Published: May 8th, 2021
Here, we present an optimized on-filter digestion protocol with detailed information about the following: protein digestion, peptide purification and data independent acquisition analysis. This strategy is applied to the analysis of expressed prostatic secretions-urine samples and allows high proteome coverage and low missing value label-free profiling of the urinary proteome.
Filter-aided sample protocol (FASP) is widely used for proteomics sample preparation because it allows to concentrate diluted samples and it is compatible with a wide variety of detergents. Bottom-up proteomics workflows like FASP increasingly rely on LC-MS/MS methods performed in data-independent analysis (DIA) mode, a scanning method that allows deep proteome coverage and low incidence of missing values.
In this report, we will provide the details of a workflow that combines a FASP protocol, a double StageTip purification step and LC-MS/MS in DIA mode for urinary proteome mapping. As a model sample, we analyzed expressed prostatic secretions (EPS)-urine, a sample collected after a digital rectal exam (DRE), which is of interest in prostate cancer biomarker discovery studies.
The constant evolution of proteomic technologies promises to have a considerable impact in helping disease diagnosis and prediction of response to treatment by providing high resolution maps of key molecular effectors present in a wide variety of samples such as tissues and biofluids. From an analytical point of view, urine offers several advantages such as ease of collection and major stability of the proteome with respect to others biofluids1. Proteomic analysis of urine is of special interest in biomarker discovery studies on urological cancers, since it allows noninvasive sampling in proximity to the tissues of interest2. In particular, a sample that seems to be promising for studying prostate-related pathologies is the EPS-urine3,4 (i.e., a urine sample collected after a digital rectal exam (DRE)). This latter operation prior to sample collection enriches urine with prostate specific proteins. EPS-urine is a good candidate to investigate disorders related to the prostate gland5 including prostate cancer (PCa), since through DRE, proteins secreted by the tumor can be poured into the urine sample, increasing the chance of detecting cancer tissue-specific proteins.
A crucial role in allowing detection and quantification of potential protein biomarkers is played by mass spectrometry (MS). Over the last two decades, MS-based protocols for proteomic analysis have allowed an ever-increasing number of proteins to be detected in a single LC-MS/MS run thanks to continuous improvements in MS instrumentation and in data analysis software6.
MS-based proteomic sample preparation generally involves enzymatic digestion of the protein mixture, which can be achieved via a wide variety of protocols such as: in-solution digestion, MStern blotting7, suspension trapping (S-trap)8, solid-phase-enhanced sample preparation (SP3)9, in-StageTip digestion10 and filter aided sample preparation (FASP)11. All protocols can be used for urinary proteomics, even though results may vary with respect to the number of identified proteins and peptides and in terms of reproducibility12.
In this work, our attention was focused on the analysis of EPS-urine by the FASP protocol. The FASP protocol was originally designed to analyze proteins extracted from tissues and cell cultures, but its use was then expanded to the analysis of other sample types, such as urine13. With respect to straightforward in-solution digestion FASP is a more flexible proteomic approach14, since by achieving effective removal of detergents and other contaminants such as salts from the protein mixture before enzymatic digestion15, it allows the choice of optimal protein solubilization conditions. Moreover, an additional characteristic of FASP is that it provides a means for sample concentration. This is of particular interest for urinary proteomic analysis, because it allows to start from relatively large sample volumes (hundreds of microliters). In the light of the potential of the FASP protocol, several studies have focused the attention on workflow automation, with the aim of reducing experimental variability and processing an elevated number of samples in parallel16.
In our workflow, FASP is followed by LC-MS/MS acquisition in data-independent analysis (DIA), which provides high proteome coverage, good quantitative precision and low incidence of missing values. The DIA approach is a sensitive method where all ions are selected for MS/MS events, opposite to what happens in data-dependent analysis (DDA) where only ions with the highest intensity are fragmented. The mass spectrometer, operating in DIA mode, performs scan cycles with different isolation width covering the whole m/z precursor range. This approach allows to reproducibly detect a high number of peptides per unit time, providing a proteomics snapshot of the sample17. Moreover, data generated by DIA have another interesting characteristic: the possibility of a posteriori analysis18. DIA data are more complex than those obtained by DDA, because MS/MS spectra in DIA result from the co-isolation of several precursor ions within each m/z window19. Disentangling the composite MS/MS spectra into distinct and specific peptide signals is achieved by using two fundamental elements: a spectral library and a dedicated software for data analysis. The spectral library is generated by a data-dependent experiment, usually involving peptide fractionation to maximize proteome coverage, which provides a list of thousands of experimentally determined precursor ions and MS/MS spectra of peptides detectable in the sample under consideration. The data analysis software, instead, uses the information contained in the spectral library to interpret the DIA data by generating specific extracted ion chromatograms which allow peptide detection and quantification. While library-free DIA data analysis is now feasible, library-based DIA still provides better results in terms of proteome coverage20.
The sample preparation protocol here described (Figure 1) consists of the following steps: a centrifugation step (to remove cell debris), FASP digestion, StageTip purification21, quantification of proteins and DIA analysis. This protocol has been designed for the analysis of EPS-urine in the context of prostate cancer biomarker discovery, but it can be applied to proteomic analysis of any urine sample.
The study was approved by the Institutional Ethical Committee of the Magna Graecia University of Catanzaro, RP 41/2018. Written informed consent was obtained from all patients enrolled in the study.
