Alternative profiling platform based on MELDI and its applicability in clinical proteomics

The presence of numerous proteomics data and their results in literature reveal the importance and influence of proteins and peptides on human cell cycle. For instance, the proteomic profiling of biological samples, such as serum, plasma or cells, and their organelles, carried out by surface-enhanced laser desorption/ionization mass spectrometry, has led to the discovery of numerous key proteins involved in many biological disease processes. However, questions still remain regarding the reproducibility, bioinformatic artifacts and cross-validations of such experimental set-ups. The authors have developed a material-based approach, termed material-enhanced laser desorption/ionization mass spectrometry (MELDI-MS), to facilitate and improve the robustness of large-scale proteomic experiments. MELDI-MS includes a fully automated protein-profiling platform, from sample preparation and analysis to data processing involving state-of-the-art methods, which can be further improved. Multiplexed protein pattern analysis, based on material morphology, physical characteristics and chemical functionalities provides a multitude of protein patterns and allows prostate cancer samples to be distinguished from non-prostate cancer samples. Furthermore, MELDI-MS enables not only the analysis of protein signatures, but also the identification of potential discriminating peaks via capillary liquid chromatography mass spectrometry. The optimized MELDI approach offers a complete proteomics platform with improved sensitivity, selectivity and short sample preparation times.     

Label-free quantification in clinical proteomics

Nowadays, proteomic studies no longer focus only on identifying as many proteins as possible in a given sample, but aiming for an accurate quantification of them. Especially in clinical proteomics, the investigation of variable protein expression profiles can yield useful information on pathological pathways or biomarkers and drug targets related to a particular disease. Over the time, many quantitative proteomic approaches have been established allowing researchers in the field of proteomics to refer to a comprehensive toolbox of different methodologies. In this review we will give an overview of different methods of quantitative proteomics with focus on label-free proteomics and its use in clinical proteomics.     

Clinical proteomics and mass spectrometry profiling for cancer detection

A key challenge in the clinical proteomics of cancer is the identification of biomarkers that would enable early detection, diagnosis and monitoring of disease progression to improve long-term survival of patients. Recent advances in proteomic instrumentation and computational methodologies offer a unique chance to rapidly identify these new candidate markers or pattern of markers. The combination of retentate affinity chromatography and mass spectrometry is one of the most interesting new approaches for cancer diagnostics using proteomic profiling. This review presents two technologies in this field, surface-enhanced laser desorption/ionization time-of-flight and Clinprot?, and aims to summarize the results of studies obtained with the first of them for the early diagnosis of human cancer. Despite promising results, the use of the proteomic profiling as a diagnostic tool brought some controversies and technical problems, and still requires some efforts to be standardized and validated.     

Bioinformatics approaches in clinical proteomics

Protein expression profiling is increasingly being used to discover, validate and characterize biomarkers that can potentially be used for diagnostic purposes and to aid in pharmaceutical development. Correct analysis of data obtained from these experiments requires an understanding of the underlying analytic procedures used to obtain the data, statistical principles underlying high-dimensional data and clinical statistical tools used to determine the utility of the interpreted data. This review summarizes each of these steps, with the goal of providing the nonstatistician proteomics researcher with a working understanding of the various approaches that may be used by statisticians. Emphasis is placed on the process of mining high-dimensional data to identify a specific set of biomarkers that may be used in a diagnostic or other assay setting.     

Chemical proteomics and its impact on the drug discovery process

Despite the rapid growth of postgenomic data and fast-paced technology advancement, drug discovery is still a lengthy and difficult process. More effective drug design requires a better understanding of the interaction between drug candidates and their targets/off-targets in various situations. The ability of chemical proteomics to integrate a multiplicity of disciplines enables the direct analysis of protein activities on a proteome-wide scale, which has enormous potential to facilitate drug target elucidation and lead drug verification. Over recent years, chemical proteomics has experienced rapid growth and provided a valuable method for drug target identification and inhibitor discovery. This review introduces basic concepts and technologies of different popular chemical proteomic approaches. It also covers the essential features and recent advances of each approach while underscoring their potentials in drug discovery and development.     

