Mass Spectrometry- and Computational Structural Biology-Based Investigation of Proteins and Peptides.

Recent developments of mass spectrometry (MS) allow us to identify, estimate, and characterize proteins and protein complexes. At the same time, structural biology helps to determine the protein structure and its structure-function relationship. Together, they aid to understand the protein structure, property, function, protein-complex assembly, protein-protein interaction, and dynamics. The present chapter is organized with illustrative results to demonstrate how experimental mass spectrometry can be combined with computational structural biology for detailed studies of protein's structures. We have used tumor differentiation factor protein/peptide as ligand and Hsp70/Hsp90 as receptor protein as examples to study ligand-protein interaction. To investigate possible protein conformation, we will describe two proteins-lysozyme and myoglobin. As an application of MS-based assignment of disulfide bridges, the case of the spider venom polypeptide Phα1ß will also be discussed.

Role of Mass Spectrometry in Investigating a Novel Protein: The Example of Tumor Differentiation Factor (TDF).

Better understanding of central nervous system (CNS) molecules can include the identification of new molecules and their receptor systems. Discovery of novel proteins and elucidation of receptor targets can be accomplished using mass spectrometry (MS). We describe a case study of such a molecule, which our lab has studied using MS in combination with other protein identification techniques, such as immunohistochemistry and Western Blotting. This molecule is known as tumor differentiation factor (TDF), a recently-found protein secreted by the pituitary into the blood. TDF mRNA has been detected in brain; not heart, placenta, lung, liver, skeletal muscle, or pancreas. Currently TDF has an unclear function, and prior to our studies, its localization was only minimally understood, with no understanding of receptor targets. We investigated the distribution of TDF in the rat brain using immunohistochemistry (IHC) and immunofluorescence (IF). TDF protein was detected in pituitary and most other brain regions, in specific neurons but not astrocytes. We found TDF immunoreactivity in cultured neuroblastoma, not astrocytoma. These data suggest that TDF is localized to neurons, not to astrocytes. Our group also conducted studies to identify the TDF receptor (TDF-R). Using LC-MS/MS and Western blotting, we identified the members of the Heat Shock 70-kDa family of proteins (HSP70) as potential TDF-R candidates in both MCF7 and BT-549 human breast cancer cells (HBCC) and PC3, DU145, and LNCaP human prostate cancer cells (HPCC), but not in HeLa cells, NG108 neuroblastoma, or HDF-a and BLK CL.4 cells fibroblasts or fibroblast-like cells. These studies have combined directed protein identification techniques with mass spectrometry to increase our understanding of a novel protein that may have distinct actions as a hormone in the body and as a growth factor in the brain.

Protein Biomarkers in Major Depressive Disorder: An Update.

Major depressive disorder (MDD) is common. Despite numerous available treatments, many individuals fail to improve clinically. Diagnosis of MDD continues to be commonly accomplished via behavioral rather than biological methods. Biomarkers may provide objective diagnosis of MDD, and could include measurements of genes, proteins, and patterns of brain activity. Proteomic analysis and validation of biomarkers is less explored than other areas of biomarker research in MDD. Mass spectrometry (MS) is a comprehensive, unbiased means of proteomic analysis, which can be complemented by directed protein measurements, such as Western Blotting. Prior studies have focused on MS analysis of several human biomaterials in MDD, including human post-mortem brain, cerebrospinal fluid (CSF), blood components, and urine. Further studies utilizing MS and proteomic analysis in MDD may help solidify and establish biomarkers for use in diagnosis, identification of new treatment targets, and understanding of the disorder. A biomarker or a biomarker signature that facilitates a convenient and inexpensive predictive test for depression treatment response is highly desirable.

Proteomics and Non-proteomics Approaches to Study Stable and Transient Protein-Protein Interactions.

