Intact stable isotope labeled plasma proteins from the SILAC-labeled HepG2 secretome

www.proteomics-journal.com Page 1 Proteomics

Received: 31-Jul-2014; Revised: 05-Nov-2014; Accepted: 05-Dec-2014

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Intact Stable Isotope Labeled Plasma Proteins from the SILAC-labeled HepG2 Secretome

John B. Mangrum1, Erika J. Martin2, Donald F. Brophy2, Adam M. Hawkridge1,2*

1Department of Pharmaceutics

2Department of Pharmacotherapy & Outcomes Science Virginia Commonwealth University, Richmond, VA 23298

Submission: July 31, 2014 Re-submission: November 5, 2014

*Author of Correspondence Adam M. Hawkridge, Ph.D. Department of Pharmaceutics Department of Pharmacotherapy & Outcomes Science VCU School of Pharmacy 410 North 12th Street | Room 644 P.O. Box 980533 Richmond, Virginia 23298-0533 Phone: (804) 828-1258 Email: [email protected]



ABSTRACT The plasma proteome remains an attractive biospecimen for mass spectrometry (MS)-based biomarker discovery studies. The success of these efforts relies on the continued development of quantitative MS-based proteomics approaches. Herein we report the use of the SILAC-labeled HepG2 secretome as a source for stable isotope labeled plasma proteins for quantitative LC-MS/MS measurements. The HepG2 liver cancer cell line secretes the major plasma proteins including serum albumin, lipoproteins, proteases inhibitors, coagulation factors, and transporters which represent some of the most abundant proteins in plasma. The SILAC-labeled HepG2 secretome was collected, spiked into human plasma (1:1 total protein), and then processed for LC-MS/MS analysis. A total of 62 and 56 plasma proteins were quantified (heavy:light peptide pairs) from un-depleted and depleted (serum albumin and IgG), respectively with log2 H/L = ±6. Major plasma proteins quantified included albumin, apolipoproteins (e.g., APOA1, APOA2, APOA4, APOB, APOC3, APOE, APOH, and APOM), protease inhibitors (e.g., A2M and SERPINs), coagulation factors (e.g., Factor V, Factor X, fibrinogen), and transport proteins (e.g., TTR). The average log2 H/L values for shared plasma proteins in both un-depleted and depleted plasma samples were 0.43 and 0.44, respectively. This work further expands the SILAC strategy into MS-based biomarker discovery of clinical biospecimens. INTRODUCTION

The pursuit of clinically useful protein biomarkers has been revolutionized by

mass spectrometry (MS)-based proteomics technology since the introduction of

electrospray[1] and matrix assisted laser desorption ionization[2]. Plasma is an

attractive biospecimen for biomarker discovery because it is easy to obtain and

contains proteins from several tissue types including the ‘classic’ plasma proteins,

immunoglobulins, hormones, acute-phase response proteins (e.g., C-reactive

protein), tissue leakage proteins (e.g., troponins), and aberrant secretions (e.g.,

prostate specific antigen and CA-125).[3, 4] Although attractive, plasma represents

one of the most complex and bio-analytically challenging proteomes to study. For

example, the difference in concentration between the most and least abundant

plasma proteins exceeds 10 orders of magnitude. Despite these challenges,

contemporary liquid chromatography tandem mass spectrometry (LC-MS/MS)

combined with protein- and peptide-level fractionation has enabled the identification

of over 10,000 proteins[5] which represents a more than 30-fold increase in



proteome coverage since 2002.[6] Historical trends suggest that newer LC-MS/MS-

based technology will continue to push these limits toward full proteome coverage,

yet MS-based plasma protein quantitation remains a significant challenge in

biomarker discovery studies.

Two main types of global quantitative LC-MS/MS strategies have been

developed that are amenable to comparative analysis of clinical samples. Label-

free quantitation (e.g., spectral counting, ion intensity)[7-9] has found widespread

use because it does not require special reagents, yet digestion efficiency and shifts

in chromatographic retention time create differential peptide ion suppression effects

that can negatively impact quantitative precision and accuracy. Isobaric tagging

(e.g., iTRAQ, TMT)[10, 11] allows for multiplexed comparative measurements which

are less sensitive to chromatographic irreproducibility, yet the cost of reagents can

be prohibitive. Both strategies rely on reproducible workflows that generate tryptic

peptide abundances representative of the original protein concentration. This proves

challenging for plasma when abundant plasma protein removal, 1D-gel

electrophoresis, and tryptic peptide-level fractionation are common steps within

biomarker discovery workflows.[12] Even with standardized protocols for plasma

collection, well-defined patient phenotypes, and the use of pooled plasma reference

standards, significant bias and pre-analytical variability remains prominent.[13, 14]

Ideally, stable isotope labeled forms of all plasma proteins could be spiked into

whole plasma samples prior to sample preparation. Pre-analytical variability

associated with sample losses, abundant protein depletion, variable digestion

efficiency, and variable peptide-level separation efficiency would be significantly

improved for comparative LC-MS/MS analysis.



