Salivary protein profiles and sensitivity to the bitter taste of caffeine

The interindividual variation in the sensitivity to bitterness is attributed in part to genetic polymorphism at the taste receptor level, but other factors, such as saliva composition, might be involved. In order to investigate this, 2 groups of subjects (hyposensitive, hypersensitive) were selected from 29 healthy male volunteers based on their detection thresholds for caffeine, and their salivary proteome composition was compared. Abundance of 26 of the 255 spots detected on saliva electrophoretic patterns was significantly different between hypo- and hypersensitive subjects. Saliva of hypersensitive subjects contained higher levels of amylase fragments, immunoglobulins, and serum albumin and/or serum albumin fragments. It also contained lower levels of cystatin SN, an inhibitor of protease. The results suggest that proteolysis occurring within the oral cavity is an important perireceptor factor associated to the sensitivity to the bitter taste of caffeine.     

Organic acid profile of isovaleric acidemia: a comprehensive metabolomics approach

Isovaleric acidemia (IVA, MIM 248600) can be a severe and potentially life-threatening disease in affected neonates, but with a positive prognosis on treatment for some phenotypes. This study presents the first application of metabolomics to evaluate the metabolite profiles derived from urine samples of untreated and treated IVA patients as well as of obligate heterozygotes. All IVA patients carried the same homozygous c.367 G > A nucleotide change in exon 4 of the IVD gene but manifested phenotypic diversity. Concurrent class analysis (CONCA) was used to compare all the metabolites from the original complete data set obtained from the three case and two control groups used in this investigation. This application of CONCA has not been reported previously, and is used here to compare four different modes of scaling of all metabolites. The variables important in discrimination from the CONCA thus enabled the recognition of different metabolic patterns encapsulated within the data sets that would not have been revealed by using only one mode of scaling. Application of multivariate and univariate analyses disclosed 11 important metabolites that distinguished untreated IVA from controls. These included well-established diagnostic biomarkers of IVA, endogenous detoxification markers, and 3-hydroxycaproic acid, an indicator of ketosis, but not reported previously for this disease. Nine metabolites were identified that reflected the effect of treatment of IVA. They included detoxification products and indicators related to the high carbohydrate and low protein diet which formed the hallmark of the treatment. This investigation also provides the first comparative metabolite profile for heterozygotes of this inherited metabolic disorder. The detection of informative metabolites in even very low concentrations in all three experimental groups highlights the potential advantage of the holistic mode of analysis of inherited metabolic diseases in a metabolomics investigation.     

人体特征的头发代谢组学及蛋白质组学研究进展

人类头发是以角蛋白和角蛋白相关蛋白为主要成分的天然纤维,是一种可表征一定时间内机体状态的良好生物学样本。头发易采集、低成本、易于运输和存储等优点使其在毒品、酒精及兴奋剂等的检测中具有独特优势。蛋白质组学是一种在整体水平上研究蛋白表达和调控的新兴技术,在生命科学领域应用广泛。蛋白质组学技术可用于不同人群头发蛋白组成及动态变化研究,在寻找疾病标志物、区分个人特质等方面具有巨大潜力。本文从头发的结构及组成、心理压力下头发的变化以及头发蛋白质组学分析技术的研究进展进行了全面综述,对理解头发蛋白质组学表征人体特征以及指导相关研究具有重要意义。     

Protein nanocrystallography: a new approach to structural proteomics

This article describes a new approach to structural proteomics that can produce and characterize diffracting, stable and radiation-resistant crystals of miniscule dimensions using nanotechnology. We believe that the protein microcrystals obtained by nanotechnology-based protein thin-film template crystallization, as well as groundbreaking technology, such as atomic force microscopy, nanogravimetry and synchrotron microfocus, have enabled protein nanocrystallography to be defined as a unique technology capable of forming and characterizing stable protein microcrystals down to atomic resolution. A new route from art to science and technology has, therefore, been opened in protein crystallography, and it could be used to unravel the mysteries of many systems that remain unsolved.     

