Conventional Proteomic Analysis Research Articles

Comprehensive identification of molecules at synapses and non-synaptic cell-adhesion structure

The brain is incredibly complex and there is so much we donâ–™t know about this organ and its mechanisms. Assistant Professor Tetsuya Takano, School of Medicine, Keio University, Japan, is working to better understand neuroscience. One area of interest is neurons and astrocytes; specifically elucidating the protein component functions in each neural circuit. He and his team are working to shed light on the pathological mechanism of psychiatric and neurological disorders and, in doing so, enabling improved treatments and benefiting patients across the globe. The team has developed spatio-temporal proteome technologies: TurboID-surface and Split-TurboID, that can not only explain the formation and operation principle of neural networks, but also provide essential knowledge for research into psychiatric and neurological diseases. To overcome limitations associated with conventional proteome analysis, Takano and the team recently developed a new in vivo proximal-dependent biotin labelling (BioID) method. Using this, the researchers can label and analyse adjacent proteins with biotin, which enables them to comprehensively analyse local protein components within cells with extremely high spatial resolution. The team has used the BioID method to develop the Split-TurboID method and an innovative spatial proteome technique for searching for molecular groups among heterogeneous cells that makes it possible to comprehensively analyse the protein components in the vicinity of the adhesion site. Using the Split-TurboID method, the team has comprehensively searched for functional molecules between astrocytes and neurons and revealed that astrocytes directly control the formation of inhibitory synapses and neuronal activity in neurons via a novel tripartite synaptic molecule known as NRCAM.

The utility of proteases in proteomics, from sequence profiling to structure and function analysis.

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.

Integrated Proteomic and N-Glycoproteomic Analyses of Human Breast Cancer.

Breast cancer is one of the most common cancers in women worldwide. In the past decades, many advances have been made in understanding and treating breast cancer. However, due to the highly heterogeneous nature of this disease, a precise characterization of breast cancer on the molecular level is of great importance but not yet readily available. In the present study, we systematically profiled proteomes and N-glycoproteomes of cancerous, paracancerous, and distal noncancerous tissues from patients with breast cancer. The data revealed distinct proteomic and N-glycoproteomic landscapes between different tissues, showing biological insights obtained from the two data sets were complementary. Specifically, the complement and angiogenesis pathways in the paracancerous tissues were activated. Taken together, the changes that occurred in paracancer tissue and N-glycoproteomics are important complements to the conventional proteomic analysis of cancer tissue. Their combination provides more precise and sensitive molecular correlates of breast cancer. Our data and strategy shed light on precisely defining breast cancer, providing valuable information for individual patient diagnosis and treatment. The MS data of this study have been deposited under the accession number IPX0001924000 at iProX.

Probing the Proteomics Dark Regions by VAILase Cleavage at Aliphatic Amino Acids.

Proteomics emerges from the protein identification to protein functional elucidation, which depends to a large extent on the characterization of protein sequences. However, a large part of proteome sequences remains unannotated due to the limitation in proteolytic digestion by golden standard protease trypsin. Herein, we demonstrated that a cyanobacterial protease VAILase could specifically cleave at the short-chain aliphatic amino acids valine, alanine, leucine, isoleucine and threonine with cleavage specificity about 92% in total for proteomic analysis. The unique features of VAILase cleavage facilitate the characterization of most proteins and exhibit high complementarity to trypsin, and 22% of the covered sequences by VAILase are unique. VAILase can greatly improve the coverages of sequences with abundant aliphatic residues that are usually dark regions in conventional proteomic analysis, such as the transmembrane regions within anion exchanger 1 and photosystem II.

Absolute proteomic quantification of the activity state of proteases and proteolytic cleavages using proteolytic signature peptides and isobaric tags