Stable isotope labeling of amino acids in cell culture (SILAC) has emerged as

a powerful global quantitative LC-MS/MS strategy that was originally developed for in

vitro systems.[15] Unlike label-free and isobaric tagging approaches, SILAC is less

susceptible to pre-analytical variability introduced during proteomic sample

processing because of the presence of intact un-labeled and labeled proteins.[15]

More recently, SILAC (i.e., Super-SILAC) has been applied to global comparative

studies of clinical biospecimens including tumor tissues[16, 17] and human

plasma[18] for cancer biomarker studies. In these studies, the heavy-labeled

intracellular and secreted proteins from multiple cell lines (e.g., breast cancer) were

harvested and then used as intact stable isotope labeled internal standards spiked

into the respective clinical biospecimen. This emerging approach has great potential

for comparative LC-MS/MS biomarker studies in clinical specimens with continued

development.

Herein we report the use of the SILAC-labeled secretome from the HepG2 cell

line as an internal standard for the major plasma proteins. HepG2 is a

hepatocarcinoma cell line established in 1980[19] that secretes plasma proteins[6]

including apolipoproteins, proteases inhibitors, fibrinogen, and transporters.[19-25]

MS-based studies on the HepG2 secretome have been demonstrated,[26, 25]

including a recent report by Chen et al. that investigated the thyroid-hormone

regulated HepG2 secretome using SILAC.[27] In the current study, we harvested

the SILAC-labeled HepG2 secretome and then spiked this sample into human

plasma. LC-MS/MS analysis of the ‘heavy secretome:plasma’ sample (H/L) with and

without albumin and IgG removal quantified 56 and 62 proteins, respectively.

Multiple classes of major plasma proteins were identified with H/L peptide pairs

including apolipoproteins (e.g., APOA1, APOA2, APOA4, APOB, APOC3, APOE,



APOH, and APOM), protease inhibitors (e.g., A2M and SERPINs), complement

factors (e.g., C3 and C5), coagulation factors (e.g., FV, FX, and Fibrinogen-α, -β, -γ

chains), and transport proteins (e.g., TTR). Average log2 H/L values for non-

depleted and depleted H/L plasma samples were 0.43 and 0.44, respectively. The

preservation of the H/L peptides throughout the sample preparation workflow and the

extensive proteome coverage for the major plasma proteins suggests that the

SILAC-labeled HepG2 secretome could be combined with additional SILAC-labeled

cell line secretomes to generate a representative ‘heavy’ form of plasma proteins for

highly accurate LC-MS/MS comparative studies and biomarker discovery.

EXPERIMENTAL

Materials: HepG2 cells were obtained from ATCC (HG-8065, Manassas, VA)

and stored in liquid nitrogen. SILAC media reagents were purchased as a kit

(Thermo Scientific) which contained arginine- and lysine-free DMEM-high glucose

media, 13C6 L-arginine-HCl (>98%), 13C6 L-lysine-2HCl (>98%), and dialyzed fetal

bovine serum. Penicillin, streptomycin, and amphotericin B were obtained as a 100x

solution (Invitrogen). LC-MS grade acetonitrile and water were obtained from

Burdick and Jackson. LC-MS grade formic acid, iodoacetamide, and dithiothreitol

were purchased from SIGMA-Aldrich; reagent grade Tris base and 12M hydrochloric

acid were obtained from Fisher Scientific; and trypsin gold was obtained from

Promega. An EDTA-plasma sample was collected from a healthy volunteer and

stored at -80°C prior to analysis.

HepG2 Cell Culture: HepG2 cells were grown in SILAC DMEM-high glucose

media supplemented with 50 mg 13C6 L-arginine-HCl and 50 mg 13C6 L-lysine-2HCl,

10% dialyzed fetal bovine serum (FBS), and 1% pen/strep/amp at 37°C and 5%



CO2. Cells were cultured for 9 cell population doublings (3 passages) and

determined to be ≥95% labeled based on the H/L ratios for serum albumin

(Supplemental Table 1). The extent of arginine to proline conversion was checked

by searching the peptides with 13C5-P as a possible modification and only six high

confident peptides containing heavy 13C5 proline were identified (Supplemental

Table 2). Two sets of heavy secretome samples were prepared for this study from

an estimated 10 million SILAC-labeled cells (80% confluency). The serum-

containing SILAC DMEM media was removed from the ~10 million cells, the cells

were washed once with 5 ml of warm (37°C) serum-free heavy DMEM media, and

replaced with a fresh 12 ml of serum-free heavy DMEM media. Cells were incubated

for 24 hours (37°C, 5% CO2) and the first heavy secretome sample collected. A

fresh heavy serum-free DMEM was then added and incubated another 24 hours

after which the second heavy secretome sample collected. Thus, the two heavy

secretome samples are hereafter referred to as ‘24 hr’ and ‘48 hr’ secretome. The

media containing the 24 hr and 48 hr secretomes were centrifuged at 5000 ×g for 10

minutes to remove cellular debris, then 3 × ~4 mL aliquots were transferred to 3 × 15

mL Amicon Ultra 3K MWCO filters (Millipore), then all three MWCO filters centrifuged

at 7500 x g for 15 minutes at 4°C, and then washed with 4 x 3 mL aliquots of 100mM

Tris-buffer pH 8.0 to remove traces of phenol red. The concentrated solutions were

combined, and then analyzed at 280 nm using a BioTek Synergy H1 fitted with a

Take3 Plate for total protein concentration.

