Characterization of Sample Loss Caused by Competitive Adsorption of

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Characterization of Sample Loss Caused by Competitive Adsorption of Milk Proteins in Vials Using SDS-PAGE Ameya V. Ranade, Rustam Mukhtarov, Ken Jia An Liu, Melissa A Behrner, and Bingyun Sun Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b04281 • Publication Date (Web): 28 Feb 2019 Downloaded from http://pubs.acs.org on March 3, 2019

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Characterization of Sample Loss Caused by Competitive Adsorption of Proteins in Vials Using SDS-PAGE Ameya V. Ranade1, Rustam Mukhtarov1, Ken Jia An Liu2, Melissa A. Behrner2, and Bingyun Sun1,2*

1. Department of Chemistry, Simon Fraser University, Burnaby, British Columbia, Canada 2. Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada

* Corresponding author: Bingyun Sun, Simon Fraser University, Burnaby, BC, Canada, V5A 1S6, Email: [email protected]

Keywords: Interfacial protein adsorption, protein adsorption at solid surfaces, sample loss, sample vials, SDS-PAGE, Direct Protein Analysis, proteomics, multiplexed quantification of protein adsorption

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ABSTRACT: Sample loss caused by competitive protein adsorption on solid surfaces from complex samples remains to be a major hurdle in sensitive analyses of proteins. No label-free techniques can easily quantify individual proteins adsorbed on irregular surfaces of Eppendorf vials or Falcon tubes, which are commonly used to contain complex biological samples. Multiplexed characterization of such adsorption by different proteins is technically challenging. Herein, we developed a Direct Protein Analysis based on SDSPAGE (SDS-PAGE/DPA) for characterization of sample loss occurred on curved surface with limited area. Using this simple and easily accessible method, we discovered the effect of EDTA on surface adsorption of different milk proteins, specifically an augmented loss of milk proteins in low-binding sample vials. In this study, we also identified severe biases of silver staining, and established proteomics-based mapping of protein distribution in biological samples, for absolute quantification of competitive protein adsorption on irregular surfaces.


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INTRODUCTION: Protein adsorption is the accumulation and adhesion of protein molecules to solid surfaces 1-3. It is critical in a variety of fields including biosensors, microfluidics, and medical implants 4-8. The non-specific adsorption of target proteins on sample vials can be detrimental to many sensitive analyses 9-11, because the degree of sample loss escalates as protein concentration gets lower. In particular in single-cell proteomics for example, the adsorption-caused loss of sample has been the major obstacle in successful detection of thousands to millions of different protein species from less than 1 ng of total proteins 12-17.

In bulk proteomic analysis, sample loss caused by non-specific adsorption can also

skew the quantitation accuracy and detection sensitivity 18-21. Successful prevention of sample loss, particularly in complex biological samples is challenging. Quantitative assessment of adsorbed proteins with individual protein resolution is a priori for both mechanistic understanding and successful prevention of the nonspecific adsorption events 3, 8, 22, 23. Decades of research at interfaces has greatly advanced our knowledge of protein behavior on solid surfaces and helped to develop a series of commercial products to decrease such undesired adsorption, using surface modifications, novel materials, special processing steps and so on 24. Yet the understanding of individual protein adsorption in complex samples remains elusive. The challenge lies in the limited approaches that are available to quantify trace yet complex proteins adsorbed on irregular surfaces25. However, commonly used tubes and vials to handle biological samples are always having an irregularly curved surface with limited area of a few centimeters. For classic characterization techniques such as


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quartz crystal microbalance (QCM), surface plasma resonance (SPR), atomic force microscopy (AFM), special instruments are often required, the surface that can be characterized are restricted, and only total proteins can be studied but not the individual proteins in mixture 25-26. Surface-flexible techniques such as fluorescence or radioisotope characterization, which are also suitable for multiplexed analysis, often need labeling of target proteins. Alternatively, an affinity compound is required such as antibodies for enzymatically linked immunosorbent assay (ELISA) 25. These extra steps consume time, have varied yields, or can alter the conformation thereof the adsorption property of proteins. Current understanding and prevention of adsorption is mostly built from the characterization of individual model protein(s), yet it is known that adsorption event highly depends on proteins and their interacting substrates 18, 27. In biological samples, numerous proteins coexist and compete for occupancy at the interface, i.e. Vroman effect 28.

