Systematic discovery of ectopic pregnancy serum biomarkers using 3-D protein profiling coupled with label-free quantitation

Ectopic pregnancy (EP) and normal intrauterine pregnancy (IUP) serum proteomes were quantitatively compared to systematically identify candidate biomarkers. A 3-D biomarker discovery strategy consisting of abundant protein immunodepletion, SDS gels, LC-MS/MS, and label-free quantitation of MS signal intensities identified 70 candidate biomarkers with differences between groups greater than 2.5-fold. Further statistical analyses of peptide quantities were used to select the most promising 12 biomarkers for further study, which included known EP biomarkers, novel EP biomarkers (ADAM12 and ISM2), and five specific isoforms of the pregnancy specific beta-1-glycoprotein family. Technical replicates showed good reproducibility and protein intensities from the label-free discovery analysis compared favorably with reported abundance levels of several known reference serum proteins over at least 3 orders of magnitude. Similarly, relative abundances of candidate biomarkers from the label-free discovery analysis were consistent with relative abundances from pilot validation assays performed for five of the 12 most promising biomarkers using label-free multiple reaction monitoring of both the patient serum pools used for discovery and the individual samples that constituted these pools. These results demonstrate robust, reproducible, in-depth 3-D serum proteome discovery, and subsequent pilot-scale validation studies can be achieved readily using label-free quantitation strategies.     

A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQ-FT MS mass spectrometer (or other high-resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed "cross-assignment", is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC-MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of Escherichia coli samples spiked with known amounts of non-E. coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC-MS data sets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication.     

A general strategy for studying multisite protein phosphorylation using label-free selected reaction monitoring mass spectrometry

The majority of eukaryotic proteins are phosphorylated in vivo, and phosphorylation may be the most common regulatory posttranslational modification. Many proteins are phosphorylated at numerous sites, often by multiple kinases, which may have different functional consequences. Understanding biological functions of phosphorylation events requires methods to detect and quantify individual sites within a substrate. Here we outline a general strategy that addresses this need and relies on the high sensitivity and specificity of selected reaction monitoring (SRM) mass spectrometry, making it potentially useful for studying in vivo phosphorylation without the need to isolate target proteins. Our approach uses label-free quantification for simplicity and general applicability, although it is equally compatible with stable isotope quantification methods. We demonstrate that label-free SRM-based quantification is comparable to conventional assays for measuring the kinetics of phosphatase and kinase reactions in vitro. We also demonstrate the capability of this method to simultaneously measure relative rates of phosphorylation and dephosphorylation of substrate mixtures, including individual sites on intact protein substrates in the context of a whole cell extract. This strategy should be particularly useful for characterizing the physiological substrate specificity of kinases and phosphatases and can be applied to studies of other protein modifications as well.     

Combination of peptide OFFGEL fractionation and label-free quantitation facilitated proteomics profiling of extraocular muscle

Several label-free quantitation strategies have been introduced that obliterate the need for expensive isotopically labeled molecules. However label-free approaches have considerably higher demands in respect of repeatability of sample preparation and fractionation than multiplexing isotope labeling-based strategies. OFFGEL fractionation promises the necessary separation efficiency and repeatability. To test this platform, 12-fraction peptide OFFGEL electrophoresis and online reversed-phase LC connected to a quadrupole TOF mass spectrometer were used to determine differences of the physiological, pathological and biochemical distinct extraocular muscle allotype in comparison to hind-limb muscle. Close to 70% of the peptides separated by OFFGEL electrophoresis were detected only in a single fraction. To determine the separation repeatability of four samples, we compared the ion volumes of multiple peptides deriving from the thick filament-associated protein titin over several fractions and determined a coefficient of variation below 20%. Of the 474 proteins identified, 61 proteins were differently expressed between the two muscle allotypes and were involved in metabolism, muscle contraction, stress response, or gene expression. Several expression differences were validated using immunohistochemistry and Western blot analysis. We therefore consider peptide OFFGEL fractionation an effective and efficient addition to our label-free quantitative proteomics workflow.     

