Data management and functional annotation of the Korean reference plasma proteome

Construction and characterization of the Korean whole saliva proteome to determine ethnic differences in human saliva proteome

As the first step to discover protein disease biomarkers from saliva, global analyses of the saliva proteome have been carried out since the early 2000s, and more than 3,000 proteins have been identified in human saliva. Recently, ethnic differences in the human plasma proteome have been reported, but such corresponding studies on human saliva in this aspect have not been previously reported. Thus, here, in order to determine ethnic differences in the human saliva proteome, a Korean whole saliva (WS) proteome catalogue indexing 480 proteins was built and characterized through nLC-Q-IMS-TOF analyses of WS samples collected from eleven healthy South Korean male adult volunteers for the first time. Identification of 226 distinct Korean WS proteins, not observed in the integrated human saliva protein dataset, and significant gene ontology distribution differences in the Korean WS proteome compared to the integrated human saliva proteome strongly support ethnic differences in the human saliva proteome. Additionally, the potential value of ethnicity-specific human saliva proteins as biomarkers for diseases highly prevalent in that ethnic group was confirmed by finding 35 distinct Korean WS proteins likely to be associated with the top 10 deadliest diseases in South Korea. Finally, the present Korean WS protein list can serve as the first level reference for future proteomic studies including disease biomarker studies on Korean saliva.

Rationalising the role of Keratin 9 as a biomarker for Alzheimer's disease

Keratin 9 was recently identified as an important component of a biomarker panel which demonstrated a high diagnostic accuracy (87%) for Alzheimer's disease (AD). Understanding how a protein which is predominantly expressed in palmoplantar epidermis is implicated in AD may shed new light on the mechanisms underlying the disease. Here we use immunoassays to examine blood plasma expression patterns of Keratin 9 and its relationship to other AD-associated proteins. We correlate this with the use of an in silico analysis tool VisANT to elucidate possible pathways through which the involvement of Keratin 9 may take place. We identify possible links with Dickkopf-1, a negative regulator of the wnt pathway, and propose that the abnormal expression of Keratin 9 in AD blood and cerebrospinal fluid may be a result of blood brain barrier dysregulation and disruption of the ubiquitin proteasome system. Our findings suggest that dysregulated Keratin 9 expression is a consequence of AD pathology but, as it interacts with a broad range of proteins, it may have other, as yet uncharacterized, downstream effects which could contribute to AD onset and progression.

Quantitative Profiling of Post-translational Modifications by Immunoaffinity Enrichment and LC-MS/MS in Cancer Serum without Immunodepletion

A robust method was developed and optimized for enrichment and quantitative analysis of posttranslational modifications (PTMs) in serum/plasma samples by combining immunoaffinity purification and LC-MS/MS without depletion of abundant proteins. The method was used to survey serum samples of patients with acute myeloid leukemia (AML), breast cancer (BC), and nonsmall cell lung cancer (NSCLC). Peptides were identified from serum samples containing phosphorylation, acetylation, lysine methylation, and arginine methylation. Of the PTMs identified, lysine acetylation (AcK) and arginine mono-methylation (Rme) were more prevalent than other PTMs. Label-free quantitative analysis of AcK and Rme peptides was performed for sera from AML, BC, and NSCLC patients. Several AcK and Rme sites showed distinct abundance distribution patterns across the three cancer types. The identification and quantification of posttranslationally modified peptides in serum samples reported here can be used for patient profiling and biomarker discovery research.

Proteomic analysis of the aqueous humor in age-related macular degeneration (AMD) patients