Of the 25,000-30,000 human genes, about 2 % code for proteins. However, there are about 1-2 million protein entities. This is primarily due to alternative splicing, post-translational modifications (PTMs) or protein-protein interactions. Proteomics sets out to identify proteins, their sequence and known modifications as well as their quantitation in a biological sample for the purpose of understanding biological processes, protein cellular functions, and their physiological and pathological involvement in diseases.Proteins interact at the molecular level with other proteins, nucleic acids, lipids, carbohydrates and metabolites to perform numerous cellular activities. Protein complexes can consist of sets of more stably (stable PPIs) and less stably (transient PPIs) interacting proteins or combination of both. Here, we discuss the proteomics and non-proteomics approaches to study stable and transient PPIs.

Identification of Posttranslational Modifications (PTMs) of Proteins by Mass Spectrometry.

There are only 30,000 human genes, which, according to the central dogma from biology, it means that there should be 30,000 mRNA and 30,000 proteins. However, there are at least 1-2 million protein entities that are expressed in a cell at a given time. This is primarily due to alternative splicing in different cells and tissues, which may lead to expression of different protein isoforms within one cell, but also different protein isoforms in different tissues. A new level of complexity of proteins and protein isoforms is then given by posttranslational modifications (PTMs) of proteins. Here, we discuss the PTMs in proteins and how they are identified by mass spectrometry and proteomics, with specific examples on identification of acetylation, phosphorylation, glycosylation, alkylation, hydroxinonenal-modification or assignment of intramolecular and intermolecular disulfide bridges.

Mass Spectrometry for the Study of Autism and Neurodevelopmental Disorders.

Mass spectrometry (MS) has been increasingly used to study central nervous system (CNS) disorders, including autism spectrum disorders (ASDs). The first studies of ASD using MS focused on the identification of external toxins, but current research is more directed at understanding endogenous protein changes that occur in ASD (ASD proteomics). This chapter focuses on how MS has been used to study ASDs, with particular focus on proteomic analysis. Other neurodevelopmental disorders have been investigated using this technique, including genetic syndromes associated with autism such as fragile X syndrome (FXS) and Smith-Lemli-Opitz Syndrome (SLOS).

Mass Spectrometry for Proteomics-Based Investigation.

Within the past years, we have witnessed a great improvement is mass spectrometry (MS) and proteomics approaches in terms of instrumentation, protein fractionation, and bioinformatics. With the current technology, protein identification alone is no longer sufficient. Both scientists and clinicians want not only to identify the proteins, but also to identify the protein's post-translational modifications (PTMs), protein isoforms, protein truncation, protein-protein interactions (PPI), and protein quantitation. Here, we describe the principle of MS and proteomics, and strategies to identify proteins, protein's PTMs, protein isoforms, protein truncation, PPIs, and protein quantitation. We also discuss the strengths and weaknesses within this field. Finally, in our concluding remarks we assess the role of mass spectrometry and proteomics in the scientific and clinical settings, in the near future. This chapter provides an introduction and overview for subsequent chapters that will discuss specific MS proteomic methodologies and their application to specific medical conditions. Other chapters will also touch upon areas that expand beyond proteomics, such as lipidomics and metabolomics.

Comparative two-dimensional polyacrylamide gel electrophoresis of the salivary proteome of children with autism spectrum disorder.

In the last decades, prevalence of autism spectrum disorder (ASD) has been on the rise. However, clear aetiology is still elusive and improvements in early diagnosis are needed. To uncover possible biomarkers present in ASD, we used two-dimensional polyacrylamide gel electrophoresis and nanoliquid chromatography-tandem mass spectrometry (nanoLC-MS/MS), to compare salivary proteome profiling of children with ASD and controls. A total of 889 spots were compared and only those spots with a fold change ≥1.7 and a P-value <0.05 or a fold change of ≥3.0 between ASD cases and controls were analysed by nanoLC-MS/MS. Alpha-amylase, CREB-binding protein, p532, Transferrin, Zn alpha2 glycoprotein, Zymogen granule protein 16, cystatin D and plasminogen were down-regulated in ASD. Increased expression of proto-oncogene Frequently rearranged in advanced T-cell lymphomas 1 (FRAT1), Kinesin family member 14, Integrin alpha6 subunit, growth hormone regulated TBC protein 1, parotid secretory protein, Prolactin-inducible protein precursor, Mucin-16, Ca binding protein migration inhibitory factor-related protein 14 (MRP14) was observed in individuals with ASD. Many of the identified proteins have previously been linked to ASD or were proposed as risk factors of ASD at the genetic level. Some others are involved in pathological pathways implicated in ASD causality such as oxidative stress, lipid and cholesterol metabolism, immune system disturbances and inflammation. These data could contribute to protein signatures for ASD presence, risk and subtypes, and advance understanding of ASD cause as well as provide novel treatment targets for ASD.