Sample Preparation: Secretome:plasma samples were prepared using the

Filter Aided Sample Preparation (FASP). [28] Prior to FASP processing, one set of

secretome:plasma samples were depleted of serum albumin and immunoglobulins

(Pierce Top 2 abundant protein depletion spin column) according to the



manufacturer’s protocol. Proteome samples (400 μg total protein) were added to 10

kDa MWCO FASP filters (Millipore) and washed with 300uL of Tris buffer, pH 8.0

followed by centrifugation at 14,000g for 10min. The proteomes were reduced by

adding 48uL of a 50mM DTT solution (Sigma-Aldrich) and incubated at 56°C for 45

minutes. Following reduction, 48uL of a 142mM iodoacetamide solution was added

and incubated for 15 minutes in the dark at room temperature. Tris-HCl, pH 8.0 was

added to the FASP filters and spun at 14,000g for 10 min to remove residual DTT

and iodoacetamide. Trypsin was dissolved in 50mM acetic acid to a concentration of

1μg/μL and added directly to the FASP filter at a trypsin:substrate ratio of 1:50 for

overnight digestion at 37°C. After overnight digestion, a second aliquot of trypsin

was added at 1:20 (trypsin:substrate) and incubated for an additional three hours to

ensure complete protein digestion. Following digestion, the peptides were removed

from the FASP filter with the addition of 200uL of 50mM acetic acid solution followed

by gentle agitation and then spinning at 14,000g for 10 min to ensure all the peptides

were removed from the filter. The concentration of tryptic peptides was determined

at 280nm and each solution diluted in 50mM acetic acid for LC-MS/MS analysis.

Representative 10 μg fractions from the heavy secretome and un-fractionated

plasma were combined 1:1 (v:v) with 55 mM DTT in 2x Laemmli buffer (Bio-rad) and

heated for 5 minutes at 95°C. 30 μl of each sample was loaded onto a 10% Criterion

Tris-HCl 1D gel (Bio-Rad) along with 15 μl of a Broad-range MW standard (Bio-Rad).

The gel was run at a constant 200V for 1 hour, removed from the cassette and

rinsed 3x with deionized water, and then stained for 1 hour with BioSafe Coomassie

(Bio-Rad) (Figure 1B).

LC-MS/MS System: The LC-MS/MS system included an Eksigent (ABSciex)

nLC 415 with the cHiPLC NanoFlex system configured to trap and elute. The reverse



phase trap column chip (200 μm x 0.5mm) and analytical column (75μm x 15cm)

were both packed with ChromXP C18-CL 3um and 120Å material. The nLC system

was coupled to a Q-Exactive (Thermo Scientific, San Jose, CA) equipped with the

Nanospray-Flex ionization source fitted with a 10 μm i.d. emitter tip (New Objective).

2 μl of digested sample (160 ng/injection) was loaded onto the trap column chip at 2

μl/min using mobile phase A (98% H2O/2% acetonitrile, 0.1% formic acid) for 5

minutes. Desalted peptides were then eluted at 300nL/min with increasing mobile

phase B (2% H2O/98% acetonitrile, 0.1% formic acid) using the following gradient:

2% B (0 minutes), 2-5% B (5 minutes), 25% B (120 minutes), 90 % B (132 minutes)

and held for 11 minutes, 2% B (157 minutes) and held for 8 minutes until the run

finishes at 165 minutes. Eluting peptides were ionized at 2.10 kV in positive ion

mode and the Q-Exactive inlet temperature and S-lens setting were maintained at

200C and 60 V, respectively. Full scan (400-1600 m/z) resolution was set at 70,000

FWHM with an AGC target of 3 × 106. MS/MS was set to a resolution of 17,500 with

an AGC target of 2 × 104 at 120 ms maximum inject time and selection of the top 12

ions at a 30 second dynamic exclusion. HCD voltage was maintained at 27 NCE

throughout.

LC-MS/MS Data Analysis: Proteomic datasets were processed using

Proteome Discoverer (ver. 1.4) with both SequestHT and Mascot search engines.

Data was searched against the Uniprot human target and reverse-decoy database

(4/16/14 download). Mass accuracies for precursor and fragmentation spectra were

set at 5 ppm and 0.02 Da, respectively. Variable modifications were set for

oxidation(M), deamidation(N,Q), and 13C6 – R, K. Fixed modifications were set for

carbamidomethyl(C). All protein identifications were made at a false discovery rate

of 1%.



