inspection and by comparing cell confluency between
different conditions.
Analysis of Transfection
Cells electroporated with the pCMVi-Luc plasmid were assayed
for luciferase activity. Cells electroporated with fluorescently
labeled siRNA were washed with PBS, trypsinized, pelleted,
and resuspended in PBS for analysis by flow cytometry or
fluorescence microscopy. Delivery of the GAPDH siLentMer
siRNA was also assessed by real-time quantitative (rt-qPCR). Total
RNA was extracted from electroporated cells (Aurum™ total RNA
kit) and used for cDNA synthesis (iScript™ cDNA synthesis kit),
followed by rt-PCR using gene-specific primers and iQ™ SYBR®
Green supermix on the iQ™5 real-time PCR detection system (all
from Bio-Rad) to analyze for gene silencing.
© 2008 Bio-Rad Laboratories, Inc.
TECHNICAL REPORT
Results and Discussion
siRNA Delivery Into HeLa Cells
To define the best conditions for siRNA delivery, HeLa cells were
electroporated on the Gene Pulser MXcell system with a negative
control or GAPDH-specific siLentMer siRNA using the preset
protocol Opt mini 96-well/Exp, Sqr in a 96-well format. This
protocol uses three square-wave and three exponential decay
conditions in six well sets as shown in Figure 2A. Gene silencing
was used as a measure of the transfection efficiency for siRNA
delivery (Figure 2B, C). Using this protocol, conditions in well set 2 (250 V, 2,000 µF, 20 ms) were found to be optimal. Cell viability
was high as measured by cell confluency, and a greater than 95%
reduction in transcript levels was observed in cells electroporated
with siRNA targeting GAPDH compared to those electroporated
with the negative control.
Plasmid Delivery Into HeLa Cells
To find the best electroporation conditions for plasmid delivery into HeLa cells, the preset protocol Opt 24-well/Exp, Sqr (Figure 3A) was applied using a 24-well electroporation plate. This
protocol delivers either a voltage or capacitance gradient with an
exponential waveform to the top half of the plate, and either a
voltage or duration gradient to the bottom half of the plate using a
square-wave protocol. Transfection efficiency, indicated by relative
light unit (RLU) values, was double in the exponential-decay
protocol compared to the square-wave protocol (Figure 3B, C).
Cell density was also higher for the exponential-decay than for the
square-wave protocols 24 hr after electroporation. Together, these
results indicate that the better protocol for electroporating HeLa
cells with this plasmid DNA is an exponential-decay waveform
(200 V and 350 µF or 250 V and 200 µF).
A
A
EXP
SQR
EXP
SQR
B
100
*
*
96
B
20,000
94
92
90
88
Cell viability 200 250 300 Square-wave voltage, V
350 500 750
Exponential decay capacitance, µF
95%
95%
95%
80%
90%
12,000
8,000
4,000
0
35%
150
200
250
300
350
450
Voltage gradient, V (350 µF)
200
250
350
500
750 1,000
Capacitance gradient, µF (250 V)
Cell viability 100% 90% 80% 50% 10% 5%
C
70% 70% 70% 55% 15% 5%
C
10,000
103
8,000
RLU
PCR baseline-subtracted curve fit RFU
*
*
16,000
RLU
% Silencing
98
102
6,000
4,000
2,000
0
5
10
15
20 25
Cycle
30
35
40
45
Fig. 2. Preset protocol for siRNA delivery into HeLa cells. A, schematic of the
partial-plate preset protocol Opt mini 96-well/Exp, Sqr used in the experiment
showing the electroporation parameters and well sets used. Conditions shown in row
A are applied to all 4 wells in the column; B, percentage of GAPDH silencing, which
is calculated by comparing GAPDH expression levels in cells electroporated with the
negative control to that of cells electroporated with siRNA targeting GAPDH. The best
conditions for the square-wave and exponential decay protocols are indicated by
asterisks; C, qPCR traces from knockdown experiments. GAPDH (—) and negative
control (—) qPCR traces from the best square-wave protocol (250 V, 2,000 µF, 20 ms). Associated table shows resulting cell viability for each change in condition.
RFU, relative fluorescent units.
Visit us on the Web at discover.bio-rad.com 0
150
200
250
300
350
Voltage gradient, V (20 ms)
450
5
10
15
20
25
30
Duration gradient, ms (250 V)
Cell viability 100% 65% 40% 20% 10% 0% 100% 55% 30% 30% 40% 40%
Fig. 3. Optimization of plasmid electroporation in HeLa cells in a 24-well
format. A, schematic of the preset protocol Opt 24-well/Exp, Sqr used in the
experiment showing the exponential-decay electroporation parameters for each
column in rows A–D and square-wave parameters for each column in rows E–H;
B, results from the preset exponential decay protocol, which allows for a voltage
gradient (n) and a capacitance gradient (n); C, results for the square-wave
protocol, which allows for a voltage gradient (n) and a pulse duration gradient (n).
Optimal electroporation conditions (B) are marked by asterisks. Associated tables
show resulting cell viability for each change in condition. RFU, relative fluorescent units.
