Mass spectrometry-based proteomic analysis of proteins adsorbed by hexadecyl-immobilized cellulose bead column for the treatment of dialysis-related amyloidosis.

BACKGROUND: Dialysis-related amyloidosis (DRA) is a severe complication in end-stage kidney disease (ESKD) patients undergoing long-term dialysis treatment, characterized by the deposition of ß2-microglobulin-related amyloids (Aß2M amyloid). To inhibit DRA progression, hexadecyl-immobilized cellulose bead (HICB) columns are employed to adsorb circulating ß2-microglobulin (ß2M). However, it is possible that the HICB also adsorbs other molecules involved in amyloidogenesis. METHODS: We enrolled 14 ESKD patients using HICB columns for DRA treatment; proteins were extracted from HICBs following treatment and identified using liquid chromatography-linked mass spectrometry. We measured the removal rate of these proteins and examined the effect of those molecules on Aß2M amyloid fibril formation in vitro. RESULTS: We identified 200 proteins adsorbed by HICBs. Of these, 21 were also detected in the amyloid deposits in the carpal tunnels of patients with DRA. After passing through the HICB column and hemodialyzer, the serum levels of proteins such as ß2M, lysozyme, angiogenin, complement factor D and matrix Gla protein were reduced. These proteins acted in the Aß2M amyloid fibril formation. CONCLUSIONS: HICBs adsorbed diverse proteins in ESKD patients with DRA, including those detected in amyloid lesions. Direct hemoperfusion utilizing HICBs may play a role in acting Aß2M amyloidogenesis by reducing the amyloid-related proteins.

Urinary proteome profiles associated with cognitive decline in community elderly residents-A pilot study.

Non-invasive and simple methods enabling easy identification of individuals at high risk of cognitive decline are needed as preventive measures against dementia. This pilot study aimed to explore protein biomarkers that can predict cognitive decline using urine, which can be collected non-invasively. Study subjects were selected from participants in a cohort study of middle-aged and older community-dwelling adults who underwent cognitive testing using the Mini-Mental State Examination and provided spot urine samples at two time points with an interval of approximately 5 years. Seven participants whose cognitive function declined 4 or more points from baseline (Group D) and 7 sex- and age-matched participants whose cognitive function remained within the normal range during the same period (Group M) were selected. Urinary proteomics using mass spectrometry was performed and discriminant models were created using orthogonal partial least squares-discriminant analysis (OPLS-DA). OPLS-DA yielded two models that significantly discriminated between the two groups at baseline and follow-up. Both models had ORM1, ORM2, and SERPINA3 in common. A further OPLS-DA model using baseline ORM1, ORM2, and SERPINA3 data showed similar predictive performance for data at follow-up as it did for baseline data (sensitivity: 0.85, specificity: 0.85), with the receiver operating characteristic curve analysis yielding an area under the curve of 0.878. This prospective study demonstrated the potential for using urine to identify biomarkers of cognitive decline.

Establishing protein expression profiles involved in tooth development using a proteomic approach.

Various growth and transcription factors are involved in tooth development and developmental abnormalities; however, the protein dynamics do not always match the mRNA expression level. Using a proteomic approach, this study comprehensively analyzed protein expression in epithelial and mesenchymal tissues of the tooth germ during development. First molar tooth germs from embryonic day 14 and 16 Crlj:CD1 (ICR) mouse embryos were collected and separated into epithelial and mesenchymal tissues by laser microdissection. Mass spectrometry of the resulting proteins was carried out, and three types of highly expressed proteins [ATP synthase subunit beta (ATP5B), receptor of activated protein C kinase 1 (RACK1), and calreticulin (CALR)] were selected for immunohistochemical analysis. The expression profiles of these proteins were subsequently evaluated during all stages of amelogenesis using the continuously growing incisors of 3-week-old male ICR mice. Interestingly, these three proteins were specifically expressed depending on the stage of amelogenesis. RACK1 was highly expressed in dental epithelial and mesenchymal tissues during the proliferation and differentiation stages of odontogenesis, except for the pigmentation stage, whereas ATP5B and CALR immunoreactivity was weak in the enamel organ during the early stages, but became intense during the maturation and pigmentation stages, although the timing of the increased protein expression was different between the two. Overall, RACK1 plays an important role in maintaining the cell proliferation and differentiation in the apical end of incisors. In contrast, ATP5B and CALR are involved in the transport of minerals and the removal of organic materials as well as matrix deposition for CALR.

