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Establishing Quality Control Metrics for Immunodepletion of High- Abundance Plasma Proteins and Applying to a Large Clinical Cohort Meredith Turner ; Erik J. Soderblom; J. Will Thompson; Laura G. Dubois; M. Arthur Moseley Duke Proteomics Core Facility, Institute for Genome Sciences & Policy, Duke University School of Medicine, Durham, NC INTRODUCTION Human plasma is a commonly interrogated biological matrix to identify candidate protein biomarkers because of its wide range of expressed protein functionalities. These samples are also relatively easy to obtain from large patient cohorts with routine sample collection procedures. However, measuring changes in biologically relevant low-abundance proteins by LC-MS strategies is hindered by the large dynamic range of these biological matrices. In human plasma, the concentrations of proteins span over ten orders of magnitude with the fourteen most abundant proteins making up about 94% of the total protein mass. This large dynamic range of protein concentrations represents a challenge to the identification and characterization of biologically significant low-abundance proteins due to a “masking” effect. To address these challenges, immunodepletion of these high-abundance proteins is often employed and results in a subsequent increase in protein identification depth of coverage. As variations in immunodepletion efficiencies can have consequences on downstream LC-MS based protein quantitation, we have developed a series of quality control metrics which allow us to assess the efficiency of immunodepletions using Agilent’s Multi-Affinity Removal System (MARS-14) LC column. The metrics focus on bound versus unbound peak area ratios from UV chromatograms, pre- and post- depletion protein concentration ratios, and image analysis of 1D SDS-PAGE gels. These metrics provide unique insights into basic sample preparation variables and importantly allow the identification of potential outliers in the cohort prior to LC- MS/MS analysis. Potential outliers can then be flagged for statistical consideration in the downstream analysis or excluded from further analysis all together. METHODS Fifty uL aliquots of EDTA human plasma from a 243 patient chronic hepatitis C clinical cohort were subjected to immunodepletion using a 4.6x100 mm Agilent MARS14 HPLC column (part number 5188-6558) on an Agilent 1100 series LC system. Before immunodepletion, the aliquots were diluted with 200 uL of Agilent Buffer A , and then 100 uL of the 5x dilution samples was injected on the column. The manufacturer’s recommended LC gradient protocol was followed. Areas under the curve for bound and unbound fractions (automated peak integration) were recorded from each UV chromatogram (280 nm) within Agilent ChemStation (v10.02). and their ratios were utilized for one depletion metric. Bradford assays (Bio-Rad) were performed on plasma samples pre- and post-depletion (post-depletion done after a buffer exchange and ~20x concentration into 50 mM ammonium bicarbonate) and the values were plotted as the total plasma protein concentration versus the percentage of total protein in the unbound fraction. Finally, 5 ug of each depleted plasma sample was run on an Invitrogen NuPAGE 4-12% Bis-Tris gel, stained with Colloidal Blue (Invitrogen) and subjected to semi-automated densiotometery measurements within TotalLab Quant (Non-Linear Dynamics). 20000 40000 60000 80000 100000 120000 140000 160000 0 20000 40000 60000 80000 AUC Unbound Fraction AUC Bound Fraction Flow Cell 2 Unbound AUC vs. Bound AUC 243 sample HCV study MARS14 Depletion min 10 15 20 25 30 mAU -100 0 100 200 300 400 500 600 700 DAD1 A, Sig=280,16 Ref =360,100 (042009\004-0201.D) 11.018 Area: 2387.19 22.150 Area: 647.967 23.455 DAD1 A, Sig=280,16 Ref =360,100 (042009\003-0101.D) QC Metric 1 Characterizing Depletion Chromatogram QC Metric 2 Bradford Assay QC Metric 3 SDS-PAGE Gel Image Analysis QC METRIC 1 - Characterizing Depletion Chromatogram 100 80 60 40 20 0 [Total Serum Protein] (ug/uL) 35 30 25 20 15 10 5 Percentage of Total in Unbound Fraction (%) Unbound (non-depleted) proteins Bound (depleted) proteins **The samples showing the extra peak were previously noted to be cloudy. Early eluting peak possible lipid (micelle) contamination. QC METRIC 2 Bradford Assay 0 10 20 30 40 50 60 70 80 0 5 10 [Pre-Depletion Total Serum Protein] (ug/uL) Percentage of Total Protein in Unbound Fraction (%) Depletion QC Based on Bradford Assays *Samples highlighted are more than two standard deviations away from the average. QC METRIC 3 - SDS-PAGE Gel Image Analysis The three sets of depletion QC metrics described are effective at identifying potential outliers to assess the efficiency of the depletion protocol. The flagged samples can then be set aside in statistical analyses so as not to affect the biological variability calculations. The QC metrics were applied to a large clinical cohort and successfully found samples that were potential outliers. Features of UV (A280) Chromatogram of Depleted Human Plasma Integration of Unbound Peak 20000 40000 60000 80000 100000 120000 140000 160000 0 20000 40000 60000 80000 AUC Unbound Fraction AUC Bound Fraction Unbound AUC vs. Bound AUC 179 sample HCV study Raw AUC Intensities 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 50.0 55.0 60.0 65.0 70.0 Unbound/Bound AUC Ratio % of Total AUC in the Unbound AUC Depletion QC Based on AUC Ratios from 243 sample HCV Study The area under both curves is included in the AUC determination. www.genome.duke.edu/proteomics/ 450 Research Drive, Durham, NC 27710 Flow Cell 1 Unbound/Bound AUC Ratio Unbound AUC / Bound AUC % of Total AUC in Unbound AUC [Unbound AUC / (Unbound AUC + Bound AUC)] * 100 Red Boxes Samples highlighted in red are not within two standard deviations of the average point, so are flagged for further consideration. Pre-Depletion Total Serum Bradford Post-Depletion Bradford Percentage of Total Protein in Unbound Fraction (%) Seven bands monitored across all samples Representative gel from 243 patient HCV cohort min 5 10 15 20 25 mAU -100 0 100 200 300 400 500 600 DAD1 A, Sig=280,16 Ref =360,100 (040909\019-1501.D) 1-P2-E-07 1-P2-E-08 1-P2-E-09 1-P2-F-01 1-P2-F-02 1-P2-F-03 1-P2-F-04 0.00 0.10 0.20 0.30 0.40 1 2 3 4 5 Protein Concentration Bradford Assay (A 595 ) [ug/ul] QC 1 Characterizing Depletion Chromatogram Samples not within two standard deviations of the average point are flagged for further examination QC 2 Bradford Assay Samples with an extremely low post-depletion concentration are not normalized with the other samples QC 3 SDS-PAGE Gel Image Analysis Samples showing a hemoglobin band are run at the end of the queue [(Volume of plasma depleted* pre-depletion concentration) / (Volume of depleted plasma obtained * post-depletion concentration)] * 100 OVERVIEW Analysis of Atypical Chromatogram Features CONCLUSIONS
Transcript

