Characterization of transcription factors by mass spectrometry and the role of SELDI-MS

Modeling Modulation of the Tick Regulome in Response to Anaplasma phagocytophilum for the Identification of New Control Targets

Ticks act as vectors of pathogens affecting human and animal health worldwide, and recent research has focused on the characterization of tick-pathogen interactions using omics technologies to identify new targets for developing novel control interventions. The regulome (transcription factors-target genes interactions) plays a critical role in cell response to pathogen infection. Therefore, the application of regulomics to tick-pathogen interactions would advance our understanding of these molecular interactions and contribute to the identification of novel control targets for the prevention and control of tick infestations and tick-borne diseases. However, limited information is available on the role of tick regulome in response to pathogen infection. In this study, we applied complementary in silico approaches to modeling how Anaplasma phagocytophilum infection modulates tick vector regulome. This proof-of-concept research provided support for the use of network analysis in the study of regulome response to infection, resulting in new information on tick-pathogen interactions and potential targets for developing interventions for the control of tick infestations and pathogen transmission. Deciphering the precise nature of circuits that shape the tick regulome in response to pathogen infection is an area of research that in the future will advance our knowledge of tick-pathogen interactions, and the identification of new antigens for the control of tick infestations and pathogen infection/transmission.

Bioinformatics and Translation Elongation

Codon usage depends on mutation bias, tRNA-mediated selection, and the need for high efficiency and accuracy in translation. One codon in a synonymous codon family is often strongly over-used, especially in highly expressed genes, which often leads to a high dN/dS ratio because dS is very small. Many different codon usage indices have been proposed to measure codon usage and codon adaptation. Sense codon could be misread by release factors and stop codons misread by tRNAs, which also contribute to codon usage in rare cases. This chapter outlines the conceptual framework on codon evolution, illustrates codon-specific and gene-specific codon usage indices, and presents their applications. A new index for codon adaptation that accounts for background mutation bias (Index of Translation Elongation) is presented and contrasted with codon adaptation index (CAI) which does not consider background mutation bias. They are used to re-analyze data from a recent paper claiming that translation elongation efficiency matters little in protein production. The reanalysis disproves the claim.

Biomarker Characterization by MALDI-TOF/MS

Mass spectrometric techniques frequently used in clinical diagnosis, such as gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, ambient ionization mass spectrometry, and matrix-assisted laser desorption ionization/time-of-flight mass spectrometry (MALDI-TOF/MS), are discussed. Due to its ability to rapidly detect large biomolecules in trace amounts, MALDI-TOF/MS is an ideal tool for characterizing disease biomarkers in biologic samples. Clinical applications of MS for the identification and characterization of microorganisms, DNA fragments, tissues, and biofluids are introduced. Approaches for using MALDI-TOF/MS to detect various disease biomarkers including peptides, proteins, and lipids in biological fluids are further discussed. Finally, various sample pretreatment methods which improve the detection efficiency of disease biomarkers are introduced.

A role for the MS analysis of nucleic acids in the post-genomics age

The advances of mass spectrometry in the analysis of nucleic acids have tracked very closely the exciting developments of instrumentation and ancillary technologies, which have taken place over the years. However, their diffusion in the broader life sciences community has been and will be linked to the ever evolving focus of biomedical research and its changing demands. Before the completion of the Human Genome Project, great emphasis was placed on sequencing technologies that could help accomplish this project of exceptional scale. After the publication of the human genome, the emphasis switched toward techniques dedicated to the exploration of sequences not coding for actual protein products, which amount to the vast majority of transcribed elements. The broad range of capabilities offered by mass spectrometry is rapidly advancing this platform to the forefront of the technologies employed for the structure-function investigation of these noncoding elements. Increasing focus on the characterization of functional assemblies and their specific interactions has prompted a re-evaluation of what has been traditionally construed as nucleic acid analysis by mass spectrometry. Inspired by the accelerating expansion of the broader field of nucleic acid research, new applications to fundamental biological studies and drug discovery will help redefine the evolving role of MS-analysis of nucleic acids in the post-genomics age.

