PROTEOMICS

Proteomics data in vitiligo: a scoping review

An unbiased screening of which proteins are deregulated in vitiligo using proteomics can offer an enormous value. It could not only reveal robust biomarkers for detecting disease activity but can also identify which patients are most likely to respond to treatments. We performed a scoping review searching for all articles using proteomics in vitiligo. Eight manuscripts could be identified. Unfortunately, very limited overlap was found in the differentially expressed proteins between studies (15 out of 272; 5,51%) with variable degrees of the type of proteins and a substantial variety in the prevalence of acute phase proteins (range: 6-65%). Proteomics research has therefore brought little corroborating evidence on which proteins are differentially regulated between vitiligo patients and healthy controls or between active and stable vitiligo patients. While a limited patient size is an obvious weakness for several studies, an incomplete description of patient characteristics is an unfortunate and avoidable shortcoming. Additionally, the variations in the used methodology and analyses may further contribute to the overall observed variability. Nonetheless, more recent studies investigating the response to treatment seem to be more robust, as more differentially expressed proteins that have previously been confirmed to be involved in vitiligo were found. The further inclusion of proteomics analyses in clinical trials is recommended to increase insights into the pathogenic mechanisms in vitiligo and identify reliable biomarkers or promising drug targets. A harmonization in the study design, reporting and proteomics methodology could vastly improve the value of vitiligo proteomics research.

Defining atherosclerotic plaque biology by mass spectrometry-based omics approaches

Atherosclerosis is the principal cause of vascular diseases and one of the leading causes of worldwide death. Even though several insights into its natural course, risk factors and interventions have been identified, it is still an ongoing global pandemic. Since the structure and biochemical composition of the plaques show high heterogeneity, a comprehensive understanding of the intraplaque composition, its microenvironment, and the mechanisms of the progression and instability across different vascular beds at their progression stages is crucial for better risk stratification and treatment modalities. Even though several cell-based studies, animal studies, and extensive multicentric population studies have been conducted concerning cardiovascular diseases for assessing the risk factors and plaque biology, the studies on human clinical samples are very limited. New novel approaches utilize samples from percutaneous coronary interventions, which could possibly gain more access to clinical samples at different stages of the diseases without complex invasive resections. As an emerging technological platform in disease discovery research, mass spectrometry-based omics technologies offer capabilities for a comprehensive understanding of the mechanisms linked to several vascular diseases. Here, we discuss the cellular and molecular processes of atherosclerosis, different mass spectrometry-based omics approaches, and the studies mostly done on clinical samples of atheroma plaque using mass spectrometry-based proteomics, metabolomics and lipidomics approaches.

Updates of Genomics and Proteomics of Parathyroid Carcinoma

Parathyroid carcinoma is a rare disease that needs an additional diagnostic tool and wide therapeutic options. The genomics and proteomics approach may help to find the tools to improve the prognosis of the disease by early detection and metastatic control. The findings from genomics were mainly CDC73, PRUNE2, CCND1, and genes related to PI3K/AKT/mTOR and Wnt pathways. CDC73, PRUNE2, and CCND1 were closely related to each other, and PRUNE2 and CCND1 genes are related to expression levels of parafibromin protein, which may aid in supporting the definite diagnosis of the disease. PI3K/AKT/mTOR and Wnt pathways could be a potential therapeutic target for the disease, which needs further basket trials to prove the concept. In this review, current findings from genomics and proteomics studies in parathyroid carcinoma were reviewed.

Metabolic Functions of Lysine 2-Hydroxyisobutyrylation

Lysine 2-hydroxyisobutyrylation (Khib) is one of the newly identified post-translational modifications (PTMs) primitively identified by mass spectrometry (MS). Research in animals suggests that histone Khib is related to regulation of chromatin and cellular functions. However, there is no review to summarize and elaborate on the current understanding of Khib. In this review, we start with the basic description of Khib, such as sequence preference and subcellular localization. We then analyze the lysine 2-hydroxyisobutyrylated sites with the purpose of learning its functions and activities. We finally discuss the regulation toward Khib and the way it regulates, thus opening an avenue for us to illustrate the diverse cellular metabolites associated with (Khib).

