Step-Wise Assessment and Optimization of Sample Handling

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Step-wise assessment and optimization of sample handling recovery yield for nanoproteomic analysis of 1000 mammalian cells Ruilin Wu, Sansi Xing, Maryam Badv, Tohid F. Didar, and Yu Lu Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.9b02092 • Publication Date (Web): 18 Jul 2019 Downloaded from pubs.acs.org on July 19, 2019

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Analytical Chemistry

Step-wise assessment and optimization of sample handling recovery yield for nanoproteomic analysis of 1,000 mammalian cells Ruilin Wu†,‡, Sansi Xing†,‡, Maryam Badv£, Tohid F. Didar*,§,£,, Yu Lu*,†,‡. †

Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8S 4K1, Canada.

‡

Stem Cell and Cancer Research Institute, McMaster University, Hamilton, ON L8S 4K1, Canada.

£ School

of Biomedical Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada.

§ Department 

of Mechanical Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada.

Institute for Infectious Disease Research (IIDR), McMaster University, Hamilton, ON L8S 4K1, Canada

ABSTRACT: Protein and peptide adhesion is a major factor contributing to sample loss during proteomic sample preparation workflows. Sample loss often has detrimental effects on the quality of proteomic analysis by compromising protein identification and data reproducibility. When starting with low sample amount, only the most abundant proteins can be identified, which often offers little insights for biological research. While the general idea about severe sample loss from low-amount starting materials is widely presumed in the proteomics field, quantitative assessment on the impact of sample loss has been poorly investigated. In the present study, we have quantitatively assessed sample loss during each step of a conventional in-solution sample preparation workflow using Bicinchoninic Acid (BCA) and targeted LC-MS/MS protein and peptide assays. According to our assessment, for starting materials of ~1,000 mammalian cells, surface adhesion, along with desalting and speed-vacuum drying steps, all contribute heavily to sample loss, in particular for low-abundant proteins. With this knowledge, we have adapted slippery liquid infused porous surface (SLIPS) treatment, commercial LoBind tubes, and in-line desalting during sample processing. With these improvements, we were able to use a conventional in-solution sample handling method to identify on average 829 proteins with 1,000 U2OS osteosarcoma cells (~100ng) with 75-min LC-MS/MS runs, an eleven-fold increase in protein identification. Our optimized in-solution workflow is straightforward and also much less equipment- and technique-demanding than other advanced sample preparation protocols in the field.

In the proteomics field, there are two major objectives driving continuous technological advancements. One is to obtain the highest number of protein identification. From mass spectrometry (MS) instrumentation innovation1 to sample fractionation method development2, researchers aim to achieve deep proteome representation in their findings. Deep proteome coverage has the potential to encompass broad dynamic range of proteins in biological samples and reveal low abundance proteins, which are often key regulatory proteins involved in cellular and disease processes3. Another objective is to utilize minimal amount of starting biological materials, or nanoproteomics4. Nanoproteomics is critical when the accessible sample is scarce, as it is often the case in clinical settings or with primary cells that do not grow in vitro. In addition, many research topics require proteome analysis at sub-cellular or single cell resolution5, 6. Although deep proteome coverage and nanoproteomics clearly offer great value to biomedical research, both remain challenging to the proteomics field and require continuous technology and methodology improvements. There is a widely accepted concept that the quality of proteomic data is only as good as the quality of injected samples. For both deep proteome coverage and nanoproteomics, sample preparation is undoubtedly one of the crucial factors to consider. Aside from conventional sample preparation techniques7, some of the effective strategies to enhance protein

identification include filter-aided sample preparation (FASP)8, single-pot solid-phase enhanced sample preparation (SP3)9 and Stage Tip10. Focusing on nanoproteomics, the most recent technological advances involving nano-droplet processing11 and microfluidic chips12 allow for proteomic analysis of 100 or fewer mammalian cells. Although these methods have shown improved protein identification, each has its own limitations. FASP has been criticized for its sample recovery and robustness13, 14. Variations of FASP, such as gel-aided sample preparation14 and enhanced FASP15, seem to have no significant improvement in protein coverage from low-amount samples14, 16. As for SP3, pH changes during sample preparation could lead to protein loss during wash steps13. Stage Tip requires fine manipulation skills and experience that can be challenging to many researchers. Nanodroplet processing and microfluidic approaches rely on specialized equipment, making them inaccessible to most laboratories. While each of the protocols described above has its own benefits and limitations, there is a common trait contributing to their improved performance against conventional workflows. All protocols focus on reducing sample processing steps or volume to minimize sample loss. Protein and peptide adhesion to labware surface is a well-known phenomenon limiting deep proteome coverage and nanoproteomics17. An early study18 showed that peptides are lost to labware surface nonspecifically and even high abundance peptides can suffer significant signal