Urinary Apolipoprotein C3 Is a Potential Biomarker for Alzheimer's Disease.

INTRODUCTION: Biomarkers of Alzheimer's disease (AD) that can easily be measured in routine health checkups are desirable. Urine is a source of biomarkers that can be collected easily and noninvasively. We previously reported on the comprehensive profile of the urinary proteome of AD patients and identified proteins estimated to be significantly increased or decreased in AD patients by a label-free quantification method. The present study aimed to validate urinary levels of proteins that significantly differed between AD and control samples from our proteomics study (i.e., apolipoprotein C3 [ApoC3], insulin-like growth factor-binding protein 3 [Igfbp3], and apolipoprotein D [ApoD]). METHODS: Enzyme-linked immunosorbent assays (ELISAs) were performed using urine samples from the same patient and control groups analyzed in the previous proteomics study (18 AD and 18 controls, set 1) and urine samples from an independent group of AD patients and controls (13 AD, 5 mild cognitive impairment [MCI], and 32 controls) from the National Center for Geriatrics and Gerontology Biobank (set 2). RESULTS: In set 1, the crude urinary levels of ApoD, Igfbp3, and creatinine-adjusted ApoD were significantly higher in the AD group relative to the control group (p = 0.003, p = 0.002, and p = 0.019, respectively), consistent with our previous proteomics results. In set 2, however, the crude urinary levels of Igfbp3 were significantly lower in the AD+MCI group than in the control group (p = 0.028), and the levels of ApoD and ApoC3 did not differ significantly compared to the control group. Combined analysis of all samples revealed creatinine-adjusted ApoC3 levels to be significantly higher in the AD+MCI group (p = 0.015) and the AD-only group (p = 0.011) relative to the control group. CONCLUSION: ApoC3 may be a potential biomarker for AD, as validated by ELISA. Further analysis of ApoC3 as a urinary biomarker for AD is warranted.

Utilization of the Proteome Data Deposited in SRMAtlas for Validating the Existence of the Human Missing Proteins in GPM.

The Human Proteome Project (HPP) has made great efforts to clarify the existing evidence of human proteins since 2012. However, according to the recent release of neXtProt (2019-1), approximately 10% of all human genes still have inadequate or no experimental evidence of their translation at the protein level. They were categorized as missing proteins (PE2-PE4). To further the goal of HPP, we developed a two-step bioinformatic strategy addressing the utilization of the SRMAtlas synthetic peptides corresponding to the missing proteins as an exclusive reference in order to explore their natural counterparts within GPM. In the first step, we searched the GPM for the non-nested SRMAtlas peptides corresponding to the missing proteins, taking under consideration only those detected via ≥2 non-nested unitypic/proteotypic peptides "Stranded peptides" with length ≥9 amino acids in the same proteomic study. As a result, 51 missing proteins were newly detected in 35 different proteomic studies. In the second step, we validated these newly detected missing proteins based on matching the spectra of their synthetic and natural peptides in SRMAtlas and GPM, respectively. The results showed that 23 of the missing proteins with ≥2 non-nested peptides were validated by careful spectral matching.

Proteomics Analysis of Urine to Examine Physical Effects of Warm Nano Mist Sauna Bathing.

Conventional sauna bathing may have some health benefits as it facilitates relaxing, detoxing and promoting metabolism. However, conventional sauna bathing at a high temperature may be harmful for the body by increasing the risk of heart failure. The nano-mist sauna has been developed to provide nano-size water particles at a lower temperature. Hence, nano-mist sauna bathing is expected to be useful for health without the risks that arise at high temperatures. In this study, we performed a comprehensive proteomics analysis of urine samples obtained from healthy volunteers before and after they had taken a sauna bath with nano-mist (n = 10) or with conventional mist (n = 10) daily for two weeks (4 groups). The average numbers of urine proteins identified by liquid chromatography-linked mass chromatography in each group varied from 678 to 753. Interestingly, the protein number was increased after sauna bathing both with nano-mist or with conventional mist. Quantitative analysis indicated that considerable numbers of proteins were obviously up-regulated, with more than two-folds in urine samples after the nano-mist sauna bathing. The KEGG pathway analysis showed significant stimulation of the lysosome pathway (p = 5.89E-6) after the nano-mist bathing, which may indicate the nano-mist sauna bathing promotes metabolism related to the lysosome pathway more efficiently than conventional mist sauna bathing and may provide more health benefits.

