Sample preparation for detection of low abundance proteins in human plasma using ultra-high performance liquid chromatography coupled with highly accurate mass spectrometry

Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%-19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Preparation of the Low Molecular Weight Serum Proteome for Mass Spectrometry Analysis

The ability to cure or manage many diseases is highly dependent on the ability to correctly diagnose them at the earliest possible stage. Diagnosis relies heavily on biomarkers whether these be visual symptoms or molecules found within samples acquired from the patient. For conditions that lack useful biomarkers, researchers are often faced with the task of sifting through very complex biological samples (i.e., serum, plasma, urine, tissue, cells, etc.) with the hope of discovering a small number of molecules that are exquisitely diagnostic for the condition of interest. One discovery strategy that has been frequently used is to fractionate the biological samples being studied into simpler aliquots that can be more easily characterized using existing technologies. One such fractionation method is to isolate a specific portion based on a specific property (i.e., size, phosphorylation state, charge, etc.) of the proteins within the sample. This method provides a simplified sample that can be characterized at a higher coverage level than the complex sample from which it was derived. This chapter details one of these methods, the extraction and analysis of the low molecular weight proteome of human serum.

MS-Based Proteomic Analysis of Serum and Plasma: Problem of High Abundant Components and Lights and Shadows of Albumin Removal

Blood serum or plasma proteome is a gold mine of disease biomarkers. However, complexity and a huge dynamic range of their components, combined with multiple mechanisms of degradation and posttranslational modifications, further complicated by the presence of lipids, salts, and other metabolites, represent a real challenge for analytical sensitivity, resolution, and reproducibility. This problem exists particularly in the case of potential disease-specific markers, most typically represented by low-abundant proteins (LAPs), whose detection is usually impaired by the dominance of albumins, immunoglobulins, and other high-abundant serum/plasma proteins (HAPs). Hence, analysis of biomarker candidates in serum/plasma samples frequently requires separation of their components, usually including depletion of albumin in a fraction of interest. Such "preprocessing" of serum/plasma specimens is critical in proteomic analysis based on mass spectrometry. This approach is very potent; nevertheless a wide range of protein concentrations in serum/plasma represents a particular challenge, since high-abundant proteins (mostly albumin) dominate in a sample subjected to mass spectrometry and suppress peptide ions originating from low-abundant proteins, thus limiting probability and reliability of their detection. An emerging approach in serum-/plasma-based biomarker-oriented studies is the proteome component of exosomes - nanovesicles secreted by cells and involved in multiple aspects of intercellular communication. However, the presence of albumin, frequent contaminant of exosomes isolated from human serum/plasma, represents a real challenge also in this type of study. A similar problem is encountered in proteomic studies based on exosomes obtained in in vitro experiments where culture media are normally supplemented with fetal bovine serum containing growth factors and hormones. In this case exosomes are frequently contaminated with bovine serum albumin and other bovine serum proteins which should be removed before proteomic analysis of exosome cargo.