BioRadiations 124
23
TECHNICAL REPORT
A
C
Voltage gradient
Voltage gradient
Duration gradient
Duration gradient
D
B
70,000
180,000
60,000
150,000
120,000
40,000
*
30,000
RLU
RLU
50,000
60,000
20,000
30,000
10,000
0
200
250
300
Voltage gradient, V (20 ms)
Cell viability 90,000
90%
70%
45%
15
20
25
Duration gradient, ms (250 V)
85%
75%
80%
0
100
200
300
400
Voltage gradient, V (20 ms)
Cell viability 100%
90%
50%
10
15
20
30
Duration gradient, ms (250 V)
5%
90%
90%
70%
60%
Fig. 4. Optimization of plasmid electroporation in CHO cells. A schematic of the preset protocol used in each experiment is shown above the results chart. The partial-plate
preset protocol Opt mini 96-well/Sqr (A) and whole-plate protocol Opt 96-well/Sqr, NP, D (C) were performed on 96-well electroporation plates. The optimal electroporation conditions
are defined by the highest RLU values and the highest cell densities (marked by an asterisk) (B, D). Associated tables show resulting cell viability for each change in condition.
Plasmid Delivery in CHO Cells
Previous electroporation conditions in the Gene Pulser Xcell™
single cuvette system, indicated that the highest transfection efficiency for CHO cells is obtained using square-wave protocols.
In the following experiments, different preset square-wave
protocols were applied to CHO cells to determine the optimal
electroporation conditions for plasmid delivery in CHO cells. The
preset protocol Opt mini 96-well/Sqr (Figure 4A) was applied
first. This protocol applies a square wave and generates either
a voltage or duration gradient for six well sets. Although 300 V
yielded the highest luciferase activity, cell viability was only 45%.
Lower voltage conditions (250 V) resulted in greater cell viability,
but lower luciferase activity.
A final experiment in which voltage and duration were varied
was performed in a 96-well plate (Figure 4C). The results from
this experiment further verified those already obtained. The
optimal voltage was 250 V and duration was 20–30 msec.
24
BioRadiations 124
Conclusions
Preset protocols on the Gene Pulser MXcell electroporation
system allow rapid, thorough optimization of electroporation
parameters to improve transfection efficiency of siRNA and
plasmid DNA in mammalian cells. Preset protocols were
created to allow many factors that affect electroporation to be
tested simultaneously. The data shown exemplifies how preset
protocols can be used for optimizing electroporation conditions
for the mammalian cell line of interest. Both mini- and wholeplate preset protocols utilizing 96- or 24-well electroporation
plate formats were used to electroporate siRNA targeting
human GAPDH into HeLa, plasmid (pCMV-iLuc), or CHO cells
using exponential-decay or square-wave pulses. The data also
demonstrate the benefits of fine-tuning or optimizing transfection
experiments, which results in significantly greater transfection
efficiency and cell viability.
For additional copies of this article, request bulletin 5687.
© 2008 Bio-Rad Laboratories, Inc.
TECHNICAL REPORT
Effect of PMA on Phosphorylation of Cx43: A Quantitative Evaluation
Using Blotting With Multiplex Fluorescent Detection
Lily Woo,1 Kevin McDonald,1 Marina Pekelis,1 James Smyth,2 and Robin Shaw,2
1
Bio-Rad Laboratories, Inc., Hercules, CA 94547 USA,
2
University of California, San Francisco, Cardiovascular Research Institute, San Francisco, CA 94143 USA
Introduction
Cardiac action potentials are normally transmitted through
intercellular gap junctions, which consist primarily of the
phosphoprotein connexin 43 (Cx43). Cx43 has a relatively short
half-life of less than 3 hours, which facilitates rapid changes in
cell-to-cell coupling in response to various stimuli (Beardslee
et al. 1998). Downregulation of myocardial Cx43 is observed
following ischemia, resulting in reduced dissemination of
potentially harmful factors via gap junctions (Saffitz et al. 2007).
Protein kinase C (PKC) is a well-documented stress sensor, and
PKC-mediated phosphorylation of Cx43 reduces gap junction
permeability and flags the Cx43 molecule for internalization and
degradation following ischemia (Girao and Pereira 2003, Laird
2005, Lampe et al. 2000). Phorbol 12-myristate 13-acetate
(PMA) is a potent activator of PKC and is utilized in this study to
simulate a stress response and induce phosphorylation of
Cx43 in the murine cardiomyocyte cell line HL-1 (Claycomb
et al. 1998, Liu and Heckman 1998). The phosphorylation
status of Cx43 at serine 368 (Ser368) as a response to PMA
treatment was evaluated.
In this study, changes in Cx43 levels and phosphorylation
were quantitatively evaluated using western blotting
methodology with fluorescent detection. Data demonstrate the
ability to detect both protein standards and sample proteins
on a blot in a single image capture session using fluorescent
signals from multiple color channels. This fluorescent multicolor
imaging approach provides a simplified and robust western
blotting workflow that allows a shorter protein detection process
and results in high-quality quantitative data, including molecular
weight (MW) estimation of sample proteins directly from a blot.
