Statistical Application and Challenges in Global Gel-Free Proteomic Analysis by Mass Spectrometry

Global gel-free proteomic analysis by mass spectrometry has been widely used as an important tool for exploring complex biological systems at the whole genome level. Simultaneous analysis of a large number of protein species is a complicated and challenging task. The challenges exist throughout all stages of a global gel-free proteomic analysis: experimental design, peptide/protein identification, data preprocessing and normalization, and inferential analysis. In addition to various efforts to improve the analytical technologies, statistical methodologies have been applied in all stages of proteomic analyses to help extract relevant information efficiently from large proteomic datasets. In this review, we summarize current applications of statistics in several stages of global gel-free proteomic analysis by mass spectrometry. We discuss the challenges associated with the applications of various statistical tools. Whenever possible, we also propose potential solutions on how to improve the data collection and interpretation for mass-spectrometry-based global proteomic analysis using more sophisticated and/or novel statistical approaches.     

Principles and applications of multidimensional protein identification technology

Multidimensional chromatography coupled to tandem mass spectrometry is an emerging technique for the analysis of proteomes and is rapidly being implemented by many researchers for proteomic analysis. In this technology profile, a particular proteomic approach known as multidimensional protein identification technology (MudPIT) is discussed. In MudPIT, a biphasic microcapillary column is packed with high-performance liquid chromatography grade reversed phase and strong cation exchange packing materials, loaded with a complex peptide mixture and placed in line with quaternary high-performance liquid chromatography and a tandem mass spectrometer. MudPIT has the capability to analyze highly complex proteomic mixtures such as whole proteomes, organelles and protein complexes.     

PeptideDepot: Flexible relational database for visual analysis of quantitative proteomic data and integration of existing protein information

Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through MS/MS. Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to various experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker‐driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end‐users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our high throughput autonomous proteomic pipeline used in the automated acquisition and post‐acquisition analysis of proteomic data.     

Principles and applications of Multidimensional Protein Identification Technology

Multidimensional chromatography coupled to tandem mass spectrometry is an emerging technique for the analysis of proteomes and is rapidly being implemented by many researchers for proteomic analysis. In this technology profile, a particular proteomic approach known as multidimensional protein identification technology (MudPIT) is discussed. In MudPIT, a biphasic microcapillary column is packed with high-performance liquid chromatography grade reversed phase and strong cation exchange packing materials, loaded with a complex peptide mixture and placed in line with quaternary high-performance liquid chromatography and a tandem mass spectrometer. MudPIT has the capability to analyze highly complex proteomic mixtures such as whole proteomes, organelles and protein complexes.     

HTAPP: High‐throughput autonomous proteomic pipeline

Recent advances in the speed and sensitivity of mass spectrometers and in analytical methods, the exponential acceleration of computer processing speeds, and the availability of genomic databases from an array of species and protein information databases have led to a deluge of proteomic data. The development of a lab‐based automated proteomic software platform for the automated collection, processing, storage, and visualization of expansive proteomic data sets is critically important. The high‐throughput autonomous proteomic pipeline described here is designed from the ground up to provide critically important flexibility for diverse proteomic workflows and to streamline the total analysis of a complex proteomic sample. This tool is composed of a software that controls the acquisition of mass spectral data along with automation of post‐acquisition tasks such as peptide quantification, clustered MS/MS spectral database searching, statistical validation, and data exploration within a user‐configurable lab‐based relational database. The software design of high‐throughput autonomous proteomic pipeline focuses on accommodating diverse workflows and providing missing software functionality to a wide range of proteomic researchers to accelerate the extraction of biological meaning from immense proteomic data sets. Although individual software modules in our integrated technology platform may have some similarities to existing tools, the true novelty of the approach described here is in the synergistic and flexible combination of these tools to provide an integrated and efficient analysis of proteomic samples.     

Utility of mass spectrometry for proteome analysis: part II. Ion-activation methods,statistics, bioinformatics and annotation

This is the second article in a series, intended as a tutorial to provide the interested reader with an overview of the concepts not covered in part I, such as: the principles of ion-activation methods, the ability of mass-spectrometric methods to interface with various proteomic strategies, analysis techniques, bioinformatics and data interpretation and annotation. Although these are different topics, it is important that a reader has a basic and collective understanding of all of them for an overall appreciation of how to carry out and analyze a proteomic experiment. Different ion-activation methods for MS/MS, such as collision-induced dissociation (including postsource decay) and surface-induced dissociation, electron capture and electron-transfer dissociation, infrared multiphoton and blackbody infrared radiative dissociation have been discussed since they are used in proteomic research. The high dimensionality of data generated from proteomic studies requires an understanding of the underlying analytical procedures used to obtain these data, as well as the development of improved bioinformatics tools and data-mining approaches for efficient and accurate statistical analyses of biological samples from healthy and diseased individuals, in addition to determining the utility of the interpreted data. Currently available strategies for the analysis of the proteome by mass spectrometry, such as those employed for the analysis of substantially purified proteins and complex peptide mixtures, as well as hypothesis-driven strategies, have been elaborated upon. Processing steps prior to the analysis of mass spectrometry data, statistics and the several informatics steps currently used for the analysis of shotgun proteomic experiments, as well as proteomics ontology, are also discussed.     