Ex Vivo Equine Cartilage Explant Osteoarthritis Model: A Metabolomics and Proteomics Study

Osteoarthritis is an age-related degenerative musculoskeletal disease characterized by loss of articular cartilage, synovitis, and subchondral bone sclerosis. Osteoarthritis pathogenesis is yet to be fully elucidated with no osteoarthritis-specific biomarkers in clinical use. Ex vivo equine cartilage explants (n = 5) were incubated in tumor necrosis factor-α (TNF-α)/interleukin-1β (IL-1β)-supplemented culture media for 8 days, with the media removed and replaced at 2, 5, and 8 days. Acetonitrile metabolite extractions of 8 day cartilage explants and media samples at all time points underwent one-dimensional (1D) ¹H nuclear magnetic resonance metabolomic analysis, with media samples also undergoing mass spectrometry proteomic analysis. Within the cartilage, glucose and lysine were elevated following TNF-α/IL-1β treatment, while adenosine, alanine, betaine, creatine, myo-inositol, and uridine decreased. Within the culture media, 4, 4, and 6 differentially abundant metabolites and 154, 138, and 72 differentially abundant proteins were identified at 1–2, 3–5, and 6–8 days, respectively, including reduced alanine and increased isoleucine, enolase 1, vimentin, and lamin A/C following treatment. Nine potential novel osteoarthritis neopeptides were elevated in the treated media. Implicated pathways were dominated by those involved in cellular movement. Our innovative study has provided insightful information on early osteoarthritis pathogenesis, enabling potential translation for clinical markers and possible new therapeutic targets.

Characterizing Intracellular Proteomes for Microbes: An Experimental Approach Using Label-Free Protein Quantitation

Genomic and transcriptomic studies generate a rich source of molecular information; however, neither a static genome nor the presence of a messenger RNA provides the most direct insight into the functional state of a microbial cell at any given time. Rather, it is the ensemble of proteins (i.e., proteome) that is the primary workhorse for most biological processes that are concurrent and coordinately active in a living cell. Currently, mass-spectrometry-based (MS) technologies provide unprecedented information into the composition of the proteome, shedding light on the numerous complex biological processes actively shaping observed phenotypes. Herein, we detail a protocol for the exploration of intracellular proteomes through the large-scale, unbiased identification of proteins and their relative abundances using liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS). In general, this protocol is applicable to both microbial and eukaryotic systems.

Omics approaches for microalgal applications: Prospects and challenges

In recent impetus of phycological research, microalgae have emerged as a potential candidate for various arena of application-driven research. Omics-based tactics are used for disentangling the regulation and network integration for biosynthesis/degradation of metabolic precursors, intermediates, end products, and identifying the networks that regulate the metabolic flux. Multi-omics coupled with data analytics have facilitated understanding of biological processes and allow ample access to diverse metabolic pathways utilized for genetic manipulations making microalgal factories more efficient. The present review discusses state-of-art "Algomics" and the prospect of microalgae and their role in symbiotic association by using omics approaches including genomics, transcriptomics, proteomics and metabolomics. Microalgal based uni- and multi-omics approaches are critically analyzed in wastewater treatment, metal toxicity and remediation, biofuel production, and therapeutics to provide an imminent outlook for an array of environmentally sustainable and economically viable microalgal applications.

Quantitative proteomics analysis of sporadic parathyroid adenoma tissue samples

OBJECTIVE

Molecular pathogenesis of parathyroid tumors is incompletely understood. Identification of novel molecules and understanding their role in parathyroid tumorigenesis by proteomics approach would be informative with potential clinical implications.

METHOD

Adenomatous (n = 5) and normal (n = 2) parathyroid tissue lysates were analyzed for protein profile by LC-MS/MS method and the proteins were classified using bioinformatics tools such as PANTHER and toppfun functional enrichment tool. Identified proteins were further validated by western blotting and qRT-PCR (n = 20).

RESULT

Comparative proteomics analysis revealed that a total of 206 proteins (74 upregulated and 132 downregulated) were differentially expressed (≥ twofold change) in adenomas. Bioinformatics analysis revealed that 48 proteins were associated with plasma membrane, 49 with macromolecular complex, 39 were cytoplasm, 38 were organelle related, 21 were cell junction and 10 were extracellular proteins. These proteins belonged to a diverse protein family such as enzymes, transcription factors, cell signalling, cell adhesion, cytoskeleton proteins, receptors, and calcium-binding proteins. The major biological processes predicted for the proteins were a cellular, metabolic and developmental process, cellular localization, and biological regulation. The differentially expressed proteins were found to be associated with MAPK, phospholipase C (PLC) and phosphatidylinositol (PI) signalling pathways, and with chromatin organization. Western blot and qRT-PCR analysis of three proteins (DNAJC2, ACO2, and PRDX2) validated the LC-MS/MS findings.