Methods
HL-1 cells were maintained in Claycomb medium
(Sigma-Aldrich Co.), supplemented with 10% fetal bovine
serum (Invitrogen Corporation), 100 U/ml penicillin,
100 μg/ml streptomycin (Invitrogen), 0.1 mM norepinephrine
(Sigma-Aldrich), and 2 mM L-glutamine (Invitrogen), and
maintained at 37°C, 5% CO2, 95% air. Cells were cultured in
100 mm cell culture dishes (Corning, Inc.), coated with gelatin
and fibronectin (Sigma-Aldrich). Confluent monolayers of cells
were treated with 1 μM PMA (Sigma-Aldrich) for 15, 30, 45,
and 60 min. Control cells were treated with vehicle (DMSO,
Visit us on the Web at discover.bio-rad.com Fisher Scientific) for 60 min, and cells were sampled at the
end of each treatment, starting from time 0. During sampling,
cells were washed with 5 ml Dulbecco’s phosphate buffered
saline (PBS) (Invitrogen) on ice, lysed in 150 μl RIPA lysis
buffer, scraped, and transferred to Eppendorf tubes. Lysates
were sonicated and centrifuged at 13,000 rpm at 4°C. Protein
concentrations were determined using the DC™ protein assay.
Proteins were resolved at a concentration of 30 μg/well
using SDS-PAGE and transferred to FluoroTrans PVDF lowfluorescence membranes (Pall Corporation). Membranes were
rinsed in TNT buffer twice, blocked for 1 hr at room temperature
(RT) in TNT buffer containing 5% nonfat dried milk, washed
twice in TNT, and incubated overnight at 4°C with rabbit antiphospho Cx43 Ser368 (Cell Signaling Technology, Inc.; 1:500 in
TNT containing 5% BSA). After incubation, membranes were
washed 3 x 5 min in TNT to remove unbound antibody and
probed with mouse total anti-Cx43 (Sigma-Aldrich; 1:1,000)
and rat anti-tubulin (Abcam Inc.; 1:1,000) for 2 hr at RT in TNT
buffer containing 5% nonfat dried milk. Unbound antibody
was removed by rinsing twice and washing 3 x 5 min in
TNT. Membranes were incubated in the dark with secondary
antibodies: goat anti-rabbit Alexa Fluor 488, goat anti-rat
Alexa Fluor 555, and goat anti-mouse Alexa Fluor 633
(Invitrogen; 1:1,000 in TNT buffer containing 5% nonfat dried
milk) for 1 hr at RT. Unbound secondary antibody was removed
by washing 4 x 5 min in TNT. Membranes were soaked in 100%
methanol for 2 min and allowed to air dry in the dark prior to
detection using the Molecular Imager® VersaDoc™ MP 4000
imaging system. Quantitative analyses of blots were performed
with Quantity One® 1-D analysis software.
A validation experiment was performed to ensure that data
from multiplexed fluorescent western blotting can be quantitated.
Two proteins, actin (a housekeeping control protein whose
concentration was kept constant) and human transferrin (with
varied concentrations), were used for validation. Samples were
loaded on a Criterion™ 4–20% gradient Tris-HCl gel, with actin
at a concentration of 150 ng/lane and transferrin at 25, 12.5,
and 5 ng/lane (n = 3 for each concentration). To determine MW
and to assess transfer efficiency, 5 µl of Precision Plus Protein™
WesternC™ standards were run alongside the sample proteins
on the gel. Proteins were transferred to FluoroTrans PVDF
membrane and blocked with BSA-PBS buffer for 1 hr at RT.
BioRadiations 124
25
TECHNICAL REPORT
Membrane was then incubated with two primary antibodies:
rabbit anti-human transferrin (Dako; 1:1,000) and mouse antiactin (Sigma-Aldrich; 1:3,000) for 1 hr at RT and washed
3 x 10 min in TBS buffer. The blot was incubated at RT with
secondary antibodies — goat anti-rabbit Alexa Fluor 647 and
goat anti-mouse Alexa Fluor 568 (Invitrogen; 1:1,000 in blocking
buffer) for 1 hr in the dark before being washed in TBS wash
buffer 3 x 10 min. The membrane was equilibrated in methanol
for 2 min and air dried. Imaging was achieved using a
Molecular Imager® PharosFX™ system. Alexa Fluor 568 and
standards with MWs of 75, 50, and 25 were detected with a
532 nm laser and a 605 nm bandpass filter. A 635 nm laser and
a 695 nm bandpass filter were used to detect Alexa Fluor 647,
and standards with MWs of 150, 100, and 37. Images were
viewed and analyzed using Quantity One software.
Results
Validation of Quantitative Fluorescent Western Blotting
Precision Plus Protein WesternC standards can be used to
estimate MW directly from blots by plotting the log MW of the
standard bands against the relative migration distance (Rf) of the
standards and sample protein bands (for more information, see
bulletin 5576).
