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Liquid chromatography–mass spectrometry (LC–MS) has been widely used throughout biotherapeutic development. However, its implementation in GMP-compliant commercial quality control (QC) laboratories remains a challenge. In this publication, we describe the covalidation and implementation of an automated, high-throughput, and GMP compliant subunit LC–MS method for monitoring antibody oxidation for commercial product release and stability testing. To our knowledge, this is the first report describing the implementation of a high-resolution LC–MS method in commercial QC laboratories for product release and stability testing in the biopharmaceutical industry. This work paves the road for implementing additional LC–MS methods to modernize testing in commercial QC with more targeted control of product quality.

Glycation has been observed in antibody therapeutics manufactured by the fed-batch fermentation process. It not only increases the heterogeneity of antibodies, but also potentially affects product safety and efficacy. In this study, non-glycated and glycated fractions enriched from a monoclonal antibody (mAb1) as well as glucose-stressed mAb1 were characterized using a variety of biochemical, biophysical and biological assays to determine the effects of glycation on the structure and function of mAb1. Glycation was detected at multiple lysine residues and reduced the antigen binding activity of mAb1. Heavy chain Lys100, which is located in the complementary-determining region of mAb1, had the highest levels of glycation in both stressed and unstressed samples, and glycation of this residue was likely responsible for the loss of antigen binding based on hydrogen/deuterium exchange mass spectrometry analysis. Peptide mapping and intact liquid chromatography-mass spectrometry (LC-MS) can both be used to monitor the glycation levels. Peptide mapping provides site specific glycation results, while intact LC-MS is a quicker and simpler method to quantitate the total glycation levels and is more useful for routine testing. Capillary isoelectric focusing (cIEF) can also be used to monitor glycation because glycation induces an acidic shift in the cIEF profile. As expected, total glycation measured by intact LC-MS correlated very well with the percentage of total acidic peaks or main peak measured by cIEF. In summary, we demonstrated that glycation can affect the function of a representative IgG1 mAb. The analytical characterization, as described here, should be generally applicable for other therapeutic mAbs.

Methionine oxidation is a common posttranslational modification (PTM) of monoclonal antibodies (mAbs). Oxidation can reduce the in-vivo half-life, efficacy and stability of the product. Peptide mapping is commonly used to monitor the levels of oxidation, but this is a relatively time-consuming method. A high-throughput, automated subunit mass analysis method was developed to monitor antibody methionine oxidation. In this method, samples were treated with IdeS, EndoS and dithiothreitol to generate three individual IgG subunits (light chain, Fd’ and single chain Fc). These subunits were analyzed by reversed phase-ultra performance liquid chromatography coupled with an online quadrupole time-of-flight mass spectrometer and the levels of oxidation on each subunit were quantitated based on the deconvoluted mass spectra using the UNIFI software. The oxidation results obtained by subunit mass analysis correlated well with the results obtained by peptide mapping. Method qualification demonstrated that this subunit method had excellent repeatability and intermediate precision. In addition, UNIFI software used in this application allows automated data acquisition and processing, which makes this method suitable for high-throughput process monitoring and product characterization. Finally, subunit mass analysis revealed the different patterns of Fc methionine oxidation induced by chemical and photo stress, which makes it attractive for investigating the root cause of oxidation.

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 Phα1β will also be discussed.

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.

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.

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.

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.

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.

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.

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 Phα1β will also be discussed.

Tumor differentiation factor (TDF) is a protein produced by the pituitary and secreted into the blood stream. The mechanism of its action has still not been elucidated, although the associated protein receptor was identified. Furthermore, the TDF protein does not have any homology with other known proteins, and the crystal structure of TDF also is not available at this time. To gain some insight into the structure of this rather underexplored protein, we have performed a molecular dynamics simulation of a model TDF structure. The structural stability of this protein is evaluated as a function of time. The time dependent structural changes of four cysteine residues present in this structure also are explored.