Polymeric inverse micelles as selective peptide extraction agents for MALDI-MS analysis

Analyses of peptides in complex mixtures are significant challenges in proteomics applications. Here, we report an amphiphilic polymer-based nanoassembly that is capable of selectively extracting peptides, on the basis of their isoelectric points, into an immiscible organic phase from an aqueous solution. The isoelectric point (pI) cutoff in these extractions depends on the pH of the aqueous solution, and thus, sequential fractionation of peptide mixtures based on pI can be accomplished by varying the pH of the aqueous solution. Additionally, we observe an unexpected enhancement in the MALDI-MS signal for extracted peptides ionized in the presence of the polymer, which allows us to obtain reproducible ion signals for some peptides at concentrations as low as 10 pM.

Proteomics of human cerebrospinal fluid - the good, the bad, and the ugly

The development of MALDI ESI in the late 1980s has revolutionized the biological sciences and facilitated the emergence of a new discipline called proteomics. Application of proteomics to human cerebrospinal fluid (CSF) has greatly hastened the advancement of characterizing the CSF proteome as well as revealing novel protein biomarkers that are diagnostic of various neurological diseases. While impressive progressions have been made in this field, it has become increasingly clear that proteomics results generated by various laboratories are highly variable. The underlying issues are vast, including limitations and complications with heterogeneity of patients/testing subjects, experimental design, sample processing, as well as current proteomics technology. Accordingly, this review not only summarizes the current status of characterization of the human CSF proteome and biomarker discovery for major neurodegenerative disorders, i.e., Alzheimer's disease and Parkinson's disease, but also addresses a few essential caveats involved in several steps of CSF proteomics that may contribute to the variable/contradicting results reported by different laboratories. The potential future directions of CSF proteomics are also discussed with this analysis.

Is There a Role for Proteomics in Peyronie's Disease?

INTRODUCTION

Peyronie's disease (PD) continues to be a major source of sexual dysfunction among the 3-9% of affected men. The challenge in treating PD is determining the natural history and clinical course for the individual patient. Currently, there exists no reliable means to predict whether a penile plaque of PD will progress, regress, or remain stable. This represents a significant deficiency in contemporary management, one that may be addressed with newer technologies such as proteomic profiling.

AIM

This review assesses the potential use of protein alterations measured by various novel technologies, to predict progression, regression, or stabilization of PD in an affected individual.

METHODS

A comprehensive literature review of the past decade in the field of gene profiling and protein expression of PD was performed.

MAIN OUTCOME MEASURES

A critical analysis of the existing worldwide literature evaluating surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS or SELDI) and other proteonomic techniques.

RESULTS

SELDI and other technologies can provide the clinician with innovative data indicating the presence of unique individual factors that act to suppress or promote the fibrotic process in PD. Determining the clinical implications of altered protein expression in an individual is not yet defined.

CONCLUSIONS

The area of proteomics has begun to revolutionize the study of medicine in the postgenomic era, by allowing researchers to study the role that proteins play in health and disease. Applying this knowledge clinically has already led to innovative discoveries in early cancer detection in a number of malignancies, including prostate, ovarian, and bladder. Prior to the widespread use and acceptance of proteomic technology in PD, a critical assessment of its therapeutic and diagnostic value will be required.

Identification and characterization of DNA-binding proteins by mass spectrometry

Mass spectrometry is the most sensitive and specific analytical technique available for protein identification and quantification. Over the past 10 years, by the use of mass spectrometric techniques hundreds of previously unknown proteins have been identified as DNA-binding proteins that are involved in the regulation of gene expression, replication, or DNA repair. Beyond this task, the applications of mass spectrometry cover all aspects from sequence and modification analysis to protein structure, dynamics, and interactions. In particular, two new, complementary ionization techniques have made this possible: matrix-assisted laser desorption/ionization and electrospray ionization. Their combination with different mass-over-charge analyzers and ion fragmentation techniques, as well as specific enzymatic or chemical reactions and other analytical techniques, has led to the development of a broad repertoire of mass spectrometric methods that are now available for the identification and detailed characterization of DNA-binding proteins. These techniques, how they work, what their requirements and limitations are, and selected examples that document their performance are described and discussed in this chapter.