Learned models are difficult to generalize the behavior of diverse biological samples,

such as body fluids and cell lysates. Particularly in the interaction with solid surfaces, forces such as hydrophobic, electrostatic, van der Waals, and hydrogen bonding all take place 2, 24. It is a good practice to characterize sample loss in each study, particularly for sensitive or quantitative protein analysis. To facilitate such practice, we report here the development of a simple method using sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) to study multiplexed protein adsorption to solid surfaces in complex samples. SDS-PAGE has been employed in the elegant and widely used Solution-Depletion method to monitor a variety of protein adsorption events 29-31. The method however is limited to systems of particles and fibers which have large surface area. The reason is because the method 4 ACS Paragon Plus Environment

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measures the concentration difference before and after the protein solution (solute) in contact with the substrate (sorbate). Only sorbate with large enough surface can generate intensity difference distinguishable on SDS-PAGE gel. In contrast to Solution-Depletion method, our SDS-PAGE approach directly measures the desorbed proteins stripped from the vial surface, and we named this method Direct Protein Analysis (abbreviated as DPA, or SDS-PAGE/DPA) 32. Because the method measures stripped proteins, it is not constrained by either surface topology or the pre-existing high background in SolutionDepletion method. The concept behind our method for improved sensitivity than Solution-Depletion method is similar to that of fluorescence to absorption measurement. We demonstrated in the past the capacity of our method on model proteins of bovine serum albumin (BSA) and myoglobin with a detection sensitivity of nanogram to subnanogram 32. But, its ability to study multiplexed adsorption in complex biological samples was not explored. Here, we identified and overcome several challenges to make the DPA method suitable for characterization of competitive adsorptions. The key advancements are the optimization of desorption efficiency and the strategies for absolute quantification of multiple adsorbed proteins simultaneously. We carried out current studies with milk powder, which has a complex protein composition and is frequently used as blocking agent in bioassays to prevent or minimize undesired protein adsorption 33. Yet, how individual milk proteins contribute to the overall adsorption has not been addressed in detail, including the adsorption of casein micelles. In this study, we interrogated the differential adsorption of milk proteins to a subset of commercial vials, and investigated the EDTA effect to milk adsorption. 5 ACS Paragon Plus Environment

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EXPERIMENTAL METHODS: Materials: Skimmed Milk powder was procured from Saputo Inc. (Montreal, Quebec, Canada), Resolving gel buffer, stacking gel buffer, gel electrophoresis assembly, 30% acrylamide and ammonium persulphate were purchased from BioRad (Hercules, California, USA). Polypropylene vials without specification were obtained from VWR. Sodium dodecyl sulphate, bromophenol blue, silver nitrate, Tris(2carboxyethyl)phosphine (TCEP), dithiothreitol (DTT), and iodoacetamide (IAA) were from Sigma. Sequence grade bovine pancreas TPCK-treated trypsin (EC 3.4.21.4) was obtained from Worthington Biochemical Co. (Lakewood, NJ, USA). The rest of chemicals were obtained from Thermo Fisher Scientific.