Lactoferrin (Lf) was shown to exhibit its antiviral activity at an early phase of viral infection and a mechanism whereby the protein interacts with host cell surface molecules has been suggested. In this study, human Lf (HLf) and seven HLf-derived synthetic peptides (HLP) corresponding to the N-terminal domain of the native protein (1–47 amino acids sequence) were assayed for their capacity to prevent hepatitis B virus (HBV) infection and replication using the HepaRG and HepG2.2.2.15 cell lines. Of the series tested, four peptides showed 40–75% inhibition of HBV infection in HepaRG cells, HLP1–23, containing the GRRRR cationic cluster, being the most potent. Interestingly, this cluster is one of the two glycosaminoglycan binding sites of the native HLf involved in its antiviral activity; however, the mechanism of the HLP1–23 action was different from that of the full-length protein, the peptide inhibiting HBV infection when pre-incubated with the virus, while no effect was observed on the target cells. It is suggested that the cationic cluster is sufficient for the peptide to interact stably with negatively charged residues on the virion envelope, while the absence of the second glycosaminoglycan binding site prevents its efficient attachment to the cells. In conclusion, this peptide may constitute a non-toxic approach for potential clinical applications in inhibiting HBV entry by neutralizing the viral particles. J. Med. Virol. 85:780–788, 2013. © 2013 Wiley Periodicals, Inc.

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 post-translational modifications 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 mass spectrometry (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.

Precise determination of disulfide linkages between cysteine (Cys) residues in proteins is essential in the determination of protein structure. Therefore, a reliable automated method for the identification of disulfide bridges can serve as an important tool in the analysis of the tertiary structure of proteins of interest. Here, we describe the current and past methods used to identify disulfide bridges in proteins, with a focus on mass spectrometry (MS)-based methods and a particular emphasis on nanoliquid chromatography-tandem mass spectrometry (nanoLC-MS/MS)-based methods. We also show the development of an easy method based on the separation of disulfide-linked proteins by sodium dodecyl sulfate-polyacrylamide gel electrophoresis under denaturing and nonreducing conditions and selective in-gel digestion of proteins using reducing and nonreducing conditions, followed by analysis of the resulting peptide mixture by nanoACQUITY UPLC coupled to a quadrupole time-of-flight (QTOF) Micro mass spectrometer (nanoLC-MS/MS). Data-dependent analysis (DDA) nanoLC-MS/MS and information-dependent analysis (IDA) nanoLC-MS/MS were used for random and targeted identification of disulfide-linked peptides. Finally, an example of electrospray-MS (ESI-MS) and ESI-MS/MS-based determination of disulfide-linked peptides is shown.

Tumor differentiation factor (TDF) is a 17 kDa protein produced by the pituitary and secreted into the bloodstream, with no definitive function and incomplete characterization. TDF has the following four cysteine (Cys) residues: Cys17, Cys70, Cys97, and Cys98. To understand the function of TDF, we (1) overexpressed and characterized recombinant TDF (rTDF); (2) investigated native, secreted TDF; and (3) assessed potential disulfide connectivities using molecular modeling. Our results from Western blotting (WB) experiments suggest that rTDF is mostly expressed as insoluble, monomeric, and dimeric forms. Mass spectrometry analysis of the overexpressed rTDF identified a peptide that is a part of TDF protein. WB of the native, secreted TDF detected it as a 50 kDa band. In addition, investigation of TDF by molecular modeling suggests that the Cys residues may form disulfide bridges between Cys17–Cys98 and Cys70–Cys17.

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.

