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Introduction Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate invasive collection and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades, proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids. Areas covered We review proteomic technologies for the identification of biomarkers. These are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that has until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from the last 5 years in the Scopus database) using MS-based proteomics. Expert opinion While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached certain maturity. They are now better suited to discover innovative and robust biofluid biomarkers.

Children develop rapidly during the first years of life, and understanding the sources and associated levels of variation in the serum proteome is important when using serum proteins as markers for childhood diseases. The aim of this study was to establish a reference model for the evolution of a healthy serum proteome during early childhood. Label-free quantitative proteomics analyses were performed for 103 longitudinal serum samples collected from 15 children at birth and between the ages of 3–36 months. A flexible Gaussian process-based probabilistic modelling framework was developed to evaluate the effects of different variables, including age, living environment and individual variation, on the longitudinal expression profiles of 266 reliably identified and quantified serum proteins. Age was the most dominant factor influencing approximately half of the studied proteins, and the most prominent age-associated changes were observed already during the first year of life. High interindividual variability was also observed for multiple proteins. These data provide important details on the maturing serum proteome during early life, and evaluate how patterns detected in cord blood are conserved in the first years of life. Additionally, our novel modelling approach provides a statistical framework to detect associations between covariates and non-linear time series data.

Genetic variation has multiple effects on the proteome. It may influence the expression level of proteins, modify their sequences through single nucleotide polymorphisms, the occurrence of allelic variants, or alternative splicing (ASP) events. This perspective paper summarizes the major effects of genetic variability on protein expression and isoforms and provides an overview of proteomics techniques and methods that allow studying the effects of genetic variability at different levels of the proteome. The paper provides an overview of recent quantitative trait loci studies performed to explore the effect of genetic variation on protein expression (pQTL). Finally it gives a perspective view on advances in proteomics technology and the role of the Chromosome-Centric Human Proteome Project (C-HPP) by creating large-scale resources that may facilitate performing more comprehensive pQTL experiments in the future.

Proteome profiling of crude serum is a challenging task due to the wide dynamic range of protein concentrations and the presence of high-abundance proteins, which cover >90% of the total protein mass in serum. Peptide fractionation on strong cation exchange, weak anion exchange in the electrostatic repulsion hydrophilic interaction chromatography (ERLIC) mode, RP C-18 at pH 2.5 (low pH), fused-core fluorinated at pH 2.5, and RP C-18 at pH 9.7 (high pH) stationary phases resulted in two to three times more identified proteins and three to four times more identified peptides in comparison with 1D nanoChip-LC-MS/MS quadrupole TOF analysis (45 proteins, 185 peptides). The largest number of peptides and proteins was identified after prefractionation in the ERLIC mode due to the more uniform distribution of peptides among the collected fractions and on the RP column at high pH due to the high efficiency of RP separations and the complementary selectivity of both techniques to low-pH RP chromatography. A 3D separation scheme combining ERLIC, high-pH RP, and low-pH nanoChip-LC-MS/MS for crude serum proteome profiling resulted in the identification of 208 proteins and 1088 peptides with the lowest reported concentration of 11 ng/mL for heat shock protein 74.

Supernatants from cell cultures (also called conditioned media, CMs) are commonly analyzed to study the pool of secreted proteins (secretome). To reduce the exogenous protein background, serum-free media are often used to obtain CMs. Serum deprivation, however, can severely affect cell viability and phenotype, including protein secretion. We present a strategy to analyze the proteins secreted by cells in fetal bovine serum-containing CMs, which combines the advantage of metabolic labeling and protein concentration linearization techniques. Incubation of CMs with a hexapeptide ligand library was used to reduce the dynamic range of the samples and led to the identification of 3 times more proteins than in untreated CM samples. Labeling with a deuterated amino acid was used to distinguish between cellular proteins and homologous bovine proteins contained in the medium. Application of the strategy to two breast cancer cell lines led to the identification of proteins secreted in different amounts and which could correlate with their varying degree of aggressiveness. Selected reaction monitoring (SRM)-based quantitation of three proteins of interest in the crude samples yielded data in good agreement with the results from concentration-equalized samples.