RESULTS

Global Comparison of Depleted versus Un-depleted Heavy Secretome:Plasma

Samples

The classic plasma proteins (with the exception of IgGs) are primarily

secreted from the liver into blood where they serve a variety of functions to maintain

homeostasis. The HepG2 liver cancer cell line has served as an important

experimental model for liver hepatocytes in that they secrete the major plasma

proteins in proportion to the levels found in blood. Although they can not replicate

the constant dynamic flux of plasma protein clearance and activity (e.g., protease-

protease inhibitor), the levels and form of the proteins have many similarities to

blood. The sample preparation workflow used for this study is illustrated in Figure

1A. Approximately 10 million heavy-labeled HepG2 cells were incubated in 12 ml of

serum-free heavy SILAC media for 24 hours. After 24 hrs, the media was

centrifuged and then concentrated using 3×3kD MWCO filters (3×4ml

aliquots/MWCO) while a second 12 ml of serum-free media was added to generate

the second heavy secretome sample (i.e., 48 hr) for the second part of this study

(vide infra). Total protein concentration for the 24 hr heavy secretome was

determined to be 1.9 ± 0.2 mg/ml @ 280 nm (~1.8 mg total protein in the original 12

ml of media). A Coomassie-stained 1D gel of the SILAC-labeled HepG2 secretome

relative to the healthy EDTA-plasma sample is shown in Figure 1B with both

samples showing a strong serum albumin band at 69 kDa. Eight identical 1:1 (w:w)

secretome:plasma samples were prepared as follows: 109 µl of SILAC-labeled

HepG2 secretome sample was spiked into 2.9 μl of plasma at a 1:1 (200ug:200ug)

ratio and gently vortexed. The first four secretome:plasma sample sets were



processed without depletion and the second secretome:plasma sample set was

depleted of serum albumin and immunoglobulins. The 1:1 (w:w) secretome:plasma

proteomic samples were prepared by FASP in quadruplicate with and without serum

albumin and IgG removal to determine the effect of protein depletion on the number

of identified and quantified proteins (based on the heavy:light (H/L) tryptic peptide

ratio).

A summary of the two LC-MS/MS datasets is provided in Figure 1C. A total

of 528 protein groups were identified initially, 19 protein groups were removed due to

lack of quan channel information, resulting in 509 total proteins identified in the un-

depleted plasma spiked with SILAC-HepG2 secretome. These proteins were further

separated based on their presence only as heavy tryptic peptides (352 total), only as

light tryptic peptides from plasma (95 total), or quantied proteins that had H/L pairs

(62 total). Importantly, the initial Proteome Discoverer search of the un-depleted

secretome:plasma dataset yielded 95 quantified proteins. When we manually

evaluated the data we found that those proteins with H/L ratio outside of 40-0.03

were incorrectly imputed. Thus, after manual validation the number of quantified

proteins with true H/L tryptic peptides was reduced to 62. The depleted

secretome:plasma samples resulted in the identification of 582 protein groups.

These proteins were further separated based on their presence only as heavy tryptic

peptides (440 total), only as light tryptic peptides from plasma (86 total), or quantied

proteins with H/L pairs (56 total). As with the un-depleted dataset, the original

number of quantified proteins was higher (101) because it included several proteins

with imputed light or heavy tryptic peptides. After manually filtering these proteins

using the 40-0.03 H/L ratio cut-off, we were able to manually verify that 56 proteins



contained light and heavy tryptic peptide pairs. The full list of identified proteins with

associated peptides is given in Supplementary Table 3.

A surprising finding when we compared the light channel plasma proteins in

the un-depleted and depleted datasets was the lower number of protein

identifications in the depleted sample. One would have expected the samples

subjected to depletion to yield higher numbers of unique plasma proteins. We found

that out of the 95 light channel proteins in the un-depleted sample, 45 were IgGs

versus 15 IgGs identified in the 86 light channel proteins from the depleted plasma

sample. After removing the IgG contributions, the total identified plasma proteins in

the light channel was 50 (un-depleted) versus 73 (depleted) identified proteins. Thus,

the Top2 depletion kit effectively removed 32 IgGs from plasma. The same holds

true for the heavy channel wherein the removal of the high abundant IgGs and

serum albumin resulted in higher numbers of SILAC HepG2 secretome proteins

being identified.

We then evaluated the overlap between the quantified proteins in both sample

preparations (i.e., 62 protein groups in the un-depleted sample and 56 protein

groups in the depleted sample; Figure 1C). There were a total of 52 shared

quantified proteins in both sample preparations with 10 and 4 quantified proteins in

the un-depleted and depleted samples, respectively. The 52 common proteins with

H/L ratios were respresented in all four biological replicates for both

secretome:plasma samples with the exception of Kallistatin (SERPINA4), which was

identified in two of the four biolgical replicates in the un-depleted plasma samples. A

full list of quantified proteins from the bottom Venn diagram (Figure 1C) is given in

Table 1 including protein accession numbers, gene identification, protein names,

molecular weights, % sequence coverages, and log2 H/L values.