The combination of SDS-PAGE and MS is one of the most powerful and perhaps most frequently used gel-based proteomics approaches in protein identification. However, one drawback of this method is that separation takes place under denaturing and reducing (R) conditions and as a consequence, all proteins with identical apparent molecular mass (Mr) will run together. Therefore, low-abundant proteins may not be easily identified. Another way of investigating proteins by proteomics is by analyzing subproteomes from a total proteome such as phosphoproteomics, glycoproteomics, or disulfide proteomics. Here, we took advantage of the property of secreted proteins to form disulfide bridges and investigated disulfide-linked proteins, using SDS-PAGE under nonreducing (NR) conditions. We separated sera from normal subjects and from patients with various diseases by SDS-PAGE (NR) and (R) conditions, followed by LC-MS/MS analysis. Although we did not see any detectable difference between the sera separated by SDS-PAGE(R), we could easily identify the disulfide-linked proteins separated by SDS-PAGE (NR). LC-MS/MS analysis of the disulfide-linked proteins correctly identified haptoglobin (Hp), a disulfide-linked protein usually found as a heterotetramer or as a disulfide-linked heteropolymer. Western blotting under NR and R conditions using anti-Hp antibodies confirmed the LC-MS/MS experiments and further confirmed that upon reduction, the disulfide-linked Hp heterotetramers and polymers were no longer disulfide-linked polymers. These data suggest that simply by separating samples on SDS-PAGEunder NR conditions, a different, new proteomics subset can be revealed and then identified.

Tumor differentiation factor (TDF) is a pituitary protein that is secreted into the bloodstream and has an endocrine function. TDF and TDF-P1, a 20-residue peptide selected from the ORF of TDF, induce differentiation in human breast and prostate cancer cells, but not in other cells. TDF has no known mechanism of action. In our recent study, we identified heat shock 70 kDa proteins (HSP70s) as TDF receptors (TDF-Rs) in breast cancer cells. Therefore, we sought to investigate whether TDF-R candidates from prostate cancer cells are the same as those identified in breast cancer cells. Here, we used TDF-P1 to purify the potential TDF-R candidates by affinity purification chromatography from DU145 and PC3 steroid-resistant prostate cancer cells, LNCaP steroid-responsive prostate cancer cells, and nonprostate NG108 neuroblastoma and BLK CL.4 fibroblast-like cells. We identified the purified proteins by MS, and validated them by western blotting, immunofluorescence microscopy, immunoaffinity purification chromatography, and structural biology. We identified seven candidate proteins, of which three were from the HSP70 family. These three proteins were validated as potential TDF-R candidates in LNCaP steroid-responsive and in DU145 and PC3 steroid-resistant prostate cancer cells, but not in NG108 neuroblastoma and BLK CL.4 fibroblast-like cells. Our previous study and the current study suggest that GRP78, and perhaps HSP70s, are strong TDF-R candidates, and further suggest that TDF interacts with its receptors exclusively in breast and prostate cells, inducing cell differentiation through a novel, steroid-independent pathway. Structured digital abstract • TDF-P1 physicallyinteracts with GRP78and HSP70 by pulldown (Viewinteraction) • GRP78 binds to TDF-P1 by antibaitcoimmunoprecipitation (Viewinteraction) • TDF-P1 physicallyinteracts with GRP78, HSP8, HSP70, HSP90-beta, Sequestosome1 and valosin-containing-protein by pulldown (Viewinteraction)

Approximately 1/88 children are believed to be affected by Autism Spectrum Disorder (ASD). A more recent study suggests numbers as high as 1/50. With the increased diagnosis of ASD, treatment and u...

The field of proteomics and use of mass spectrometry as well as other proteomic techniques is continually growing, based on the interest of researchers for searching for potential biomarkers for numerous diseases and disorders. Currently protein biomarkers are not standardly used in clinical practice for diagnosing and monitoring neurodevelopmental disorders. The ability to predict the cause of a medical problem and aid in its treatment would be greatly increased with a biomarker or set of biomarkers. Most studies performed on neurodevelopmental disorders have been in the genomic field rather than in the proteomic realm. However, the few studies that have been performed in proteomics show promise for candidate neurodevelopmental protein biomarkers, both as research tools and in clinical use. Here, we describe potential protein biomarkers for neurodevelopmental disorders and the importance of proteomics in understanding neurodevelopmental disorders.