Molecular Network Analysis of the Urinary Proteome of Alzheimer's Disease Patients.

BACKGROUND/AIMS: The identification of predictive biomarkers for Alzheimer's disease (AD) from urine would aid in screening for the disease, but information about biological and pathophysiological changes in the urine of AD patients is limited. This study aimed to explore the comprehensive profile and molecular network relations of urinary proteins in AD patients. METHODS: Urine samples collected from 18 AD patients and 18 age- and sex-matched cognitively normal controls were analyzed by mass spectrometry and semiquantified with the normalized spectral index method. Bioinformatics analyses were performed on proteins which significantly increased by more than 2-fold or decreased by less than 0.5-fold compared to the control (p < 0.05) using DAVID bioinformatics resources and KeyMolnet software. RESULTS: The levels of 109 proteins significantly differed between AD patients and controls. Among these, annotation clusters related to lysosomes, complement activation, and gluconeogenesis were significantly enriched. The molecular relation networks derived from these proteins were mainly associated with pathways of lipoprotein metabolism, heat shock protein 90 signaling, matrix metalloproteinase signaling, and redox regulation by thioredoxin. CONCLUSION: Our findings suggest that changes in the urinary proteome of AD patients reflect systemic changes related to AD pathophysiology.

Proteome Profiling of Diabetic Mellitus Patient Urine for Discovery of Biomarkers by Comprehensive MS-Based Proteomics.

Diabetic mellitus (DM) is a disease that affects glucose homeostasis and causes complications, such as diabetic nephropathy (DN). For early diagnosis of DN, microalbuminuria is currently one of the most frequently used biomarkers. However, more early diagnostic biomarkers are desired in addition to microalbuminuria. In this study, we performed comprehensive proteomics analysis of urine proteomes of diabetic mellitus patients without microalbuminuria and healthy volunteers to compare the protein profiles by mass spectrometry. With high confidence criteria, 942 proteins in healthy volunteer urine and 645 proteins in the DM patient urine were identified with label-free semi-quantitation, respectively. Gene ontology and pathway analysis were performed with the proteins, which were up- or down-regulated in the DM patient urine to elucidate significant changes in pathways. The discovery of a useful biomarker for early DN discovery is expected.

Proteomic Analysis of Rice Golgi Membranes Isolated by Floating Through Discontinuous Sucrose Density Gradient.

The Golgi apparatus is an endomembrane system organelle and has roles in glycosylation, sorting, and secretion of proteins in the secretory pathway. It has a central function in living organism and is also essential for plant growth. Proteomic approaches to identify the Golgi membrane proteins have been performed in cell suspension cultures and many Golgi membrane-associated proteins were found, whereas it has well established in rice seedling yet. In this chapter, our recent improving published methods for isolated rice Golgi membranes by floating through a discontinuous sucrose density gradient are provided in detail with proteomic analyses.

Identification and Validation of Human Missing Proteins and Peptides in Public Proteome Databases: Data Mining Strategy.

In an attempt to complete human proteome project (HPP), Chromosome-Centric Human Proteome Project (C-HPP) launched the journey of missing protein (MP) investigation in 2012. However, 2579 and 572 protein entries in the neXtProt (2017-1) are still considered as missing and uncertain proteins, respectively. Thus, in this study, we proposed a pipeline to analyze, identify, and validate human missing and uncertain proteins in open-access transcriptomics and proteomics databases. Analysis of RNA expression pattern for missing proteins in Human protein Atlas showed that 28% of them, such as Olfactory receptor 1I1 ( O60431 ), had no RNA expression, suggesting the necessity to consider uncommon tissues for transcriptomic and proteomic studies. Interestingly, 21% had elevated expression level in a particular tissue (tissue-enriched proteins), indicating the importance of targeting such proteins in their elevated tissues. Additionally, the analysis of RNA expression level for missing proteins showed that 95% had no or low expression level (0-10 transcripts per million), indicating that low abundance is one of the major obstacles facing the detection of missing proteins. Moreover, missing proteins are predicted to generate fewer predicted unique tryptic peptides than the identified proteins. Searching for these predicted unique tryptic peptides that correspond to missing and uncertain proteins in the experimental peptide list of open-access MS-based databases (PA, GPM) resulted in the detection of 402 missing and 19 uncertain proteins with at least two unique peptides (≥9 aa) at <(5 × 10-4)% FDR. Finally, matching the native spectra for the experimentally detected peptides with their SRMAtlas synthetic counterparts at three transition sources (QQQ, QTOF, QTRAP) gave us an opportunity to validate 41 missing proteins by ≥2 proteotypic peptides.