Band analysis of actin indicated an apparent MW of 41 and
mean trace quantity (intensity x mm) of 2,279 with a standard
deviation of 159, giving a coefficient of variation (CV) of 6.98%
(Figure 1A, C). Transferrin was detected at an apparent MW of
76. The mean trace quantities of transferrin were 1,253, 570,
and 238 for each concentration. The CVs were 3.8%, 4.3%, and
24.7%, respectively (Figure 1B, C). The relative quantities of the
transferrin loads were 1, 0.5, and 0.2, and the relative calculated
quantities after western blotting were 1, 0.45, and 0.19. Data for
this analysis are shown in Table 1.
Table 1. Quantitative analysis of fluorescent blotting.
Mean trace quantity
Standard deviation
CV, %
Transferrin, ng/lane
Actin, 150 ng/lane
25
12.5
5
2,279
159.1
7.0
1,253
47.4
3.8
570
24.4
4.3
238
58.7
24.7
Effect of PMA on Phosphorylation Status of Cx43
An increase in phospho Cx43 Ser368 (green) was detected at
15 min postincubation with 1 μM PMA (Figure 2A, D). This
induction of Cx43 phosphorylation was followed by a reduction
in total Cx43 levels (red) at 30 min (Figure 2B, D), consistent
with the model of PKC regulation of Cx43 degradation through
phosphorylation at Ser368. Quantitative results were normalized
to tubulin (purple), which served as an internal control
(Figure 2C, D). Phosphorylation of Cx43 was sustained for the
duration of the experiment, relative to the total levels of Cx43,
which remained significantly reduced (Figure 2E).
26
BioRadiations 124
A
MW, kD
75—
50—
25—
B
MW, kD
150—
100—
37—
C
MW, kD
150—
100—
75—
50—
37—
25—
Fig. 1. Validation of quantitative fluorescent blotting. A, fluorescent image
of blot probed with anti-actin; all lanes had equal protein loads (150 ng/lane);
B, fluorescent image of blot probed with anti-human transferrin; amount of protein/
lane varied (lanes 1–3, 0 ng; lanes 4–6, 25 ng; lanes 7–9, 12.5 ng; lanes 10–12,
5 ng); C, merged image of A and B.
Conclusions
The loss of gap junctional intercellular communication as a
result of altered expression/localization of Cx43 seriously
impacts the function of the working myocardium in ischemic
heart disease. Despite protective effects elicited by the body
to contain the spread of potentially toxic factors, uncoupling
of gap junctions prevents cardiomyocytes from contracting in
a coordinated manner and can lead to pathologies, such as
ventricular fibrillation. In this study, we illustrate that exposure
of a cardiomyocyte cell line (HL-1) to PMA results in the rapid
PKC-mediated phosphorylation of Cx43 at Ser368. It is believed
that phosphorylation of Cx43 not only reduces gap junction
permeability, but also promotes internalization and degradation
of the Cx43 protein. Consistent with this model, we observed
a significant reduction in total Cx43 levels following induction
of PKC-mediated phosphorylation at Ser368, similar to that
observed in ischemic heart disease. The function of cardiac
PKC is being elucidated further and is emerging as an attractive
candidate for therapeutic intervention in ischemic heart disease.
© 2008 Bio-Rad Laboratories, Inc.
TECHNICAL REPORT
A
Table 2. Duration of drug treatment of HL-1 cells.
MW, kD
Lanes
Duration, min
Drug
1–2
3–4
5–6
7–8
9–10
11–12
0
15
30
45
60
60
PMA
PMA
PMA
PMA
PMA
DMSO
43—
We also investigated the practicality of fluorescent western
blotting for multiplexing protein detection and demonstrated the
method of quantitation using proteins of known concentrations.
In addition, the use of high-quality MW standards such as
Precision Plus Protein WesternC standards allows simultaneous
estimation of sample protein MW directly from blots without
additional steps. With multiplex blotting, a control “housekeeping”
protein can be used as a loading reference and correction factor
for more accurate quantitation of a second protein of interest,
which may have varying levels of expression.
B
MW, kD
43—
References
Beardslee MA et al., Rapid turnover of connexin43 in the adult rat heart,
Circ Res 83, 629–635 (1998)
C
MW, kD
Claycomb WC et al., HL-1 cells: a cardiac muscle cell line that contracts and
retains phenotypic characteristics of the adult cardiomyocyte, Proc Natl Acad Sci
USA 95, 2979–2984 (1998)
Girao H and Pereira P, Phosphorylation of connexin 43 acts as a stimuli for
proteasome-dependent degradation of the protein in lens epithelial cells, Mol Vis 9,
24–30 (2003)
Laird DW, Connexin phosphorylation as a regulatory event linked to gap junction
internalization and degradation, Biochim Biophys Acta 1711, 172–182 (2005)
Lampe PD et al., Phosphorylation of connexin43 on serine368 by protein kinase C
regulates gap junctional communication, J Cell Biol 149, 1503–1512 (2000)
Liu WS and Heckman CA, The sevenfold way of PKC regulation, Cell Signal 10,
529–542 (1998)
D
MW, kD
Saffitz JE et al., Remodeling of gap junctions in ischemic and nonischemic forms of
heart disease, J Membr Biol 218, 65–71 (2007)
For additional copies of this article, request bulletin 5685.