Adsorption and stripping: In a typical procedure, 1 mg/mL milk-protein working solution was prepared by direct dilution of a stock at ~ 12 mg/mL concentration in phosphate buffered saline (PBS). Based on a published method 32, 200μL of the working solution was incubated with 0.65 mL Eppendorf vials (VWR 87003-290) in upright position at room temperature overnight without agitation. After incubation, the protein solution was removed, and the sample vials were rinsed with 200μL of PBS by gentle pipetting (10 times). After this initial wash, the sample vials were further rinsed twice, each with 200μL of PBS and 15 seconds of vortex. The remaining adsorbed proteins on the vial surface were stripped by 200μL of 0.5% SDS in DI water or SA solution (0.5% SDS in 100mM NH4HCO3). Prior to SDS-PAGE analysis, the protein solutions including the wash as well as the stripping solutions were dried by Speedvac (Thermo Scientific). Each


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condition was tested with 2-3 replicates on one gel and for multiple times on different gels to confirm the observation.

SDS-PAGE and image analysis: The dried samples together with milk protein standards with known quantity were reconstituted in SDS-PAGE loading buffer, and separated on 15% tris-glycine SDS-PAGE gels. The resolved gel was fixed by 25% isopropanol in 10% acetic acid for 1 hour, and was subsequently stained by silver nitrate following previous protocol 34-35. The stained gel was digitized by a laser scanner (Canon LiDE 110) and analyzed by image J (http://rsb.info.nih.gov/ij/). Without specification, the total band intensity in each milk standard lane was used to construct the standard curve, which was used to calculate the total protein quantity in the sample.

EDTA effect: One milliliter of 2 mg/mL milk-protein working solution was prepared similarly as described above. Stock EDTA of 0.5M was added to the sample solution to achieve a final EDTA concentration of 4 mM. Another batch of sample was prepared without EDTA to serve as control. The samples were then split into 200 µL aliquots in testing tubes and incubated under room temperature overnight. Next day the protein solution was removed. The tubes were subsequently washed three times, each with 200 µL of PBS by 15 seconds of vortex. The remaining adsorbed proteins on the vial surface were stripped by 200 µL of SA solution and dried by Speedvac. The dried samples were reconstituted in SDS-PAGE loading buffer and resolved in a polyacrylamide gel. The gel was then fix and stained as described above.


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Screening of commercial sample vials: Four milliliters of 2 mg/mL milk-protein working solution was prepared as described above. Stock EDTA was then added to the sample for a final EDTA concentration of 4 mM. Aliquots of 200 µL of this solution was taken and added into following 11 commercial vials: C4000-1G (ThermoFisher), PI90410 (ThermoFisher), 87003-290 (VWR), 3206 (Corning), 3446-PK (ThermoFisher), AM12350 (Ambion), 352095 (Corning), 87-B600-C (Progene – UltiDent Scientific), 87B200-C (Progene – UltiDent Scientific), MC01015 (Lion International, L.L.C), and 186001437DV (Waters), respectively. The vials were incubated under room temperature overnight. After incubation, the sample vials were treated based on the same procedure described above, and final stripped samples were dried by Speedvac prior to SDS-PAGE analysis.

Trypsin digestion of milk proteins. The digestion was carried out using a typical trypsin digestion protocol with modifications. Milk proteins of 0.1 mg were dissolved in denaturation buffer (40 mM Tris pH 8.0, 5 mM EDTA, 10 mM TCEP, 0.5% SDS), and heated to 100 C for 10 min. Ultrapure urea powder was added to the cooled solution for a final concentration of 8 M before incubating the solution at 37 C for 30 min with endto-end rotation. Subsequently, IAA of 15 mM was added and the solution was incubated in the dark at room temperature for 30min before quenched by 15 mM DTT. The sample was then diluted 8 times with 40 mM Tris pH 8.0 and digested overnight with 2 µg of MS-grade trypsin (Pierce Cat. 90057) at 37 C. The obtained milk sample was purified by Oasis MCX 1 cc cartridge (Waters Co. Cat. 186004648) and dried by Speedvac.