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.     

Biomarker discovery using protein microarray technology platforms: antibody-antigen complex profiling

Protein microarrays represent an important new tool in proteomic systems biology. This review focuses on the contributions of protein microarrays to the discovery of novel disease biomarkers through antibody-based assays. Of particular interest is the use of protein microarrays for immune response profiling, through which a disease-specific antibody repertoire may be defined. The antigens and antibodies revealed by these studies are useful for clinical assay development, with enormous potential to aid in diagnosis, prognosis, disease staging and treatment selection. The discovery and characterization of novel biomarkers specifically tailored to disease type and stage are expected to enable personalized medicine by facilitating preventative medicine, predictive diagnostics and individualized curative therapies.     

High-throughput proteomics using antibody microarrays

Antibody-based microarrays are a novel technology that hold great promise in proteomics. Microarrays can be printed with thousands of recombinant antibodies carrying the desired specificities, the biologic sample (e.g., an entire proteome) and any specifically bound analytes detected. The microarray patterns that are generated can then be converted into proteomic maps, or molecular fingerprints, revealing the composition of the proteome. Using this tool, global proteome analysis and protein expression profiling will thus provide new opportunities for biomarker discovery, drug target identification and disease diagnostics, as well as providing insights into disease biology. Intense work is currently underway to develop this novel technology platform into the high-throughput proteomic tool required by the research community.     

Activity-based proteomics: enzymatic activity profiling in complex proteomes

Summary. In the postgenomic era new technologies are emerging for global analysis of protein function. The introduction of active site-directed chemical probes for enzymatic activity profiling in complex mixtures, known as activity-based proteomics has greatly accelerated functional annotation of proteins. Here we review probe design for different enzyme classes including serine hydrolases, cysteine proteases, tyrosine phosphatases, glycosidases, and others. These probes are usually detected by their fluorescent, radioactive or affinity tags and their protein targets are analyzed using established proteomics techniques. Recent developments, such as the design of probes for in vivo analysis of proteomes, as well as microarray technologies for higher throughput screenings of protein specificity and the application of activity-based probes for drug screening are highlighted. We focus on biological applications of activity-based probes for target and inhibitor discovery and discuss challenges for future development of this field.     

Serological protein profiling of neuroblastoma by ProteinChip SELDI-TOF technology

Serological proteins of neuroblastoma were profiled and analyzed by ProteinChip-SELDI-TOF MS technology with five types of protein chips. By comparing with normal control, a number of protein or polypeptide signals were found significantly and consistently different in their intensities (expression levels) in tumor sera. Interestingly, nine polypeptide peaks in these proteomic features can be simultaneously detected with consistent variations by more than one type of protein chips. None of the expression differences of these nine polypeptides was found in similar comparisons between healthy controls and hepatomas. Preliminary protein identification showed hints for that some of these proteomic alterations may be closely related to the tumorigenesis of neuroblastoma. These results demonstrated the potential of serological biomarker identification for neuroblastoma by ProteinChip-SELDI technology.     

A potential biomarker of kidney damage identified by proteomics: preliminary findings

4-Aminophenol (4-AP) and d-serine are established rodent nephrotoxins that selectively damage renal proximal tubules. In an attempt to understand the mechanism of action of these toxicants in greater detail, a high throughput proteomics approach was used to profile protein changes in the plasma of animals treated with these compounds. Male Fischer 344 and Alderley Park rats were treated with increasing doses of 4-AP or d-serine and plasma samples were collected over time. Control groups received either saline or the non-toxic enantiomer, l-serine. Using high throughput two-dimensional gel analysis, a number of plasma proteins showing dose- and time-dependent regulation were identified. One toxicity-associated plasma protein was identified as the cellular enzyme fumarylacetoacetate hydrolase (FAH), which is known to be required for tyrosine metabolism. The FAH gene is mutated in the human genetic disorder type I tyrosinaemia, which is associated with liver and kidney abnormalities and neurological disorders. FAH was elevated in the plasma of animals treated with 4-AP and d-serine at early time points and returned to baseline levels after 3 weeks. The protein was not elevated in the plasma of control animals or those treated with l-serine. The presence of FAH in plasma is intriguing as it is normally a cellular enzyme with no known function in plasma. It is possible that 4-AP and d-serine may work through a previously unknown mechanism in the kidney via regulation of tyrosine metabolism or FAH activity. Therefore, FAH may function in a fashion analogous to the aspartate aminotransferase (AST) and alanine aminotransferase (ALT) enzymes that are used to measure liver injury. The link between kidney toxicants and inherited tyrosinaemia also raises the possibility that FAH may be a marker of kidney toxicity in humans. These observations highlight the value of proteomics in identifying new biomarkers and providing new unprecedented insights into complex biological mechanisms.     