43—
E
15,000
n Phospho Cx43 Ser 368
n Total Cx43
Trace quantity
12,500
10,000
7,500
5,000
2,500
0
0
15
30
45
PMA Duration of treatment, min
Visit us on the Web at discover.bio-rad.com 60
60
DMSO
Fig. 2. Effect of 1 µM PMA on phosphorylation of Cx43 in the cardiomyocyte
cell line HL-1. A, phosphorylated Cx43; B, total Cx43; C, tubulin; D, merged
images of A, B, and C; and E, plot of trace quantity from blot probed for phospho
Cx43 and total Cx43 against duration of drug treatment. Duration of treatment is
described in Table 2.
BioRadiations 124
27
TECHNICAL REPORT
Applications of the ProteOn™ GLH Sensor Chip:
Interactions Between Proteins and Small Molecules
Boaz Turner, Moran Tabul, and Shai Nimri, Bio-Rad Laboratories, Inc., Gutwirth Park, Technion, Haifa, 32000, Israel
Introduction
The ProteOn GLH sensor chip is one of several types of sensor
chips available for use with the ProteOn™ XPR36 protein
interaction array system (Figure 1). The chip is designed for
protein-small molecule and protein-protein interaction studies in
which highest sensitivity is of primary concern.
The GLH sensor chip, similar to other general amine coupling
ProteOn sensor chips (GLC and GLM), utilizes a proprietary
surface chemistry enabling easy activation of carboxylic groups by
N-hydroxysulfosuccinimide (sulfo-NHS). This activation provides
efficient binding of proteins via their amine groups, and ensures high
ligand activity in many biological applications (see bulletin 5404).
Of the ProteOn sensor chips, the GLH chip offers the highest
ligand binding capacity, making it optimal for the study of proteinsmall molecule interactions. This higher capacity is attained through
the structure of its surface binding layer, comprising a unique
formula of modified polysaccharides. Higher binding capacity,
together with efficient preservation of the protein’s biological activity,
ensures high analytical response upon binding of the analyte to the
ligand — a key advantage when measuring the response of small
molecule compounds.
In this report, we describe the use of the ProteOn GLH
sensor chip with the ProteOn XPR36 system. To demonstrate
the high binding capacity and the versatility of the GLH chip,
immobilization levels of 11 different proteins with a wide range
of isoelectric point (pI) values were evaluated. In addition, to
demonstrate the efficient binding properties and exceptionally
high ligand activity, interaction studies between proteins and
A Analyte flow
small molecules (MW <1,000) were illustrated by two biological
models: 1) carbonic anhydrase II (CAII) and small molecule
inhibitors, and 2) a monoclonal antibody specific to the
dinitrophenyl (DNP) group and dinitrophenyl-labeled amino acids.
CAII Small Molecule Inhibitors
The family of CA proteins is a group of metalloenzymes that
catalyze the conversion of carbon dioxide to bicarbonate and
protons. Some CA inhibitors are active ingredients in drugs that
treat diseases such as glaucoma or epilepsy. Kinetic studies of the
interaction between CAII and its inhibitors appear in the literature
(for example, Myszka 2004, Myszka et al. 2003). The interaction of
CAII with ten different inhibitors was studied with the ProteOn GLH
sensor chip, showing high analytical response in comparison to
published data using conventional chip surfaces.
Additionally, the high ligand activity and analytical response
were further demonstrated by a multichip study of the interaction
of CAII with one of its inhibitors, 4-carboxybenzenesulfonamide
(CBS). CAII was immobilized at different ligand densities and
reacted with six concentrations of CBS. Analysis of the results
revealed that CAII ligand activity was more than 80% and thus
yielded exceptionally high analyte signals.
A Monoclonal Antibody Specific to the DNP Group and Three
Types of DNP-Labeled Amino Acids
The labeling of peptides, proteins, and other biomolecules with
DNP groups and the use of antibodies to bind DNP is a widely
used detection method in research and diagnostic applications;
B
Bound ligand
Immobilization of ligand proteins: • Activation — EDAC/sulfo-NHS
• Ligand injection
• Deactivation — ethanolamine
Sensor
chip
Inject analyte
1
Incident light
Detector
2
3
4
5
6
1
2
3
4
5
6
Fig. 1. Schematic illustration of ProteOn XPR36 protein interaction array system technology. A, detection of ligand to analyte interaction; B, general experimental
procedure for the parallel and simultaneous immobilization of up to six ligand proteins on the sensor chip and the simultaneous flow of small molecules as analytes for the
protein-small molecule kinetic studies. EDAC, 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride.
28
BioRadiations 124
© 2008 Bio-Rad Laboratories, Inc.
TECHNICAL REPORT
Sensorgram Acquisition and Data Analysis
In each of the kinetic studies, the interactions of six analyte
concentrations with up to five immobilized ligands and one
reference protein were monitored in parallel. The data were
analyzed with ProteOn Manager™ 2.0 software.
