Analytical investigation of secondary metabolites extracted from Camellia sinensis L. leaves using a HPLC‐DAD‐ESI/MS data fusion strategy and chemometric methods

Considerable attention has been paid to the study of green tea leaves because of their high consume and beneficial effects on human health. In this work, an appropriate strategy is proposed to investigate and resolve the major metabolites extracted from Camellia sinensis tea leaves. Statistical design mixtures of ethanol, ethyl acetate, dichloromethane, and chloroform were used to study the effects of different solvents and their mixtures on the extraction of the secondary metabolites of C. sinensis tea leaves from two different harvest seasons. Extracted samples were analyzed by high performance liquid chromatography‐diode array detection‐electrospray ionization mass spectrometer allowing the resolution of a large amount of tea metabolites with high relative abundances, especially when their extraction was performed in pure ethanol and with solvent mixtures with ethanol. Resolution of the more relevant metabolites was achieved by the simultaneous analysis of the fused diode array detection and mass spectrometer detectors data from the same samples using the multivariate curve resolution‐alternating least squares chemometric method. Peak areas finally resolved were further analyzed by orthogonal signal correction and partial least squares‐discrimination analysis to discriminate among C. sinensis tea samples. Using the Variable Importance in Projection variable selection method, epigallocatechin and caffeine were finally selected as the two more important chemical constituents of tea leaves that were discriminating more between the tea samples from two different harvest seasons. Copyright © 2016 John Wiley & Sons, Ltd.     

Metabolic profile of rosmarinic acid from Java tea (Orthosiphon stamineus) by ultra‐high‐performance liquid chromatography coupled to quadrupole‐time‐of‐flight tandem mass spectrometry with a three‐step data mining strategy

Rosmarinic acid (RA) is a caffeic acid derivative and one of the most abundant and bioactive constituents in Java tea (Orthosiphon stamineus), which has significant biological activities. However, relatively few studies have been conducted to describe this compound's metabolites in vivo. Therefore, an ultra‐high‐performance liquid chromatography coupled to quadrupole‐time‐of‐flight tandem mass spectrometry (UHPLC–QTOF–MS/MS) analysis with a three‐step data mining strategy was established for the metabolic profile of RA. Firstly, the exogenously sourced ions were filtered out by the MarkerView software and incorporated with Microsoft Office Excel software. Secondly, a novel modified mass detects filter strategy based on the predicted metabolites was developed for screening the target ions with narrow, well‐defined mass detection ranges. Thirdly, the diagnostic product ions and neutral loss filtering strategy were applied for the rapid identification of the metabolites. Finally, a total of 16 metabolites were reasonably identified in urine, bile and feces, while metabolites were barely found in plasma. The metabolites of RA could also be distributed rapidly in liver and kidney. Glucuronidation, methylation and sulfation were the primary metabolic pathways of RA. The present findings might provide the theoretical basis for evaluating the biological activities of RA and its future application.     

Chemometrics comparison of gas chromatography with mass spectrometry and comprehensive two‐dimensional gas chromatography with time‐of‐flight mass spectrometry Daphnia magna metabolic profiles exposed to salinity

The performances of gas chromatography with mass spectrometry and of comprehensive two‐dimensional gas chromatography with time‐of‐flight mass spectrometry are examined through the comparison of Daphnia magna metabolic profiles. Gas chromatography with mass spectrometry and comprehensive two‐dimensional gas chromatography with mass spectrometry were used to compare the concentration changes of metabolites under saline conditions. In this regard, a chemometric strategy based on wavelet compression and multivariate curve resolution–alternating least squares is used to compare the performances of gas chromatography with mass spectrometry and comprehensive two‐dimensional gas chromatography with time‐of‐flight mass spectrometry for the untargeted metabolic profiling of Daphnia magna in control and salinity‐exposed samples. Examination of the results confirmed the outperformance of comprehensive two‐dimensional gas chromatography with time‐of‐flight mass spectrometry over gas chromatography with mass spectrometry for the detection of metabolites in D. magna samples. The peak areas of multivariate curve resolution–alternating least squares resolved elution profiles in every sample analyzed by comprehensive two‐dimensional gas chromatography with time‐of‐flight mass spectrometry were arranged in a new data matrix that was then modeled by partial least squares discriminant analysis. The control and salt‐exposed daphnids samples were discriminated and the most relevant metabolites were estimated using variable importance in projection and selectivity ratio values. Salinity de‐regulated 18 metabolites from metabolic pathways involved in protein translation, transmembrane cell transport, carbon metabolism, secondary metabolism, glycolysis, and osmoregulation.     

