Ultrasensitive proteome analysis using paramagnetic bead technology

In order to obtain a systems‐level understanding of a complex biological system, detailed proteome information is essential. Despite great progress in proteomics technologies, thorough interrogation of the proteome from quantity‐limited biological samples is hampered by inefficiencies during processing. To address these challenges, here we introduce a novel protocol using paramagnetic beads, termed Single‐Pot Solid‐Phase‐enhanced Sample Preparation (SP3). SP3 provides a rapid and unbiased means of proteomic sample preparation in a single tube that facilitates ultrasensitive analysis by outperforming existing protocols in terms of efficiency, scalability, speed, throughput, and flexibility. To illustrate these benefits, characterization of 1,000 HeLa cells and single Drosophila embryos is used to establish that SP3 provides an enhanced platform for profiling proteomes derived from sub‐microgram amounts of material. These data present a first view of developmental stage‐specific proteome dynamics in Drosophila at a single‐embryo resolution, permitting characterization of inter‐individual expression variation. Together, the findings of this work position SP3 as a superior protocol that facilitates exciting new directions in multiple areas of proteomics ranging from developmental biology to clinical applications.     

Computational methods for the comparative quantification of proteins in label-free LCn-MS experiments

Liquid chromatography (LC) coupled to electrospray mass spectrometry (MS) is well established in high-throughput proteomics. The technology enables rapid identification of large numbers of proteins in a relatively short time. Comparative quantification of identified proteins from different samples is often regarded as the next step in proteomics experiments enabling the comparison of protein expression in different proteomes. Differential labeling of samples using stable isotope incorporation or conjugation is commonly used to compare protein levels between samples but these procedures are difficult to carry out in the laboratory and for large numbers of samples. Recently, comparative quantification of label-free LC(n)-MS proteomics data has emerged as an alternative approach. In this review, we discuss different computational approaches for extracting comparative quantitative information from label-free LC(n)-MS proteomics data. The procedure for computationally recovering the quantitative information is described. Furthermore, statistical tests used to evaluate the relevance of results will also be discussed.     

Targeted label-free quantitative analysis of secretory proteins from adipocytes in response to oxidative stress

Adipocytes are well known to release regulation factors associated with metabolic disorders. In particular, increased oxidative stress in adipocytes contributes to dysregulation of adipokine production. In this study, we applied relative quantitative proteomic analysis based on label-free multiple reaction monitoring (MRM) to discover biological changes of adipokines under oxidative stress. Among a total of 194 identified proteins, 8 proteins were selected and quantified between control and hydrogen peroxide (H₂O₂)-treated groups by label-free MRM quantification. The secretion levels of matrix metalloproteinase-2 (MMP-2), stromal cell-derived factor-1 (SDF-1, CXCL12), resistin, and complement factor D (CFD, adipsin) decreased, whereas the secretion levels of tissue inhibitor of metalloproteinase-2 (TIMP-2) and aldolase A increased. Here we suggest that our study with label-free quantitative analysis will contribute to the efficient quantitative analysis of targeted proteins in complex mixtures and specifically to a better understanding of changes of adipokines under oxidative stress.     

Proteomics for the detection of indirect markers of steroids treatment in bovine muscle

Despite the ban by the European Union, anabolic steroids might still be illicitly employed in bovine meat production. The surveillance of misuse of such potentially harmful molecules is necessary to guarantee consumers’ health. Analytical methods for drug residue control are based on LC‐MS/MS, but their efficacy can be hindered due to undetectable residual concentrations as a result of low‐dosage treatments. Screening methods based on the recognition of indirect biological effects of growth promoters’ administration, such as the alteration of protein expression, can improve the efficacy of surveillance. The present study was aimed at identifying modifications in the muscle protein expression pattern between bulls treated with an ear implant (Revalor‐XS®) containing trenbolone acetate (200 mg) and estradiol (40 mg), and untreated animals. The analysis of skeletal muscle was carried out using a tandem mass tags shotgun proteomics approach. We defined 28 candidate protein markers with a significantly altered expression induced by steroids administration. A subset of 18 candidate markers was validated by SRM and allowed to build a predictive model based on partial least square discriminant analysis. Our findings confirm the effectiveness of the proteomics approach as potential tool to overcome analytical limitations of drug residue monitoring.     