Infection with Hepatitis B virus (HBV) is the most common cause of liver disease in the world. Infection becomes chronic in up to 10 % of adults, with severe consequences on liver function, including inflammation, fibrosis, cirrhosis, and eventually hepatocellular carcinoma (HCC). HCC is a fast progressing disease causing the death of approximately one million patients annually; current treatment has very limited success, mainly due to late-stage diagnosis and poor screening methodologies. Therefore, unraveling the complex HBV-host cell interactions during progression of the disease is of crucial importance, not only to understand the mechanisms underlying carcinogenesis, but importantly, for the development of new biomarkers for prognostic and early diagnosis. This is an area of research strongly influenced by proteomic studies, which have benefited in the last decade from major technical improvements in accuracy of quantification and sensitivity, large-scale analysis of low-abundant proteins, such as those from clinical samples being now possible and widely applied. This work is a critical review of the impact of the proteomic studies on our current understanding of HBV-associated pathogenesis, diagnostics, and treatment.

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.

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.

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.

Infection with Hepatitis B virus (HBV) is the most common cause of liver disease in the world. Infection becomes chronic in up to 10 % of adults, with severe consequences on liver function, including inflammation, fibrosis, cirrhosis, and eventually hepatocellular carcinoma (HCC). HCC is a fast progressing disease causing the death of approximately one million patients annually; current treatment has very limited success, mainly due to late-stage diagnosis and poor screening methodologies. Therefore, unraveling the complex HBV-host cell interactions during progression of the disease is of crucial importance, not only to understand the mechanisms underlying carcinogenesis, but importantly, for the development of new biomarkers for prognostic and early diagnosis. This is an area of research strongly influenced by proteomic studies, which have benefited in the last decade from major technical improvements in accuracy of quantification and sensitivity, large-scale analysis of low-abundant proteins, such as those from clinical samples being now possible and widely applied. This work is a critical review of the impact of the proteomic studies on our current understanding of HBV-associated pathogenesis, diagnostics, and treatment.

Different kinds of yogurt contain different percentages of proteins. However, do they also contain different types of proteins? To answer to this question, we investigated the protein pattern in the soluble fraction of various yogurts. We found that many yogurts contain mostly two main bands: a ~20 kDa band and a ~15 kDa band. Proteomics analysis of these two bands led us to conclude that the 20 kDa band corresponds to lactoglobulin isoforms and the 15 kDa band corresponds to casein isoforms.

Receptor Tyrosine Kinases (RTKs) are transmembrane proteins that, upon stimulation by their soluble ligands dimerize or multimerize and autophosphorylate themselves on the cytoplasmic side and activate signal transduction pathways, which in turn trigger either nuclear, transcriptional responses or a cellular effect such as cytoskeletal remodeling. However, while the classical RTK pathway is well understood, the intracellular protein interaction events that lead to these responses are still not yet well understood.

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.

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.

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.

Proteins are the effector molecules of many cellular and biological processes and are thus very dynamic and flexible. Regulation of protein activity, structure, stability, and turnover is in part controlled by their post-translational modifications (PTMs). Common PTMs of proteins include phosphorylation, glycosylation, methylation, ubiquitination, acetylation, and oxidation. Understanding the biology of protein PTMs can help elucidate the mechanisms of many pathological conditions and provide opportunities for prevention, diagnostics, and treatment of these disorders. Prior to the era of proteomics, it was standard to use chemistry methods for the identification of protein modifications. With advancements in proteomic technologies, mass spectrometry has become the method of choice for the analysis of protein PTMs. In this brief review, we will highlight the biochemistry of PTMs with an emphasis on mass spectrometry.

Characterisation of proteins and whole proteomes can provide a foundation to our understanding of physiological and pathological states and biological diseases or disorders. Constant development of more reliable and accurate mass spectrometry (MS) instruments and techniques has allowed for better identification and quantification of the thousands of proteins involved in basic physiological processes. Therefore, MS-based proteomics has been widely applied to the analysis of biological samples and has greatly contributed to our understanding of protein functions, interactions, and dynamics, advancing our knowledge of cellular processes as well as the physiology and pathology of the human body. This review will discuss current proteomic approaches for protein identification and characterisation, including post-translational modification (PTM) analysis and quantitative proteomics as well as investigation of protein–protein interactions (PPIs).