A scatter plot comparison of log2 H/L values for the 52 quantified proteins from

both the un-depleted and depleted samples (Table 1) is shown in Figure 2. Linear

regression analysis of the scatter plot shows excellent overall agreement for both

samples sets with a slope = 0.97 and R2 = 0.97. Furthermore, the mean log2 H/L

values for un-depleted (0.44) and depleted (0.43) are not statistically different (p=

0.449) suggesting overall, the depletion did not affect the global quantitative

accuracy. The scatter plot in Figure 2 has several highlighted data points for the

purpose of discussion. First, the individual difference in log2 H/L values for serum

albumin in un-depleted (-1.38) and depleted (-2.25) is statistically significant (p<0.05)

suggesting the Top 2 depletion kit has a higher affinity for plasma-derived serum

albumin than HepG2-derived serum albumin (Figure 2). Although the details of the

Top2 serum albumin antibody are not known, we can speculate that the antibody

must be robust enough to work for plasma samples from a population of patients

with different genetic backgrounds. Thus, although we have almost 70% sequence

coverage for serum albumin, further investigations are needed to assess the folding

and potential post-translation modifications of HepG2-derived serum albumin to fully

understand the differential affinity to the Top2 kit.

Two sets of quantified protein groups are highlighted in Figure 2 including

apolipoproteins and protease inhibitors. Apolipoproteins form multi-protein

complexes that transport and clear extracellular lipids throughout the body. The

circulating levels in plasma can serve as biomarkers for assessing cardiovascular

disease risk and as indicators for the effectiveness of drugs.[29] The analysis of

lipoproteins by LC-MS/MS remains a challenge due to the large heterogeneous

nature of lipoprotein particles and their association with lipids that can alter

enzymatic digestion efficiency.[30, 31] A total of eight apolipoproteins were



quantified in this study (Table 1, Figure 2) including APOA1, APOA2, APOA4,

APOB, APOC3, APOE, APOH, an APOM. APOA1 (30.8 kDa) and APOA2 (5.9 kDa)

are the primary structural protein in high-density lipoprotein (HDL) whereas APOB

(515.3 kDa) is the primary structural protein in very low-density (VLDL) and low-

density lipoprotein (LDL).[29] APOA1 and APOA2 were measured in the un-

depleted sample at ~66% and ~40% sequence coverage, respectively and quantified

with average log2 H/L ratios of -0.02 and -0.7, respectively (Table 1). Albumin and

IgG depletion did not affect the sequence coverage or quantitation for APOA1 and

APOA2 (Figure 2). APOB was measured at ~27% sequence coverage in both the

un-depleted and depleted samples. However, the average log2 H/L ratio for APOB

increased significantly (p<0.01) from 0.76 to 1.20 between the un-depleted and

depleted sample, respectively.

The tryptic peptide sequence coverage maps for the eight apolipoproteins

quantified in both depleted and un-depleted samples are shown in Figure 3A with

representative H/L tryptic peptide pairs shown from the 4563 amino acid APOB

protein sequence. The representative mass spectra were selected from three

extreme regions of the protein to show the stability and similarity of expression (~1:2)

of the H/L ratio. Furthermore, the 27% sequence coverage for a 515.3 kDa protein

provides a significant amount of quantitative information for such a large and

important plasma protein. Similar extensive sequence coverage was seen for the

remaining quantified apolipoproteins shown in Figure 3A. Given the challenges

associated with measuring large, multi-component lipoproteins in plasma, these data

suggest the HepG2-derived lipoproteins may serve as useful internal standards for

comparative MS-based biomarker discovery studies in clinically relevant phenotypes

(e.g., cardiovascular disease).



Multiple protease inhibitors were quantified in this study including several

serine protease inhibitors (SERPINs) and alpha-2 macroglobulin (A2M), a broad

specificity protease inhibitor (Figure 2). Protease inhibitors are commonly up-

regulated in cancer and play important roles in the measurement of existing

biomarkers. Prostate specific antigen (PSA) is serine protease and a widely used

biomarker for prostate cancer. Interestingly, most of PSA in blood is bound

irreversibly to SERPINs[32] and A2M[33] necessitating the measurement of both free

and bound forms of PSA. A2M is one of the most abundant proteins in plasma and

inactivates proteases using a unique trapping mechanism following proteolytic

cleavage of the bait region.[34] Burgess et al. exploited this known mechanism to

characterize A2M-protease complexes from prostate cancer patient plasma by LC-

MS/MS.[35] Interestingly, the H/L ratio for the tryptic peptide pair in the A2M bait

region did not show differences relative to the remainder of the A2M H/L tryptic

peptide pairs. One might expect the bait region peptide ratios to be perturbed with

higher blood protease levels which could ultimately be used to detect differential

protease activity in patients.

Alpha-1-acid glycoprotein 2 (ORM2) is a transport protein that can bind to

acidic drugs but its biological function is not well understood. This protein is

highlighted to illustrate the potential power of the SILAC strategy for detecting

potential post-translational modifications and/or sequence variants. Figure 3B

shows representative precursor mass spectra of H/L tryptic peptide pairs identified

throughout the ORM2 sequence. The ORM243-51 and ORM2139-153 H/L tryptic

peptides both gave similar ratios whereas the light (plasma-based) ORM287-101 tryptic

peptide was absent. This peptide was detected in the Super-SILAC study of plasma

by Boersema et al.[18] as N-glycosylated following N-linked enrichment of SILAC-



labeled breast cancer secretome:plasma samples. In our study, the detected

HepG2-derived ORM287-101 peptide suggests the Asn-93 is not N-glycosylated

relative to the plasma-derived peptide. Thus, the HepG2 secretome approach is

capable of identifying and quantifying differentially modified amino acids throughout

multiple sequence regions in a protein.

