HUPO Biological Reference Material Initiative Workshop 26 September 2009, Toronto,Canada

The Biological Reference Material Initiative Workshop held at the Toronto HUPO congress on 26 September 2009, focused on the development of new biological reference materials and tools for the assessment of reproducibility, the solutions to many of the technical challenges in proteomics and protein‐based molecular diagnostics. This half‐day meeting included presentations from leading scientists from the worldwide proteomic community, who shared a common interest in standardization and increased accuracy of proteomic data. The conclusion was that proteomics is highly sensitive to both biological and technical variability. It is this biological and technical variance, when not accounted for by experiment design, that invalidates proteomic experiments, but both of these issues can be dealt with by tackling reproducibility.     

Comparison of label-free and label-based strategies for proteome analysis of hepatoma cell lines

Within the past decade numerous methods for quantitative proteome analysis have been developed of which all exhibit particular advantages and disadvantages. Here, we present the results of a study aiming for a comprehensive comparison of ion-intensity based label-free proteomics and two label-based approaches using isobaric tags incorporated at the peptide and protein levels, respectively. As model system for our quantitative analysis we used the three hepatoma cell lines HepG2, Hep3B and SK-Hep-1. Four biological replicates of each cell line were quantitatively analyzed using an RPLC–MS/MS setup. Each quantification experiment was performed twice to determine technical variances of the different quantification techniques. We were able to show that the label-free approach by far outperforms both TMT methods regarding proteome coverage, as up to threefold more proteins were reproducibly identified in replicate measurements. Furthermore, we could demonstrate that all three methods show comparable reproducibility concerning protein quantification, but slightly differ in terms of accuracy. Here, label-free was found to be less accurate than both TMT approaches. It was also observed that the introduction of TMT labels at the protein level reduces the effect of underestimation of protein ratios, which is commonly monitored in case of TMT peptide labeling. Previously reported differences in protein expression between the particular cell lines were furthermore reproduced, which confirms the applicability of each investigated quantification method to study proteomic differences in such biological systems. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Characterisation of the variation of mouse brain proteome by two-dimensional electrophoresis

Neuroproteomics is aimed to study the molecular organisation of the nervous system at the protein level. Two-dimensional electrophoresis is the most frequently used technique in quantitative proteomics. The aim of this study was to assess the experimental and biological variations on this proteomic platform using mouse brain tissue. Mice are the most generally used lab animals for modelling human disease or investigating the effect of a drug-candidate or a treatment. Experimental design plays a crucial role in quantitative proteomics, hence understanding and minimizing the variables is essential. Our results indicate that the technical variance dominantly contributes to the total variance in mouse brain and the genetic background has a negligible effect on the total variation. The results also characterise the anticipated variation using mouse brain for proteomic study hence they should be useful for future experimental design in other proteomics laboratories.     

Systematic comparison of label-free, metabolic labeling, and isobaric chemical labeling for quantitative proteomics on LTQ Orbitrap Velos

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study.     

Global Protein Differential Expression Profiling of Cerebrospinal Fluid Samples Pooled from Chinese Sporadic CJD and non-CJD Patients

The shotgun proteomic based on the approach of tandem mass tag (TMT) labeling has received increasing attention for neuroproteomics analysis and becomes an effective tool for the identification and quantification of a large number of proteins for the purpose of revealing key proteins involved in the neuronal dysfunction and an inflammatory response associated with neurodegenerative disorders. To assess the potential expression difference of proteins in cerebrospinal fluids (CSF) between Creutzfeldt–Jakob disease (CJD) and non-CJD patients, the pooled CSF samples from 39 Chinese probable sporadic CJD (sCJD) patients and from 52 non-CJD cases were comparably analyzed with the methodology of TMT labeling and RP-RP-UPLC-MS/MS. Totally, 437 possible proteins were identified in the tested CSF specimen, among them, 49 proteins with 95 % confidence interval. Differential assays showed among those 49 CSF proteins, 12 were upregulated and 13 were downregulated significantly in the sCJD compared to non-CJD. The most affected pathway of the differential expression proteins in CSF of sCJD was complement and coagulation cascade. Western blots for six selected changed proteins in the pooled CSF samples revealed the similar altering profiles in the groups of sCJD and non-CJD as proteomics. Furthermore, CSF samples from 24 CJD patients and 24 non-CJD patients were randomly selected and subjected individually into the Western blots of an increased protein (phosphoglycerate mutase 1) and a decreased one (alpha-1-antichymotrysin), which also confirmed the altering tendency of these identified proteins. Those data indicate that proteomic assay of CSF is a powerful technique not only for selection of the potential biomarkers for the development of diagnostic tool of CJD but also for supplement of useful scientific clues for understanding the CSF homeostasis during the pathogenesis of prion diseases.     