Adenocarcinoma (AdC) is the most common lung cancer subtype and is often associated with pleural effusion (PE). Its poor prognosis is attributable to diagnostic delay and lack of effective treatments and there is a pressing need in discovering new biomarkers for early diagnosis or targeted therapies. To date, little is known about lung AdC proteome. We investigated protein expression of lung AdC in PE using the isobaric Tags for Relative and Absolute Quantification (iTRAQ) approach to identify possible novel diagnostic/prognostic biomarkers. This provided the identification of 109 of lung AdC-related proteins. We further analyzed lumican, one of the overexpressed proteins, in 88 resected lung AdCs and in 23 malignant PE cell-blocks (13 lung AdCs and 10 non-lung cancers) using immunohistochemistry. In AdC surgical samples, lumican expression was low in cancer cells, whereas it was strong and diffuse in the stroma surrounding the tumor. However, lumican expression was not associated with tumor grade, stage, and vascular/pleural invasion. None of the lung cancer cell-blocks showed lumican immunoreaction, whereas those of all the other tumors were strongly positive. Finally, immunoblotting analysis showed lumican expression in both cell lysate and conditioned medium of a fibroblast culture but not in those of A549 lung cancer cell line. PE is a valid source of information for proteomic analysis without many of the restrictions of plasma. The high lumican levels characterizing AdC PEs are probably due to its release by the fibroblasts surrounding the tumor. Despite the role of lumican in lung AdC is still elusive, it could be of diagnostic value.

Proteomics has the potential to elucidate complex patterns of toxic action attributed to its unique holistic a posteriori approach. In the case of toxic compounds for which the mechanism of action is not completely understood, a proteomic approach may provide valuable mechanistic insight. This review provides an overview of currently available proteomic techniques, including examples of their application in toxicological in vivo and in vitro studies. Future perspectives for a wider application of state-of-the-art proteomic techniques in the field of toxicology are discussed. The examples concern experiments with dioxins, polychlorinated biphenyls, and polybrominated diphenyl ethers as model compounds, as they exhibit a plethora of sublethal effects, of which some mechanisms were revealed via successful proteomic studies. Generally, this review shows the added value of including proteomics in a modern tool box for toxicological studies.

Proteome profiling of crude serum is a challenging task due to the wide dynamic range of protein concentrations and the presence of high-abundance proteins, which cover >90% of the total protein mass in serum. Peptide fractionation on strong cation exchange, weak anion exchange in the electrostatic repulsion hydrophilic interaction chromatography (ERLIC) mode, RP C-18 at pH 2.5 (low pH), fused-core fluorinated at pH 2.5, and RP C-18 at pH 9.7 (high pH) stationary phases resulted in two to three times more identified proteins and three to four times more identified peptides in comparison with 1D nanoChip-LC-MS/MS quadrupole TOF analysis (45 proteins, 185 peptides). The largest number of peptides and proteins was identified after prefractionation in the ERLIC mode due to the more uniform distribution of peptides among the collected fractions and on the RP column at high pH due to the high efficiency of RP separations and the complementary selectivity of both techniques to low-pH RP chromatography. A 3D separation scheme combining ERLIC, high-pH RP, and low-pH nanoChip-LC-MS/MS for crude serum proteome profiling resulted in the identification of 208 proteins and 1088 peptides with the lowest reported concentration of 11 ng/mL for heat shock protein 74.