News in Brief

Archival formalin-fixed, paraffin-embedded (FFPE) tissue and their associated diagnostic records represent an invaluable source of retrospective proteomic information on diseases for which the clinical outcome and response to treatment are known. However, analysis of archival FFPE tissues by high-throughput proteomic methods has been hindered by the adverse effects of formaldehyde fixation and subsequent tissue histology. This review examines recent methodological advances for extracting proteins from FFPE tissue suitable for proteomic analysis. These methods, based largely upon heat-induced antigen retrieval techniques borrowed from immunohistochemistry, allow at least a qualitative analysis of the proteome of FFPE archival tissues. The authors also discuss recent advances in the proteomic analysis of FFPE tissue; including liquid-chromatography tandem mass spectrometry, reverse phase protein microarrays and imaging mass spectrometry.     

Synthesis of polymerized thin films for immobilized ligand display in proteomic analysis

We describe a new material for the display of biomolecular ligands for use in proteomic analysis. We report here on the construction of the first functionalized polymerized diacetylene thin films (PDTFs) for use in displaying immobilized ligands and their application in mass spectral proteomic analysis. Functionalized polymerized thin film surfaces were constructed with diacetylene-containing biotin lipid monomers designed for the capture of proteins (streptavidin) from a complex cellular lysate and detection with mass spectrometry (MS). These materials serve as a prototype for ligand-based spotted arrays amenable to high throughput screening. Functionalized PDTFs can be easily manufactured for customized microarrays and demonstrate high protein specificity and low nonspecific protein adsorption, and the resulting microarrays constructed from these materials are compatible with several different protein analysis platforms. Our results suggest that these materials have broad potential applications for use in mass spectral-based proteomic analysis.     

Local database and the search program for proteomic analysis of sperm proteins in the ascidian Ciona intestinalis

Separation of proteins by two-dimensional electrophoresis and following mass spectrometry (MS) is now a conventional technique for proteomic analysis. For proteomic analysis of a certain tissue with a limited information of primary structures of proteins, we have developed an analytical system for peptide mass fingerprinting in gene products in the testis of the ascidian Ciona intestinalis. Ciona sperm proteins were separated by two-dimensional gel electrophoresis and the tryptic fragments were subjected to MALDI-TOF/MS. The mass pattern was searched against on-line databases but resulted in less identification of these proteins. We have constructed a MS database from Ciona testis ESTs and the genome draft sequence, along with a newly devised, perl-based search program PerMS for peptide mass fingerprinting. This system could identify more than 80% of Ciona sperm proteins, suggesting that it could be widely applied for proteomic analysis for a limited tissue with less genomic information.     

Data mining in proteomic mass spectrometry

Data mining application to proteomic data from mass spectrometry has gained much interest in recent years. Advances made in proteomics and mass spectrometry have resulted in considerable amount of data that cannot be easily visualized or interpreted. Mass spectral proteomic datasets are typically high dimensional but with small sample size. Consequently, advanced artificial intelligence and machine learning algorithms are increasingly being used for knowledge discovery from such datasets. Their overall goal is to extract useful information that leads to the identification of protein biomarker candidates. Such biomarkers could potentially have diagnostic value as tools for early detection, diagnosis, and prognosis of many diseases. The purpose of this review is to focus on the current trends in mining mass spectral proteomic data. Special emphasis is placed on the critical steps involved in the analysis of surface-enhanced laser desorption/ionization mass spectrometry proteomic data. Examples are drawn from previously published studies and relevant data mining terminology and techniques are exlained.     

Proteomic analyses using an accurate mass and time tag strategy

An accurate mass and time (AMT) tag approach for proteomic analyses has been developed over the past several years to facilitate comprehensive high-throughput proteomic measurements. An AMT tag database for an organism, tissue, or cell line is established by initially performing standard shotgun proteomic analysis and, most importantly, by validating peptide identifications using the mass measurement accuracy of Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) and liquid chromatography (LC) elution time constraint. Creation of an AMT tag database largely obviates the need for subsequent MS/MS analyses, and thus facilitates high-throughput analyses. The strength of this technology resides in the ability to achieve highly efficient and reproducible one-dimensional reversed-phased LC separations in conjunction with highly accurate mass measurements using FTICR MS. Recent improvements allow for the analysis of as little as picrogram amounts of proteome samples by minimizing sample handling and maximizing peptide recovery. The nanoproteomics platform has also demonstrated the ability to detect >10(6) differences in protein abundances and identify more abundant proteins from subpicogram amounts of samples. The AMT tag approach is poised to become a new standard technique for the in-depth and high-throughput analysis of complex organisms and clinical samples, with the potential to extend the analysis to a single mammalian cell.     