Pharmacoproteomic investigation into antidepressant response in two mouse inbred strains

In this study, we present a pharmacoproteomic investigation of response to antidepressants two inbred strains. Our aim was to uncover molecular mechanisms underlying antidepressant action and identify new biomarkers to determine therapeutic response to two antidepressants with proven efficacy in the treatment of depression but divergent mechanisms of action. Mice were treated with the pro-noradrenergic drug nortriptyline, the pro-serotonergic drug escitalopram or saline. Quantitative proteomic analyses were undertaken on hippocampal tissue from a study design that used two inbred mouse strains, two depressogenic protocols and a control condition, (maternal separation, chronic mild stress, control), two antidepressant drugs and two dosing protocols. The proteomic analysis was aimed at the identification of specific drug-response markers. Complementary approaches, 2DE and isobaric tandem mass tagging (TMT), were applied to the selected experimental groups. To investigate the relationship between proteomic profiles, depressogenic protocols and drug response, 2DE and TMT data sets were analysed using multivariate methods. The results highlighted significant strain- and stress-related differences across both 2DE and TMT data sets and identified the three gene products involved in serotonergic (PXBD5, YHWAB, SLC25A4) and one in noradrenergic antidepressant action (PXBD6).     

Perfluorooctanoic acid for shotgun proteomics

Here, we describe the novel use of a volatile surfactant, perfluorooctanoic acid (PFOA), for shotgun proteomics. PFOA was found to solubilize membrane proteins as effectively as sodium dodecyl sulfate (SDS). PFOA concentrations up to 0.5% (w/v) did not significantly inhibit trypsin activity. The unique features of PFOA allowed us to develop a single-tube shotgun proteomics method that used all volatile chemicals that could easily be removed by evaporation prior to mass spectrometry analysis. The experimental procedures involved: 1) extraction of proteins in 2% PFOA; 2) reduction of cystine residues with triethyl phosphine and their S-alkylation with iodoethanol; 3) trypsin digestion of proteins in 0.5% PFOA; 4) removal of PFOA by evaporation; and 5) LC-MS/MS analysis of the resulting peptides. The general applicability of the method was demonstrated with the membrane preparation of photoreceptor outer segments. We identified 75 proteins from 1 μg of the tryptic peptides in a single, 1-hour, LC-MS/MS run. About 67% of the proteins identified were classified as membrane proteins. We also demonstrate that a proteolytic (18)O labeling procedure can be incorporated after the PFOA removal step for quantitative proteomic experiments. The present method does not require sample clean-up devices such as solid-phase extractions and membrane filters, so no proteins/peptides are lost in any experimental steps. Thus, this single-tube shotgun proteomics method overcomes the major drawbacks of surfactant use in proteomic experiments.     

Mixed-model of ANOVA for measurement reproducibility in proteomics

This work is a statistical analysis of reproducibility of a MALDI-TOF mass spectrometry experiment. Its aim is to evaluate measurement variability and compare peak intensities from two types of MALDI-TOF platforms. We compared and commented on the abilities of Principal Component Analysis and mixed-model analysis of variance to evaluate the biological variability and the technical variability of peak intensities in different patients. The properties and hypotheses of both methods are summarized and applied to spectra from plasma of patients with Hodgkin lymphoma. Principal Component Analysis checks rapidly the balance between the two variabilities; however, a mixed-model analysis of variance is necessary to quantify the biological and technical components of the experimental variance as well as their interactions and to split the total variance into between-subjects and within-subject components. The latter method helped to assess the reproducibility of measurements from two MALDI-TOF platforms and to decompose the technical variability according to the experimental design.     

Reversed-phase chromatography with multiple fraction concatenation strategy for proteome profiling of human MCF10A cells

In this study, we evaluated a concatenated low pH (pH 3) and high pH (pH 10) reversed-phase liquid chromatography strategy as a first dimension for two-dimensional liquid chromatography tandem mass spectrometry ("shotgun") proteomic analysis of trypsin-digested human MCF10A cell sample. Compared with the more traditional strong cation exchange method, the use of concatenated high pH reversed-phase liquid chromatography as a first-dimension fractionation strategy resulted in 1.8- and 1.6-fold increases in the number of peptide and protein identifications (with two or more unique peptides), respectively. In addition to broader identifications, advantages of the concatenated high pH fractionation approach include improved protein sequence coverage, simplified sample processing, and reduced sample losses. The results demonstrate that the concatenated high pH reversed-phased strategy is an attractive alternative to strong cation exchange for two-dimensional shotgun proteomic analysis.     