Finally, we evaluated the coefficients of variation (% CV) for H/L peptide pairs

from the 52 proteins in the un-depleted secretome:plasma sample (Table 1). The %

CV’s were determined for the H/L peptide pairs between replicates (i.e., the % CV for

the same H/L peptide pair) and within replicates (i.e., the % CV’s of all H/L peptide

pairs detected within a given protein) and plotted in Figure 4. Figure 4A contains

the % CV’s for 857 distinct H/L peptide pairs across all four replicates with an

average and median % CV = 15.5 and 11.2, respectively. Over 80% of all tryptic H/L

peptide pairs for the 52 proteins in Table 1 gave % CV’s less than 20%. Figure 4B

contains the % CV’s for the H/L peptide pairs within 196 proteins detected in the 4

replicates. The lower abundant proteins did not always have >1 H/L peptide pair per

protein, thus we did not have the theoretical maximum for comparison (i.e., 4

replicates x 52 proteins = 208). The within protein H/L % CV’s gave an average and

median % CV = 31.6 and 25.3, respectively with ~20% of within protein H/L % CV’s

falling below 20% CV. It is evident from Figure 4A and 4B that the formation of

tryptic peptides from the same proteins in the secretome and plasma are highly

reproducible for a given peptide, but significant differences within a protein contribute

to differential tryptic peptide abundances. The reason(s) for this differential

digestion efficiency (e.g., SNPs, PTMs, isoforms) is currently under investigation.

Nonetheless, the between replicate reproducibility for tryptic peptide formation



suggests this approach can be used to precisely measure plasma protein changes

within and between patient samples.

Linear range of quantification

In an effort to determine the linear range of quantitation, a serial dilution

experiment was conducted using the second secretome sample (i.e., 48 hr) spiked

into plasma. We first empirically determined the 1:1 (H/L) ratio for serum albumin by

LC-MS/MS and then generated a serial dilution series (vol:vol) covering 100×

dynamic range as follows: 0.13μl/80μl (0.0016), 0.4μl/80μl (0.005), 1.3μl/80μl

(0.016), 4.0μl/80μl (0.05), and 13.0μl/80μl (0.16) (Plasma:Secretome). The serial

dilution samples were processed by FASP and then analyzed in triplicate by LC-

MS/MS. Figure 5 shows the linear responses for serum albumin and the 8

apolipoproteins quantified in Table 1 with excellent agreement between the 9

proteins. The linear regression analysis for the 9 proteins in Figure 5 gave the

following slopes and R2 values: Serum Albumin (slope= -1.72, R2= -0.993); .ApoA1

(slope= -1.71, R2=0.985); Apo4 (slope= -1.51, R2=0.928); ApoB100 (slope= -1.84,

R2=0.991); ApoC3 (slope= -1.82, R2=0.979); ApoE (slope= -1.69, R2=0.982); ApoH

(slope= -1.47, R2=0.981) omitting the final dilution of 0.16; and ApoM (slope= -1.86,

R2=0.986) omitting the first dilution of 0.0016. The LC-MS/MS serial dilution data for

all 52 proteins is given in Supplemental Table 4 and representative H/L peptide

spectra for five of the lipoproteins vs. serum albumin are shown in Supplemental

Figure 1. The linear response for the 52 proteins over 2 orders of magnitude

illustrates the potential for high precision relative quantification in patient samples for

biomarker discovery and drug treatment monitoring using the HepG2 cocktail of

intact stable isotope labeled proteins.



CONCLUSIONS

We have successfully demonstrated the potential for using the SILAC-labeled

HepG2 secretome as source for generating intact stable isotope labeled plasma

proteins for comparative LC-MS/MS studies in human plasma. A total of 62 and 56

plasma proteins were quantified using the HepG2 secretome from undepleted and

depleted plasma, respectively. For the 52 shared quantified plasma proteins in both

samples, we found that depletion of albumin and IgG using a commercial depletion

cartridge did not significantly affect the global quantitative accuracy although

individual differences for some proteins such as serum albumin and APOB were

found significant. Furthermore, the between replicate quantitative reproducibility was

excellent for the 857 H/L peptides detected with an average % CV = 15.5%. Greater

than 80% of the H/L peptides had % CV’s less than 20%. Finally, LC-MS/MS

analysis of a secretome:plasma dilution series showed linear responses for the

quantified proteins over 2-orders of magnitude in concentration. Future directions

will focus on understanding and optimizing the effect of culture conditions secretome

composition with an emphasis on apolipoprotein and acute-phase protein production.

Apolipoproteins are notoriously difficult to measure clinically and this strategy could

prove useful as a new approach for MS-based comparative studies of patients with

cardiovascular diseases. Overall, the ability to generate large, intact plasma proteins

in sufficient quantities from a robust immortalized cell line holds great promise for

extending the application of SILAC into MS-based clinical biospecimen analysis.