Proteomics and its role in nutrition research

There are approximately 100,000 proteins in humans with various physiological functions. The complement of proteins in the organism as well as their interactions is defined as the proteome. Its analysis (proteomics) by highly specific, sensitive, and accurate MS has been made possible with matrix-assisted laser desorption ionization or electrospray ionization of proteins and large peptides. Currently, the most commonly used proteomics technologies involve either specific digestion of proteins (the bottom-up approach using 2-dimensional polyacrylamide gel electrophoresis and multidimensional protein identification technology) or direct analysis of intact proteins after their chromatographic separation (the top-down approach and surface-enhanced laser desorption ionization). Proteomics holds great promise for discoveries in nutrition research, including profiles and characteristics of dietary and body proteins; digestion, absorption, and metabolism of nutrients; functions of nutrients and other dietary factors in growth, reproduction, and health; biomarkers of the nutritional status and disease; and individualized requirements of nutrients. The proteome analysis is expected to play an important role in solving major nutrition-associated problems in humans and animals, such as obesity, diabetes, cardiovascular disease, cancer, aging, and intrauterine fetal retardation.

Mixed Monolayer-Protected Gold Nanoclusters as Selective Peptide Extraction Agents for MALDI-MS Analysis

Cationic and anionic nanoparticles selectively target peptides with low and high isoelectric points, respectively. Additionally, their high surface area-to-volume ratios make these nanoparticles (approximately 2-nm core diameter) very efficient extraction and concentration agents. Upon extraction, the peptide-bound nanoparticles can be analyzed by MALDI-MS to provide highly sensitive detection of the targeted peptides. We demonstrate that MALDI-MS can detect peptide concentrations as low as 500 pM from 250-microL solutions using these nanoparticle scaffolds as extraction and concentration agents.

Quantitative proteomic analysis of age-related changes in human cerebrospinal fluid

Identification of cerebrospinal fluid (CSF) biomarkers of the common age-related neurodegenerative diseases would be of great value to clinicians because of the difficulties in differential diagnoses of these diseases in clinical practice. Proteins are one class of potential biomarkers currently under investigation in the hope that different ensembles of proteins will aid in the diagnosis of these diseases, as well as in the assessment of progression and response to therapy. However, before undertaking a rational approach to CSF protein biomarkers of age-related neurodegeneration, we must first systematically identify CSF proteins and determine whether their levels change with normal aging. In this study, we used a powerful shotgun proteomic method, two-dimensional microcapillary liquid chromatography electrospray ionization tandem mass spectrometry, to identify proteins in human CSF. Additionally, using pooled CSF samples, we quantitatively compared the CSF proteome of younger adults with that of older adults using isotope-coded affinity tags (ICAT). From these studies we identified more than 300 proteins in CSF and found that there were 30 proteins with >20% change in concentrations between older and younger individuals. Finally, we validated changes in concentration for two of these proteins using Western blots in CSF from a separate set of individuals. These data not only expand substantially our current knowledge regarding human CSF proteins, but also supply the necessary information to appropriately interpret protein biomarkers of age-related neurodegenerative diseases.

Proteomic patterns: their potential for disease diagnosis

Alterations in proteins abundance, structure, or function, act as useful indicators of pathological abnormalities prior to development of clinical symptoms and as such are often useful diagnostic and prognostic biomarkers. The underlying mechanism of diseases such as cancer are, however, quite complicated in that often multiple dysregulated proteins are involved. It is for this reason that recent hypotheses suggest that detection of panels of biomarkers may provide higher sensitivities and specificities for disease diagnosis than is afforded with single markers. Recently, a novel approach based on the analysis of protein patterns has emerged that may provide a more effective means to diagnose diseases, such as ovarian and prostate cancer. The method is based on the use of surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry (TOF-MS) to detect differentially captured proteins from clinical samples, such as serum and plasma. This analysis results in the detection of "proteomic" patterns that have been shown in recent investigations to distinguish diseased and unaffected subjects to varying degrees. This review will discuss the basics of SELDI protein chip technology and highlight its recent applications in disease biomarker discovery with emphasis on cancer diagnosis.