Optimal allocation of replicates for measurement evaluation studies

Optimal experimental design is important for the efficient use of modern highthroughput technologies such as microarrays and proteomics. Multiple factors including the reliability of measurement system, which itself must be estimated from prior experimental work, could influence design decisions. In this study, we describe how the optimal number of replicate measures （technical replicates） for each biological sample （biological replicate） can be determined. Different allocations of biological and technical replicates were evaluated by minimizing the variance of the ratio of technical variance （measurement error） to the total variance （sum of sampling error and measurement error）. We demonstrate that if the number of biological replicates and the number of technical replicates per biological sample are variable, while the total number of available measures is fixed, then the optimal allocation of replicates for measurement evaluation experiments requires two technical replicates for each biological replicate. Therefore, it is recommended to use two technical replicates for each biological replicate if the goal is to evaluate the reproducibility of measurements.     

Application of quantitative proteomic analysis using tandem mass tags for discovery and identification of novel biomarkers in periodontal disease

Periodontal disease is a bacterial infection that destroys the gingiva and surrounding tissues of the oral cavity. Gingival crevicular fluid (GCF) is extracted from the gingival sulcus and pocket. Analysis of biochemical markers in GCF, which predict the progression of periodontal disease, may facilitate disease diagnosis. However, no useful GCF biochemical markers with high sensitivity for detecting periodontal disease have been identified. Thus, the search for biochemical markers of periodontal disease is of continued interest in experimental and clinical periodontal disease research. Using tandem mass tag (TMT) labeling, we analyzed GCF samples from healthy subjects and patients with periodontal disease, and identified a total of 619 GCF proteins based on proteomic analysis. Of these, we focused on two proteins, matrix metalloproteinase (MMP)‐9 and neutrophil gelatinase‐associated lipocalin (LCN2), which are involved in the progression of periodontal disease. Western blot analysis revealed that the levels of MMP‐9 and LCN2 were significantly higher in patients with periodontal disease than in healthy subjects. In addition, ELISA also detected significantly higher levels of LCN2 in patients with periodontal disease than in healthy subjects. Thus, LC‐MS/MS analyses of GCF using TMT labeling led to the identification of LCN2, which may be a promising GCF biomarker for the detection of periodontal disease.     

Quantitative analysis of human cerebrospinal fluid proteins using a combination of cysteine tagging and amine-reactive isobaric labeling

Highly complex and dynamic protein mixtures are hardly comprehensively resolved by direct shotgun proteomic analysis. As many proteins of biological interest are of low abundance, numerous analytical methodologies have been developed to reduce sample complexity and go deeper into proteomes. The present work describes an analytical strategy to perform cysteinyl-peptide subset enrichment and relative quantification through successive cysteine and amine-isobaric tagging. A cysteine-reactive covalent capture tag (C3T) allowed derivatization of cysteines and specific isolation on a covalent capture (CC) resin. The 6-plex amine-reactive tandem mass tags (TMT) served for relative quantification of the targeted peptides. The strategy was first evaluated on a model protein mixture with increasing concentrations to assess the specificity of the enrichment and the quantitative performances of the workflow. It was then applied to human cerebrospinal fluid (CSF) from post-mortem and ante-mortem samples. These studies confirmed the specificity of the C3T and the CC technique to cysteine-containing peptides. The model protein mixture analysis showed high precision and accuracy of the quantification with coefficients of variation and mean absolute errors of less than 10% on average. The CSF experiments demonstrated the potential of the strategy to study complex biological samples and identify differential brain-related proteins. In addition, the quantification data were highly correlated with a classical TMT experiment (i.e., without C3T cysteine-tagging and enrichment steps). Altogether, these results legitimate the use of this quantitative C3T strategy to enrich and relatively quantify cysteine-containing peptides in complex mixtures.     