The search for molecules that can act as potential biomarkers is increasing in the scientific community, including in the field of psychiatry. The field of proteomics is evolving and its indispensability for identifying biomarkers is clear. Among proteomic tools, mass spectrometry is the core technique for qualitative and quantitative identification of protein markers. While significant progress has been made in the understanding of biomarkers for neurodegenerative diseases such as Alzheimer’s disease, multiple sclerosis and Parkinson’s disease, psychiatric disorders have not been as extensively investigated. Recent and successful applications of mass spectrometry-based proteomics in fields such as cardiovascular disease, cancer, infectious diseases and neurodegenerative disorders suggest a similar path for psychiatric disorders. In this brief review, we describe mass spectrometry and its use in psychiatric biomarker research and highlight some of the possible challenges of undertaking this type of work. Further, specific examples of candidate biomarkers are highlighted. A short comparison of proteomic with genomic methods for biomarker discovery research is presented. In summary, mass spectrometry-based techniques may greatly facilitate ongoing efforts to understand molecular mechanisms of psychiatric disorders.

Autism spectrum disorders (ASDs) are increasing in incidence but have an incompletely understood etiology. Tools for uncovering clues to the cause of ASDs and means for diagnoses are valuable to the field. Mass Spectrometry (MS) has been a useful method for evaluating differences between individuals with ASDs versus matched controls. Different biological substances can be evaluated using MS, including urine, blood, saliva, and hair. This technique has been used to evaluate relatively unsupported hypotheses based on introduction of exogenous factors, such as opiate and heavy metal excretion theories of ASDs. MS has also been used to support disturbances in serotonin-related molecules, which have been more consistently observed in ASDs. Serotonergic system markers, markers for oxidative stress, cholesterol system disturbances, peptide hypo-phosphorylation and methylation have been measured using MS in ASDs, although further analyses with larger numbers of subjects are needed (as well as consideration of behavioral data). Refinements in MS and data analysis are ongoing, allowing for the possibility that future studies examining body fluids and specimens from ASD subjects could continue to yield novel insights. This review summarizes MS investigations that have been conducted to study ASD to date and provides insight into future promising applications for this technique, with focus on proteomic studies.

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.

Tumor Differentiation Factor (TDF) is a protein produced by the pituitary and secreted into the blood stream. TDF targets breast and prostate and induces cell differentiation. However, the mechanism of cell differentiation, the TDF receptor and the TDF pathway have not been adequately investigated. Here, we provide some insights about the possible composition of the TDF-R. TDF-R may be a protein complex, composed of GRP78, HSP70 and HSP90 proteins, and all three protein subunits have a docking site for TDF-P1. The question of whether the TDF-R complex is a stable or transient/inducible complex is currently being investigated.

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.

The combination of SDS-PAGE and MS is one of the most powerful and perhaps most frequently used gel-based proteomics approaches in protein identification. However, one drawback of this method is that separation takes place under denaturing and reducing (R) conditions and as a consequence, all proteins with identical apparent molecular mass (Mr) will run together. Therefore, low-abundant proteins may not be easily identified. Another way of investigating proteins by proteomics is by analyzing subproteomes from a total proteome such as phosphoproteomics, glycoproteomics, or disulfide proteomics. Here, we took advantage of the property of secreted proteins to form disulfide bridges and investigated disulfide-linked proteins, using SDS-PAGE under nonreducing (NR) conditions. We separated sera from normal subjects and from patients with various diseases by SDS-PAGE (NR) and (R) conditions, followed by LC-MS/MS analysis. Although we did not see any detectable difference between the sera separated by SDS-PAGE(R), we could easily identify the disulfide-linked proteins separated by SDS-PAGE (NR). LC-MS/MS analysis of the disulfide-linked proteins correctly identified haptoglobin (Hp), a disulfide-linked protein usually found as a heterotetramer or as a disulfide-linked heteropolymer. Western blotting under NR and R conditions using anti-Hp antibodies confirmed the LC-MS/MS experiments and further confirmed that upon reduction, the disulfide-linked Hp heterotetramers and polymers were no longer disulfide-linked polymers. These data suggest that simply by separating samples on SDS-PAGEunder NR conditions, a different, new proteomics subset can be revealed and then identified.