ACKNOWLEDGMENTS

We thank the Virginia Commonwealth University School of Pharmacy, VCU

Office of Research, and VCU Health Sciences for financial support. The authors

gratefully acknowledge the anonymous reviewers for their constructive suggestions.

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Figure 1. Overview of the experimental workflow used in this study. (A) Coomassie-stained 1-D gel for 10 µg of SILAC-HepG2 secretome (lane 2) and 10 µg of un-depleted human plasma (lane 3) with corresponding molecular weight markers (lane 1). (B) Venn diagrams showing the number of proteins identified in the SILAC-HepG2 secretome spiked into human plasma (1:1) with and without albumin and IgG depletion. 62 and 56 plasma proteins contained H/L pairs in the un-depleted and depleted sample sets, respectively. 52 plasma proteins with H/L pairs were detected in both the un-depleted and depleted samples. SILAC = stable isotope labeling with amino acids in cell culture; MWCO = molecular weight cut-off filter; FASP = filter-assisted sample preparation; H/L = Heavy/Light



Figure 2. Correlation plot showing the effect of albumin and IgG depletion on the Log2 H/L ratios for the 52 plasma proteins detected in both depleted and un-depleted plasma/SILAC HepG2-secretome samples. Plasma proteins that constitute large proportions of the quantified proteins are highlighted (apolipoproteins and protease inhibitors) and frequency plots for all 52 proteins in each dataset are provided in the upper and right margins



Figure 3. Sequence coverage for apolipoprotein H/L peptide pairs and three representative H/L peptide spectra for ApoB100 (black triangles). (A) Sequence coverage for alph-1-acid glycoprotein 2 (ORM2) H/L peptide pairs and three representative H/L peptide spectra (black triangles). The heavy QNQcFYNSSYLNVQR sequence (secretome) was detected but the light sequence was not suggesting N-linked glycosylation of the plasma-derived protein.



Figure 4. Distribution of % CV’s for H/L peptide ratios between replicates (A) and within replicates (B) for all 52 H/L plasma proteins.



Figure 5. Log2 H:L values for serum albumin and all detected apolipoproteins versus serial dilution (volume:volume) of human plasma in the SILAC-HepG2 secretome. Volume:volume ratios were centered at 1.25ul/80ul (0.016) which corresponded to the serum albumin H:L peptide ratios = 1. Spiked in ranges were as follows: (Plasma/HepG2 Secretome): 0.128ul/80ul (0.0016); 0.4ul/80ul (0.005); 1.25ul/80ul (0.016); 4ul/80ul (0.05); and 13.2ul/80ul (0.16). The serial dilution data for all 52 plasma proteins including log2 H/L, slopes, and R

2 values are given in Supplemental Table 4.

Representative H/L peptide spectrum ‘AEFAEVSK’ from Serum Albumin showing 1:1 ratio for the 0.016 dilution.



Table 1. Plasma proteins quantified in the un-depleted and depleted sample sets including the shared 52 proteins, 10 proteins in the un-depleted sample, and 4 proteins in the depleted sample.

Accession Gene ID DescriptionMW

(kDa)