An economic and robust TMT labeling approach for high throughput proteomic and metaproteomic analysis

Multiplexed quantitative proteomics using tandem mass tag (TMT) is increasingly used in –omic study of complex samples. While TMT-based proteomics has the advantages of the higher quantitative accuracy, fewer missing values, and reduced instrument analysis time, it is limited by the additional reagent cost. In addition, current TMT labeling workflows involve repeated small volume pipetting of reagents in volatile solvents, which may increase the sample-to-sample variations and is not readily suitable for high throughput applications. In this study, we demonstrated that the TMT labeling procedures could be streamlined by using pre-aliquoted dry TMT reagents in a 96 well plate or 12-tube strip. As little as 50 μg dry TMT per channel was used to label 6–12 μg peptides, yielding high TMT labeling efficiency (∼99%) in both microbiome and mammalian cell line samples. We applied this workflow to analyze 97 samples in a study to evaluate whether ice recrystallization inhibitors improve the cultivability and activity of frozen microbiota. The results demonstrated tight sample clustering corresponding to groups and consistent microbiome responses to prebiotic treatments. This study supports the use of TMT reagents that are pre-aliquoted, dried, and stored for robust quantitative proteomics and metaproteomics in high throughput applications.     

Overcoming technical variation and biological variation in quantitative proteomics

Quantitative proteomics investigates physiology at the molecular level by measuring relative differences in protein expression between samples under different experimental conditions. A major obstacle to reliably determining quantitative changes in protein expression is to overcome error imposed by technical variation and biological variation. In drug discovery and development the issue of biological variation often rises in concordance with the developmental stage of research, spanning from in vitro assays to clinical trials. In this paper we present case studies to raise awareness to the issues of technical variation and biological variation and the impact this places on applying quantitative proteomics. We defined the degree of technical variation from the process of two-dimensional electrophoresis as 20-30% coefficient of variation. On the other hand, biological variation observed experiment-to-experiment showed a broader degree of variation depending upon the sample type. This was demonstrated with case studies where variation was monitored across experiments with bacteria, established cell lines, primary cultures, and with drug treated human subjects. We discuss technical variation and biological variation as key factors to consider during experimental design, and offer insight into preparing experiments that overcome this challenge to provide statistically significant outcomes for conducting quantitative proteomic research.     

Protein identification and quantification from riverbank grape,Vitis riparia: Comparing SDS‐PAGE and FASP‐GPF techniques for shotgun proteomic analysis

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in‐gel digestion and in‐solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS‐PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP‐GPF was used. FASP‐GPF is more reproducible, less expensive and a better method than SDS‐PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 ( http://proteomecentral.proteomexchange.org/dataset/PXD001399 ).     

Critical comparison of sample preparation strategies for shotgun proteomic analysis of formalin-fixed,paraffin-embedded samples: insights from liver tissue

Background

The growing field of formalin-fixed paraffin-embedded (FFPE) tissue proteomics holds promise for improving translational research. Direct tissue trypsinization (DT) and protein extraction followed by in solution digestion (ISD) or filter-aided sample preparation (FASP) are the most common workflows for shotgun analysis of FFPE samples, but a critical comparison of the different methods is currently lacking.

Experimental design

DT, FASP and ISD workflows were compared by subjecting to the same label-free quantitative approach three independent technical replicates of each method applied to FFPE liver tissue. Data were evaluated in terms of method reproducibility and protein/peptide distribution according to localization, MW, pI and hydrophobicity.

Results

DT showed lower reproducibility, good preservation of high-MW proteins, a general bias towards hydrophilic and acidic proteins, much lower keratin contamination, as well as higher abundance of non-tryptic peptides. Conversely, FASP and ISD proteomes were depleted in high-MW proteins and enriched in hydrophobic and membrane proteins; FASP provided higher identification yields, while ISD exhibited higher reproducibility.

Conclusions

These results highlight that diverse sample preparation strategies provide significantly different proteomic information, and present typical biases that should be taken into account when dealing with FFPE samples. When a sufficient amount of tissue is available, the complementary use of different methods is suggested to increase proteome coverage and depth.     

The influence of sample preparation and replicate analyses on HeLa Cell phosphoproteome coverage

Ongoing optimization of proteomic methodologies seeks to improve both the coverage and confidence of protein identifications. The optimization of sample preparation, inclusion of technical replicates (repeated instrumental analysis of the same sample), and biological replicates (multiple individual samples) are crucial in proteomic studies to avoid the pitfalls associated with single point analysis and under-sampling. Phosphopeptides were isolated from HeLa cells and analyzed by nano-reversed phase liquid chromatography electrospray ionization tandem mass spectrometry (nano-RP-LC-MS/MS). We observed that a detergent-based protein extraction approach, followed with additional steps for nucleic acid removal, provided a simple alternative to the broadly used Trizol extraction. The evaluation of four technical replicates demonstrated measurement reproducibility with low percent variance in peptide responses at approximately 3%, where additional peptide identifications were made with each added technical replicate. The inclusion of six technical replicates for moderately complex protein extracts (approximately 4000 uniquely identified peptides per data set) affords the optimal collection of peptide information.     