Charting gene regulatory networks: strategies, challenges and perspectives

One of the foremost challenges in the post-genomic era will be to chart the gene regulatory networks of cells, including aspects such as genome annotation, identification of cis-regulatory elements and transcription factors, information on protein-DNA and protein-protein interactions, and data mining and integration. Some of these broad sets of data have already been assembled for building networks of gene regulation. Even though these datasets are still far from comprehensive, and the approach faces many important and difficult challenges, some strategies have begun to make connections between disparate regulatory events and to foster new hypotheses. In this article we review several different genomics and proteomics technologies, and present bioinformatics methods for exploring these data in order to make novel discoveries.

Affinity capture of specific DNA-binding proteins for mass spectrometric identification

We describe a general approach for affinity microcapture of site-specific, nucleic acid-binding proteins. The major difficulties to developing this method into a widely applicable protocol derived from the need for a massive enrichment and the inadvertent, extensive binding of nonspecific proteins to the bait. On the basis of a detailed analysis, we propose (i) a one-step fractionation of crude extracts on P11 phosphocellulose, followed by (ii) a discrete series of positive/negative selections on wild-type and site-mutated ligand DNA in a magnetic microparticulate format, with cobalt magnets, concatamerized and biotinylated ligands, selective salt conditions, and improved competitor DNAs. We also present rules for determining the precise number and order of selections. The approach and protocol allowed isolation of four, low-abundance transcription factors and repressors from 2 x 10(9) cultured leukemia cells. Captured proteins were 10-20,000-fold enriched from the nuclear extract, in a form and amounts that permitted facile MALDI-TOF and TOF/TOF MS-based protein identification. This is 1-2 orders of magnitude better than many previous efforts and in a fraction of the time (approximately 1 factor/week). The method can be applied to any protein that binds DNA, including those with modest to low affinity, and bridges functional-biochemical studies on replication, transcriptional regulation, and DNA repair with the analytical power of mass spectrometry-based proteomics.

Linear fuzzy gene network models obtained from microarray data by exhaustive search

BACKGROUND

Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are needed to interpret the resulting large and complex data sets. Rationally designed perturbations (e.g., gene knock-outs) can be used to iteratively refine hypothetical models, suggesting an approach for high-throughput biological system analysis. We introduce an approach to gene network modeling based on a scalable linear variant of fuzzy logic: a framework with greater resolution than Boolean logic models, but which, while still semi-quantitative, does not require the precise parameter measurement needed for chemical kinetics-based modeling.

RESULTS

We demonstrated our approach with exhaustive search for fuzzy gene interaction models that best fit transcription measurements by microarray of twelve selected genes regulating the yeast cell cycle. Applying an efficient, universally applicable data normalization and fuzzification scheme, the search converged to a small number of models that individually predict experimental data within an error tolerance. Because only gene transcription levels are used to develop the models, they include both direct and indirect regulation of genes.

CONCLUSION

Biological relationships in the best-fitting fuzzy gene network models successfully recover direct and indirect interactions predicted from previous knowledge to result in transcriptional correlation. Fuzzy models fit on one yeast cell cycle data set robustly predict another experimental data set for the same system. Linear fuzzy gene networks and exhaustive rule search are the first steps towards a framework for an integrated modeling and experiment approach to high-throughput "reverse engineering" of complex biological systems.

Proteomics and regulomics: the yin and yang of functional genomics

Protein analysis is a field of research with a long history. Recently, the development of a series of proteomics approaches, i.e., simultaneous analyses on all or a majority of proteins in a cell at a given state, has reinvigorated protein analyses. Mass Spectrometry also developed into one of the most versatile technical tools supporting or even enabling many proteomics-oriented approaches, providing a convenient link between experimental protein analysis and the corresponding amino acid sequences. Thus direct links to the genomic sequence can be established, which opens the door for a synergistic combination with genomic sequence analysis. This review focuses especially on aspects of genome-wide transcription control, regulomics in analogy to all the other -omics, and how a combination of MS-based proteomics with in silico regulomics analyses can produce synergistic effects in the quest to understand how cells function. This is illustrated on a real life example showing how the MS-analysis and in silico promoter analysis can extend the list of candidates for signaling pathways, here the MAP kinase pathway.