Glycobiomarker, Fucosylated Short-Form Secretogranin III Levels Are Increased in Serum of Patients with Small Cell Lung Carcinoma.

Secretogranin III (SgIII) is a member of the chromogranin/secretogranin family of neuroendocrine secretory proteins. Granins are expressed in endocrine and neuroendocrine cells and subsequently processed into bioactive hormones. Although granin-derived peptide expression is correlated with neuroendocrine carcinomas, little is known about SgIII. We previously identified SgIII by a comparative glycoproteomics approach for elucidation of glycobiomarker candidates in lung carcinoma. Here, we examined the expression, secretion, and glycosylation of SgIII to identify novel biomarkers of small cell lung carcinoma (SCLC). In comparative immunohistochemical analysis and secretion profiling, SgIII was observed in all types of lung cancer. However, low-molecular-weight SgIII (short-form SgIII) was specifically found in SCLC culture medium. Glycoproteomics analysis showed that a fucosylated glycan was attached to the first of three potential N-glycosylation sites and an unfucosylated glycan was detected on the second site; however, the third site was not glycosylated. Next, we performed lectin capture with a fucose-binding lectin and detected short-form SgIII specifically in the sera of patients with SCLC. The results suggested an association between the fucosylated glycoform of short-form SgIII and SCLC. Thus, fucosylated short-form SgIII may be a valuable biomarker for SCLC and could be used to monitor development of the disease. All MS data are available via ProteomeXchange and jPOST with identifiers PXD007626 and JPST000313, respectively.

Why are they missing? : Bioinformatics characterization of missing human proteins.

NeXtProt is a web-based protein knowledge platform that supports research on human proteins. NeXtProt (release 2015-04-28) lists 20,060 proteins, among them, 3373 canonical proteins (16.8%) lack credible experimental evidence at protein level (PE2:PE5). Therefore, they are considered as "missing proteins". A comprehensive bioinformatic workflow has been proposed to analyze these "missing" proteins. The aims of current study were to analyze physicochemical properties, existence and distribution of the tryptic cleavage sites, and to pinpoint the signature peptides of the missing proteins. Our findings showed that 23.7% of missing proteins were hydrophobic proteins possessing transmembrane domains (TMD). Also, forty missing entries generate tryptic peptides were either out of mass detection range (>30aa) or mapped to different proteins (<9aa). Additionally, 21% of missing entries didn't generate any unique tryptic peptides. In silico endopeptidase combination strategy increased the possibility of missing proteins identification. Coherently, using both mature protein database and signal peptidome database could be a promising option to identify some missing proteins by targeting their unique N-terminal tryptic peptide from mature protein database and or C-terminus tryptic peptide from signal peptidome database. In conclusion, Identification of missing protein requires additional consideration during sample preparation, extraction, digestion and data analysis to increase its incidence of identification.

Comprehensive data analysis of human ureter proteome.

Comprehensive human ureter proteome dataset was generated from OFFGel fractionated ureter samples. Our result showed that among 2217 non-redundant ureter proteins, 751 protein candidates (33.8%) were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48) that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease-associated biomarkers such as ureter carcinoma. In addition, Cytoscape GO annotation was examined on the final ureter dataset to better understand proteins molecular function, biological processes, and cellular component. The ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery.

A proteomic glimpse into human ureter proteome.

Urine has evolved as one of the most important biofluids in clinical proteomics due to its noninvasive sampling and its stability. Yet, it is used in clinical diagnostics of several disorders by detecting changes in its components including urinary protein/polypeptide profile. Despite the fact that majority of proteins detected in urine are primarily originated from the urogenital (UG) tract, determining its precise source within the UG tract remains elusive. In this article, we performed a comprehensive analysis of ureter proteome to assemble the first unbiased ureter dataset. Next, we compared these data to urine, urinary exosome, and kidney mass spectrometric datasets. Our result concluded that among 2217 nonredundant ureter proteins, 751 protein candidates (33.8%) were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48) that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease-associated biomarkers such as ureter carcinoma. In addition, the ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery. All MS data have been deposited in the ProteomeXchange with identifier PXD002620 (http://proteomecentral.proteomexchange.org/dataset/PXD002620).

Complementary protein and peptide OFFGEL fractionation for high-throughput proteomic analysis.