A novel targeted proteomics method for identification and relative quantitation of difference in nitration degree of OGDH between healthy and diabetic mouse

For analysis of nitration modification of α oxoglutarate dehydrogenase (α‐OGDH) induced by diabetes, a targeted proteomics strategy was developed through the use of Skyline. All peptides containing Y and W of the target proteins were nitrated in silico and output to produce parallel reaction monitoring (PRM) or SRM method for nitration analysis. A nitrated casein mixture was used as standard protein to assess the feasibility of this method. The results demonstrated the availability of this strategy for nitration identification, and subsequently this method was used to analyze the nitration of α‐OGDH from myocardial tissue extracts of diabetic mouse. The PRM method was primarily generated by Skyline for identification of the actual nitrated peptides from all possible nitrated peptides of α‐OGDH due to the complexity of α‐OGDH. The PRM‐based data were analyzed by SEQUEST, and transitions of the identified nitrated peptides were used to develop an SRM method for relative quantitation of nitration degree. The nitration degree of α‐OGDH for diabetic mouse is higher than that for control mouse, indicating that α‐OGDH of the diabetic mouse suffered from more intense oxidative damage. We believe that this approach for obtaining information regarding nitration will facilitate the study of other PTMs in complex mixtures.     

Label-free quantitation, an extension to 2DB

Determining the differential expression of proteins under different conditions is of major importance in proteomics. Since mass spectrometry-based proteomics is often used to quantify proteins, several labelling strategies have been developed. While these are generally more precise than label-free quantitation approaches, they imply specifically designed experiments which also require knowledge about peptides that are expected to be measured and need to be modified. We recently designed the 2DB database which aids storage, analysis, and publication of data from mass spectrometric experiments to identify proteins. This database can aid identifying peptides which can be used for quantitation. Here an extension to the database application, named MSMAG, is presented which allows for more detailed analysis of the distribution of peptides and their associated proteins over the fractions of an experiment. Furthermore, given several biological samples in the database, label-free quantitation can be performed. Thus, interesting proteins, which may warrant further investigation, can be identified en passant while performing high-throughput proteomics studies.     

Less label, more free: approaches in label-free quantitative mass spectrometry

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation.     

定量蛋白质组学无标记定量方法的研究进展

依靠质谱技术的蛋白质组学快速发展,寻求速度快、重复性好以及准确度高的定量方法是该领域的一项艰巨任务,定量蛋白质组学分支领域应运而生．其中,无标记定量方法以其样品制备简单、耗材费用低廉以及结果数据分析便捷等优点渐露锋芒．无标记定量方法通常分为信号强度法和谱图计数法两大类．本文在这两种无标记定量方法计算原理的基础上,针对各种常用的无标记定量方法及最新进展做一个较为全面的介绍,并将详细讨论两类方法的异同点,以及目前蛋白质组学中无标记定量方法所面临的主要挑战,希望能为这一领域的研究人员在选择无标记定量方法时提供一个合理的参考．     

Signal transduction profiling using label-free biosensors

Knowledge of the way in which ligands modulate cellular responses via membrane-associated receptors is of central importance to drug discovery and elucidation of signal transduction pathways. Biophysical label-free methods can be used to characterize ligand and drug candidate interactions with neurotransmitters, cytokine receptors, tyrosine kinase receptors, ligand- and voltage-gated ion channels, G protein-coupled receptors (GPCRs), and antibody receptors. Ligand or drug candidate screening typically involves selecting ligands or subsets of a compound library for analysis, transfecting a cell line overexpressing the target receptor, then monitoring one or two downstream reporters of receptor activation such as Ca²⁺, cAMP, inositol phosphate, etc. Inevitably, this process leads to a data set predicated by these selections. In contrast, label-free screening techniques allow a holistic, pathway-independent screening strategy to provide a functional or phenotypic readout of receptor activation. Detection techniques that measure changes in cell conductance, viscoelastic properties, refractive index, and other optical parameters that are modulated as a consequence of receptor activation are reviewed.     