Proteomics and physiology of erythritol-producing strains

In-depth knowledge bases on physiological properties of microbes are required to design a better microbial system at a gene level and to develop an industrially viable process in an optimized scheme. Proteomic analyses of industrially useful microorganisms are particularly important for achieving such objectives. In this review, industrial application of erythritol in food and pharmaceutical areas and proteomic techniques for erythritol-producing microbes were presented. Proteomic technologies for erythritol-producing strains such as Candida magnoliae contained protein or peptide sample preparation for two-dimensional electrophoresis and mass spectrometry, analysis of proteome with matrix assisted laser desorption-ionization/time-of-flight mass spectrometry, liquid chromatography/electrospray ionization/tandem mass spectrometry and similarity searching algorithms. The proteomic information was applied to predict the carbon metabolism of erythritol-synthesizing microorganisms.     

Role of chromatographic techniques in proteomic analysis

Proteomics, the characterization of the proteome, is conceptually simple but technically challenging. Development of such technologies as mass spectrometry, multidimensional protein separation, and DNA sequencing has allowed the new field of proteomics to flourish. Proteomic analysis relies on a set of techniques chosen on the basis of the biological question. In any proteomic analysis, the first and most important task is the separation of a complex protein mixture, i.e. the proteome. Chromatography, one of the most powerful methods of separation, employs one or more inherent characteristics of a protein-its mass, isoelectric point, hydrophobicity or biospecificity. This review emphasizes high-performance liquid chromatography as an integrated part of technologies used to study the proteome, discusses the capabilities and limitations of current instruments, and highlights the potential of multidimensional liquid chromatography in proteomic analysis.     

Improved proteomic discovery by sample pre-fractionation using dual-column ion-exchange high performance liquid chromatography

Clinically relevant biomarkers are urgently needed for improving patient diagnosis, risk stratification, prognosis and therapeutic treatments. There is a particularly compelling motivation for identifying protein-based indicators of early-stage disease for more effective interventions. Despite recent progress, the proteomic discovery process remains a daunting challenge due to the sheer heterogeneity and skewed protein abundances in biofluids. Even the most advanced mass spectrometry systems exhibit limiting overall dynamic ranges and sensitivities relative to the needs of modern biomedical applications. To this end, we report the development of a robust, rapid, and reproducible high performance ion-exchange liquid chromatography pre-fractionation method that allows for improved proteomic detection coverage of complex biological specimens using basic tandem mass spectrometry screening procedures. This form of sample simplification prior to global proteomic profiling, which we refer to collectively as 'fractionomics', increases the number and diversity of proteins that can be confidently identified in tissue and cell lysates as compared to the straight analysis of unfractionated crude extracts.     

The proteomic reactor: a microfluidic device for processing minute amounts of protein prior to mass spectrometry analysis

Gel-free proteomics has emerged as a complement to conventional gel-based proteomics. Gel-free approaches focus on peptide or protein fractionation, but they do not address the efficiency of protein processing. We report the development of a microfluidic proteomic reactor that greatly simplifies the processing of complex proteomic samples by combining multiple proteomic steps. Rapid extraction and enrichment of proteins from complex proteomic samples or directly from cells are readily performed on the reactor. Furthermore, chemical and enzymatic treatments of proteins are performed in 50 nL effective volume, which results in an increased number of generated peptides. The products are compatible with mass spectrometry. We demonstrated that the proteomic reactor is at least 10 times more sensitive than current gel-free methodologies with one protein identified per 440 pg of protein lysate injected on the reactor. Furthermore, as little as 300 cells can be directly introduced on the proteomic reactor and analyzed by mass spectrometry.     

Advances in shotgun proteomics and the analysis of membrane proteomes

The emergence of shotgun proteomics has facilitated the numerous biological discoveries made by proteomic studies. However, comprehensive proteomic analysis remains challenging and shotgun proteomics is a continually changing field. This review details the recent developments in shotgun proteomics and describes emerging technologies that will influence shotgun proteomics going forward. In addition, proteomic studies of integral membrane proteins remain challenging due to the hydrophobic nature in integral membrane proteins and their general low abundance levels. However, there have been many strategies developed for enriching, isolating and separating membrane proteins for proteomic analysis that have moved this field forward. In summary, while shotgun proteomics is a widely used and mature technology, the continued pace of improvements in mass spectrometry and proteomic technology and methods indicate that future studies will have an even greater impact on biological discovery.