BuildSummary: using a group-based approach to improve the sensitivity of peptide/protein identification in shotgun proteomics

The target-decoy database search strategy is widely accepted as a standard method for estimating the false discovery rate (FDR) of peptide identification, based on which peptide-spectrum matches (PSMs) from the target database are filtered. To improve the sensitivity of protein identification given a fixed accuracy (frequently defined by a protein FDR threshold), a postprocessing procedure is often used that integrates results from different peptide search engines that had assayed the same data set. In this work, we show that PSMs that are grouped by the precursor charge, the number of missed internal cleavage sites, the modification state, and the numbers of protease termini and that the proteins grouped by their unique peptide count should be filtered separately according to the given FDR. We also develop an iterative procedure to filter the PSMs and proteins simultaneously, according to the given FDR. Finally, we present a general framework to integrate the results from different peptide search engines using the same FDR threshold. Our method was tested with several shotgun proteomics data sets that were acquired by multiple LC/MS instruments from two different biological samples. The results showed a satisfactory performance. We implemented the method in a user-friendly software package called BuildSummary, which can be downloaded for free from http://www.proteomics.ac.cn/software/proteomicstools/index.htm as part of the software suite ProteomicsTools.     

Cancer proteomics: from signaling networks to tumor markers

Along with the great strides that have been made towards understanding cancer, has come a realization of the complexity of molecular events that lead to malignancy. Proteomics-based approaches, which enable the quantitative investigation of both cellular protein expression levels and protein–protein interactions involved in signaling networks, promise to define the molecules controlling the processes involved in cancer.     

Cancer proteomics: from signaling networks to tumor markers

Along with the great strides that have been made towards understanding cancer, has come a realization of the complexity of molecular events that lead to malignancy. Proteomics-based approaches, which enable the quantitative investigation of both cellular protein expression levels and protein–protein interactions involved in signaling networks, promise to define the molecules controlling the processes involved in cancer.     

Binding and solubility of oleic acid to laboratory materials: a possible artifact

The possibility that significant amounts of fatty acids were dissolved in or bound to the surfaces of common laboratory materials was examined. The uptake or adsorption of radioisotopically labeled oleic acid and cholic acid by plastic tubing of Tygon, Teflon, and polyethylene, and Pyrex, and borosilicate glass, and steel was measured. 3H-oleic acid and 14C-cholic acid were used in the presence of different concentrations of unlabeled oleic acid, cholic acid, and/or bovine serum albumin. Concentrations, composition, pH, and perfusion rates were varied. Relatively large amounts (10-95%) of oleic acid (25 microM) were lost by dissolving in plastic and adsorption to glass or metal. The degree of losses decreased in the presence of compounds in the perfusion solution which could bind or dissolve oleic acid. In contrast, cholic acid was not lost to plastic, glass or metal. The magnitude of and influence of perfusion rate, composition, pH, and sequence of perfusion solutions on oleic acid losses were sufficiently large that the results of certain studies, such as those of unstirred water layers of albumin - stimulated fatty acid uptake by hepatocytes may need to be reexamined.     

A combined proteomics and computational approach provides a better understanding of HCV-induced liver disease

Evaluation of: Diamond DL, Krasnoselsky AL, Burnum KE et al. Proteome and computational analyses reveal new insights into the mechanisms of hepatitis C virus-mediated liver disease posttransplantation. Hepatology 56(1), 28–38 (2012).

HCV is a major cause of chronic liver disease worldwide and is a formidable therapeutic challenge. Recently, Diamond et al. analyzed the proteomic profiles of liver samples from HCV-positive liver transplant recipients, supplemented with an independent metabolite analysis. They used a computational approach, which highlighted the enriched functional themes and topological attributes associated with the protein association network based on their clinical data and suggested a crucial role of oxidative stress in fibrosis progression in HCV infection. Their findings provide new insights into the mechanisms that regulate the progression of HCV-associated liver fibrosis, which may be useful for identification of suitable biomarkers to evaluate the onset and severity of hepatic fibrosis and the development of new therapeutic and anti-HCV strategies.     

Biomarkers in renal cell carcinoma: a metabolomics approach

Since Otto Warburg, many studies have explored the unique metabolic phenotype of cancer cells highlighting the value and applicability of metabolomics in the oncology field, particularly in the development of cancer biomarkers. With respect to renal cell carcinoma (RCC), a metabolomics approach would own a great potential since urinary system is intimately connected with urine and, this biofluid, offers some advantages allowing the development of an assay suitable for use in clinical practice. Moreover, the assessment of metabolic derangements characteristics of RCC might provide a complete health assessment of this pathology, enabling the development of novel targeted therapies and even the stratification of responsive patients to specific therapeutic options improving the effectiveness of therapy. Metabolomic studies performed so far showed that the RCC metabolic signature is characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid catabolism, known to be crucial to cell proliferation. Despite some of those alterations are common to carcinogenesis, the potential role of acylcarnitines, gentisate, α-ketoglutarate and quinolinate in RCC pathophysiology has been proposed recently. The ability of metabolomics to discriminate between RCC and normal samples shows convincing evidence of its applicability in RCC management. Furthermore, the studies already carried out have not only tried to unveil the metabolic profile of RCC but also to evaluate the impact of some factors, namely technical, in RCC-metabolomics research. This type of study is pivotal in the design of metabolomics studies, helping to increase the reliability of the results. The present review updates the current knowledge on the metabolic alterations recognized in the RCC, and provides insight to the characteristics, strengths, limitations, and recent advances in RCC-metabolomics studies, always keeping in mind its potential application in clinical/health areas as a biomarker discovery tool.     