Proteolytic processing alters the structure and function of a wide range of proteins in the proteome. We describe a method for the absolute quantification of proteolysis that is compatible with existing quantitative proteomic applications and could be applied on a protein-family wide scale. A tryptic peptide spanning a cleavage site differentiates this intact form of the protein from the corresponding semi-tryptic peptides of a protease cleaved protein. We term such proteomic signatures of specific proteolytic events "proteolytic signature peptides" (PSPs). By quantifying both the tryptic and semi-tryptic PSPs simultaneously with proteotypic peptides common to all forms of the protein both the relative and the absolute amounts of the intact and cleaved protein can be determined. Using synthetic PSP standards of cleavage sites in intact and cleaved proteins the absolute amounts of each form of the protein can be determined. The technique was demonstrated by the simultaneous identification and quantification of matrix metalloproteinase zymogens and their proteolytically activated forms in parallel with conventional absolute quantification of their TIMP inhibitors. For quantification we synthesized a pair of isobaric mass tags, we term CLIP-TRAQ, using C(13) labeled reagents that when fragmented during CID generate signature ions at 113.1 or 114.1 respectively. As an expandable platform this allows for the simultaneous identification of multiple proteins and their proteolytic state in complex proteomes on a family-wide scale in parallel with conventional proteomic analysis. This article is part of a Special Issue entitled: CNPN 2013. Proteolysis is key to various biological processes and the activity and function of many proteins are dictated by their proteolytic state. The development of methods to quantify protein abundance in conjunction to determining their proteolytic state and hence activity is essential for the complete understanding of the processes for which proteolysis is involved. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?

Focus on MALDI imaging

Matrix-assisted laser desorption/ionization (MALDI) emerged in the late 1980s concomitantly with electrospray ionization and contributed substantially to the promotion of mass spectrometry as an invaluable tool for analysis of biological macromolecules. Because MALDI is based on the production of ions from solid-phase samples deposited onto a conducting surface, some researchers attempted to analyse directly biological materials without any preliminary extraction step. MALDI analysis of bacterial cultures as early as the mid-1990s illustrates this approach, the objective of these studies being to characterize and identify microorganisms on the basis of a set of characteristic peaks present in their mass spectra. Identification of bacteria by MALDI mass spectrometry is now a routine method for clinical use. The ability of MALDI mass spectrometry to obtain spectra on well-defined surfaces with a focus of approximately 50–100 μm should also enable linking of the histological characteristics of biological tissue with local molecular composition. The driving idea was that tissue heterogeneity could be correlated with a difference in the mass spectral peak patterns. MALDI “profiling” of tissue sections was then proposed by the Todd and Caprioli groups at the end of the 1990s to differentiate, on a molecular basis, healthy or pathological areas present within the same tissue section. Soon after, the Caprioli team proposed a method for systematic profiling in which mass spectra were recorded at regularly spaced points on a biological surface, leading to a global vision of the molecular composition of the sample. By translating the relative intensity values of the ion peaks into a colour code, differences in local abundances in the x–y plane of the sample were revealed as contrast changes in the generated images. Immediately, MALDI mass spectrometry imaging (MALDI–MSI) seemed to be a unique method to record simultaneously as many images as ion peaks present on the mass spectra and without any a priori information about the nature of the detected molecules. It is therefore logical that MALDI imaging has initially been developed for research on biomarkers of pathologies, in a context in which the “omics” methods, in particular proteomics, have experienced explosive growth. If MALDI imaging was originally devoted to protein analysis only, this approach quickly met its limits in this area. Measuring the protein ions at low or moderate mass resolution is, indeed, not sufficient for their straightforward identification. In this area, MALDI imaging seemed more a complementary step to conventional proteomic analysis rather than an alternative method. In this way, MALDI imaging can provide precious indications of in situ protein-expression changes, making this technique attractive as a future diagnostic tool in biomedical research (Hanrieder et al., in this special issue). Recent years have seen a growing number of methodological developments and applications of MALDI imaging in the field of “small molecules”. For such compounds, accurate mass measurements, associated or not with tandemmass spectrometry (MS–MS), are often sufficient for assignment of the structures of the detected ions. Illustrating this evolution, the analysis of lipids is now a major field of application of MALDI imaging (Fernandez et al., Garrett et al., and Hart et al., in this special issue). Published in the special issue MALDI Imaging with Guest Editor Olivier Laprevote

The untiring search for the most complete proteome representation: reviewing the methods

Proteomic research has proved valuable for understanding the molecular mechanisms of biological processes, as well as in the search for biomarkers for a variety of diseases which lack a molecular diagnostic. While several new approaches are being developed, two-dimensional (2-DE) gel electrophoresis is still one of the most commonly used techniques, despite its many limitations. However, for biomarker research, 2-DE gel electrophoresis alone does not fulfill the necessary pre-requisites. If such a technique is utilized exclusively, a great part of a given proteome remains unseen. Therefore, very precise and sensitive techniques are needed. Here, we present a brief review of known methodologies that try to overcome the limitations of conventional proteome analysis as well as their respective advantages and limitations.