Metabolite profiling to discriminate different species and genus from thistles in Korea using liquid chromatography with quadrupole time‐of‐flight mass spectrometry

This study was designed to classify and identify closely related thistle species in the genus Cirsium, as well as Carduus and Cephalonoplos species, which are also thistles. The comprehensive and untargeted metabolite profiles of nine Korean thistles were determined using ultra high performance liquid chromatography combined with hybrid quadrupole time‐of‐flight mass spectrometry. The difference in metabolite profiles among species was explored using principal component analysis and hierarchical clustering analysis. The significantly different metabolites (Bonferroni‐corrected P‐value < 0.001) were used to construct a partial least squares discriminant analysis model to predict the species of thistle. Nine species were successfully classified using a partial least squares discriminant analysis model and confirmed using a cross‐validation method. Species with similar features were grouped based on unique patterns in variable clusters. The present study suggests that liquid chromatography with quadrupole time‐of‐flight mass spectrometry untargeted metabolomic profiling with chemometric analysis is an efficient and powerful tool for discriminating between different species of medicinal herbs.     

Gas chromatography coupled to mass spectrometry‐based metabolomic to screen for anabolic practices in cattle: identification of 5α‐androst‐2‐en‐17‐one as new biomarker of 4‐androstenedione misuse

The use of anabolic steroids as growth promoters for meat‐producing animals is banned within the European Union. However, screening for the illegal use of natural steroid hormones still represents a difficult challenge because of the high interindividual and physiological variability of the endogenous concentration levels in animals. In this context, the development of untargeted profiling approaches for identifying new relevant biomarkers of exposure and/or effect has been emerging for a couple of years. The present study deals with an untargeted metabolomics approach on the basis of GC‐MS aiming to reveal potential biomarkers signing a fraudulent administration of 4‐androstenedione (AED), an anabolic androgenic steroid chosen as template. After a sample preparation based on microextraction by packed sorbent, urinary profiles of the free and deglucurono‐conjugates urinary metabolites were acquired by GC‐MS in the full‐scan acquisition mode. Data processing and chemometric procedures highlighted 125 ions, allowing discrimination between samples collected before and after an administration of 4‐AED. After a first evaluation of the signal robustness using additional and independent non‐compliant samples, 17 steroid‐like metabolites were pointed out as relevant candidate biomarkers. All these metabolites were then monitored using a targeted GC‐MS/MS method for an additional assessment of their capacity to be used as biomarkers. Finally, two steroids, namely 5α‐androstane‐3β,17α‐diol and 5α‐androst‐2‐en‐17‐one, were concluded to be compatible with such a definition and which could be finally usable for screening purpose of AED abuse in cattle. Copyright © 2012 John Wiley & Sons, Ltd.     

On‐line high‐performance liquid chromatography coupled with biochemical detection method for screening of α‐glucosidase inhibitors in green tea

An on‐line high‐performance liquid chromatography–biochemical detection (HPLC‐BCD) method, in which compounds separated by HPLC were on‐line reacted with enzyme and substrate solutions delivered by flow injection and the enzyme inhibition signal was collected by UV detection, was developed to rapidly screen α‐glucosidase inhibitors from green tea extracts in this study. The chromatographic fingerprints and enzyme inhibition profiles of the different brands of green tea could be simultaneously detected by the on‐line HPLC‐BCD method. Enzyme inhibition profiles were detected by the UV detector at 415 nm based on the reaction of α‐glucosidase and p‐nitrophenyl α‐d ‐glucopyranoside (PNPG). PNPG (1.25 mm ), α‐glucosidase (0.4 U/mL) and the flow rate 0.07 mL/min were applied as optimized parameters to detect α‐glucosidase inhibitors in green tea. Four components in green tea showed α‐glucosidase inhibition action and three of them were identified as HHDP‐galloyl glucose, (−)‐epigallocatechin‐3‐gallate and (−)‐epicatechin‐3‐gallate by HPLC–fourier‐transform mass spectrometry (HPLC‐FTMS). Two brands of green tea derived from Mengding and Enshi mountainous areas might be superior to the other samples in the prevention and treatment of diabetes owing to their stronger activities of enzyme inhibitors. The proposed on‐line HPLC‐BCD method could be used to rapidly identify the potential enzyme inhibitors in complex matrixes.     