Sample size determination in clinical proteomic profiling experiments using mass spectrometry for class comparison

Mass spectrometric profiling approaches such as MALDI‐TOF and SELDI‐TOF are increasingly being used in disease marker discovery, particularly in the lower molecular weight proteome. However, little consideration has been given to the issue of sample size in experimental design. The aim of this study was to develop a protocol for the use of sample size calculations in proteomic profiling studies using MS. These sample size calculations can be based on a simple linear mixed model which allows the inclusion of estimates of biological and technical variation inherent in the experiment. The use of a pilot experiment to estimate these components of variance is investigated and is shown to work well when compared with larger studies. Examination of data from a number of studies using different sample types and different chromatographic surfaces shows the need for sample‐ and preparation‐specific sample size calculations.     

厌氧产氢颗粒污泥蛋白质组分析样品的高效制备方法

【背景】厌氧产氢颗粒污泥比絮状产氢污泥具有更高的生物量、沉降性与反应效率,对颗粒污泥进行蛋白质组学研究,有助于揭示其代谢调控的分子机制,从而对厌氧代谢过程进行优化调控。目前关于产氢颗粒污泥蛋白质组分析样品制备方法的研究尚未见文献报道。革兰氏阳性菌Ethanoligenens harbinense YUAN-3是自凝集产氢发酵细菌,在间歇和连续流培养中可形成自聚集的厌氧颗粒,由于其全基因组信息清楚,可作为模式研究材料对制备方法进行评估。【目的】针对厌氧产氢颗粒污泥的蛋白质组学研究,比较不同蛋白质提取方法进行优化。【方法】分别利用液氮研磨、超声破碎、匀浆破碎对产氢颗粒污泥破碎,比较这3种方法对总蛋白提取量的影响;通过双向电泳比较三氯乙酸(Trichloroacetic acid,TCA)-丙酮沉淀法与苯酚抽提法对总蛋白提取效果的影响;对总蛋白样品分别进行同位素标记相对和绝对定量标记(Isobarictagsforrelativeandabsolutequantification,i TRAQ)、串联质谱标签(Tandemmasstag,TMT)标记以及质谱鉴定。【结果】液氮研磨、超声破碎、匀浆破碎3种破碎方法下总蛋白的提取量分别是对照样品的2.0、3.9与5.2倍。与TCA-丙酮沉淀法相比,苯酚抽提法总蛋白样品在双向电泳图谱上的蛋白质点明显增多,分布均匀,同时其在碱性蛋白端与小分子量蛋白端的蛋白质点也明显增多。质谱分析发现,iTRAQ标记样品与TMT标记样品中分别鉴定到1797个与1644个蛋白,在分子量、等电点、亚细胞定位的各个分布范围内,这些蛋白良好地覆盖了E.harbinenseYUAN-3中各个类型的蛋白。【结论】匀浆破碎与苯酚抽提法联用的总蛋白制备方法更适用于厌氧产氢颗粒污泥,该方法有利于后续的蛋白质双向电泳和定量蛋白质组质谱分析,可作为产氢颗粒污泥以及革兰氏阳性菌总蛋白制备的方法参考。     

Statistical analysis of the experimental variation in the proteomic characterization of human plasma by two-dimensional difference gel electrophoresis

The complexity of human plasma presents a number of challenges to the efficient and reproducible proteomic analysis of differential expression in response to disease. Before individual variation and disease-specific protein biomarkers can be identified from human plasma, the experimental variability inherent in the protein separation and detection techniques must be quantified. We report on the variation found in two-dimensional difference gel electrophoresis (2-D DIGE) analysis of human plasma. Eight aliquots of a human plasma sample were subjected to top-6 highest abundant protein depletion and were subsequently analyzed in triplicate for a total of 24 DIGE samples on 12 gels. Spot-wise standard deviation estimates indicated that fold changes greater than 2 can be detected with a manageable number of replicates in simple ANOVA experiments with human plasma. Mixed-effects statistical modeling quantified the effect of the dyes, and segregated the spot-wise variance into components of sample preparation, gel-to-gel differences, and random error. The gel-to-gel component was found to be the largest source of variation, followed by the sample preparation step. An improved protocol for the depletion of the top-6 high-abundance proteins is suggested, which, along with the use of statistical modeling and future improvements in gel quality and image processing, can further reduce the variation and increase the efficiency of 2-D DIGE proteomic analysis of human plasma.