A potential biomarker of kidney damage identified by proteomics: preliminary findings

4-Aminophenol (4-AP) and d-serine are established rodent nephrotoxins that selectively damage renal proximal tubules. In an attempt to understand the mechanism of action of these toxicants in greater detail, a high throughput proteomics approach was used to profile protein changes in the plasma of animals treated with these compounds. Male Fischer 344 and Alderley Park rats were treated with increasing doses of 4-AP or d-serine and plasma samples were collected over time. Control groups received either saline or the non-toxic enantiomer, l-serine. Using high throughput two-dimensional gel analysis, a number of plasma proteins showing dose- and time-dependent regulation were identified. One toxicity-associated plasma protein was identified as the cellular enzyme fumarylacetoacetate hydrolase (FAH), which is known to be required for tyrosine metabolism. The FAH gene is mutated in the human genetic disorder type I tyrosinaemia, which is associated with liver and kidney abnormalities and neurological disorders. FAH was elevated in the plasma of animals treated with 4-AP and d-serine at early time points and returned to baseline levels after 3 weeks. The protein was not elevated in the plasma of control animals or those treated with l-serine. The presence of FAH in plasma is intriguing as it is normally a cellular enzyme with no known function in plasma. It is possible that 4-AP and d-serine may work through a previously unknown mechanism in the kidney via regulation of tyrosine metabolism or FAH activity. Therefore, FAH may function in a fashion analogous to the aspartate aminotransferase (AST) and alanine aminotransferase (ALT) enzymes that are used to measure liver injury. The link between kidney toxicants and inherited tyrosinaemia also raises the possibility that FAH may be a marker of kidney toxicity in humans. These observations highlight the value of proteomics in identifying new biomarkers and providing new unprecedented insights into complex biological mechanisms.     

Combining bioinformatics and MS-based proteomics: clinical implications

Clinical proteomics research aims at i) discovery of protein biomarkers for screening, diagnosis and prognosis of disease, ii) discovery of protein therapeutic targets for improvement of disease prevention, treatment and follow-up, and iii) development of mass spectrometry (MS)-based assays that could be implemented in clinical chemistry, microbiology or hematology laboratories. MS has been increasingly applied in clinical proteomics studies for the identification and quantification of proteins. Bioinformatics plays a key role in the exploitation of MS data in several aspects such as the generation and curation of protein sequence databases, the development of appropriate software for MS data treatment and integration with other omics data and the establishment of adequate standard files for data sharing. In this article, we discuss the main MS approaches and bioinformatics solutions that are currently applied to accomplish the objectives of clinical proteomic research.     

Recent advances in quantitative and chemical proteomics for autophagy studies

Macroautophagy/autophagy is an evolutionarily well-conserved cellular degradative process with important biological functions that is closely implicated in health and disease. In recent years, quantitative mass spectrometry-based proteomics and chemical proteomics have emerged as important tools for the study of autophagy, through large-scale unbiased analysis of the proteome or through highly specific and accurate analysis of individual proteins of interest. At present, a variety of approaches have been successfully applied, including (i) expression and interaction proteomics for the study of protein post-translational modifications, (ii) investigating spatio-temporal dynamics of protein synthesis and degradation, and (iii) direct determination of protein activity and profiling molecular targets in the autophagic process. In this review, we attempted to provide an overview of principles and techniques relevant to the application of quantitative and chemical proteomics methods to autophagy, and outline the current landscape as well as future outlook of these methods in autophagy research.     