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loss. The nonspecific nature of sample loss can be attributed to the roughness of labware surfaces where proteins and peptides randomly occupy potential binding sites19. In addition, hydrophobic peptides are more prone to surface adhesion18, which is likely due to hydrophobic interaction as common labware is made of hydrophobic materials20. Several studies have also examined the impact of sample adhesion to MS signal intensity and reproducibility21, 22. Although these studies offer valuable insights to the field, they still do not paint the full picture of sample loss in proteomic analysis. Specifically, quantitative information on the extent of sample loss seems to be poorly investigated. Most sample loss studies only compare final protein identification and lack details on protein and peptide loss during sample processing21. In addition, many studies on sample adhesion have used simple peptide mixtures, such as bovine serum albumin digest23 or standard peptides18, 20, which may not recapitulate the sample loss pattern in complex lysates. In this study, we have quantified protein and peptide sample loss using the U2OS human osteosarcoma cell line with a conventional in-solution sample preparation protocol, which is often being criticized for its low sample recovery. By quantitatively understanding sample loss in each sample preparation step, targeted adjustments were made to the insolution workflow. Specifically, we adapted two different modified tube surfaces to improve sample recovery yield. Of these two surface technologies, omniphobic slippery liquid infused porous surface (SLIPS)24 treatment helps to address surface roughness and reduce non-specific protein adhesion25, 26, while commercially available LoBind tubes (Eppendorf Corporate) have hydrophilic surface to mitigate protein and peptide loss due to hydrophobic interactions27. Together with in-line desalting, we were able to minimize sample loss and enhance protein identification from 1,000 mammalian cells using a simple workflow.

SLIPS Treatment and Lubrication. Regular 1.5mL microcentrifuge tubes (VWR, USA) were placed vertically on a petri dish and oxygen plasma treated for one minute (Harrick Plasma Cleaner, PDC-002, 230 V). Immediately after, hydroxyl terminated tubes were placed in a vacuum desiccator (Bel-Art SP Scienceware, USA) containing 200 µL of tridecafluoro1,1,2,2-tetrahydrooctyl trichlorosilane (Sigma-Aldrich, USA). The tubes were kept under vacuum for 5 hours and silanized using chemical vapor deposition (CVD). After the CVD treatment, tubes were placed in an oven and heat treated overnight at 60 ºC to complete the silanization procedure. SLIPS coated tubes were washed with ethanol. Immediately before use, 300µL of Perfluoroperhydrophenanthrene (SigmaAldrich, USA) was added into each SLIPS-coated tube to lubricate the SLIP surface. Excess lubricant was pipetted out.

RESULTS AND DISCUSSION

EXPERIMENTAL SECTION Liquid Chromatography and Tandem Mass Spectrometry (LC-MS/MS). Peptides in mobile phase A (0.1% formic acid) were injected and separated on home-made trap and analytical columns with a 75-minute reversed-phase gradient, delivered by a Thermo Fisher Ultimate 3000 RSLCNano UPLC system coupled to a Thermo QExactive HF quadrupole-Orbitrap mass spectrometer. LC-MS conditions are detailed in the Supporting Information. MS raw files are available via PRIDE partner repository with the data set identifier PXD013702. MS Data Analysis and Protein Identification. LC-MS/MS raw files were searched using Proteome Discoverer V2.2 (Thermo Fisher) against the SwissProt human database (released in June 2017), with the following parameters: full tryptic specificity with up to two missed cleavage sites, carbamidomethylation of cysteine residues as fixed modification, and protein N-terminal acetylation plus methionine oxidation as variable modifications. False discovery rate was set to 0.01. AQUA Targeted Peptide Loss Assessment. Stable-isotope labeled Absolute Quantification (AQUA) peptides for eight proteins expressed in U2OS cells at various abundance levels were synthesized by Thermo Fisher (Table S1). The amounts of AQUA peptides for each sample of 10g, 2g, and 0.2g peptides (~100,000, ~20,000, and ~2,000 U2OS cells) are listed in Table S2. AQUA targeted protein and peptide measurement conditions are described in Supporting Information.