Establishing Quality Control Metrics for Immunodepletion of High-

Abundance Plasma Proteins and Applying to a Large Clinical CohortMeredith Turner; Erik J. Soderblom; J. Will Thompson; Laura G. Dubois; M. Arthur Moseley

Duke Proteomics Core Facility, Institute for Genome Sciences & Policy, Duke University School of Medicine, Durham, NC

INTRODUCTION

Human plasma is a commonly interrogated biological matrix to identify candidate

protein biomarkers because of its wide range of expressed protein functionalities.

These samples are also relatively easy to obtain from large patient cohorts with

routine sample collection procedures. However, measuring changes in biologically

relevant low-abundance proteins by LC-MS strategies is hindered by the large

dynamic range of these biological matrices. In human plasma, the concentrations of

proteins span over ten orders of magnitude with the fourteen most abundant proteins

making up about 94% of the total protein mass. This large dynamic range of protein

concentrations represents a challenge to the identification and characterization of

biologically significant low-abundance proteins due to a “masking” effect. To address

these challenges, immunodepletion of these high-abundance proteins is often

employed and results in a subsequent increase in protein identification depth of

coverage.

As variations in immunodepletion efficiencies can have consequences on

downstream LC-MS based protein quantitation, we have developed a series of quality

control metrics which allow us to assess the efficiency of immunodepletions using

Agilent’s Multi-Affinity Removal System (MARS-14) LC column. The metrics focus on

bound versus unbound peak area ratios from UV chromatograms, pre- and post-

depletion protein concentration ratios, and image analysis of 1D SDS-PAGE

gels. These metrics provide unique insights into basic sample preparation variables

and importantly allow the identification of potential outliers in the cohort prior to LC-

MS/MS analysis. Potential outliers can then be flagged for statistical consideration in

the downstream analysis or excluded from further analysis all together.

METHODS

Fifty uL aliquots of EDTA human plasma from a 243 patient chronic hepatitis C clinical

cohort were subjected to immunodepletion using a 4.6x100 mm Agilent MARS14

HPLC column (part number 5188-6558) on an Agilent 1100 series LC system. Before

immunodepletion, the aliquots were diluted with 200 uL of Agilent Buffer A , and then

100 uL of the 5x dilution samples was injected on the column. The manufacturer’s

recommended LC gradient protocol was followed. Areas under the curve for bound

and unbound fractions (automated peak integration) were recorded from each UV

chromatogram (280 nm) within Agilent ChemStation (v10.02). and their ratios were

utilized for one depletion metric. Bradford assays (Bio-Rad) were performed on

plasma samples pre- and post-depletion (post-depletion done after a buffer exchange

and ~20x concentration into 50 mM ammonium bicarbonate) and the values were

plotted as the total plasma protein concentration versus the percentage of total

protein in the unbound fraction. Finally, 5 ug of each depleted plasma sample was run

on an Invitrogen NuPAGE 4-12% Bis-Tris gel, stained with Colloidal Blue (Invitrogen)

and subjected to semi-automated densiotometery measurements within TotalLab

Quant (Non-Linear Dynamics).