Dose-effect of dietary oleic acid: oleic acid is conditionally essential for some organs

The minimum dietary intake of oleic acid that is indispensable to maintain a normal content of this fatty acid in several tissues (heart, muscle, kidney and testis) was determined in the rat. For this purpose, a dose-effect study was conducted using an experimental protocol with 7 groups of rats who received a diet in which the oleic acid level varied from 0 to 6000 mg per 100 g diet, but the other ingredients were identical (in particular the essential fatty acids, linoleic and alpha-linolenic acid). Female rats were fed the diets from two weeks before mating, and their pups were killed aged either 21 or 60 days. When the level of oleic acid in the diet was increased, the main modifications observed in 21-day-old deficient pups were as follows: (i) for 18:1n-9, in the liver, muscle, heart, kidney, and testis, a plateau was reached at about 4 g oleic acid per 100 g diet. Below this level, the higher the dose the greater the response; (ii) for 16:1n-7, the concentration decreased in the liver, muscle, heart, kidney and testis; (iii) the concentration of 18:1n-7 decreased in the kidney, muscle, and testis; (iv) some minor modifications were noted for the other fatty acids. In mother's milk at 14 days of lactation, when dietary oleic acid increased, the levels of 18:1(n-9) also increased; the increase was regular and did not reach a plateau. In 60-day-old rats, the results were generally similar to those in 21-day-old rats, but with some differences, in particular a slight decrease in oleic acid concentration in the liver and kidney at the highest dietary oleic acid level.     

POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis

Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively.     

Follicular fluid content and oocyte quality: from single biochemical markers to metabolomics

The assessment of oocyte quality in human in vitro fertilization (IVF) is getting increasing attention from embryologists. Oocyte selection and the identification of the best oocytes, in fact, would help to limit embryo overproduction and to improve the results of oocyte cryostorage programs. Follicular fluid (FF) is easily available during oocyte pick-up and theorically represents an optimal source on non-invasive biochemical predictors of oocyte quality. Unfortunately, however, the studies aiming to find a good molecular predictor of oocyte quality in FF were not able to identify substances that could be used as reliable markers of oocyte competence to fertilization, embryo development and pregnancy. In the last years, a well definite trend toward passing from the research of single molecular markers to more complex techniques that study all metabolites of FF has been observed. The metabolomic approach is a powerful tool to study biochemical predictors of oocyte quality in FF, but its application in this area is still at the beginning. This review provides an overview of the current knowledge about the biochemical predictors of oocyte quality in FF, describing both the results coming from studies on single biochemical markers and those deriving from the most recent studies of metabolomics     

The sensitivity of yeast mutants to oleic acid implicates the peroxisome and other processes in membrane function

The peroxisome, sole site of beta-oxidation in Saccharomyces cerevisiae, is known to be required for optimal growth in the presence of fatty acid. Screening of the haploid yeast deletion collection identified approximately 130 genes, 23 encoding peroxisomal proteins, necessary for normal growth on oleic acid. Oleate slightly enhances growth of wild-type yeast and inhibits growth of all strains identified by the screen. Nonperoxisomal processes, among them chromatin modification by H2AZ, Pol II mediator function, and cell-wall-associated activities, also prevent oleate toxicity. The most oleate-inhibited strains lack Sap190, a putative adaptor for the PP2A-type protein phosphatase Sit4 (which is also required for normal growth on oleate) and Ilm1, a protein of unknown function. Palmitoleate, the other main unsaturated fatty acid of Saccharomyces, fails to inhibit growth of the sap190delta, sit4delta, and ilm1delta strains. Data that suggest that oleate inhibition of the growth of a peroxisomal mutant is due to an increase in plasma membrane porosity are presented. We propose that yeast deficient in peroxisomal and other functions are sensitive to oleate perhaps because of an inability to effectively control the fatty acid composition of membrane phospholipids.