A comparative evaluation of software for the analysis of liquid chromatography-tandem mass spectrometry data from isotope coded affinity tag experiments

The options available for processing quantitative data from isotope coded affinity tag (ICAT) experiments have mostly been confined to software specific to the instrument of acquisition. However, recent developments with data format conversion have subsequently increased such processing opportunities. In the present study, data sets from ICAT experiments, analysed with liquid chromatography/tandem mass spectrometry (MS/MS), using an Applied Biosystems QSTAR Pulsar quadrupole-TOF mass spectrometer, were processed in triplicate using separate mass spectrometry software packages. The programs Pro ICAT, Spectrum Mill and SEQUEST with XPRESS were employed. Attention was paid towards the extent of common identification and agreement of quantitative results, with additional interest in the flexibility and productivity of these programs. The comparisons were made with data from the analysis of a specifically prepared test mixture, nine proteins at a range of relative concentration ratios from 0.1 to 10 (light to heavy labelled forms), as a known control, and data selected from an ICAT study involving the measurement of cytokine induced protein expression in human lymphoblasts, as an applied example. Dissimilarities were detected in peptide identification that reflected how the associated scoring parameters favoured information from the MS/MS data sets. Accordingly, there were differences in the numbers of peptides and protein identifications, although from these it was apparent that both confirmatory and complementary information was present. In the quantitative results from the three programs, no statistically significant differences were observed.     

Comparative analysis of proteome differential regulation during cell dedifferentiation in Arabidopsis

Cell dedifferentiation is a cell fate switching process in which differentiated cells undergo genome reprogramming to regain the competency of cell division and organ regeneration. The molecular mechanism underlying the cell dedifferentiation process remains obscure. In this report, we investigate the cell dedifferentiation process in Arabidopsis using a shotgun proteomics approach. A total of 758 proteins are identified by two or more matched peptides. Comparative analyses at four time points using two label-free methods reveal that 193 proteins display up-regulation and 183 proteins display down-regulation within 48 h. While the results of the two label-free quantification methods match well with each other, comparison with previously published 2-DE gel results reveal that label-free quantification results differ substantially from those of the 2-DE method for proteins with peptides common to multiple proteins, suggesting a limitation of the label-free methods in quantifying proteins with closely related family members in complex samples. Our results show that the shotgun approach and the traditional 2-DE gel approach complement each other in both protein identification and quantification. An interesting observation is that core histones and histone variants are subjected to extensive down-regulation, indicating that there is a dramatic change in the chromatin during cell differentiation.     

Characterising live cell behaviour: Traditional label-free and quantitative phase imaging approaches

Label-free imaging uses inherent contrast mechanisms within cells to create image contrast without introducing dyes/labels, which may confound results. Quantitative phase imaging is label-free and offers higher content and contrast compared to traditional techniques. High-contrast images facilitate generation of individual cell metrics via more robust segmentation and tracking, enabling formation of a label-free dynamic phenotype describing cell-to-cell heterogeneity and temporal changes. Compared to population-level averages, individual cell-level dynamic phenotypes have greater power to differentiate between cellular responses to treatments, which has clinical relevance e.g. in the treatment of cancer. Furthermore, as the data is obtained label-free, the same cells can be used for further assays or expansion, of potential benefit for the fields of regenerative and personalised medicine.     

A label-free mass spectrometry method for the quantification of protein isotypes

Successful quantitative mass spectrometry (MS) requires strategies to link the mass spectrometer response to the analyte abundance, with the response being dependent on more factors than just analyte abundance. Label-dependent strategies rely on the incorporation of an isotopically labeled internal standard into the sample. Current label-free strategies (performed without internal standards) are useful for analyzing samples that are unsuitable for isotopic labeling but are less accurate. Here we describe a label-free technique applicable to analysis of products from related genes (isotypes). This approach enables the invariant tryptic peptide sequences within the family to serve as “built-in” internal standards and the isotype-specific peptide sequences to report the amount of the various isotypes. A process of elimination segregates reliably trypsin-released standard and reporter peptides from unreliably released peptides. The specific MS response factors for these reporter and standard peptides can be determined using synthetic peptides. Analysis of HeLa tubulin digests revealed peptides from βI-, βII-, βIII-, βIVb-, and βV-tubulin, eight of which were suitable; along with five standard peptides for quantification of the β-tubulin isotypes. To show the utility of this method, we determined that βI-tubulin represented 77% and βIII-tubulin represented 3.2% of the total HeLa β-tubulin.     