CONCLUSION

This exploratory study demonstrates the feasibility of proteomics approach in finding the dysregulated proteins in benign parathyroid adenomas, and our preliminary results suggest that MAPK, PLC and PI signalling pathways and chromatin organization are involved in parathyroid tumorigenesis.

TDP-43 post-translational modifications in health and disease

INTRODUCTION

Nuclear factor TDP-43 is a ubiquitously expressed RNA binding protein that plays a key causative role in several neurodegenerative diseases, especially in the ALS/FTD spectrum. In addition, its aberrant aggregation and expression has been recently observed in other type of diseases, such as myopathies and Niemann-Pick C, a lysosomal storage disease. Areas covered: This review aims to specifically cover the post-translational modifications (PTMs) that can affect TDP-43 function and cellular status both in health and disease. To this date, these include phosphorylation, formation of C-terminal fragments, disulfide bridge formation, ubiquitination, acetylation, and sumoylation. Recently published articles on these subjects have been reviewed in this manuscript. Expert opinion: Targeting aberrant TDP-43 expression in neurodegenerative diseases is a very challenging task due to the fact that both its overexpression and downregulation are considerably toxic to cells. This characteristic makes it difficult to therapeutically target this protein in a generalized manner. An alternative approach could be the identification of specific aberrant PTMs that promote its aggregation or toxicity, and developing novel therapeutic approaches toward their selective modification.

Proteome-wide identification of lysine 2-hydroxyisobutyrylation reveals conserved and novel histone modifications in Physcomitrella patens

Protein lysine 2-hydroxyisobutyrylation (K_hib) is a newly identified post-translational modification found in animal and yeast cells. Previous research suggested that histone K_hib is involved in male cell differentiation and plays a critical role in the regulation of chromatin functions in animals. However, information regarding protein K_hib in plants is still limited. In this study, using a specific antibody and LC-MS/MS methods, we identified 11,976 K_hib sites in 3,001 proteins in Physcomitrella patens. The bioinformatics analysis indicated that these K_hib-modified proteins were involved in a wide range of molecular functions and cellular processes, and showed diverse subcellular localizations. Furthermore, an comparism of K_hib sites in histone proteins among human, mouse and P. patens found conserved sites in the H3 and H4 histone proteins and novel sites in H1, H2A and H2B histone proteins in P. patens. This is the first report on K_hib post-translational modifications in plants, and the study provides a comprehensive profile of K_hib sites in histone and non-histone proteins in Physcomitrella patens.

Fungal Biofilms and Polymicrobial Diseases

Biofilm formation is an important virulence factor for pathogenic fungi. Both yeasts and filamentous fungi can adhere to biotic and abiotic surfaces, developing into highly organized communities that are resistant to antimicrobials and environmental conditions. In recent years, new genera of fungi have been correlated with biofilm formation. However, Candida biofilms remain the most widely studied from the morphological and molecular perspectives. Biofilms formed by yeast and filamentous fungi present differences, and studies of polymicrobial communities have become increasingly important. A key feature of resistance is the extracellular matrix, which covers and protects biofilm cells from the surrounding environment. Furthermore, to achieve cell–cell communication, microorganisms secrete quorum-sensing molecules that control their biological activities and behaviors and play a role in fungal resistance and pathogenicity. Several in vitro techniques have been developed to study fungal biofilms, from colorimetric methods to omics approaches that aim to identify new therapeutic strategies by developing new compounds to combat these microbial communities as well as new diagnostic tools to identify these complex formations in vivo. In this review, recent advances related to pathogenic fungal biofilms are addressed.