Values derived from the spots containing immobilized reference
protein (rabbit IgG) were used for reference subtraction. Although
the ProteOn XPR36 system enables the use of unmodified spots
or interspots as references, it is recommended in cases of very
high ligand density to use spots with a reference protein, where
the conditions are more similar to the active spots.
Each set of six reference-subtracted sensorgrams was fitted
globally to curves describing a homogeneous 1:1 biomolecular
reaction model. Global kinetic rate constants (ka and kd) were
derived for each reaction, and the equilibrium dissociation constant,
KD, was calculated using the equation KD = kd / ka. The Rmax values,
the maximal analyte signals at saturation of the active binding sites
of the ligand, were also calculated from this analysis.
Determination of KD in the CAII/methylsulfonamide interaction
was done by measurement of the equilibrium response for each
of the six analyte concentrations. These equilibrium response
levels (Req) were then fitted to a simple bimolecular equilibrium
model at 50% saturation response.
Visit us on the Web at discover.bio-rad.com 25,000
20,000
15,000
10,000
5,000
CA
ll
Ne
ut
rA
vid
in
M
yo
gl
ob
Po
in
lyc
lo
na
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G
Al
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las
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n
Methods
Instrument and Reagents
Experiments were performed using the ProteOn XPR36 protein
interaction array system with ProteOn GLH sensor chips. ProteOn
PBS/Tween running buffer (phosphate buffered saline, pH 7.4
with 0.005% Tween 20) was used. In certain cases, 3% or 10%
dimethyl sulfoxide was added to enable dissolution of the organic
analytes. For immobilization of proteins, ProteOn reagents and
buffers were used as described in Bronner et al. 2006. The
ProteOn amine coupling reagents were EDAC, sulfo-NHS, and
1 M ethanolamine hydrochloride solution, pH 8.5. The ProteOn
immobilization buffers were 10 mM sodium acetate solutions,
pH 4.0, 4.5, 5.0, or 5.5; manual pH adjustment with 1 M HCl or
NaOH was used to generate other pH values. All proteins and
small molecule analytes were purchased from Sigma-Aldrich Co.
All experiments were performed at 25°C. For details on further
assay conditions, see bulletin 5679.
Results and Discussion
Immobilization of Proteins With Different pI Values
Proteins with various pI values were immobilized onto the ProteOn
GLH chips. The results are illustrated in Figure 2 and summarized
in Table 1. Figure 2 compares the immobilization levels of the
GLH chip to the ProteOn GLM chip, and to published results for a
series of proteins immobilized under similar conditions (Johnsson
et al. 1991). The GLH chip, used with sulfo-NHS activation, is
capable of immobilizing high levels of proteins with a wide range
of pI values. Effective binding of even very-low pI proteins such
as pepsin, which is difficult with other methods as reported in the
literature, is possible with the GLH sensor chip.
RU
for example, using immunoperoxidase (Jasani et al. 1992). This
biological model was chosen to illustrate the ability of the GLH
chip to measure the binding of small analytes to large proteins
such as antibodies.
Fig. 2. Comparison of ligand immobilization levels for various proteins between
previously published values using conventional surface (n) chips, and results
obtained on GLM (n) and GLH (n) chips. Data for conventional surfaces with HSA
and NeutrAvidin were not reported in the literature. RU, response units.
Table 1. Results of immobilization of 12 proteins with various pI values
onto ProteOn GLH chips.
Protein
pI
MW
Immobilization Conditions*
Final Amount of
Bound Ligand, RU
2,470
Pepsin
3.0
34,700
800 μg/ml, pH 2.7
Ovalbumin
4.5
43,500
400 μg/ml, pH 4.0 6,800
Soybean trypsin inhibitor
4.5
20,000
400 μg/ml, pH 4.0 21,200 Protein A
5.1
41,000
300 μg/ml, pH 4.5
18,800
Human serum
albumin (HSA)
5.1
66,000
50 μg/ml, pH 5.0 22,000 Carbonic anhydrase II
5.9
29,000
125 μg/ml, pH 5.0 21,200
NeutrAvidin
6.3
60,000
50 μg/ml, pH 4.5 22,350
Myoglobin
6.9–7.4
17,000
400 μg/ml, pH 6.0
12,200
Polyclonal rabbit IgG
6.0–8.0 150,000
25 μg/ml, pH 5.0 22,200
Aldolase
8.2–8.6 161,000
100 μg/ml, pH 6.0
14,850 400 μg/ml, pH 6.0 11,300
Ribonuclease A
9.3
13,700
* In 10 mM sodium acetate solution at the indicated pH.
BioRadiations 124
29
TECHNICAL REPORT
CAII Small Molecule Inhibitors
CAII protein was immobilized at a level of 20,000 RU, and the
binding of ten small molecule inhibitors was studied. The data
for the kinetic analysis are shown in Figure 3, and the results
are summarized in Table 2. While the ka and kd values are in
agreement with data published in the literature, the maximal
analytical response was found to be at least four times higher
in all cases than shown in similar studies with a conventional
sensor chip (Myszka 2004).