Rapid discovery and identification of the prototypes and their metabolites of Da‐Huang‐Xiao‐Shi decoction in rat plasma by an integrative strategy based on liquid chromatography coupled with mass spectrometry

Da‐Huang‐Xiao‐Shi decoction has been used to treat damp‐heat jaundice for centuries in China. However, the absorbed components of the decoction and their related metabolites are little known until now. In this work, an integrative strategy based on liquid chromatography coupled with mass spectrometry (time‐of‐flight/triple‐quadruple tandem) was adopted to effectively identify the prototypes and their metabolites and to speculate the possible transformation pathways among these compounds. Using pattern recognition approaches, the exogenous compounds in rat plasma were screened out from endogenous compounds and then distinguished into prototypes and metabolites according to the characteristic information from the self‐building database of Da‐Huang‐Xiao‐Shi decoction. On this basis, the metabolic profiles of main prototypes (such as iridoid glycosides, alkaloids, and anthraquinones) were proposed. As a result, a total of 62 related prototypes and their metabolites were detected and tentatively identified in rat plasma after administration, and among them, three prototypes were found for the first time. Glucuronidation and sulfation were deduced to be the main metabolic pathways of alkaloids, iridoid glycosides, and anthraquinones. The integrative strategy used in this study was an effective approach to rapidly discover and characterize the prototypes and their metabolites from a complex bio‐sample without the use of standard substances.     

Accurate discrimination of Gastrodia elata from different geographical origins using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis

Gastrodia elata from different geographical origins varies in quality and pharmacological activity. This study focused on the classification and identification of Gastrodia elata from six producing areas using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis. Before recognition analysis, a principal component analysis was applied to ascertain the discrimination possibility with high‐performance liquid chromatography fingerprints. And then, boosting partial least‐squares discriminant analysis and conventional partial least‐squares discriminant analysis were applied in this study. Experimental results indicated that the adaptive iteratively reweighted penalized least‐squares algorithm could eliminate the baseline drift of high‐performance liquid chromatography chromatograms effectively. And compared with partial least‐squares discriminant analysis, the total recognition rates using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis for the calibration sets and prediction sets were improved from 94 to 100% and 86 to 97%, respectively. In conclusion, high‐performance liquid chromatography combined with boosting partial least‐squares discriminant analysis, which has such advantages as effective, specific, accurate, non‐polluting, has an edge for discrimination of traditional Chinese medicine from different geographical origins. And the proposed methodology is a useful tool to classify and identify Gastrodia elata from different geographical origins.     

Geographical discrimination of Chinese winter wheat using volatile compound analysis by HS‐SPME/GC‐MS coupled with multivariate statistical analysis

This study aimed to develop a potential analytical method to discriminate the Chinese winter wheat according to geographical origin and cultivars. A total of 90 wheat samples of 10 different wheat cultivars among three regions were examined by headspace solid phase microextraction coupled with gas chromatography‐mass spectrometry (GC‐MS). The peak areas of 32 main volatile compounds were selected and subjected to statistical analysis, which revealed significant differences among different regions and cultivars. Multivariate analysis of variance showed a significant influence of regions, wheat genotypes, and their interaction on the volatile composition of wheat. Principal component analysis of the aromatic profile showed better visualization for wheat geographical origins. Finally, a classification model based on the linear discriminant analysis was successfully constructed for the discrimination of regions and cultivars with the correct classification percentages of 90 and 100%, respectively.     

Rapid profiling of polymeric phenolic acids in Salvia miltiorrhiza by hybrid data‐dependent/targeted multistage mass spectrometry acquisition based on expected compounds prediction and fragment ion searching

Phenolic acids are the major water‐soluble components in Salvia miltiorrhiza (>5%). According to previous studies, many of them contribute to the cardiovascular effects and antioxidant effects of S. miltiorrhiza. Polymeric phenolic acids can be considered as the tanshinol derived metabolites, e.g., dimmers, trimers, and tetramers. A strategy combined with tanshinol‐based expected compounds prediction, total ion chromatogram filtering, fragment ion searching, and parent list‐based multistage mass spectrometry acquisition by linear trap quadropole‐orbitrap Velos mass spectrometry was proposed to rapid profile polymeric phenolic acids in S. miltiorrhiza. More than 480 potential polymeric phenolic acids could be screened out by this strategy. Based on the fragment information obtained by parent list‐activated data dependent multistage mass spectrometry acquisition, 190 polymeric phenolic acids were characterized by comparing their mass information with literature data, and 18 of them were firstly detected from S. miltiorrhiza. Seven potential compounds were tentatively characterized as new polymeric phenolic acids from S. miltiorrhiza. This strategy facilitates identification of polymeric phenolic acids in complex matrix with both selectivity and sensitivity, which could be expanded for rapid discovery and identification of compounds from complex matrix.     