Figure 1. Challenge for nanoproteomic analysis of 1,000 mammalian cells. (A) Schematic illustration of conventional in-solution proteomic sample preparation procedure. (B-C) 106 and 1,000 U2OS cells were processed with the conventional in-solution sample preparation method. 0.1% and 100% of the 106-cell and 1,000-cell samples were injected for LC-MS analyses, respectively. Peptide (B) and protein (C) identification were compared. (D) Protein recovery yields for 8 selected proteins (Table S1) throughout the conventional in-solution sample preparation procedure with 10g, 2g, and 200ng starting U2OS protein amount, assessed using AQUA assays. Error bars represent standard deviations of triplicate repeats.

Low Protein Identification and Severe Sample Loss from ~1,000 Mammalian Cells Using Conventional In-Solution Sample Processing Method. We first tested peptide and protein identification using conventional in-solution sample preparation workflow (Figure 1A) to assess the overall sample loss. With our nanoflow LC-MS/MS platform, in a 75-minute LC gradient run, we were able to identify on average 14,745 unique peptides and 2,349 unique proteins with an injection of 0.1% (~1,000 cells equivalent) from 106 U2OS cell (~100g total protein) tryptic peptides. In comparison, when we started with 1,000 U2OS cells (~100ng total protein), we were only able to detect 141 peptides and 76 proteins on average (Figure


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Analytical Chemistry 1B-1C). To ensure the result was not cell line specific, we repeated the experiment using HL-60 myeloid leukemia cells and observed similar trend in protein and peptide identification (Figure S1). These results highlighted the severe sample handling loss with small amount (~1,000 mammalian cells) of starting material. To quantitatively assess sample handling loss, we used targeted AQUA method28 to track individual protein losses. Two representative proteins (eight proteins in total) were chosen from each of the 103, 104, 105, and 106 copy number levels per cell in the U2OS cell line, based on a previous study3 (Table S1). We found that there was little protein loss (except for CDC2) when started from ~100,000 U2OS cells (10g total protein), while protein recovery dropped significantly for these eight proteins when we started from ~20,000 U2OS cells (2g total protein). Furthermore, when we started from ~2,000 U2OS cells (200ng total protein), only three proteins (GSK3B, MYL6, and H4) were still detectable, among which only the most abundant protein H4 remained at similar recovery yield to that acquired from ~20,000 U2OS cells (Figure 1D). These results clearly demonstrated the severe sample loss that incurred during the sample handling process from ~1,000-2,000 U2OS cells, which explained the afore-mentioned low protein identification coverage from ~1,000 U2OS cells. To improve protein identification rate from such small sample amount, we decided to assess and rectify sample loss in each of the conventional proteomic sample preparation steps.

Figure 2. Modified labware surfaces helped to mitigate protein adhesion and improved sample recovery. (A) Schematic illustration of in-tandem sample tube transfer test to assess protein loss to tube surfaces. (B) Protein recovery decreased with extended exposure to 1.5mL microcentrifuge tube surfaces with 50g, 10g, and 2g U2OS lysate, assessed by protein BCA assays. (C-D) Protein loss to tube surfaces were greatly mitigated with both LoBind tubes and SLIPS treated tubes, with 10g (C) and 2g (D) U2OS lysate, assessed by protein BCA assays. Error bars represent standard deviations of triplicate repeats.

Assessment and Improvement of Protein Loss to Labware Surface. To assess protein loss to labware surface during the sample handling workflow, we analyzed 50μg, 10μg, and 2μg total proteins from U2OS lysate (~500,000, ~100,000, and ~20,000 cells, respectively). Each sample was transferred in tandem into four 1.5mL microcentrifuge tubes to assess total protein loss (Figure 2A), which mimicked surface exposure during the conventional in-solution workflow - initial cell sample tube, desalting well, elution well and speed-vacuum tube. As expected, samples with lower protein amounts tend to