CBS (MW, 201)
120
100
80
60
40
20
0
–20
–100
0
Benzenesulfonamide (MW, 157)
100
200
300
400
Furosemide (MW, 331)
200
100
50
Highest
Concentration ka , Analyte
MW Used, μM M–1sec–1 kd , sec–1
0
Rmax,
RU
KD , M
Sulpiride 341
250
2.52 x 103 2.62E-01 1.04E-04 188
Sulfanilamide
172
50
2.40 x 104 1.15E-01 4.79E-06 112
331
50
5.15 x
CBS
201
50
2.83 x 104 3.34E-02 1.18E-06 105
Dansylamide
250
10
1.33 x 105 8.67E-02 6.52E-07 105
1,3-Benzene-
disulfonamide
236
10
1.11 x 105 8.96E-02 8.07E-07
Benzenesulfonamide 157
50
1.17 x 105 1.18E-01 1.01E-06 114
3.66E-02 7.10E-07 180
99
7-Fluoro-2,1,
3-benzoxadiazole-
4-sulfonamide
217
2
4.64 x 105 1.32E-02 2.84E-08
82
Acetazolamide
222
2
9.28 x 105 2.43E-02 2.62E-08
99
95
2,500
0
50 100 150 200 250 300
7-Fluoro-2,1,3-benzoxadiazole-4-sulfonamide
(MW, 217)
100
104
Furosemide
Methylsulfonamide
–50
–50
—
3.15E-04
22
30
20
34
10
72
204
336
468
600
Acetazolamide (MW, 222)
120
94
68
16
100
80
60
40
20
0
–20
–50
150 200
20
65
110
155
200
28
126
–10
–50
0
50
100
150
200
Sulfanilamide (MW, 172)
224
322
420
1,3 -Benzenedisulfonamide (MW, 236)
Monoclonal Antibody and DNP-Labeled Amino Acids
The binding of three DNP-labeled amino acids (DNP-glycine,
DNP-valine, and DNP-tryptophan) was studied to illustrate the
ability of the ProteOn GLH sensor chip to measure the binding
of small analytes to large ligands (Table 3, Figure 4). The amount
of immobilized anti-DNP was 18,550 RU. Greater than 50% of
the total binding sites were active. In the case of DNP-glycine, the
molecular weight ratio of ligand to analyte is greater than 300
(assuming two available ligand binding sites per ligand molecule),
and binding of such analytes is readily detected and measured. 100
0
12
–10
–70
50
Methylsulfonamide (MW, 95)
56
42
—
180
140
100
60
20
–20
–25
78
–10
–60
0
Dansylamide (MW, 250)
150
Table 2. Results of the interactions of CAII (MW 29 kD) with ten different
inhibitors.
120
100
80
60
40
20
0
–20
–100 -50
108
88
68
48
28
8
–12
–34
16
66
116
166
216
Sulpiride (MW, 341)
164
114
64
14
0
50
100 150
200 250
–36
–48
2
52
102
152
Fig. 3. Sensorgrams and analysis fit from each of the kinetic studies of CAII
(20,000 RU) and the pertinent inhibitor. The kinetic parameters are shown in Table 2.
45
35
RU
Table 3. Results of the interactions of monoclonal anti-DNP (150 kD)
with three DNP-labeled amino acids.
Analyte
MW
ka, M–1sec–1
kd , sec–1
KD , M
Rmax, RU
DNP-glycine
DNP-valine
DNP-tryptophan
241
283
370
1.99E+06
1.24E+06
7.14E+05
0.095
0.098
0.251
4.77 x 10–8
7.90 x 10–8
3.52 x 10–7
36
41
75
25
15
5
–5
–10
40
90
Time, sec
Fig. 4. Sensorgrams and analysis fit from the kinetic study of anti-DNP
(18,550 RU) and the DNP-valine analyte. The kinetic parameters are shown in
Table 3.
30
BioRadiations 124
© 2008 Bio-Rad Laboratories, Inc.
TECHNICAL REPORT
B. Multiuser SPR study
A. ProteOn GLH chip
160
CBS binding level (Rmax ), RU
140
75
--- Theoretical
—– Actual
120
50
100
80
60
25
40
20
0
0
5,000
10,000
15,000
20,000
25,000
30,000
0
0
2,000
4,000
6,000
8,000
10,000
12,000
CA II immobilization level, RU
Fig. 5. Analytical response of CBS binding versus the amount of CAII immobilized onto the sensor chip. A, ProteOn GLH chip; B, conventional chip (Myszka et al. 2003).
The black dotted line shows the theoretical maximal response, assuming that 100% of the bound ligand molecules are active. The gold line is a linear fit of the actual response
values. Actual ligand activity is 82% of theoretical for the GLH chip and 46% for the conventional chip surfaces.