A simple peak detection and label-free quantitation algorithm for chromatography-mass spectrometry

Background

Label-free quantitation of mass spectrometric data is one of the simplest and least expensive methods for differential expression profiling of proteins and metabolites. The need for high accuracy and performance computational label-free quantitation methods is still high in the biomarker and drug discovery research field. However, recent most advanced types of LC-MS generate huge amounts of analytical data with high scan speed, high accuracy and resolution, which is often impossible to interpret manually. Moreover, there are still issues to be improved for recent label-free methods, such as how to reduce false positive/negatives of the candidate peaks, how to expand scalability and how to enhance and automate data processing. AB3D (A simple label-free quantitation algorithm for Biomarker Discovery in Diagnostics and Drug discovery using LC-MS) has addressed these issues and has the capability to perform label-free quantitation using MS1 for proteomics study.

Results

We developed an algorithm called AB3D, a label free peak detection and quantitative algorithm using MS1 spectral data. To test our algorithm, practical applications of AB3D for LC-MS data sets were evaluated using 3 datasets. Comparisons were then carried out between widely used software tools such as MZmine 2, MSight, SuperHirn, OpenMS and our algorithm AB3D, using the same LC-MS datasets. All quantitative results were confirmed manually, and we found that AB3D could properly identify and quantify known peptides with fewer false positives and false negatives compared to four other existing software tools using either the standard peptide mixture or the real complex biological samples of Bartonella quintana (strain JK31). Moreover, AB3D showed the best reliability by comparing the variability between two technical replicates using a complex peptide mixture of HeLa and BSA samples. For performance, the AB3D algorithm is about 1.2 - 15 times faster than the four other existing software tools.

Conclusions

AB3D is a simple and fast algorithm for label-free quantitation using MS1 mass spectrometry data for large scale LC-MS data analysis with higher true positive and reasonable false positive rates. Furthermore, AB3D demonstrated the best reproducibility and is about 1.2- 15 times faster than those of existing 4 software tools.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0376-0) contains supplementary material, which is available to authorized users.     

A multiplexed homogeneous fluorescence-based assay for protein kinase activity in cell lysates

New methods to quantify protein kinase activities directly from complex cellular mixtures are critical for understanding biological regulatory pathways. Herein, a fluorescence-based chemosensor strategy for the direct measurement of kinase activities in crude mammalian cell lysates is described. We first designed a new fluorescent peptide reporter substrate for each target kinase. These kinase chemosensors were readily phosphorylated by recombinant target enzyme and underwent a several-fold fluorescence increase upon phosphorylation. Then, using unfractionated cell lysates, a homogeneous kinase assay was developed that was reproducible, linear and highly preferential for monitoring changes in cellular activity of the target kinase. The general protocol was developed for the kinase Akt and then easily extended to measure protein kinase A (PKA) and mitogen-activated protein kinase-associated protein kinase 2 (MK2) activities. This assay platform is immediately useful for studying protein kinase signaling in crude cellular extracts.     

High-content proteomics: fluorescence multiplexing using an integrated,high-sensitivity,multiwavelength charge-coupled device imaging system

The detection of proteins in 2-D gels and their subsequent identification by MS is still the "gold standard" in proteomics. Fluorescent detection has increasingly replaced colorimetric and radiometric detection on gels and blots. The reasons for this are multiple and varied and include higher sensitivity, better quantitation, increased dynamic range, speed, safety and ease of use. Unlike other methods, fluorescent protein detection is also typically very consistent in response from protein to protein and in many cases is compatible with MS methods for protein identification. The superior sensitivity and benefits achieved by fluorescent techniques have spurred the development of instrumentation capable of delivering precise, sensitive, high-resolution image acquisition over a wide variety of excitation and emission wavelengths. This report focuses on applications using the highly sensitive, charge-coupled device based ProXPRESS multilabel imager, readily configurable for image acquisition over a wide variety of wavelengths (380-700 nm and ultraviolet (UV)) using xenon lamp or UV excitation. The ability to simultaneously detect enzyme activities or protein modifications with different color fluorescent probes in addition to total protein amounts (multiplexing) allows the further mining of proteomic data content from a single set of protein samples. To this end, the development of instrumentation that enables a multiplexing strategy will become central to in-depth proteomic studies. The ProXPRESS maximizes the efficiency of experimental strategies that require flexibility and multicolor fluorescence detection.     