Identification of Pro-MMP-7 as a Serum Marker for Renal Cell Carcinoma by Use of Proteomic Analysis

No validated renal cell carcinoma (RCC) marker is known for detection of asymptomatic disease in selected populations or for prognostic purposes or treatment monitoring. We identified immunogenic proteins as tumor markers for RCC by combining conventional proteome analysis with serological screening, and we investigated the diagnostic clinical value of such markers in serum. We studied the immunogenic protein expression profile of CAL 54, a human RCC cell line, by 2-dimensional electrophoresis combined with immunoblotting using sera from healthy donors compared with RCC patients. We developed a homogeneous, fluorescent, dual-monoclonal immunoassay for metalloproteinase 7 (MMP-7) and used it to measure MMP-7 in sera from 30 healthy donors, 30 RCC patients, and 40 control patients. Pro-MMP-7 (29 kDa; pI 7.7) in the CAL 54 cell line secretome was an immunogenic protein reactive with RCC patient sera but not with control sera. The concentrations of pro-MMP-7 were increased (P <0.0001) in sera of RCC patients (median 7.56 microg/L; range 3.12-30.5 microg/L) compared with healthy controls (median 2.13 microg/L; range 0.17-3.5 microg/L). Serum pro-MMP-7 had a sensitivity of 93% (95% CI 78%-99%) at a specificity of 75% (59%-87%) for RCC in the samples tested. Proteomics technology combined with serology led to the identification of serum pro-MMP-7 as a marker of RCC and represents a powerful tool in searching for candidate proteins as biomarkers.

Identification of markers for the selection of patients undergoing renal cell carcinoma‐specific immunotherapy

Renal cell carcinoma (RCC) represents the most common malignant tumor in the kidney and is resistant to conventional therapies. The diagnosis of RCC is often delayed leading to progression and metastatic spread of the disease. Thus, validated markers for the early detection of the disease as well as selection of patients undergoing specific therapy is urgently needed. Using treatment with the monoclonal antibody (mAb) G250 as a model, proteome-based strategies were implemented for the identification of markers which may allow the discrimination between responders and nonresponders prior to application of G250-mediated immunotherapy. Flow cytometry revealed G250 surface expression in approximately 40% of RCC cell lines, but not in the normal kidney epithelium cell lines. G250 expression levels significantly varied thereby distinguishing between low, medium and high G250 expressing cell lines. Comparisons of two-dimensional gel electrophoresis expression profiles of untreated RCC cell lines versus RCC cell lines treated with a mAb directed against G250 and the characterization of differentially expressed proteins by mass spectrometry and/or Edman sequencing led to the identification of proteins such as chaperones, antigen processing components, transporters, metabolic enzymes, cytoskeletal proteins and unknown proteins. Moreover, some of these differentially expressed proteins matched with immunoreactive proteins previously identified by proteome analysis combined with immunoblotting using sera from healthy donors and RCC patients, a technique called PROTEOMEX. Immunohistochemical analysis of a panel of surgically removed RCC lesions and corresponding normal kidney epithelium confirmed the heterogeneous expression pattern found by proteome-based technologies. In conclusion, conventional proteome analysis as well as PROTEOMEX could be successfully employed for the identification of markers which may allow the selection of patients prior to specific immunotherapy.

Identification of metabolic enzymes in renal cell carcinoma utilizing PROTEOMEX analyses