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LC-MS/MS proteomics analysis. The digested and purified milk sample was resuspended in 0.1% formic acid (FA) and analyzed following a previous procedure 36. An EASY-nLC 1000 coupled with Q-Exactive HF through an EASY-Spray source (Thermo Scientific, Mississauga, ON, Canada) was used. One microgram of sample was first loaded on a commercial Pepmap EASY-spray C18 capillary trap column (75 µm x 20 mm, 3 µm resin and 100 Å pore size, Thermo Fisher Cat. 164535), and eluted onto an EASY-spray C18 capillary separation column (50 µm x 150 mm, 2 µm resin and 100 Å pore size, Thermo Fisher Cat. 03052572). The elution gradient was 20 min of 2-35% buffer B (0.1% FA in acetonitrile) in buffer A (0.1% FA) at a constant flow rate of 200 nL/min. The inlet voltage of Q-Exactive HF was 2.5 kv and the inlet temperature was 250 C. For Q-Exactive HF MS/MS analysis, data-dependent method was used to select top 5 most abundant precursor ions in MS 1 scan for higher energy collisional dissociation (HCD) MS/MS fragmentation with a dynamic exclusion of 10 s. The MS1 precursor scan range was 400-2000 Th with mass resolution of 60,000 and the MS2 resolution is 30,000. The automatic gain control (AGC) values for MS1 and MS2 scans are 3E6 and 1E5, respectively. Precursors with unassigned change(s) of 1 and > 5 were excluded from MS2 scans.

Database search and protein inference. The resolved raw files from Q-Exactive HF were processed by Proteome Discoverer 2.1 (Thermo Scientific). The acquired spectra were searched using Sequest HT against Bovine Uniprot Fasta database appended with common contaminants. The monoisotopic precursor mass tolerance was set to be 10 ppm,


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and the monoisotopoic fragment mass tolerance was 0.02 Da. Criteria of a minimum of 6 amino acids and 1 miss cleavages were used for search. Cysteine carbamidomethylation was treated as a fixed modification. Protein N-terminal acetylation and methionine oxidation was treated as dynamic modifications. Final identified peptides were filtered against a strict FDR of 0.01.

RESULTS AND DISCUSSION: Feasibility of the method Prior to the current studies, we did not test the SDS-PAGE Direct Protein Analysis (SDS-PAGE/DPA) on complex biological samples. To begin with, we characterized the wash efficiency and reproducibility of the method on bovine milk proteins. Figure 1A shows the results, in which 3 milk samples at 1 mg/mL concentration were incubated with Eppendorf vials. In the gel shown in Fig. 1A, proteins in the wash and stripping solutions were examined. Multiple protein bands representing major milk proteins of caseins, βlactoglobulin, and α-lactalbumin 37 were visible. The intensity of protein bands decreased drastically as the number of rinses increased; in the last (i.e. the third) wash, only trace amount of protein was observed on the gel, suggesting an effective removal of free or loosely adhered proteins in the vial. The strong bands from final stripped samples demonstrated that the method can effectively detect adsorbed proteins. Comparing with the faint bands in the last wash, the desorbed proteins were prominent and the residual proteins in the vial after last wash had limited interference to the quantitation of the desorbed proteins. In typical storage or preparation of samples, these proteins would be permanently


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lost if not been recovered appropriately. On the contrary, these results also explained why milk can serve as a good blocking agent in bioassays for preventing non-specific adsorption. Comparative analysis of the gel-lane intensity was carried out using image J among the three stripped samples and those in corresponding wash solutions. The resolved coefficient of variations (CVs) are plotted in Fig. 1B. Stripped samples showed the smallest CV of 10%, whereas those in washes varied largely from 50% to more than 100%. The large CVs in washes indicated that the amount of free proteins left in the vial was not consistent from each preparation, and multiple washes were needed for reproducible desorption in the end. Additional washes did not further reduce the CVs in the final stripped samples, therefore three washes were used for all of the rest experiments without specification.