20000

40000

60000

80000

100000

120000

140000

160000

0 20000 40000 60000 80000AU

C U

nb

ou

nd

Fra

cti

on

AUC Bound Fraction

Flow Cell 2

Unbound AUC vs. Bound AUC

– 243 sample HCV study

MARS14 Depletion

min10 15 20 25 30

mAU

-100

0

100

200

300

400

500

600

700

DAD1 A, Sig=280,16 Ref =360,100 (042009\004-0201.D)

11.018

Area: 2387.19

22.150

Area: 647.967

23.455

DAD1 A, Sig=280,16 Ref =360,100 (042009\003-0101.D)

QC Metric 1 – Characterizing

Depletion Chromatogram

QC Metric 2 – Bradford AssayQC Metric 3 – SDS-PAGE

Gel Image Analysis

QC METRIC 1 - Characterizing Depletion Chromatogram

100

80

60

40

20

0

[To

tal S

eru

m P

rote

in]

(ug

/uL

)

3530252015105

Percentage of Total in Unbound Fraction (%)

55 HCV Samples (1797)

34 DARPA Samples (1871)

MARS14 "Typical" Depletion "Average" Serum Protein Conc (55ug/ul)

Unbound (non-depleted)

proteinsBound (depleted) proteins

**The samples

showing the extra

peak were

previously noted to

be cloudy.

Early eluting peak

possible lipid

(micelle)

contamination.

QC METRIC 2 – Bradford Assay

0

10

20

30

40

50

60

70

80

0 5 10

[Pre

-Dep

leti

on

To

tal S

eru

m

Pro

tein

] (u

g/u

L)

Percentage of Total Protein in Unbound Fraction (%)

Depletion QC Based on Bradford Assays

*Samples highlighted are more than two standard deviations away from the average.

QC METRIC 3 - SDS-PAGE Gel Image Analysis

The three sets of depletion QC metrics described are effective at identifying potential outliers to

assess the efficiency of the depletion protocol. The flagged samples can then be set aside in

statistical analyses so as not to affect the biological variability calculations. The QC metrics were

applied to a large clinical cohort and successfully found samples that were potential outliers.

Features of UV (A280) Chromatogram of

Depleted Human Plasma

Integration of

Unbound Peak

20000

40000

60000

80000

100000

120000

140000

160000

0 20000 40000 60000 80000

AU

C U

nb

ou

nd

Fra

cti

on

AUC Bound Fraction

Unbound AUC vs. Bound AUC

–179 sample HCV study

Raw AUC Intensities

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

50.0 55.0 60.0 65.0 70.0

Un

bo

un

d/B

ou

nd

AU

C R

ati

o

% of Total AUC in the Unbound AUC

Depletion QC Based on AUC Ratios

from 243 sample HCV Study

The area under both curves

is included in the AUC

determination.

www.genome.duke.edu/proteomics/

450 Research Drive, Durham, NC 27710

Flow Cell 1

Unbound/Bound AUC Ratio

Unbound AUC / Bound AUC

% of Total AUC in Unbound AUC

[Unbound AUC / (Unbound AUC +

Bound AUC)] * 100

Red Boxes

Samples highlighted in red are not

within two standard deviations of

the average point, so are flagged

for further consideration.

Pre-Depletion Total Serum

Bradford

Post-Depletion Bradford

Percentage of Total Protein in

Unbound Fraction (%)

Seven bands monitored

across all samples

Representative gel from

243 patient HCV cohort

min5 10 15 20 25

mAU

-100

0

100

200

300

400

500

600

DAD1 A, Sig=280,16 Ref =360,100 (040909\019-1501.D)

1-P2-

E-07

1-P2-

E-08

1-P2-

E-09

1-P2-

F-01

1-P2-

F-02

1-P2-

F-03

1-P2-

F-04

0.00

0.10

0.20

0.30

0.40

1 2 3 4 5

Pro

tein

Con

ce

ntr

ation

Bra

dfo

rd A

ssa

y (

A595)

[ug/u

l]

QC 1

• Characterizing Depletion Chromatogram• Samples not within two standard deviations of the average point are flagged

for further examination

QC 2

• Bradford Assay• Samples with an extremely low post-depletion concentration are not

normalized with the other samples

QC 3• SDS-PAGE Gel Image Analysis• Samples showing a hemoglobin band are run at the end of the queue

[(Volume of plasma depleted* pre-depletion

concentration) / (Volume of depleted plasma

obtained * post-depletion concentration)] * 100

OVERVIEW

Analysis of Atypical Chromatogram Features

CONCLUSIONS

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