Background: The comprehensive analysis of human kidney glomerulus we previously performed using highly purified glomeruli, provided a dataset of 6,686 unique proteins representing 2,966 distinct genes. This dataset, however, contained considerable redundancy resulting from identification criteria under which all the proteins matched with the same set of peptides and its subset were reported as identified proteins. In this study we reanalyzed the raw data using the Mascot search engine and highly stringent criteria in order to select proteins with the highest scores matching peptides with scores exceeding the “Identity Threshold” and one or more unique peptides. This enabled us to exclude proteins with lower scores which only matched the same set of peptides or its subset. This approach provided a high-confidence, non-redundant dataset of identified proteins for extensive profiling, annotation, and comparison with other proteome datasets that can provide biologically relevant knowledge of glomerulus proteome. Results: Protein identification using the Mascot search engine under highly stringent, computational strategy generated a non-redundant dataset of 1,817 proteins representing 1,478 genes. These proteins were represented by 2-D protein array specifying observed molecular weight and isoelectric point range of identified proteins to demonstrate differences in the observed and calculated physicochemical properties. Characteristics of glomerulus proteome could be illustrated by GO analysis and protein classification. The depth of proteomic analysis was well documented via comparison of the dynamic range of identified proteins with other proteomic analyses of human glomerulus, as well as a high coverage of biologically important pathways. Comparison of glomerulus proteome with human plasma and urine proteomes, provided by comprehensive analysis, suggested the extent and characteristics of proteins contaminated from plasma and excreted into urine, respectively. Among the latter proteins, several were demonstrated to be highly or specifically localized in the glomerulus by cross-reference analysis with the Human Protein Atlas database, and could be biomarker candidates for glomerular injury. Furthermore, comparison of ortholog proteins identified in human and mouse glomeruli suggest some biologically significant differences in glomerulus proteomes between the two species. Conclusions: A high-confidence, non-redundant dataset of proteins created by comprehensive proteomic analysis could provide a more extensive understanding of human glomerulus proteome and could be useful as a resource for the discovery of biomarkers and disease-relevant proteins., 学位の種類: 博士（医学）. 報告番号: 甲第3810号. 学位記番号: 新大院博（医）甲第562号. 学位授与年月日: 平成25年9月20日, 新大院博（医）甲第562号

Background The comprehensive analysis of human kidney glomerulus we previously performed using highly purified glomeruli, provided a dataset of 6,686 unique proteins representing 2,966 distinct genes. This dataset, however, contained considerable redundancy resulting from identification criteria under which all the proteins matched with the same set of peptides and its subset were reported as identified proteins. In this study we reanalyzed the raw data using the Mascot search engine and highly stringent criteria in order to select proteins with the highest scores matching peptides with scores exceeding the “Identity Threshold” and one or more unique peptides. This enabled us to exclude proteins with lower scores which only matched the same set of peptides or its subset. This approach provided a high-confidence, non-redundant dataset of identified proteins for extensive profiling, annotation, and comparison with other proteome datasets that can provide biologically relevant knowledge of glomerulus proteome. Results Protein identification using the Mascot search engine under highly stringent, computational strategy generated a non-redundant dataset of 1,817 proteins representing 1,478 genes. These proteins were represented by 2-D protein array specifying observed molecular weight and isoelectric point range of identified proteins to demonstrate differences in the observed and calculated physicochemical properties. Characteristics of glomerulus proteome could be illustrated by GO analysis and protein classification. The depth of proteomic analysis was well documented via comparison of the dynamic range of identified proteins with other proteomic analyses of human glomerulus, as well as a high coverage of biologically important pathways. Comparison of glomerulus proteome with human plasma and urine proteomes, provided by comprehensive analysis, suggested the extent and characteristics of proteins contaminated from plasma and excreted into urine, respectively. Among the latter proteins, several were demonstrated to be highly or specifically localized in the glomerulus by cross-reference analysis with the Human Protein Atlas database, and could be biomarker candidates for glomerular injury. Furthermore, comparison of ortholog proteins identified in human and mouse glomeruli suggest some biologically significant differences in glomerulus proteomes between the two species. Conclusions A high-confidence, non-redundant dataset of proteins created by comprehensive proteomic analysis could provide a more extensive understanding of human glomerulus proteome and could be useful as a resource for the discovery of biomarkers and disease-relevant proteins.

International audience; Cardiovascular disease (CVD) mortality rates are lower in Asian countries where dietary patterns are very different from Western diet. A number of studies have linked these lower rates to the inclusion of soy products as a staple food in those countries. Soy is the richest dietary source of isoflavones, a type of phytoestrogen associated with many potentially beneficial effects. Isoflavone-containing soy protein consumption has been linked to reduced levels of LDL cholesterol in hypercholesterolemic patients. This effect is increased with the concomitant administration of isoflavones, and seems to be also complemented by the isoflavone capacity to restore the endothelial function in patients with weak and moderated endothelial dysfunction. The effects are variable depending on individuals' metabolism and in particular to their ability to convert daidzein to equol that seems to be restricted to approximately 1/3 of the population. Equol production has been indeed linked to a decreased arterial stiffness and antiatherosclerotic effects via NO production. Because the relevance of isoflavones consumption on the modulation of cardiovascular risk still remains unclear, this paper aims to review the existing knowledge on the biological activity of the isoflavones on the human cardiovascular system from an epidemiological, clinical and -omics point of view.