Qualitative and quantitative analysis of the adult Drosophila melanogaster proteome

Drosophila melanogaster is one of the most widely used model organisms in life sciences. Mapping its proteome is of great significance for understanding the biological characteristics and tissue functions of this species. However, the comprehensive coverage of its proteome remains a challenge. Here, we describe a high‐coverage analysis of whole fly through a 1D gel electrophoresis and LC‐MS/MS approach. By combining the datasets of two types of SDS‐PAGE and two kinds of tagmata, the high‐coverage analysis resulted in the identification of 5262 genes, which correspond to 38.23% of the entire coding genes. Moreover, we found that the fly head and body have different molecular weight distributions of their proteomes when the proteins were resolved with SDS‐PAGE and image analysis of the stained gel. This phenomenon was further confirmed by both label‐free and isobaric tags for relative and absolute quantitation‐based quantitative approaches. The consistent results of the two different quantitation methods also demonstrated the stability and accuracy of the LC‐MS/MS platform. The MS proteomics data have been deposited to the ProteomeXchange with identifiers PXD000454 and PXD000455 ( http://proteomecentral.proteomexchange.org/dataset/PXD000454 ; ( http://proteomecentral.proteomexchange.org/dataset/PXD000455 ).     

Differential gene alteration among hepatoma cell lines demonstrated by cDNA microarray-based comparative genomic hybridization

We assayed chromosomal abnormalities in hepatoma cell lines using the microarray-based comparative genomic hybridization (array-CGH) method and investigated the relationship between genomic copy number alterations and expression profiles in these hepatoma cell lines. We modified a cDNA array-CGH assay to compare genomic DNAs from seven hepatoma cell lines, as well as DNA from two non-hepatoma cell lines and from normal cells. The mRNA expression of each sample was assayed in parallel by cDNA microarray. We identified small amplified or deleted chromosomal regions, as well as alterations in DNA copy number not previously described. We predominantly found alterations of apoptosis-related genes in Hep3B and HepG2, cell adhesion and receptor molecules in HLE, and cytokine-related genes in PLC/PRF/5. About 40% of the genes showing amplification or loss showed altered levels of mRNA (p < 0.05). Hierarchical clustering analysis showed that the expression of these genes allows differentiation between alpha-fetoprotein (AFP)-producing and AFP-negative cell lines. cDNA array-CGH is a sensitive method that can be used to detect alterations in genomic copy number in tumor cells. Differences in DNA copy alterations between AFP-producing and AFP-negative cells may lead to differential gene expression and may be related to the phenotype of these cells.     

The emerging role of ICP-MS in proteomic analysis

Quantitative proteomics and absolute determination of proteins are topics of fast growing interest, since only the quantity of proteins or changes in their abundance reflect the status and extent of changes of a given biological system. Quantification of the desired proteins has been carried out by molecule specific MS techniques, but relative quantifications are commonplace so far even resorting to stable isotope labelling techniques such as ICAT and SILAC. In the last decade the idea of using element-selective mass spectrometric detection (e.g. ICP-MS instruments) to achieve absolute quantification has been realised and ICP-MS stands now as a new tool in the field of quantitative proteomics.In this review the emerging role of ICP-MS in protein and proteomic analysis is highlighted. The potential of ICP-MS methods and strategies for screening multiple heteroatoms (e.g. S, P, Se, metals) in proteins and their mixtures and extraordinary capabilities to tackle the problem of absolute protein quantifications, via heteroatom determinations, are discussed and illustrated. New avenues are also open derived from the use of ICP-MS for precise isotope abundance measurements in polyisotopic heteroatoms. The “heteroatom (isotope)-tagged proteomics” concept is focused on the use of naturally present element tags and also extended to any protein by resorting to bioconjugation reactions (i.e. labelling sought proteins and peptides with ICP-MS detectable heteroatoms). A major point of this review is displaying the possibilities of using a “hard” ion source, the ICP, to complement well-established “soft” ion sources for mass spectrometry to tackle present proteomic analysis.     