Activity- and reactivity-based proteomics: Recent technological advances and applications in drug discovery

Activity-based protein profiling (ABPP) is recognized as a powerful and versatile chemoproteomic technology in drug discovery. Central to ABPP is the use of activity-based probes to report the activity of specific enzymes or reactivity of amino acid types in complex biological systems. Over the last two decades, ABPP has facilitated the identification of new drug targets and discovery of lead compounds in human and infectious disease. Furthermore, as part of a sustained global effort to illuminate the druggable proteome, the repertoire of target classes addressable with activity-based probes has vastly expanded in recent years. Here, we provide an overview of ABPP and summarise the major technological advances with an emphasis on probe development.     

Use of proteomics for the identification of novel drug targets in brain diseases

In spite of the rapid advances in the development of the new proteomic technologies, there are, to date, relatively fewer studies aiming to explore the neuronal proteome. One of the reasons is the complexity of the brain, which presents high cellular heterogeneity and a unique subcellular compartmentalization. Therefore, tissue fractionation of the brain to enrich proteins of interest will reduce the complexity of the proteomics approach leading to the production of manageable and meaningful results. In this review, general considerations and strategies of proteomics, the advantages and challenges to exploring the neuronal proteome are described and summarized. In addition, this article presents an overview of recent advances of proteomic technologies and shows that proteomics can serve as a valuable tool to globally explore the changes in brain proteome during various disease states. Understanding the molecular basis of brain function will be extremely useful in identifying novel targets for the treatment of brain diseases.     

SELDI-TOF serum proteomics and breast cancer: which perspective?

Despite the efforts of recent years, clinicians still lack reliable biomarkers for diagnosis, prognosis and prediction of clinical outcomes in breast cancer patients. Owing to the large number of people potentially involved in the management of this clinical problem, the search for noninvasive and repeatable laboratory assays has been intensive. Recently, the proteomic profiling performed by SELDI-TOF mass spectrometry, has been proposed in order to identify new clusters of serum markers that could be potentially useful in breast cancer management. The purpose of this special report is to review the literature on SELDI-TOF technology applied on serum coming from healthy people and breast cancer patients, in order to verify the clinical applicability of such approach. We conclude that potential new biomarkers, first of all for early diagnosis of breast cancer, need to be validated in larger clinical series.     

叶绿体基因编码蛋白质在水稻叶片生长过程中的表达研究

叶绿体是绿色植物把光能转化为化学能的重要细胞器.目前,多种植物的叶绿体基因组序列已经获得,对叶绿体内发生的各种生物学过程人们也已经有相当深入的了解,但对叶绿体基因编码蛋白质的表达还所知甚少.用蛋白质印迹实验系统地检测了15个叶绿体基因编码蛋白质在水稻叶片不同生长时期的表达.其中7个与光合作用相关蛋白质的表达具有相似的模式,其表达量随叶片生长而增加,一般在孕穗期、开花期达到最高峰,在成熟期叶片下降,这种模式与水稻生长对光合作用的需求有明显相关性.4个与DNA复制相关的RNA聚合酶在苗期叶片中表达量达到最高,说明这些聚合酶在较早时期发挥作用.4个NADH脱氢酶蛋白质的表达呈2种不同的模式,其中亚基2和4在种子萌发后的早期叶片中就达到最高峰,亚基5和7的最高峰出现在中后期,反映了它们之间功能上的不同.实验结果直观且相对定量地揭示了叶绿体编码蛋白质的表达与叶片生长之间的关联关系,为深入了解其功能提供了重要的线索.     

Translating clinical proteomics: the importance of study design

Mass spectrometry-based clinical proteomics approaches were introduced into the biomedical field more than two decades ago. Despite recent developments both in the field of mass spectrometry and bioinformatics, the gap between proteomics results and their translation into clinical practice still needs to be closed, as implementation of proteomics results in the clinic appears to be scarce. An extra focus on the importance of the experimental design is therefore of crucial importance.