1. Sample preparation
2. Sample thawing
3. Reagent preparation for FASP
4. Protein digestion by FASP
5. Reagent preparation for SCX purification
6. SCX purification
7. Protein quantification by external standard using DDA analysis (Figure 2)
8. Reagent preparation for C18 StageTip protocol
9. SCX/C18 StageTip protocol
NOTE: Purify EPS-urine digests by C18 StageTip protocol to remove salts.
10. DIA Analysis (Figure 3)
11. High- pH reversed phase C18 fractionation for library generation
NOTE: Pool EPS-urine representative samples in an amount of higher than 10 µg in order to build a data-dependent library for DIA analysis by the following procedure:
12. Data analysis
This protocol for urinary proteomic analysis includes the following steps: FASP digestion, estimation of protein amount via external standard calibration, double StageTip purification (SCX and C18), and LC-MS/MS analysis in DIA mode.
After protein digestion, preliminary injections are performed after StageTip SCX purification of the resulting peptides. LC-MS/MS raw files are processed to obtain the number of identified peptides, the number of identified proteins and the area of detected peptides. The total area obtained by summing up all identified peptides is used to estimate protein content via interpolation to an external standard: a HeLa protein digest injected at five different amounts (2, 5, 15, 50, 150 ng, respectively). The protein amount for the six samples analyzed in this study varied from sample to sample, showing an average value of 78 ng/µL.
After protein estimation, 2 µg of digested proteins from each sample are purified by sequential SCX and C18 StageTip before DIA analysis. The spectral library for searching DIA data is created after high-pH reversed-phase fractionation and DDA LC-MS/MS analysis of a representative sample (e.g., a sample pool). Using the parameters described above, we have identified and quantified, cumulatively, 2387 protein groups in the six EPS-urine samples under consideration (Supplementary Table 1 and Figure 4).
In order to evaluate from a qualitative point of view the relevance of the list of identified and quantified proteins, the obtained matrix was compared to a list of 624 proteins previously identified in direct- EPS22, a sample collected in a more invasive procedure, which has proven to be a source of interesting candidate prostate cancer biomarkers. In total, 508 out of 624 proteins were successfully detected by our FASP/DIA protocol on EPS-urine.
Figure 1: Proteomic workflow. Please click here to view a larger version of this figure.
Figure 2: Representation of our experimental design for protein quantification based on external standard (HeLa digest). Please click here to view a larger version of this figure.
Figure 3: Key steps of DIA analysis: (i) elaboration of the spectral library through high-pH reversed-phase fractionation and DDA analysis, (ii) sample analysis using the DIA approach, (iii) data analysis by Spectronaut. Please click here to view a larger version of this figure.
Figure 4: Ranked plot for the detected EPS-urinary proteins. A few selected hits are labelled. Please click here to view a larger version of this figure.
Supplementary Table 1: Representative table of quantified proteins in six EPS-urine samples in Spectronaut. Please click here to download this Table.
In this work, a strategy for analyzing EPS-urine samples is presented. The FASP protocol is an ideal choice for urinary proteomics because it allows sample concentration before enzymatic digestion. In fact, using this workflow, several hundreds of microliters of urine can be loaded on a single filter and processed. Moreover, on-filter digestion offers relative freedom in the choice of denaturation conditions. In our work, protein denaturation is achieved by diluting urine samples in a buffer containing Tris, SDS and DTT (final concentration: 50 mM Tris, 1% SDS, 50 mM DTT). Proteins are efficiently denatured immediately after thawing the sample, in order to avoid unwanted degradation by active proteases. The original FASP protocol has been improved by increasing the volume of washes from 100 µL to 200 µL. In this way, better removal of residues, especially detergents from the filter, is achieved.
After enzymatic digestion, protein estimation by external standard using a fast LC-MS/MS, data-dependent method is performed before the last steps of the protocol, which comprise double StageTip purification and LC-MS/MS analysis in DIA mode, on equal starting material for all samples (2 µg).
The versatility of FASP is associated with the DIA approach, a sensitive method providing a low number of missing values17. In our work, 2387 proteins were identified and quantified, thus enabling a detailed proteomic profile of EPS-urine to be drawn. The identification and quantification of 2387 proteins was possible through the generation of a rich spectral library, obtained via high-pH reversed fractionation of peptides, and by our DIA method, directed at a wide m/z precursor range. This workflow identified over 80% of proteins previously found in direct-EPS analysis, demonstrating that a considerable fraction of the EPS-urinary proteome is indeed derived from expressed prostatic secretions, thus is a rich source of prostate tissue-specific proteins26.
In conclusion, our experimental design couples the versatility of FASP with the sensitivity of DIA in order to obtain a rich map of the urinary proteome. This strategy is recommended for analyzing EPS-urine samples, but its use can be extended to urinary proteomics in general, or even to other sample types.
All authors declare no conflict of interest.
This work was supported by MIUR (Ministero Università Ricerca, PRIN 2017 to MG) and by POR Calabria FESR 2014-2020, action 1.2.2, "INNOPROST".
|1 M Tris HCL pH 8.0
|2-iodoacetamide for synthesis
|Acetonitrile for HPLC LC-MS grade
|ammonium hydroxide solution
|ammonium hydroxide volumetric standard, 5N solution in water
|Empore Cation 47mm Extraction Disks
|Empore Disk C18
|Formic acid optima
|Hela Protein Digest Standard
|Microcon-10kDa Centrifugal Filter Unit with Ultracel-10 membrane
|sodium dodecyl sulfate solution
|Thiethylammonium bicarbonate buffer
|Trypsin from porcine pancreas
|Water HPLC gradient grade
|Proteome Discoverer 1,4
|Thermo Fisher Scientific
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