Stripping efficiency: Stripping efficiency is an important factor directly affects the accuracy of the absolute quantitation. It is known that different proteins respond to the same stripping agent differently 38. Previously, we demonstrated that 0.5% SDS was sufficient to desorb BSA from polypropylene vials. Yet, no agents have been studied on their efficiency to remove milk proteins from polypropylene surface. In our evaluation as shown in Fig. 2A, 0.5% SDS cannot liberate all milk proteins off the polypropylene surface. In the figure, second stripping of the same vial removed additional proteins. Reagents for the secondary stripping included both acidic and alkaline conditions, such as 100 mM HCl, 30% NH4OH, and 100 mM NH4HCO3. The pH of 11 ACS Paragon Plus Environment

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solution is known to affect surface charge of milk proteins and their interaction to the solid surface39-40. The isoelectric points of milk caseins and whey proteins are around pH 3-5 41, away from the overall neutral charge of proteins will introduce electroreplusion to protein molecules and will assist their dissociation from each other and from surfaces. A water rinse was introduced between the two consecutive strippings to minimize the carryover. The test was finished by a tertiary stripping with 80% acetonitrile to disrupt the residual hydrophobic interactions if any. To improve desorption efficiency, we screened a set of different agents and their combinations. The conditions included organics, acids, and bases together with 0.5% SDS as the control. Fig. 2B summarizes the results, in which high concentrations of acids or bases are more effective than low strength solutions, which agreed with the phenomenon that neutrally charged proteins adsorb more. After several rounds of tests, we finalized the stripping solution to be 0.5% SDS in 100 mM NH4HCO3 and abbreviated as SA solution. Fig. 2C shows that after SA treatment, further secondary stripping with organics (disruption of hydrophobic interactions) or 1M HCl (reverse of charge polarity) cannot obtain any observable bands in the gel. Using milk with known protein quantity as standards in the same gel, we constructed a calibration curve as shown in Fig. 2D. The R2 value is higher than 0.95, suggesting a good linearity that agrees with previous studies30. The measured quantity of tightly adsorbed milk proteins was 2.0 ± 0.5 µg corresponding to 1.1 µg/cm2, which also agreed with previous reports 42-43. The value doubled the amount obtained by 0.5% SDS alone, i.e. 0.55 µg/cm2. Because major casein proteins in milk, i.e. α-S1, α-S2, and β- caseins as well as major whey proteins such as β-lactoglobulin and αlactalbumin are negatively charged, the effective stripping under basic conditions is likely 12 ACS Paragon Plus Environment

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contributed by the electrostatic repulsion between negatively charged milk proteins and the negatively charged polypropylene vial surface 44.

EDTA effect. Predominantly negatively charged milk proteins such as caseins bind to calcium ions that are abundant in the milk (2.5-3.4 mM/L 45) to form micelles and give the classic opaque milky color 46. Even though the structure of the micelle core is still a subject of debate, the consensus of the outer layer of κ-casein is clear with its hydrophobic N-termini inserting into the micelle core and charged C-termini oriented towards the aqueous solution 47-48.

The removal of calcium with chelators such as EDTA, can reduce micelle size,

increase free caseins, and decrease the turbidity of the solution 49-51. From our tests, 4 mM EDTA can effectively clear the turbidity of 2 mg/mL milk determined by A280 UV-Vis absorption. In solution, caseins are rheomorphic proteins adapting an unfolded and flexible structure that cannot form crystals for X-ray diffraction analysis 52-53. In addition, caseins are amphipathic molecules with β-casein to be the most polarized 41 having highly charged N-terminal and hydrophobic C-terminal residues that are responsible to the adhesion of hydrophobic surfaces

54-57.