Phosphoproteomics strategies for the functional analysis of signal transduction

Protein phosphorylation is a key regulatory mechanism of cellular signalling processes. The analysis of phosphorylated proteins and the characterisation of phosphorylation sites under different biological conditions are some of the most challenging tasks in current proteomics research. Reduction of the sample complexity is one major step for the analysis of low-abundance kinase substrates, which can be achieved by various subcellular fractionation techniques. One strategy is the enrichment of phosphorylated proteins or peptides by immunoprecipitation or chromatography, e.g. immobilised metal affinity chromatography, prior to analysis. 2-DE gels are powerful tools for the analysis of phosphoproteins when combined with new multiplexing techniques like DIGE, phosphospecific stains, autoradiography or immunoblotting. In addition, several gel-free methods combining chromatography with highly sensitive MS have been successfully applied for the analysis of complex phosphoproteomes. Recently developed approaches like KESTREL or 'chemical genetics' and also protein microarrays offer new possibilities for the identification of specific kinase targets. This review summarises various strategies for the analyses of phosphoproteins with a special focus on the identification of novel kinase substrates.     

Automation of PRM‐dependent D3‐Leu tracer enrichment in HDL to study the metabolism of apoA‐I,LCAT and other apolipoproteins

We developed an automated quantification workflow for PRM‐enabled detection of D3‐Leu labeled apoA‐I in high‐density lipoprotein (HDL) isolated from humans. Subjects received a bolus injection of D3‐Leu and blood was drawn at eight time points over three days. HDL was isolated and separated into six size fractions for subsequent proteolysis and PRM analysis for the detection of D3‐Leu signal from ～0.03 to 0.6% enrichment. We implemented an intensity‐based quantification approach that takes advantage of high‐resolution/accurate mass PRM scans to identify the D3‐Leu 2HM3 ion from non‐specific peaks. Our workflow includes five modules for extracting the targeted PRM peak intensities (XPIs): Peak centroiding, noise removal, fragment ion matching using Δm/z windows, nine intensity quantification options, and validation and visualization outputs. We optimized the XPI workflow using in vitro synthesized and clinical samples of D0/D3‐Leu labeled apoA‐I. Three subjects’ apoA‐I enrichment curves in six HDL size fractions, and LCAT, apoA‐II and apoE from two size fractions were generated within a few hours. Our PRM strategy and automated quantification workflow will expedite the turnaround of HDL apoA‐I metabolism data in clinical studies that aim to understand and treat the mechanisms behind dyslipidemia.     

Batch effects correction improves the sensitivity of significance tests in spectral counting-based comparative discovery proteomics

Shotgun proteomics has become the standard proteomics technique for the large-scale measurement of protein abundances in biological samples. Despite quantitative proteomics has been usually performed using label-based approaches, label-free quantitation offers advantages related to the avoidance of labeling steps, no limitation in the number of samples to be compared, and the gain in protein detection sensitivity. However, since samples are analyzed separately, experimental design becomes critical. The exploration of spectral counting quantitation based on LC-MS presented here gathers experimental evidence of the influence of batch effects on comparative proteomics. The batch effects shown with spiking experiments clearly interfere with the biological signal. In order to minimize the interferences from batch effects, a statistical correction is proposed and implemented. Our results show that batch effects can be attenuated statistically when proper experimental design is used. Furthermore, the batch effect correction implemented leads to a substantial increase in the sensitivity of statistical tests. Finally, the applicability of our batch effects correction is shown on two different biomarker discovery projects involving cancer secretomes. We think that our findings will allow designing and executing better comparative proteomics projects and will help to avoid reaching false conclusions in the field of proteomics biomarker discovery.     