incur higher total protein loss in Tube 4, with sample recovery yields in Tube 4 for 50μg, 10μg, and 2μg total protein levels at 84.6%, 28.2%, and 10.9%, respectively (Figure 2B). Specifically, at 2μg total protein level, 56.3% of the initial sample content was lost even in the first microcentrifuge tube, while only 1.8% was lost at the 50μg total protein level. These findings demonstrated that even single tube strategies (FASP, SP3, and Stage Tip) could suffer from significant sample loss at low protein amount. Although the percentages of proteins left in Tubes 2-4 seemed constant at around 10% for 2μg, this could be caused by falling below the detection limit of the BCA assay. The experiment was repeated using 0.5mL microcentrifuge tubes (Figure S2). Less sample loss incurred in 0.5mL tubes than 1.5mL tubes, which is attributed to the decreased surface area of 0.5mL tubes. Next, we tested the performance of two modified tube surfaces - omniphobic SLIPS24 and hydrophilic LoBind surface. LoBind tubes are made of proprietary polymer materials27 and are commercially available (Eppendorf Corporate). We treated regular microcentrifuge tubes in house to make SLIPS tubes (Figure S3). After successive tube transfer of samples with 10µg total proteins, protein recovery in Tube 4 for SLIPS and LoBind tubes were 40.4% and 46.8% (Figure 2C), both of which were significantly higher than the regular tubes (28.2%). The experiment was repeated with 2μg total proteins samples, in which the percentages of proteins left in Tube 4 for SLIPS and LoBind tubes were 44.2% and 52.2%, respectively (Figure 2D).These were significantly higher when compared with 10.9% for regular tubes. Even in the first tube, SLIPS and LoBind tubes showed significant improvement than regular tubes, which suggested potential application of these modified tube surfaces for the afore-mentioned single-tube sample processing strategies (FASP, Stage Tip, SP3). Additionally, sample preparation using SLIPS and LoBind tubes were more reproducible when compared with regular tubes as shown by the variability of measurements. SLIPS treatment offered flexibility as it could be applied to all types of labware surfaces and connection tubing inner surfaces, while commercially available LoBind tubes were more convenient and time-saving. Assessment and Improvement of Peptide Loss to Sample Desalting and Drying Steps. The desalting step removes cell lysis byproducts and ensures quality of LC-MS analysis. However, it is inevitable to experience peptide loss due to the additional surface exposure, C18 resin binding, and wash steps. In our peptide BCA assays, 72.2% of 50µg, 64.0% of 10µg and 67.4% of 2µg total U2OS tryptic peptides were recovered after desalting (Figure S4) using wells containing 10mg SOLA C18 resin for 50µg peptides and 2mg resin for 10µg and 2µg peptides. In the AQUA assays, we further confirmed that recovery yields for selected peptides from individual proteins (Figure 3A) during C18 desalting remained relatively stable, when we started with 10µg, 2µg, and 0.2µg U2OS tryptic peptides. The selected peptides that represented the two lowestabundance proteins (NEK9 and SCYL2) did display reduced recovery with 0.2µg (~2,000 cells) samples (Figure 3A). For the speed-vacuum drying step, high peptide loss was observed with 2µg U2OS tryptic peptides (26.2% of peptide loss) but not with 10µg and higher starting material (Figure S5). In the AQUA assays, all eight selected peptides experienced more than 90% recovery when 10µg U2OS tryptic peptides were dried using speed-vacuum. However, sample recovery yields for all eight selected peptides dramatically decreased from 10g (ranging from 89-100%) to 2µg U2OS peptide



samples (ranging from 70-88%), and went further down with 200ng samples (ranging from 53-68%). In particular, selected peptides representing the two lowest abundant proteins, NEK9 and SCYL2, were not detected during the tests at the 200ng total peptide level (Figure 3B). These results clearly demonstrated severe sample loss during the sample drying step for samples starting from ~1,000-2,000 mammalian cells. To mitigate the above losses for samples with ~1,000-2,000 total cells, we decided to test in-line desalting with the C18 trap column. In the test, 200ng U2OS tryptic peptides (from ~2,000 U2OS cells) were injected onto a one-time use home-made trap column, whereas desalted peptides were then separated on the downstream analytical column. This setup alleviated labware surface exposure during regular desalting and speed vacuum steps. It also shortened the time of sample treatment. As shown in Figure 3C, in-line desalting successfully enhanced AQUA peptide recovery, especially for selected peptides that represented low abundance proteins NEK9, SCYL2, GSK3B, and NTKL. Conversely, selected peptides representing higherabundance proteins (SPTA2, CDC2, MYL6, and H4) showed little recovery improvement between the two desalting strategies. These results suggested that we could use in-line desalting to improve sample recovery yield for low-abundant peptides in samples from ~1,000 to 2,000 mammalian cells.