The potential of biomarkers in psychiatry: focus on proteomics.

The etiology and pathogenesis of many psychiatric disorders are unclear with many signaling pathways and complex interactions still unknown. Primary information provided from gene expression or brain activity imaging experiments is useful, but can have limitations. There is a current effort focusing on the discovery of diagnostic and prognostic proteomic potential biomarkers for psychiatric disorders. Despite this work, there is still no biological diagnostic test available for any mental disorder. Biomarkers may advance the care of psychiatric illnesses and have great potential to knowledge of psychiatric disorders but several drawbacks must be considered. Here, we describe the potential of proteomic biomarkers for better understanding and diagnosis of psychiatric disorders and current putative biomarkers for schizophrenia, depression, autism spectrum disorder and attention deficit/hyperactivity disorder.

Protein-protein interactions: switch from classical methods to proteomics and bioinformatics-based approaches.

Following the sequencing of the human genome and many other organisms, research on protein-coding genes and their functions (functional genomics) has intensified. Subsequently, with the observation that proteins are indeed the molecular effectors of most cellular processes, the discipline of proteomics was born. Clearly, proteins do not function as single entities but rather as a dynamic network of team players that have to communicate. Though genetic (yeast two-hybrid Y2H) and biochemical methods (co-immunoprecipitation Co-IP, affinity purification AP) were the methods of choice at the beginning of the study of protein-protein interactions (PPI), in more recent years there has been a shift towards proteomics-based methods and bioinformatics-based approaches. In this review, we first describe in depth PPIs and we make a strong case as to why unraveling the interactome is the next challenge in the field of proteomics. Furthermore, classical methods of investigation of PPIs and structure-based bioinformatics approaches are presented. The greatest emphasis is placed on proteomic methods, especially native techniques that were recently developed and that have been shown to be reliable. Finally, we point out the limitations of these methods and the need to set up a standard for the validation of PPI experiments.

Mass spectrometry investigation of glycosylation on the NXS/T sites in recombinant glycoproteins.

We used a targeted proteomics approach to investigate whether introduction of new N-linked glycosylation sites in a chimeric protein influence the glycosylation of the existing glycosylation sites. To accomplish our goals, we over-expressed and purified a chimeric construct that contained the Fc region of the IgG fused to the exons 7 & 8 of mouse ZP3 (IgG-Fc-ZP3E7 protein). Immunoglobulin heavy chain (IgG-HC protein) was used as control. We then analyzed the IgG-HC and IgG-Fc-ZP3E7 proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and by Western blotting (WB). We concluded that in control experiments, the glycosylation site was occupied as expected. However, in the IgG-Fc-ZP3E7 protein, we concluded that only one out of three NXS/T glycosylation sites is occupied by N-linked oligosaccharides. We also concluded that in the IgG-Fc-ZP3E7 protein, upon introduction of additional potential NXS/T glycosylation sites within its sequence, the original NST/S glycosylation site from the Fc region of the IgG-Fc-ZP3E7 protein is no longer glycosylated. The biomedical significance of our findings is discussed.

A pilot proteomic study of protein markers in autism spectrum disorder.

Autism spectrum disorder (ASD) diagnosis is increasing, with 1/88 children believed to be affected by the disorder, with a most recent survey suggesting numbers as high as 1/50. Treatment and understanding of ASD causes is a pressing health concern. ASD protein biomarkers may provide clues about ASD cause. Protein biomarkers for ASDs could be used for ASD diagnosis, subtyping, treatment monitoring, and identifying therapeutic targets. Here, we analyzed the sera from seven children with ASD and seven matched controls using Tricine gel electrophoresis (Tricine-PAGE) and LC-MS/MS. Overall, we found increased levels of apolipoproteins ApoA1 and ApoA4, involved in cholesterol metabolism and of serum paraoxanase/arylesterase 1, involved in preventing oxidative damage, in the sera of children with ASD, compared with their matched controls. All three proteins are predicted to interact with each other and are parts of high-density lipoproteins. Further studies are needed to validate these findings in larger subject numbers.