Progress of new label-free techniques for biosensors: a review

The detection techniques used in biosensors can be broadly classified into label-based and label-free. Label-based detection relies on the specific properties of labels for detecting a particular target. In contrast, label-free detection is suitable for the target molecules that are not labeled or the screening of analytes which are not easy to tag. Also, more types of label-free biosensors have emerged with developments in biotechnology. The latest developed techniques in label-free biosensors, such as field-effect transistors-based biosensors including carbon nanotube field-effect transistor biosensors, graphene field-effect transistor biosensors and silicon nanowire field-effect transistor biosensors, magnetoelastic biosensors, optical-based biosensors, surface stress-based biosensors and other type of biosensors based on the nanotechnology are discussed. The sensing principles, configurations, sensing performance, applications, advantages and restriction of different label-free based biosensors are considered and discussed in this review. Most concepts included in this survey could certainly be applied to the development of this kind of biosensor in the future.     

Improvement of phosphoproteome analyses using FAIMS and decision tree fragmentation. application to the insulin signaling pathway in Drosophila melanogaster S2 cells

This report examines the analytical benefits of high-field asymmetric waveform ion mobility spectrometry (FAIMS) coupled to liquid chromatography mass spectrometry (LC-MS) for phosphoproteomics analyses. The ability of FAIMS to separate multiply charged peptide ions from chemical interferences confers a unique advantage in phosphoproteomics by enhancing the detection of low abundance phosphopeptides. LC-FAIMS-MS experiments performed on TiO(2)-enriched tryptic digests from Drosophila melanogaster provided a 50% increase in phosphopeptide identification compared to conventional LC-MS analysis. Also, FAIMS can be used to select different population of multiply charged phosphopeptide ions prior to their activation with either collision activated dissociation (CAD) or electron transfer dissociation (ETD). Importantly, FAIMS enabled the resolution of coeluting phosphoisomers of different abundances to facilitate their unambiguous identification using conventional database search engines. The benefits of FAIMS in large-scale phosphoproteomics of D. melanogaster are further investigated using label-free quantitation to identify differentially regulated phosphoproteins in response to insulin stimulation.     

无化学修饰的小分子药物靶蛋白鉴定技术及其应用进展

鉴定小分子药物的靶蛋白对于理解药物的作用机理以及药物副作用至关重要。传统方法需要对药物进行化学修饰共价交联,可能会导致药物活性的改变。目前已经发展多种无需化学修饰便可以对药物靶蛋白鉴定的方法,包括药物亲和力反应靶标稳定性技术(Drug affinity responsive target stability,DARTS)、蛋白质氧化速率稳定性技术(Stabilityofproteinsfromratesofoxidation,SPROX)、细胞热移位分析技术(Cellularthermalshiftassay, CETSA)和热蛋白组分析技术(Thermalproteomeprofiling, TPP)等。文中将介绍这些技术的原理、应用以及各自的优点和局限性,另外也介绍了这些技术最新的优化方案。     

Use of DNA ladders for reproducible protein fractionation by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) for quantitative proteomics

In proteomics, one-dimensional (1D) sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) is widely used for protein fractionation prior to mass spectrometric analysis to enhance the dynamic range of analysis and to improve the identification of low-abundance proteins. Such protein prefractionation works well for quantitation strategies if the proteins are labeled prior to separation. However, because of the poor reproducibility of cutting gel slices, especially when small amounts of samples are analyzed, its application in label-free and peptide-labeling quantitative proteomics methods has been greatly limited. To overcome this limitation, we developed a new strategy in which a DNA ladder is mixed with the protein sample before PAGE separation. After PAGE separation, the DNA ladder is stained to allow for easy, precise, and reproducible gel cutting. To this end, a novel visible DNA-staining method was developed. This staining method is fast, sensitive, and compatible with mass spectrometry. To evaluate the reproducibility of DNA-ladder-assisted gel cutting for quantitative protein fractionation, we used stable isotope labeling with amino acids in cell culture (SILAC). Our results show that the quantitative error associated with fractionation can be minimized using the DNA-assisted fractionation and multiple replicates of gel cutting. In conclusion, 1D PAGE fractionation in combination with DNA ladders can be used for label-free comparative proteomics without compromising quantitation.