PROTEOMEX, an approach which combines conventional proteome analysis with serological screening, is a powerful tool to separate proteins and identify immunogenic components in malignant diseases. By applying this approach, we characterized nine metabolic enzymes which were differentially expressed in renal cell carcinoma (RCC) cell lines and compared their expression profiles to that of normal kidney epithelium cells. Four of these proteins, superoxide dismutase (SODC), triosephosphatase isomerase (TPIS), thioredoxin (THIO) and ubiquitin carboxyl-terminal hydrolase (UBL1) were further analysed for both their constitutive and interferon (IFN)-γ inducible protein expression pattern in cell lines or tissue specimens derived from RCC or normal kidney epithelium using Western blot analysis and immunohistochemistry, respectively. With the exception of the RCC cell line MZ1940RC, which completely lacks the expression of UBL1, a heterogeneous and variable expression pattern of the different metabolic enzymes was detected in RCC and normal renal epithelium. The highest differences in the expression levels were found for THIO in the RCC cell lines, which was 2-fold upregulated when compared to autologous normal kidney epithelium. Moreover, IFN-γ treatment did not influence the constitutive expression of these metabolic enzymes. Thus, PROTEOMEX represents a valuable approach for the identification of metabolic enzymes which might be used as markers for the diagnosis of RCC.

Design of proteome-based studies in combination with serology for the identification of biomarkers and novel targets.

Recently proteome analysis has rapidly developed in the post-genome era and is now widely accepted as a complementary technology to genetic profiling. The improvement in the technology of both two-dimensional electrophoresis (2-DE) analysis as well as protein identification has made proteomics a valuable and powerful tool to study human diseases. A combination of conventional proteome analysis with serology has been developed as a promising experimental approach for the discovery of serological markers in different malignancies. However, the design of proteome-based studies has to be carefully performed since there are a number of critical needs for systematic and reproducible proteome analysis. In particular, the selection of tissue and its preparation represent an important step in proteome analysis. Besides the preparation of protein samples, the 2-DE and protein identification is a further critical issue. So far proteome-based technologies have been successfully used in tumor immunnology for the identification of tumor-specific autoantigens. Similarly, this technology has been employed for the detection of virulence factors, antigens and vaccine candidates in infectious diseases, as well as for the identification of diagnostic and prognostic markers, suggesting that proteome-based analysis is a promising tool for the identification of prognostic, diagnostic markers as well as for novel therapeutic targets which could be used for treatment of diseases. The integration of proteome-based approaches with data from genomic or genetic profiling will lead to a better understanding of different diseases, which will then contribute to the direct translation of the research findings into clinical practice.

効率的な発現プロファイリングのためのプロテオーム解析システムの開発 疾患標的蛋白質の迅速な同定と定量に向けて

In the post-genome era, there is an immediate requirement for the analysis of proteome, which gives a great impact on the methodology of disease diagnosis and drug discovery in medicine and pharmaceutical sciences. Mass spectrometry (MS) is essential for high throughput and accurate detection/identification of potential drug target proteins in low abundance localized to intrinsic functions at the extremely early stage of disease progression. Conventional proteome analysis strategy with two-dimensional electrophoresis (2-DE) techniques is not compatible for the drug discovery process and MS analysis, mainly due to poor solubility of many hydrophobic proteins in the current 2-DE sample buffers and its drawbacks including being low reproducibility, time consuming and very labor intensive. Higher throughput identification of proteins, including membrane-binding ones, was accomplished by introducing one-dimensional (1D) sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE) for protein fractionation coupled with nano-liquid chromatography (nanoLC)/nano-electrospray ionization (nanoESI)/ion trap (IT)-MS/MS. Toward fully automated proteome analysis, a five-dimensional (5D)-LC-based system was constructed, consisting of two-dimensional LC for protein fractionation, followed by proteolytic fragmentation of each protein fraction, and two-dimensional nanoLC for peptide fractionation directly linked with nanoESI/IT-MS/MS. A combination of the isotope-coded affinity tags (ICAT) assay with 1D-SDS-PAGE fractionation or the 5D-LC proteome workstation followed by nanoESI/IT-MS/MS data-dependent measurements under the dynamic exclusion mode will bring a promising approach for identification and quantification of proteins expressed in a disease progression. This strategy leads to the high throughput discovery of key target components related to disease progression or origin.

Current perspectives in cancer proteomics.

Proteome technology has been used widely in cancer research and is a useful tool for the identification of new cancer markers and treatment-related changes in cancer. This article details the use of proteome technology in cancer research, and laboratory-based and clinical cancer research studies are described. New developments in proteome technology that enable higher sample-throughput are evaluated and methods for enhancing conventional proteome analysis (based on two-dimensional electrophoresis) discussed. The need to couple laboratory-based proteomics research with clinically relevant models of the disease is also considered, as this remains the next main challenge of cancer-related proteome research.