Characterization of tumor differentiation factor (TDF) and its receptor (TDF-R).

Tumor differentiation factor (TDF) is an under-investigated protein produced by the pituitary with no definitive function. TDF is secreted into the bloodstream and targets the breast and prostate, suggesting that it has an endocrine function. Initially, TDF was indirectly discovered based on the differentiation effect of alkaline pituitary extracts of the mammosomatotropic tumor MtTWlO on MTW9/PI rat mammary tumor cells. Years later, the cDNA clone responsible for this differentiation activity was isolated from a human pituitary cDNA library using expression cloning. The cDNA encoded a 108-amino-acid polypeptide that had differentiation activity on MCF7 breast cancer cells and on DU145 prostate cancer cells in vitro and in vivo. Recently, our group focused on identification of the TDF receptor (TDF-R). As potential TDF-R candidates, we identified the members of the Heat Shock 70-kDa family of proteins (HSP70) in both MCF7 and BT-549 human breast cancer cells (HBCC) and PC3, DU145, and LNCaP human prostate cancer cells (HPCC), but not in HeLa cells, NG108 neuroblastoma, or HDF-a and BLK CL.4 cells fibroblasts or fibroblast-like cells. Here we review the current advances on TDF, with particular focus on the structural investigation of its receptor and on its functional effects on breast and prostate cells.

Biomarkers in major depressive disorder: the role of mass spectrometry.

Major depressive disorder (MDD) is common. Despite numerous available treatments, many individuals fail to improve clinically. MDD continues to be diagnosed exclusively via behavioral rather than biological methods. Biomarkers-which include measurements of genes, proteins, and patterns of brain activity-may provide an important objective tool for the diagnosis of MDD or in the rational selection of treatments. Proteomic analysis and validation of its results as biomarkers is less explored than other areas of biomarker research in MDD. Mass spectrometry (MS) is a comprehensive, unbiased means of proteomic analysis, which can be complemented by directed protein measurements, such as Western Blotting. Prior studies have focused on MS analysis of several human biomaterials in MDD, including human post-mortem brain, cerebrospinal fluid (CSF), blood components, and urine. Further studies utilizing MS and proteomic analysis in MDD may help solidify and establish biomarkers for use in diagnosis, identification of new treatment targets, and understanding of the disorder. The ultimate goal is the validation of a biomarker or a biomarker signature that facilitates a convenient and inexpensive predictive test for depression treatment response and helps clinicians in the rational selection of next-step treatments.

Utility of computational structural biology in mass spectrometry.

Recent developments of mass spectrometry (MS) allow us to identify, estimate, and characterize proteins and protein complexes. At the same time, structural biology helps to determine the protein structure and its structure-function relationship. Together, they aid to understand the protein structure, property, function, protein-complex assembly, protein-protein interaction and dynamics. The present chapter is organized with illustrative results to demonstrate how experimental mass spectrometry can be combined with computational structural biology for detailed studies of protein's structures. We have used tumor differentiation factor protein/peptide as ligand and Hsp70/Hsp90 as receptor protein as examples to study ligand-protein interaction. To investigate possible protein conformation we will describe two proteins, lysozyme and myoglobin.

Mass spectrometric analysis of post-translational modifications (PTMs) and protein-protein interactions (PPIs).

Of the 25,000-30,000 human genes, about 2 % code for proteins. However, there are about one to two million protein entities. This is primarily due to alternative splicing and post-translational modifications (PTMs). Identifying all these modifications in one proteome at a particular time point during development or during the transition from normal to cancerous cells is a great challenge to scientists. In addition, identifying the biological significance of all these modifications, as well as their nature, such as stable versus transient modifications, is an even more challenging. Furthermore, interaction of proteins and protein isoforms that have one or more stable or transient PTMs with other proteins and protein isoforms makes the study of proteins daunting and complex. Here we review some of the strategies to study proteins, protein isoforms, protein PTMs, and protein-protein interactions (PPIs). Our goal is to provide a thorough understanding of these proteins and their isoforms, PTMs and PPIs and to shed light on the biological significance of these factors.