OFFGEL fractionation of mouse kidney protein lysate and its tryptic peptide digest has been examined in this study for better understanding the differences between protein and peptide fractionation methods and attaining maximum recruitment of this modern methodology for in-depth proteomic analysis. With the same initial protein/peptide load for both fractionation methods, protein OFFGEL fractionation showed a preponderance in terms of protein identification, fractionation efficiency, and focusing resolution, while peptide OFFGEL was better in recovery, number of peptide matches, and protein coverage. This result suggests that the protein fractionation method is more suitable for shotgun analysis while peptide fractionation suits well quantitative peptide analysis [isobaric tags for relative and absolute quantitation (iTRAQ) or tandem mass tags (TMT)]. Taken together, utilization of the advantages of both fractionation approaches could be attained by coupling both methods to be applied on complex biological tissue. A typical result is shown in this article by identification of 8262 confident proteins of whole mouse kidney under stringent condition. We therefore consider OFFGEL fractionation as an effective and efficient addition to both label-free and quantitative label proteomics workflow.

Glycoproteomics approach for identifying Glycobiomarker candidate molecules for tissue type classification of non-small cell lung carcinoma.

Histopathological classification of lung cancer has important implications in the application of clinical practice guidelines and the prediction of patient prognosis. Thus, we focused on discovering glycobiomarker candidates to classify the types of lung cancer tissue. First, we performed lectin microarray analysis of lung cancer tissue specimens and cell lines and identified Aleuria aurantia lectin (AAL), Hippeastrum hybrid lectin (HHL), and Concanavalia ensiformis agglutinin (ConA) as lectin probes specific to non-small cell lung carcinoma (NSCLC). LC-MS-based analysis was performed for the comprehensive identification of glycoproteins and N-linked glycosylation sites using lectin affinity capture of NSCLC-specific glycoforms of glycoproteins. This analysis identified 1092 AAL-bound glycoproteins (316 gene symbols) and 948 HHL/ConA-bound glycoproteins (279 gene symbols). The lectin microarray-assisted verification using 15 lung cancer cell lines revealed the NSCLC-specific expression of fibronectin. The glycosylation profiling of fibronectin indicated that the peanut agglutinin (PNA) signal appeared to differentiate two NSCLC types, adenocarcinoma and large cell carcinoma, whereas the protein expression level was similar between these types. Our glycoproteomics approach together with the concurrent use of an antibody and lectin is applicable to the quantitative and qualitative monitoring of variations in glycosylation of fibronectin specific to certain types of lung cancer tissue.

New SINE families from rice, OsSN, with poly(A) at the 3' ends.

A database search of the sequences flanking a member of rice retrotransposon RIRE7 revealed that a 298-bp sequence in the region downstream of the member is a repetitive sequence interspersed in the genome of Oryza sativa cv. Nipponbare. Most of the repetitive sequences were flanked by a direct repeat of a target-site sequence, about 14 bp in length. The consensus sequence, 293 bp in length, had no regions encoding any proteins but had sequence motifs of an internal promoter of RNA polymerase III. These indicate that the sequence is a retroposon SINE, designated OsSN1 (Oryza sativa SINE1). OsSN1 is a new rice SINE, because it has no homology with any of the three p-SINE families previously identified from rice, and because it has a stretch of A at the 3' end, unlike p-SINE and any other Gramineae SINEs which have a stretch of T at the 3' end. The Nipponbare genome was found to have many members related to OsSN1, forming two additional new SINE families (designated OsSN2 and OsSN3). OsSN2 and OsSN3 are highly homologous to the 3' and 5' regions of OsSN1, respectively. This suggests that OsSN1 has a mosaic structure, which is generated by sequence exchange (or shuffling) between ancestral OsSN2 and OsSN3. Despite the absence of homology in the 3' regions between OsSN1 (or OsSN2) and OsSN3, a sequence, 5'-TTCTC-3', is commonly present in the region preceding the A stretch at the 3' end. This sequence together with the A stretch and a stem-loop structure found in the region near the A stretch are assumed to be important for retroposition. OsSN members were present in strains of Oryza species, as were p-SINE members. Some of the members showed insertion polymorphism at the respective loci among the rice strains. p-SINE had such polymorphic members, which are useful for classification and phylogenetic analysis of various strains of Oryza species. The polymorphic members of OsSN were more frequently found than those of p-SINE, and therefore, such members are likely to be useful for extensive taxonomic and phylogenetic studies on various rice strains.