Multichip Study of the CAII/CBS Interaction
The bound amount of the CAII ligand ranged from 7,000 to
more than 24,000 RU, depending on the level of surface
activation. The kinetic analysis of the interaction with CBS was
performed for each of the 35 sets of results; each set contained
six analyte sensorgrams relating to one ligand density. The
average results of kinetic constants were: ka = 3.2 ± 0.7 × 104
M–1sec–1; kd = 0.037 ± 0.003 sec–1; KD = 1.2 × 10–6 ± 0.3 ×
10–6 M. These values are in agreement with published data
(Myszka et al. 2003).
The mean ligand activity of the CAII was determined by
plotting the maximal response of the analyte (Rmax) versus
the ligand density (Figure 5A). Assuming a stoichiometric
relationship between reactants in molar terms, the theoretical
CBS binding response is 150-fold lower than the immobilized
level of CAII due to the mass difference between the interacting
pair. The dotted trend line in Figure 5A represents the theoretical
correlation between the surface density of CAII and maximal
binding signal of CBS. Experimental data typically falls below
this line because some of the immobilized protein is inactive.
However, the data for the ProteOn GLH chip (Figure 5A) shows
that actual CBS binding values lie very close to the theoretical
trend line, indicating that more than 80% of the immobilized
ligand is active. These results demonstrate exceptionally high
ligand activity of the CAII/CBS interaction, and are a significant
improvement over the reported literature results of less than
50% ligand activity (Figure 5B, from Myszka et al. 2003). In
absolute terms, analyte signals of more than 120 RU could
be gained with the GLH chip, while less than 40 RU was the
maximal value recorded with conventional surfaces.
Visit us on the Web at discover.bio-rad.com Conclusions
The ProteOn GLH sensor chip offers exceptionally high binding
capacities while preserving ligand activity, providing enhanced
analyte signal in situations where the molecular weight ratio of
ligand to analyte is very high (~100 or more). These advantages
make the GLH chip an ideal choice for protein-small molecule
and protein-protein interaction studies where highest sensitivity
is desired. Used with the ProteOn XPR36 protein interaction
array system, up to 36 biomolecular interactions can be
assayed simultaneously in one experiment, yielding valuable
kinetic, concentration, and equilibrium data, and reducing
research time from days to hours. The GLH chip is a valuable
tool for the lead identification and optimization processes of
drug development, as well as areas of fundamental research in
protein-small molecule interactions and developmental work in
assay optimization.
References
Bronner V et al., Rapid optimization of immobilization and binding conditions for
kinetic analysis of protein-protein interactions using the ProteOn XPR36 protein
interaction array system, Bio-Rad bulletin 5367 (2006)
Jasani B et al., Dinitrophenyl (DNP) hapten sandwich staining (DHSS) procedure.
A 10 year review of its principal reagents and applications, J Immunol Methods
150,193–198 (1992)
Johnsson B et al., Immobilization of proteins to a carboxymethyldextran-modified
gold surface for biospecific interaction analysis in surface plasmon resonance
sensors, Anal Biochem 198, 268–277 (1991)
Myszka DG, Analysis of small-molecule interactions using Biacore S51 technology,
Anal Biochem 329, 316–323 (2004)
Myszka DG et al., The ABRF-MIRG’02 study: assembly state, thermodynamic, and
kinetic analysis of an enzyme/inhibitor interaction, J Biomol Tech 14, 247–269 (2003)
For an expanded version of this article, request bulletin 5679.
BioRadiations 124
31
WHAT’S
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Sample Preparation
5635 ProteoMiner™ system brochure
5602ProteinChip SELDI system qualification and calibration kits product
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5632Accessing low-abundance proteins in serum and plasma with a novel,
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Multiplex Suspension Array Technology
Chromatography
5651 Bio-Plex Pro human diabetes assay panel product information sheet
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Gene Transfer
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5700 Gene Pulser MXcell system optimization tree flier
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Amplification/PCR
5692 Real-time qPCR as a tool for evaluating RNAi-mediated gene silencing
5685 Effect of PMA on phosphorylation of Cx43
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5689 1000-Series thermal cycling platform interactive demo CD
Protein Interaction Analysis
5648 S1000™ thermal cycler flier
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Surface-Enhanced Laser Desorption Ionization
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Purchase of this instrument conveys a limited non-transferable immunity from suit for the purchaser’s own internal research and development
and for use in applied fields other than Human In Vitro Diagnostics under one or more of U.S. Patents Nos. 5,656,493, 5,333,675, 5,475,610
(claims 1, 44, 158, 160–163 and 167 only), and 6,703,236 (claims 1–7 only), or corresponding claims in their non-U.S. counterparts, owned by
Applera Corporation. No right is conveyed expressly, by implication or by estoppel under any other patent claim, such as claims to apparatus,
reagents, kits, or methods such as 5’ nuclease methods. Further information on purchasing licenses may be obtained by contacting the
Director of Licensing, Applied Biosystems, 850 Lincoln Centre Drive, Foster City, California 94404, USA.
To find your local sales office, visit www.bio-rad.com/contact/
In the U.S., call toll free at 1-800-4BIO-RAD (1-800-424-6723)
Visit us on the Web at discover.bio-rad.com
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