The release of caseins from micellar aggregation to aqueous

solution would affect its adsorption to solid surfaces; however, the effect of EDTA on surface adsorption of milk proteins was less studied 58. We wanted to test the capacity of our method to characterize such EDTA effect in milk. To this end, we used 2 mg/mL milk working solution, where the turbidity of the solution was better observed. Fig. 3A shows the gel image on a side-by-side comparison 13 ACS Paragon Plus Environment

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of desorbed milk samples treated with and without 4 mM EDTA. Quantitative analysis by Image J (Fig. 3B) showed that EDTA significantly increased the amount of adsorbed milk proteins from a two-tail, non-paired, and equal variant student t test with a P value less than 0.05. It is known that the sequestering free Ca2+ by EDTA in solution disrupts the casein micelle and increases free caseins and casein aggregates in solution49-51. Our results showed that these non-miceller casein molecules resolved by EDTA treatment exhibited enhanced surface adsorption.

Surfaces: Using bovine milk, we also examined commercial low-binding vials on their prevention of protein surface adsorption. Figs. 4A & 4B show the gel image and quantitation from a comparison between glass vials and regular Progene 1.7 ml Eppendorf vials to Fisher and Froggbio 1.7ml low-binding vials. Among different vials, glass ones adsorbed the most, whereas low-binding vials adsorbed the least, which clearly demonstrated their preventative effect on protein loss. As EDTA can increase surface adsorption of proteins, we further screened 11 types of commercial vials and tubes on their adsorption of EDTA-treated milk solutions as shown in Fig. 4C. To our surprise, all of the examined vials showed clear adsorption including the low-binding vials. The difference between regular and low-binding vials was not significant. Among all the compared surfaces, those of falcon tubes and glass vials showed highest adsorption, which agreed with the results from no EDTA condition. The EDTA effect on low-binding vials uncovered a limitation on their ability to preventing protein loss. 14 ACS Paragon Plus Environment

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Caseins are loosely structured proteins with polarized hydrophobicity. In the case of βcasein, except for its phosphorylated N-terminal end, the molecule is quite hydrophobic. Calcium ions bind to β-casein, help to neutralize the negative charges on the molecule, and assist the formation of micelles with other proteins. In our experiment, EDTA disrupted casein micelles by sequestering Ca2+, which appeared to augment the adsorption of these proteins to vials. Collectively, our results here demonstrated the strength of SDS-PAGE/DPA method in characterization of protein adsorption on sample vials. The low-binding vials can largely prevent the non-specific adsorption of soluble proteins but were less effective for the EDTA treated milk.

Quantification of individually adsorbed milk proteins. One advantage of SDS-PAGE analysis is the separation of complex proteins by their molecular weight. Using the method to achieve quantification requires appropriate standards to calibrate the output signal, in this case the silver staining intensity. Different from quantitation of the total adsorbed proteins as demonstrated above, quantifying absolute adsorption of individual proteins in complex mixture is challenging. To achieve latter requires the standard (or calibration) curve of each to be quantified components. Instead of generating these standard curves separately, SDS-PAGE allows the multiplexed measure of these calibration curves simultaneously. The main difficulty is to obtain the standards of each milk protein. Since not all proteins are commercially available, to generalize such quantitation we seek to develop a means to directly quantify the amount of 15 ACS Paragon Plus Environment