Investigating a novel protein using mass spectrometry: the example of tumor differentiation factor (TDF).

Better understanding of central nervous system (CNS) molecules can include the identification of new molecules and their receptor systems. Discovery of novel proteins and elucidation of receptor targets can be accomplished using mass spectrometry (MS). We describe a case study of such a molecule, which our lab has studied using MS in combination with other protein identification techniques, such as immunohistochemistry (IHC) and Western blotting. This molecule is known as tumor differentiation factor (TDF), a recently-found protein secreted by the pituitary into the blood. TDF mRNA has been detected in brain; not heart, placenta, lung, liver, skeletal muscle, or pancreas. Currently TDF has an unclear function, and prior to our studies, its localization was only minimally understood, with no understanding of receptor targets. We investigated the distribution of TDF in the rat brain using IHC and immunofluorescence (IF). TDF protein was detected in pituitary and most other brain regions, in specific neurons but not astrocytes. We found TDF immunoreactivity in cultured neuroblastoma, not astrocytoma. These data suggest that TDF is localized to neurons, not to astrocytes. Our group also conducted studies to identify the TDF receptor (TDF-R). Using LC-MS/MS and Western blotting, we identified the members of the Heat Shock 70-kDa family of proteins (HSP70) as potential TDF-R candidates in both MCF7 and BT-549 human breast cancer cells (HBCC) and PC3, DU145, and LNCaP human prostate cancer cells (HPCC), but not in HeLa cells, NG108 neuroblastoma, or HDF-a and BLK CL.4 cell fibroblasts or fibroblast-like cells. These studies have combined directed protein identification techniques with mass spectrometry to increase our understanding of a novel protein that may have distinct actions as a hormone in the body and as a growth factor in the brain.

Mass spectrometry for proteomics-based investigation.

Within the past years, we have witnessed a great improvement in mass spectrometry (MS) and proteomics approaches in terms of instrumentation, protein fractionation, and bioinformatics. With the current technology, protein identification alone is no longer sufficient. Both scientists and clinicians want not only to identify proteins but also to identify the protein's posttranslational modifications (PTMs), protein isoforms, protein truncation, protein-protein interaction (PPI), and protein quantitation. Here, we describe the principle of MS and proteomics and strategies to identify proteins, protein's PTMs, protein isoforms, protein truncation, PPIs, and protein quantitation. We also discuss the strengths and weaknesses within this field. Finally, in our concluding remarks we assess the role of mass spectrometry and proteomics in scientific and clinical settings in the near future. This chapter provides an introduction and overview for subsequent chapters that will discuss specific MS proteomic methodologies and their application to specific medical conditions. Other chapters will also touch upon areas that expand beyond proteomics, such as lipidomics and metabolomics.

Mass spectrometry for the study of autism and neurodevelopmental disorders.

Mass spectrometry (MS) has been increasingly used to study central nervous system disorders, including autism spectrum disorders (ASDs). The first studies of ASD using MS focused on the identification of external toxins, but current research is more directed at understanding endogenous protein changes that occur in ASD (ASD proteomics). This chapter focuses on how MS has been used to study ASDs, with particular focus on proteomic analysis. Other neurodevelopmental disorders have been investigated using this technique, including genetic syndromes associated with autism such as fragile X syndrome and Smith-Lemli-Opitz syndrome.

Investigation of stable and transient protein-protein interactions: Past, present, and future.

This article presents an overview of the literature and a review of recent advances in the analysis of stable and transient protein-protein interactions (PPIs) with a focus on their function within cells, organs, and organisms. The significance of PTMs within the PPIs is also discussed. We focus on methods to study PPIs and methods of detecting PPIs, with particular emphasis on electrophoresis-based and MS-based investigation of PPIs, including specific examples. The validation of PPIs is emphasized and the limitations of the current methods for studying stable and transient PPIs are discussed. Perspectives regarding PPIs, with focus on bioinformatics and transient PPIs are also provided.