A recommended and verified procedure for in situ tryptic digestion of formalin‐fixed paraffin‐embedded tissues for analysis by matrix‐assisted laser desorption/ionization imaging mass spectrometry

Matrix‐assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a molecular imaging technology uniquely capable of untargeted measurement of proteins, lipids, and metabolites while retaining spatial information about their location in situ. This powerful combination of capabilities has the potential to bring a wealth of knowledge to the field of molecular histology. Translation of this innovative research tool into clinical laboratories requires the development of reliable sample preparation protocols for the analysis of proteins from formalin‐fixed paraffin‐embedded (FFPE) tissues, the standard preservation process in clinical pathology. Although ideal for stained tissue analysis by microscopy, the FFPE process cross‐links, disrupts, or can remove proteins from the tissue, making analysis of the protein content challenging. To date, reported approaches differ widely in process and efficacy. This tutorial presents a strategy derived from systematic testing and optimization of key parameters, for reproducible in situ tryptic digestion of proteins in FFPE tissue and subsequent MALDI IMS analysis. The approach describes a generalized method for FFPE tissues originating from virtually any source.     

Searching for in silico predicted metabolites and designer modifications of (cortico)steroids in urine by high‐resolution liquid chromatography/time‐of‐flight mass spectrometry

Glucocorticosteroids are a restricted class of substances and appear on the ‘in‐competition’ prohibited list of the World Anti‐Doping Agency (WADA). Analysis of glucocorticosteroids is complicated since they show significant phase 1 and 2 metabolism in the human body and are excreted into urine in concentrations in the µg/L range. Full scan, high‐resolution time‐of‐flight mass spectrometry analysis generates information on all ionisable components in urine, including known and unknown metabolites of steroids and even designer modifications of anabolic steroids. However, evaluation of the data obtained can be difficult and time‐consuming because of the need to differentiate between endogenous components and compounds of interest. MetaboLynx?, a spectral and chromatographic search program, was modified for the determination of in silico predicted metabolites of glucocorticosteroids and designer modifications of anabolic steroids in human urine. Spiked urine samples were successfully screened for known components in a targeted approach and for unknown species in a non‐targeted approach using data filtering to limit potential false‐positives. A simplified combined approach of targeted and untargeted screening was used for the detection of metabolites and designer modifications of existing compounds. This approach proved successful and showed its strength in the detection of tetrahydrogestrinone (THG), a designer modification of gestrinone. THG was positively detected in a spiked urine sample and correctly identified as a twofold hydrogenation of gestrinone. The developed screening method can easily be adapted to specific needs and it is envisaged that a similar approach would be amendable to the discovery of metabolites or designer modifications of other compounds of interest. Copyright © 2009 John Wiley & Sons, Ltd.     

Metabolic profiling for the identification of Huntington biomarkers by on‐line solid‐phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools

In this work, an untargeted metabolomic approach based on sensitive analysis by on‐line solid‐phase extraction capillary electrophoresis mass spectrometry (SPE‐CE‐MS) in combination with multivariate data analysis is proposed as an efficient method for the identification of biomarkers of Huntington's disease (HD) progression in plasma. For this purpose, plasma samples from wild‐type (wt) and HD (R6/1) mice of different ages (8, 12, and 30 weeks), were analyzed by C₁₈‐SPE‐CE‐MS in order to obtain the characteristic electrophoretic profiles of low molecular mass compounds. Then, multivariate curve resolution alternating least squares (MCR‐ALS) was applied to the multiple full scan MS datasets. This strategy permitted the resolution of a large number of metabolites being characterized by their electrophoretic peaks and their corresponding mass spectra. A total number of 29 compounds were relevant to discriminate between wt and HD plasma samples, as well as to follow‐up the HD progression. The intracellular signaling was found to be the most affected metabolic pathway in HD mice after 12 weeks of birth, when mice already showed motor coordination deficiencies and cognitive decline. This fact agreed with the atrophy and dysfunction of specific neurons, loss of several types of receptors, and changed expression of neurotransmitters.     