Un-depleted Depleted

% Sequence

Coveragelog2 H/L

% Sequence

Coveragelog2 H/L

P02763 ORM1 Alpha-1-acid glycoprotein 1 23.5 48.3 -1.29 48.3 -1.28

P19652 ORM2 Alpha-1-acid glycoprotein 2 23.6 47.3 -1.11 33.8 -0.66

P01011 SERPINA3 Alpha-1-antichymotrypsin 47.6 31.2 -0.51 30.7 -0.42

P01009 SERPINA1 Alpha-1-antitrypsin 46.7 61 0.61 55.5 0.77

P04217 A1BG Alpha-1B-glycoprotein 54.2 21.4 -0.88 24.4 -0.84

C9JMH6 SERPINF2 Alpha-2-antiplasmin 27.8 32.2 1.08 24.7 1.07

P02765 AHSG Alpha-2-HS-glycoprotein 39.3 31.6 2.52 26.7 2.53

P01023 A2M Alpha-2-macroglobulin 163.2 52.2 0.84 51 0.97

P01019 AGT Angiotensinogen 53.1 24.5 1.71 18.1 1.73

P01008 SERPINC1 Antithrombin-III 52.6 37.7 -1.09 31.5 -0.92

P02647 APOA1 Apolipoprotein A-I 30.8 66.3 -0.02 66.7 0.00

V9GYE3 APOA2 Apolipoprotein A-II 5.9 40.4 -0.70 36.5 -0.85

P06727 APOA4 Apolipoprotein A-IV 45.4 48.2 -5.13 41.4 -4.91

P04114 APOB Apolipoprotein B-100 515.3 27 0.76 27.5 1.20

P02656 APOC3 Apolipoprotein C-III 10.8 34.3 -0.39 27.3 -0.42

P02649 APOE Apolipoprotein E 36.1 53.6 3.12 50.8 3.44

O95445-2 APOM Apolipoprotein M 13 38.8 1.83 38.8 2.07

P02749 APOH Beta-2-glycoprotein 1 38.3 51 4.22 44.1 4.23

P22792 CPN2 Carboxypeptidase N subunit 2 60.5 15.2 0.26 15.2 0.16

P00450 CP Ceruloplasmin 122.1 32.5 -1.71 27.2 -1.52

P10909-4 CLU Clusterin 48.8 28.1 0.67 27.9 0.57

P12259 F5 Coagulation factor V 251.5 8.7 3.09 12 3.73

P00742 F10 Coagulation factor X 54.7 17.2 1.57 21.9 1.44

P01024 C3 Complement C3 187 56.3 0.10 46.9 0.18

P0C0L5 C4B Complement C4-B 192.6 33.9 -0.59 28.5 -0.28

P01031 C5 Complement C5 188.2 11.8 -0.78 15.2 -0.98

B4E1Z4 CFB Complement factor B 140.9 28.4 -0.73 24.6 -0.55

G3XAM2 CFI Complement factor I light chain 65 25.5 0.90 26.7 0.88

P08185 SERPINA6 Corticosteroid-binding globulin 45.1 19.3 -0.53 21.2 -0.51

P02671 FGA Fibrinogen alpha chain 94.9 35.5 -1.05 33 -1.20

P02675 FGB Fibrinogen beta chain 55.9 57.6 -2.32 54.8 -2.23

C9JPQ9 FGG Fibrinogen gamma chain 13.5 69.8 -1.16 69.8 -1.12

P02679-2 FGG Fibrinogen gamma chain (Isoform Gamma-A) 49.5 63.2 -1.03 58.8 -1.10

P02751-17 FN1 Fibronectin 256.3 35 2.25 31.4 2.16

P00738 HP Haptoglobin 45.2 53 -4.98 44.1 -4.95

P00739 HPR Haptoglobin-related protein 39 50.9 -4.40 50.3 -3.91

P05546 SERPIND1 Heparin cofactor 2 57 33.1 1.12 22.7 1.18

P01344 IGF2 Insulin-like growth factor II 20.1 18.3 4.52 18.3 4.40

Q5T985 ITIH2 Inter-alpha-trypsin inhibitor heavy chain H2 105.2 44.4 2.14 39.8 2.20

Q06033-2 ITIH3 Inter-alpha-trypsin inhibitor heavy chain H3 99.3 18 4.48 10.7 2.41

P29622 SERPINA4 Kallistatin 48.5 4.7 0.06 14.8 0.33

P02788-2 LTF Lactotransferrin 73.1 3.9 -0.38 3.2 0.19

P36955 SERPINF1 Pigment epithelium-derived factor 46.3 26.3 4.91 27.5 4.85

P05154 SERPINA5 Plasma serine protease inhibitor 45.6 28.3 5.06 25.4 5.15

P02760 AMBP Protein AMBP 39 42.9 3.47 41.2 3.86

Q5VY30 RBP4 Retinol binding protein 4, plasma, isoform CRA_b 23 29.7 1.88 29.7 1.90

P02787 TF Serotransferrin 77 59.9 0.71 54.4 0.80

P02768 ALB Serum albumin 69.3 68 -1.38 55.8 -2.25

P05543 SERPINA7 Thyroxine-binding globulin 46.3 15.7 1.88 21 1.39

P02766 TTR Transthyretin 15.9 48.3 -0.20 32.7 -1.24

P04004 VTN Vitronectin 54.3 24.1 -0.54 21.1 -0.54

P25311 AZGP1 Zinc-alpha-2-glycoprotein 34.2 23.5 -0.48 26.5 -0.36

Q96IY4-2 CPB2 Carboxypeptidase B2 40.9 4.2 -0.30

F8W7M9 FBLN1 Fibulin-1 77.1 15.4 2.39

P06396 GSN Gelsolin 85.6 21.1 1.73

P18669 PGAM1 Phosphoglycerate mutase 1 28.8 24.8 3.67

P00747 PLG Plasminogen 90.5 43 -4.84

Q15113 PCOLCE Procollagen C-endopeptidase enhancer 1 47.9 13.6 4.39

P00734 F2 Prothrombin 70 39.4 0.21

P07996 THBS1 Thrombospondin-1 129.3 4.8 -0.60

G8JLA8 TGFBI Transforming growth factor β-induced protein ig-h3 74.6 10 4.02

K7ERI9 APOC1 Truncated apolipoprotein C-I 8.6 26 -2.34

P16870-2 CPE Carboxypeptidase E 49.9 30.91 0.81

P06396-2 GSN Gelsolin 80.6 17.1 1.94

E9PIT3 F2 Thrombin light chain 65.4 34.48 0.27

P07225 PROS1 Vitamin K-dependent protein S 75.1 12.72 -1.52

Table 1. Plasma proteins quantified in the un-depleted and depleted sample sets including the shared 52

proteins, 10 proteins in the un-depleted sample, and 4 proteins in the depleted sample.

Table 1

Documents

Intact stable isotope labeled plasma proteins from the SILAC-labeled HepG2 secretome