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individual proteins in bulk samples, and use them to serve as standards for quantification of trace proteins in SDS-PAGE/DPA. The total protein quantity in a sample can be measured by a variety of protein quantitation techniques such as Bradford or bicinchoninic acid (BCA) assay. To obtain the quantity of individual proteins in the mixture requires an accurate mapping of the relative distribution of each protein. One way to obtain these values is to measure the protein band intensity in the gel. However, both Coomassie and silver staining exhibit staining bias 59. In our case, the β-lactoglobulin stained much stronger in the gel than those of caseins, albeit the fact that caseins are 5-6 fold higher in quantity than β-lactoglobulin in bovine milk. To obtain an unbiased distribution of milk proteins, we employed shotgun proteomics based on liquid chromatography and mass spectrometry (LC-MS/MS). Using spectra counting 60-61, a semi-quantitative approach to evaluate the relative quantity among different milk proteins, we obtained the percentage of common protein components in our milk sample as shown in Table 1. Because the purpose was to characterize major milk proteins instead of a comprehensive elucidation of the milk proteome62-63, we did not use any pre-fractionation steps as of previous studies 50, 51. For high detection confidence, we only considered protein identification with more than 2 unique peptides. The obtained percentage of major milk proteins is listed in Table 1, i.e. α-S1 casein (28%), α-S2 casein (7.2%), β casein (22%), κ casein (7.2%), β-lactoglobulin (12%), and α-lactalbumin (3.9%). The result showed a ratio of 5.5:1 between total caseins and β-lactoglobulin, which agrees well with literature report 64, demonstrating proteomics can be a better and more reliable means than gel staining to establish protein distribution in unknown samples. 16 ACS Paragon Plus Environment

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Using the measured quantity, we generated three separated calibration curves from the gel shown in Fig. 3A for total caseins, β-lactoglobulin, and α-lactalbumin, respectively. These calibration curves are shown in Fig. 5A, from which the estimated adsorption quantity of these three types of proteins is derived (Fig. 5B). Caseins are dominant among the three, and the ratio is 6:1 between the total caseins and β-lactoglobulin in the adsorbed layer, which is slightly higher than that of 5.5:1 in the milk solution. Caseins in milk have been reported to preferentially adsorb at water/air interface in foaming and emulsification process, the occupancy on regular sample vials has never been addressed. Our SDS-PAGE method enabled direct analysis of these events and the results suggested that the behavior on the slightly curved polypropylene surface may share similarity with those in the foam. In the end, we would like to discuss the strength and limitations of the SDSPAGE/DPA method. For quantification, only absolute quantification of individual proteins will require an orthogonal characterization of protein composition in the biological samples. MS based mapping of protein distribution is more accurate and sensitive than stainingbased approaches in aiding the multiplexed quantification of individual protein species in biological samples. For relative quantification, SDS-PAGE alone is adequate enough, and the bias of staining would not interfere as the stained intensity will be compared across the same protein in the sample. We have demonstrated such analysis in Fig. 2B for screening of effective stripping agent. One of the limitations of the DPA method is the protein separation efficiency achieved by SDS-PAGE. In the case of milk, different casein isoforms cannot be resolved in the gel65. Even though LC-MS proteomics can provide relative distribution of hundreds of milk proteins, we only quantified a few major protein components in milk by SDS17 ACS Paragon Plus Environment

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PAGE. This limitation can be compensated by 2D-gel or capillary electrophoresis to certain extent. Another disadvantage of method is the staining-dependent limit of detection. The silver staining we applied is more sensitive than Coomassie; however, the staining efficiency is not consistent across the proteome with best sensitivity of sub-nanogram as we demonstrated on BSA. Direct MS characterization could be another ideal means to increase separation efficiency and lower detection limit. However, current stripping condition is not compatible to MS due to the deleterious effect of SDS to the ionization step. In addition, necessary sample preprocessing such as enzymatic digestion and desalting steps will introduce additional sample loss and compromise the sensitivity of the analysis. Therefore, SDS-PAGE/DPA is a simple and practical technique, although not perfect, but can address sample loss occurred in sample vials.

CONCLUSIONS: We report here critical developments of the SDS-PAGE Direct Protein Analysis (SDS-PAGE/DPA) for multiplexed quantification of surface non-specific adsorption of proteins on regular sample vials. First, we discovered the limit of SDS to liberate all proteins in biological samples, such as milk. After screening different stripping reagents based on the regulation of hydrophobicity and charge, we identified SA solution, i.e. 0.5% SDS in 100 mM NH4HCO3, as an effective desorption reagent to remove tightly adhered milk proteins from sample vials, particularly polypropylene vials. Second, we discovered the severe bias among different milk proteins in silver staining, and used shotgun proteomics as a more accurate and sensitive means to characterize protein distribution in