An integrated strategy for the geographical origin traceability of Goji berries by antioxidants characteristic fingerprint based online ultra-performance liquid chromatography-2,2-diphenyl-1-picrylhydrazyl- photodiode array detector-mass spectrometry combined with multivariate statistics analysis

Goji berries are now becoming increasingly popular in the human diet due to their potential health benefits. Unscrupulous traders deliberately mislabel with certain origins to gain illegal profits, which seriously affected the consumers’ benefits. In this study, an online ultra-performance liquid chromatography-2,2-diphenyl-1 -picrylhydrazyl-photodiode array detector-electrospray ionization-quadrupole time of flight mass was developed for rapid screening and identification of the antioxidants from Goji berry; then, the antioxidants characteristic fingerprint was established and explored in the origins discrimination of Goji berries from China combined with multivariate statistics analysis. As a result, twenty-eight compounds were screened from Goji berry extract, 19 of which were identified by accurate molecular and ultraviolet information according to references. Principal components analysis and partial least squares discrimination analysis achieved the accurate classification from the four regions, eight compounds were selected as origin-related antioxidant markers with variable importance in projection >1 and one-way analysis of variance (P<0.05), including rutin, rutin di-hexose, P-coumaric acid tri-hexose, dicaffeoylquinic acid isomer, Quercetin-rhamno-di-hexoside, peak14, peak16, and peak27. This study provides a feasible strategy for the geographical origins discrimination of Goji berries based on antioxidant ingredients difference and will be helpful for improving the quality control level of Goji berries.     

Detection of volatile organic compounds in the headspace above mold fungi by GC‐soft X‐radiation–based APCI‐MS

Mold fungi on malting barley grains cause major economic loss in malting and brewery facilities. Possible proxies for their detection are volatile and semivolatile metabolites. Among those substances, characteristic marker compounds have to be identified for a confident detection of mold fungi in varying surroundings. The analytical determination is usually performed through passive sampling with solid phase microextraction, gas chromatographic separation, and detection by electron ionization mass spectrometry (EI‐MS), which often does not allow a confident determination due to the absence of molecular ions. An alternative is GC‐APCI‐MS, generally, allowing the determination of protonated molecular ions. Commercial atmospheric pressure chemical ionization (APCI) sources are based on corona discharges, which are often unspecific due to the occurrence of several side reactions and produce complex product ion spectra. To overcome this issue, an APCI source based on soft X‐radiation is used here. This source facilitates a more specific ionization by proton transfer reactions only. In the first part, the APCI source is characterized with representative volatile fungus metabolites. Depending on the proton affinity of the metabolites, the limits of detection are up to 2 orders of magnitude below those of EI‐MS. In the second part, the volatile metabolites of the mold fungus species Aspergillus, Alternaria, Fusarium, and Penicillium are investigated. In total, 86 compounds were found with GC‐EI/APCI‐MS. The metabolites identified belong to the substance classes of alcohols, aldehydes, ketones, carboxylic acids, esters, substituted aromatic compounds, terpenes, and sesquiterpenes. In addition to substances unspecific for the individual fungus species, characteristic patterns of metabolites, allowing their confident discrimination, were found for each of the 4 fungus species. Sixty‐seven of the 86 metabolites are detected by X‐ray–based APCI‐MS alone. The discrimination of the fungus species based on these metabolites alone was possible. Therefore, APCI‐MS in combination with collision induced dissociation alone could be used as a supervision method for the detection of mold fungi.     

Solid‐phase microextraction with fast GC combined with a high‐speed triple quadrupole mass spectrometer for targeted and untargeted food analysis

The present contribution is focused on the evaluation of a high‐speed triple quadrupole mass spectrometer, carried out under moderately fast GC conditions (analysis time: 16.6 min). The mass spectrometric instrument can be operated under high‐speed GC conditions, in both full‐scan (maximum scan speed: 20 000 amu/s) and multiple reaction monitoring (MRM) modes (minimum dwell time: 0.01 s). Additionally, the mass spectrometric system can generate full scan and MRM information, simultaneously and rapidly. A headspace solid‐phase microextraction with fast GC coupled to triple quadrupole MS approach was developed for the: (i) qualitative untargeted analysis of brewed tea volatiles, and (ii) MRM qualitative and quantitative analysis of targeted volatiles (also in brewed tea), namely 30 phytosanitary contaminants. The performance of the triple quadrupole instrument was satisfactory both for identification and quantification purposes. Furthermore, the method sensitivity was more than sufficient for the requirements of current legislation. Method validation, related to the MRM analysis, was performed considering: precision of quantification data (maximum coefficient of variation value: 12.0%) and quantification/qualification ion ratios (maximum coefficient of variation value: 14.4%), along with limits of detection (4 parts per trillion–5 parts per billion range) and quantification (14 parts per trillion–16 parts per billion range).     