The secretome represents the set of proteins secreted into the extracellular space of cells. These proteins have been shown to play a major role in cell-cell communication. For example, recent observations revealed the presence of diffusible factors with proliferative properties in the secretome of cancer cells. Thus, a qualitative and quantitative analysis of the secretome could lead to the identification of these factors and consequently to the development of new therapeutic strategies. Here, we provide an automated simple and effective strategy to identify novel targets in the secretome of specifically treated cells using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Furthermore, we explore the supportive role of mass spectrometry (MS) in the development of functional assays of identified secreted target molecules. Simplicity is achieved by growing cells in medium free of serum, which eliminates the need to remove the most abundant serum proteins and at the same time reduces disturbing matrix effects. Upon identification of these factors, their validation and characterization will follow. Moreover, this approach can also lead to the identification of proteins abnormally secreted, shed, or oversecreted by cells as response to a stimulus. Furthermore, we also discuss the problems that one may encounter. Finally, we discuss the broad application of automated MS-based proteomics, particularly in cancer research, highlighting new horizons for the use of MS.

Measuring biomarkers to identify and assess illness is a strategy growing in popularity and relevance. Although already in clinical use for treating and predicting cancer, no biological measurement is used clinically for any psychiatric disorder. Biomarkers could predict the course of a medical problem, and aid in determining how and when to treat. Several studies have indicated that of candidate psychiatric biomarkers detected using proteomic techniques, cholesterol and associated proteins, specifically apolipoproteins (Apos), may be of interest. Cholesterol is necessary for brain development and its synthesis continues at a lower rate in the adult brain. Apos are the protein component of lipoproteins responsible for lipid transport. There is extensive evidence that the levels of cholesterol and Apos may be disturbed in psychiatric disorders, including autistic spectrum disorders (ASD). Here, we describe putative serum biomarkers for psychiatric disorders, and the role of cholesterol and Apos in central nervous system (CNS) disorders.

In a proteomics experiment, reduction and alkylation of proteins prior to enzymatic digestion ensures high sequence coverage of that protein during a database search. However, the alkylation procedure uses an excess of an alkylating agent such as iodoacetamide (IAA). Therefore, although other amino acids are alkylated, these modified peptides are not identified in a database search. Here we show that a large proportion of peptides are mono- and di-alkylated by IAA and therefore not identified via a database search. The first alkylation consistently takes place at the N-terminal amino acid. Therefore, we propose that during the database search conducted during a proteomics experiment, one should have the option of searching for any alkylated peptide at the N-terminal amino acid.

Tumor differentiation factor (TDF) is a recently discovered protein, produced by the pituitary gland and secreted into the bloodstream. TDF and TDF-P1, a 20-amino acid peptide selected from the open reading frame of TDF, induce differentiation in human breast and prostate cancer cells but not in other cells. TDF protein has no identified site of action or receptor, and its mechanism of action is unknown. Here, we used TDF-P1 to purify and identify potential TDF receptor (TDF-R) candidates from MCF7 steroid-responsive breast cancer cells and non-breast HeLa cancerous cells using affinity purification chromatography (AP), and mass spectrometry (MS). We identified four candidate proteins from the 70-kDa heat shock protein (HSP70) family in MCF7 cells. Experiments in non-breast HeLa cancerous cells did not identify any TDF-R candidates. AP and MS experiments were validated by AP and Western blotting (WB). We additionally looked for TDF-R in steroid-resistant BT-549 cells and human dermal fibroblasts (HDF-a) using AP and WB. TDF-P1 interacts with potential TDF-R candidates from MCF7 and BT-549 breast cells but not from HeLa or HDF-a cells. Immunofluorescence (IF) experiments identified GRP78, a TDF-R candidate, at the cell surface of MCF7, BT-549 breast cells, and HeLa cells but not HDF-a cells. IF of other HSP70 proteins demonstrated labeling on all four cell types. These results point toward GRP78 and HSP70 proteins as strong TDF-R candidates and suggest that TDF interacts with its receptor, exclusively on breast cells, through a steroid-independent pathway.