of U2OS cells. This time, we first processed ~10,000 U2OS cells, followed by 10% injection of the resulted peptides (i.e., ~1,000-cell equivalent) and 75-minute LC-MS/MS runs with each sample handling method. With LoBind tubes plus in-line peptide desalting, unique protein identification for 1,000-cell equivalent injection from 10,000 U2OS cells reached 1,277 and unique peptide identification of 5,453. This represented ~2.5and ~2.9-fold increase over the conventional workflow. Replacing the LoBind tubes with SLIPS-treated tubes, we identified 758 unique proteins and 2,936 unique peptides, both ~1.5-fold increase over the conventional sample handling workflow (Figure 4A and Figure S6A). When we directly started from ~1,000 U2OS cells using LoBind tubes and in-line desalting, we identified 829 unique proteins and 2,957 unique peptides (Figure 4B and Figure S6B), marking ~11- and ~21fold increase over the conventional workflow. With SLIPS treated tubes, from ~1,000 U2OS cells, we identified 294 proteins and 792 peptides, still ~3.8- and ~5.6-fold increase over the conventional workflow (Figure 4B and Figure S6B). The underperformance of SLIPS tubes versus LoBind tubes could be due to the incompatibility of SLIPS with the insolution workflow. Lubricant used in the SLIPS treatment procedure could evaporate during incubation at 37°C, which compromised the non-adhesion ability of the SLIPS surface. The evaporation issue can be mitigated by keeping the lubricant infused SLIP surfaces in closed environments, such as in microfluidic devices and fluidic connection tubing. These measures can help to achieve optimal recovery with samples of ~100 to ~1,000 mammalian cells.

Figure 4. Optimized analysis of 1,000 mammalian cells. (A-B) Unique proteins identifed with conventional, SLIPS tubes plus in-line desalting, and LoBind tubes plus in-line desalting workflows, respectively, from 1,000-cell equivalent injection of 10,000 U2OS cells (A) and from 1,000 U2OS cells (B). Error bars represent standard deviations of triplicate repeats.

CONCLUSION

Figure 3. In-line desalting improved peptide recovery. (A-B) Recovery yields for individual peptides representing the eight selected proteins during desalting (A) and speed-vacuum drying steps (B), with 10g, 2g, and 200ng U2OS tryptic peptides, assessed by AQUA assays. (C) In-line desalting of 200ng U2OS tryptic peptides led to improved recovery yields for peptides representing low-abundant proteins (NEK9, SCYL2, GSK3B, NTKL), assessed by AQUA method. Error bars represent standard deviations of triplicate repeats.

MS Analysis with Improved Sample Handling Workflow. After step-wise assessment and optimization of sample handling recovery yields, we went on to analyze small amount

In summary, we have provided quantitative information on step-wise sample handling loss during the conventional insolution proteomic sample preparation workflow. For samples of ~1,000 mammalian cells, we demonstrated that the major sources of sample loss included protein surface adhesion, peptide desalting, and speed-vacuum drying. Even single tube sample preparation strategies may not be sufficient for processing such low amount of samples. Instead, by adaptation of modified labware surfaces (LoBind and SLIPS), along with in-line desalting, we can achieve substantial increase in protein identification using the most basic sample preparation workflow, without any complex technology, equipment, and extensive training. The quantitative analysis of sample loss provides valuable information to researchers for future optimization and application of advanced nanoproteomic sample preparation workflows to push the boundary of detection sensitivity and proteome coverage with 1,000 or fewer mammalian cells.


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Analytical Chemistry

ASSOCIATED CONTENT Supporting Information Supporting Information (experimental procedures, supplementary table and figures) is available on the ACS Publications website.

AUTHOR INFORMATION Corresponding Authors * Email addresses: Yu Lu: [email protected]; Tohid F. Didar: [email protected]

ORCID Yu Lu: 0000-0003-4522-6823

Author Contributions R.W. and Y.L. designed research, coordinated the project and wrote the manuscript; R.W., S.X., Y. L. performed experiments; M. B. and T.F.D. helped to prepare labware SLIPS surfaces; All authors have given approval to the final version of the manuscript.

ACKNOWLEDGMENT Support for this work was provided by Canadian Natural Science and Engineering Research Council Discovery Grant (RGPIN2017-06159), Canada Foundation for Innovation JELF (35544), Ontario Ministry of Economic Development, Job Creation and Trade ORF-RI (35544), and the Marta and Owen Boris Foundation.

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Step-Wise Assessment and Optimization of Sample Handling

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