Enhanced pseudotargeted analysis using a segment data dependent acquisition strategy by liquid chromatography–tandem mass spectrometry for a metabolomics study of liquiritin in the treatment of depression

An enhanced pseudotargeted method using a segment data‐dependent acquisition mode based on ultra‐high performance liquid chromatography–tandem mass spectrometry was developed. This segment data dependent acquisition‐based pseudotargeted method could improve the detection of co‐eluted ions and extend the coverage of analytes. A set of 502 multiple reaction monitoring channels were obtained by this segment strategy, which was twice the number created by the traditional data‐dependent acquisition mode. Compared with the untargeted method, the pseudotargeted profiling demonstrated higher sensitivity and higher precision. More than 90% of the metabolites detected by the enhanced pseudotargeted method had relative standard deviations less than 15%. The segment data dependent acquisition‐based pseudotargeted method was successfully applied to the metabolomics study of the depressed rats with the treatment of liquiritin. Forty‐seven differential metabolites were screened and five metabolic pathways were found to be related to depression including retinol metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, terpenoid backbone biosynthesis, and lysine degradation. The segment data dependent acquisition‐based pseudotargeted method widened the coverage of metabolites with good sensitivity and precision, which exhibited great potential in the discovery of differential metabolites in metabolomics studies.     

UHPLC–Q‐TOF‐MS‐based metabolomics approach to compare the saponin compositions of Xueshuantong injection and Xuesaitong injection

Various traditional Chinese medicine preparations developed from Notoginseng total saponins, including Xueshuantong injection and Xuesaitong injection, are extensively used in China to treat cardiocerebrovascular diseases. However, the difference of their saponin compositions remains unknown. An ultra high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry based metabolomics approach was developed to probe the saponin discrimination between Xueshuantong and Xuesaitong and the related factors by large sample analysis. A highly efficient chromatographic separation was achieved on an HSS T3 column within 20 min with the holistic metabolites information recorded in the negative MS^E mode. A six‐step data pretreatment procedure mainly based on Progenesis QI and mass defect filtering was established. Pattern recognition chemometrics was used to discover the potential saponin markers. The saponin composition of Wuzhou Xueshuantong showed distinct discrimination from the other products. Wuzhou Xueshuantong contains more abundant protopanaxatriol‐type noto‐R₁, Rg₁, Re, and protopanaxadiol‐type Rb₁, but less Rd and other low‐polarity protopanaxadiol‐type ginsenosides. These differences could not directly correlate to the use of different parts of Panax notoginseng , but possibly to the different preparation techniques employed by different manufacturers. These results are beneficial to the establishment of pharmacopoeia standards and the assessment of the efficacy and adverse drug reactions for these homologous products.     

应用非同质荷比规则提高蛋白质组学检索结果的可信度和灵敏度

如何筛选合理的数据库匹配结果对于基于质谱的蛋白质组学研究至关重要。但是目前,基于打分体系和反转数据库的筛选方法都无法有效的避免假阳性和假阴性匹配的存在。因此,本文提出了一种系统的搜索策略: 非同质荷比检索规则 (INMZS)。在该策略中,所有匹配结果都需要检查相关匹配质荷比的分享程度,只有那些相关质荷比均为专有匹配时,蛋白质才会被作为可信结果保留,策略还采用迭代搜索方法以提高鉴定低丰度组分的灵敏度。最终,所有的匹配结果由诱饵数据库方法进行评估以得到最终结果列表。INMZS策略在标准蛋白质混合物和大规模人肝蛋白质组数据上进行了模拟及应用,结果显示,INMZS规则和诱饵数据库评估方法的结和可以有效的保证蛋白质组学数据匹配的可信度及灵敏度,可以广泛适用于基于二维凝胶电泳及非shotgun技术的蛋白组学研究中。