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bovine milk. The obtained information enabled multiplexed quantitation of three types of milk proteins for their surface adsorption by SDS-PAGE/DPA. Because bovine milk proteins have been well documented for their protein composition, our proteomics quantification did not provide any novel knowledge. However, for other less studied and unknown complex biosamples such as protein extracts from mammalian tissues and cells, the proteomic approach will be powerful. Finally, we demonstrated here that the SDSPAGE/DPA even though simple, but can provide insightful information on the EDTA effect to surface adsorption of milk proteins. Using this approach, we ─ for the first time ─ discovered that EDTA can succumb low binding vials to the non-specific adsorption of milk proteins. Together, we hope our study can raise necessary cautions to sample loss in sensitive protein analysis. We also hope the method can be a useful addition to the existing toolbox for the multiplexed characterization of protein competitive adsorption on irregular surfaces.

ACKNOWLEDGEMENTS: This work is supported by National Sciences and Engineering Research Council of Canada, the Canada Foundation of Innovation, and the British Columbia Knowledge Development Fund. R. M. had been partially supported by British Columbia Proteomics Network Training Award.


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Table 1. Major protein distribution in milk characterized by shotgun proteomics. Accession P02662 P02663 P02666 P02668 P02754 P00711

Description Alpha-S1-casein Alpha-S2-casein Beta-casein Kappa-casein Beta-lactoglobulin Alpha-lactalbumin

Proteomic distribution (%) 28% 7.2% 22% 7.2% 12% 3.9%

MW [kDa] 24.513 26.002 25.091 21.256 19.870 16.236


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Fig. 1. Characterization of wash sufficiency and reproducibility. A, gel results of washed off and stripped milk proteins from sample vials in three parallel sample preparations. Standards are milk proteins with known quantity. B, coefficient of variations of the total quantity of milk proteins in three parallel preparations.


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Fig. 2. Characterization of stripping efficiency. A, a gel result of desorbed proteins from thee parallel experiments, each had primary (0.5% SDS), secondary (acid and base), and tertiary (80% acetonitrile, ACN) stripping. Lanes marked as DI water are for proteins obtained from Deionized (DI) water rinse applied between primary and secondary stripping. B, relative desorption of samples in panel A normalized against that in primary stripping, i.e. 0.5% SDS. Error bar is the standard deviation of the triplicates. C, gel results of three parallel preparations of proteins desorbed from optimized primary stripping by SA (0.5% SDS in 100 mM NH4HCO3) followed by secondary (80% ACN) and tertiary (1 M HCl) stripping. Standards are milk proteins with known quantity. D, the calibration curve of milk standards in panel C obtained from Image J analysis.


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Fig. 3. EDTA effect. A, gel results of adsorbed milk proteins on 0.65 mL Eppendorf vials with and without 4 mM EDTA in the incubation solution. Three replicates were carried out for each condition. Standards are milk proteins with known quantity. B, quantity of total desorbed proteins in panel A analyzed by Image J. The error bar is the standard deviation of three replicates. The asterisk sign marks p < 0.05.


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Fig. 4. Milk protein adsorption to different commercial sample vials. A, gel results of adsorbed proteins on glass and polypropylene Eppendorf vials from different companies. MS 1.7 mL vials were low binding vials from Thermo Fisher, and glass vials were from Waters. B, quantity of total desorbed proteins in panel A analyzed by Image J. C, gel results of adsorbed proteins on commercial vails in the presence of 4 mM EDTA in the incubation solution. Standards are milk proteins with known quantity.


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Fig. 5. Absolute quantification of major milk proteins adsorbed to polypropylene sample vials. A, standard curves of three major types of milk proteins derived from gel image in Fig. 2C. B, histogram of the quantity of these milk proteins.


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Characterization of Sample Loss Caused by Competitive Adsorption of

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