Spermatogenesis‐associated proteins at different developmental stages of buffalo testicular seminiferous tubules identified by comparative proteomic analysis

The testicular seminiferous tubules contain Sertoli cells and different types of spermatogenic cells. They provide the microenvironment for spermatogenesis, but the precise molecular mechanism of spermatogenesis is still not well known. Here, we have employed tandem mass tag coupled to LC‐MS/MS with the high‐throughput quantitative proteomics technology to explore the protein expression from buffalo testicular seminiferous tubules at three different developmental stages (prepuberty, puberty, and postpuberty). The results show 304 differentially expressed proteins with a ≥2‐fold change, and bioinformatics analysis indicates that 27 of these may be associated with spermatogenesis. Expression patterns of seven selected proteins were verified via Western blot and quantitative RT‐PCR analysis, and further cellular localizations of these proteins by immunohistochemical or immunofluorescence analysis. Taken together, the results provide potential molecular markers of spermatogenesis and provide a rich resource for further studies on male reproduction regulation.     

The influence of signals from chilled roots on the proteome of shoot tissues in rice seedlings

Low root temperature causes a decrease in water uptake, which leads to mineral and nutrient deficiencies with potentially decreased root and shoot growth. Differential temperature effects in plants have been studied extensively, however, the effect of root chilling on the global protein expression in shoots has not been explored. In this study, we imposed chilling temperatures on roots of rice plants while maintaining shoots at optimum atmospheric temperature. Shoot materials (growing zones and leaves) were harvested at five points over a time course of four days, including a two‐day recovery period. Proteins were quantified by tandem mass tags and triple stage MS, using a method developed to overcome ratio compression in isobaric‐labelled quantitation. Over 3000 proteins in each of the tissues were quantified by multiple peptides. Proteins significantly differentially expressed as compared with the control included abscisic acid‐responsive and drought‐associated proteins. The data also contained evidence of a possible induction of a sugar signalling pathway.     

Comprehensive quantitative proteome analysis of 20S proteasome subtypes from rat liver by isotope coded affinity tag and 2-D gel-based approaches

Quantitative protein profiling is an essential part of proteomics and requires technologies that accurately, reproducibly, and comprehensively identify and quantify proteins. Over the past years, many quantitative proteomic methods have been developed. Here, 20S proteasome subtypes isolated from rat were compared by four approaches based on the combination of isotope-coded affinity tag (ICAT), 2-DE, LC and ESI and MALDI MS: (i) 2-DE, (ii) ICAT/2-DE MALDI-MS, (iii) ICAT/LC-ESI-MS, (iv) ICAT/LC-MALDI-MS. A definite qualitative advantage of 2-DE gels was the separation of all known protein species, the identification of cysteine sulfoxide of alpha-4 (RC6-IS) and N-terminal acetylation of several subunits. Furthermore, quantitative differences between the standard subunits beta-2, and beta-5 and their immunosubunits were only detected by 2-DE image analysis revealing a higher replacement of standard- by immuno-beta-subunits in subtype IV. It was obvious that for relative quantification only protein spot and mass peaks with a certain level of intensity displayed acceptable values of SD. However, ICAT in conjunction with LC/MALDI-MS was the most accurate method for quantification. The experimental data of this investigation are accessible via http://www.mpiib-berlin.mpg.de/2D-PAGE/.     

A label-free photonic crystal biosensor imaging method for detection of cancer cell cytotoxicity and proliferation

A label-free method for detecting the attachment of human cancer cells to a biosensor surface for rapid screening for biological activity is described, in which attachment of a cell results in highly localized increase of the resonant reflected wavelength of a photonic crystal narrowband reflectance filter incorporated into a standard 96-well microplate. An imaging detection instrument is used to determine the spatial distribution of attached cells by mapping the shift in reflected resonant wavelength as a function of position. The method enables monitoring of cancer cell attachment, cell proliferation, and cell detachment that is induced by exposure of the cells to drug compounds. We demonstrate the efficacy of this method as an early screening technique for the rapid quantification of the rate of cancer cell proliferation on the sensor surface, and subsequently as a means for quantifying cell detachment resulting from apoptosis that is induced by exposure of the cells to cytotoxic chemicals.