Age-related macular degeneration (AMD) can lead to irreversible central vision loss in the elderly. Although large number of growth factor pathways, including the vascular endothelial growth factor (VEGF), has been implicated in the pathogenesis of AMD, no study has directly assessed the whole proteomic composition in the aqueous humor (AH) among AMD patients. The AH contains proteins secreted from the anterior segment tissue, and these proteins may play an important role in the pathogenesis of AMD. Thus, comparisons between the AH proteomic profiles of AMD patients and non-AMD controls may lead to the verification of novel pathogenic proteins useful as potential clinical biomarkers. In this study, we used discovery-based proteomics and Multiple Reaction Monitoring Mass Spectrometry (MRM-MS) to analyze AH from AMD patients and AH from controls who underwent cataract surgery. A total of 154 proteins with at least two unique peptides were identified in the AH. Of these 154 proteins identified by discovery-based proteomics, 10 AH proteins were novel identifications. The protein composition in the AH was different between AMD patients and non-AMD controls. Subsequently, a systematic MRM-MS assay was performed in seven highly abundant differentially expressed proteins from these groups. Differential expression of three proteins was observed in the AH of AMD patients compared with that of cataract controls (p<0.0312). Elucidation of the aqueous proteome will establish a foundation for protein function analysis and identify differentially expressed markers associated with AMD. This study demonstrates that integrated proteomic technologies can yield novel biomarkers to detect exudative AMD.

Differential gel-based proteomic approach for cancer biomarker discovery using human plasma

Two-dimensional fluorescence difference gel electrophoresis (2D DIGE) has become a general platform for analysis of various clinical samples such as biofluids and tissues. In comparison to conventional 2-D polyacrylamide gel electrophoresis (2D PAGE), 2D DIGE offers several advantages, such as accuracy and reproducibility between experiments, which facilitate spot-to-spot comparisons. Although whole plasma can be easily obtained, the complexity of plasma samples makes it challenging to analyze samples with good reproducibility. Here, we describe a method for decreasing protein complexity in plasma samples within a narrow pH range by depleting high-abundance plasma proteins. In combination with analysis of differentially expressed spots, trypsin digestion, identification of protein by mass spectrometry, and standard 2D PAGE and DIGE, this method has been optimized for comparison of plasma samples from healthy donors and patients diagnosed with hepatocellular carcinoma.

Combinatorial peptide ligand library treatment followed by a dual-enzyme, dual-activation approach on a nanoflow liquid chromatography/orbitrap/electron transfer dissociation system for comprehensive analysis of swine plasma proteome

The plasma proteome holds enormous clinical potential, yet an in-depth analysis of the plasma proteome remains a daunting challenge due to its high complexity and the extremely wide dynamic range in protein concentrations. Furthermore, existing antibody-based approaches for depleting high-abundance proteins are not adaptable to the analysis of the animal plasma proteome, which is often essential for experimental pathology/pharmacology. Here we describe a highly comprehensive method for the investigation of the animal plasma proteome which employs an optimized combinatorial peptide ligand library (CPLL) treatment to reduce the protein concentration dynamic range and a dual-enzyme, dual-activation strategy to achieve high proteomic coverage. The CPLL treatment enriched the lower abundance proteins by >100-fold when the samples were loaded in moderately denaturing conditions with multiple loading-washing cycles. The native and the CPLL-treated plasma were digested in parallel by two enzymes (trypsin and GluC) carrying orthogonal specificities. By performing this differential proteolysis, the proteome coverage is improved where peptides produced by only one enzyme are poorly detectable. Digests were fractionated with high-resolution strong cation exchange chromatography and then resolved on a long, heated nano liquid chromatography column. MS analysis was performed on a linear triple quadrupole/orbitrap with two complementary activation methods (collisionally induced dissociation (CID) and electron transfer dissociation). We applied this optimized strategy to investigate the plasma proteome from swine, a prominent animal model for cardiovascular diseases (CVDs). This large-scale analysis results in identification of a total of 3421 unique proteins, spanning a concentration range of 9-10 orders of magnitude. The proteins were identified under a set of commonly accepted criteria, including a precursor mass error of <15 ppm, Xcorr cutoffs, and ≥2 unique peptides at a peptide probability of ≥95% and a protein probability of ≥99%, and the peptide false-positive rate of the data set was 1.8% as estimated by searching the reversed database. CPLL treatment resulted in 55% more identified proteins over those from native plasma; moreover, compared with using only trypsin and CID, the dual-enzyme/activation approach enabled the identification of 2.6-fold more proteins and substantially higher sequence coverage for most individual proteins. Further analysis revealed 657 proteins as significantly associated with CVDs (p < 0.05), which constitute five CVD-related pathways. This study represents the first in-depth investigation of a nonhuman plasma proteome, and the strategy developed here is adaptable to the comprehensive analysis of other highly complex proteomes.