Bioactive Nutrients and Nutrigenomics in Age-Related Diseases

The increased life expectancy and the expansion of the elderly population are stimulating research into aging. Aging may be viewed as a multifactorial process that results from the interaction of genetic and environmental factors, which include lifestyle. Human molecular processes are influenced by physiological pathways as well as exogenous factors, which include the diet. Dietary components have substantive effects on metabolic health; for instance, bioactive molecules capable of selectively modulating specific metabolic pathways affect the development/progression of cardiovascular and neoplastic disease. As bioactive nutrients are increasingly identified, their clinical and molecular chemopreventive effects are being characterized and systematic analyses encompassing the "omics" technologies (transcriptomics, proteomics and metabolomics) are being conducted to explore their action. The evolving field of molecular pathological epidemiology has unique strength to investigate the effects of dietary and lifestyle exposure on clinical outcomes. The mounting body of knowledge regarding diet-related health status and disease risk is expected to lead in the near future to the development of improved diagnostic procedures and therapeutic strategies targeting processes relevant to nutrition. The state of the art of aging and nutrigenomics research and the molecular mechanisms underlying the beneficial effects of bioactive nutrients on the main aging-related disorders are reviewed herein.

Proteomics perspectives in rotator cuff research: a systematic review of gene expression and protein composition in human tendinopathy

BACKGROUND

Rotator cuff tendinopathy including tears is a cause of significant morbidity. The molecular pathogenesis of the disorder is largely unknown. This review aimed to present an overview of the literature on gene expression and protein composition in human rotator cuff tendinopathy and other tendinopathies, and to evaluate perspectives of proteomics--the comprehensive study of protein composition--in tendon research.

MATERIALS AND METHODS

We conducted a systematic search of the literature published between 1 January 1990 and 18 December 2012 in PubMed, Embase, and Web of Science. We included studies on objectively quantified differential gene expression and/or protein composition in human rotator cuff tendinopathy and other tendinopathies as compared to control tissue.

RESULTS

We identified 2199 studies, of which 54 were included; 25 studies focussed on rotator cuff or biceps tendinopathy. Most of the included studies quantified prespecified mRNA molecules and proteins using polymerase chain reactions and immunoassays, respectively. There was a tendency towards an increase of collagen I (11 of 15 studies) and III (13 of 14), metalloproteinase (MMP)-1 (6 of 12), -9 (7 of 7), -13 (4 of 7), tissue inhibitor of metalloproteinase (TIMP)-1 (4 of 7), and vascular endothelial growth factor (4 of 7), and a decrease in MMP-3 (10 of 12). Fourteen proteomics studies of tendon tissues/cells failed inclusion, mostly because they were conducted in animals or in vitro.

CONCLUSIONS

Based on methods, which only allowed simultaneous quantification of a limited number of prespecified mRNA molecules or proteins, several proteins appeared to be differentially expressed/represented in rotator cuff tendinopathy and other tendinopathies. No proteomics studies fulfilled our inclusion criteria, although proteomics technologies may be a way to identify protein profiles (including non-prespecified proteins) that characterise specific tendon disorders or stages of tendinopathy. Thus, our results suggested an untapped potential for proteomics in tendon research.

Photosynthetic activity and protein overexpression found in Cr(III)-tolerant cells of the green algae Dictyosphaerium chlorelloides

Chromium is an important constituent in effluents obtained from chromium plating industries. Due to the highly toxic nature of Cr(VI), attention has been shifted to less hazardous Cr(III) electroplating processes. This study evaluated aquatic toxicity of Cr(III)-containing laboratory samples representative of effluents from chromium electroplating industries, on the photosynthetic activity exhibited by both Cr(III)-sensitive (Dc1M(wt)) and tolerant (Dc1M(Cr(III)R30)) Dictyosphaerium chlorelloides strains. Additionally, selected de novo-determined peptide sequences, obtained from Dc1M(Cr(III)R30), have been analyzed to evidence the possible Cr(III) toxic mechanism involved in the resistance of these cells to high Cr(III) levels in aquatic environments. Dc1M(Cr(III)R30) strain exhibited a gross photosynthetic balance of about five times lower than that exhibited by Dc1M(wt) strain, demonstrating that Dc1M(Cr(III)R30) has a photosynthetic yield significantly lower than Dc1M(wt). SDS-PAGE of Dc1M(Cr(III)R30) samples showed the presence of at least two protein bands (23.05 and 153.46 KDa, respectively) absent in wild-type strain samples. Although it has achieved a low coincidence between the lower molecular weight band and a GTPase identified from genome of the green alga Chlamydomonas reinhardtii, none of de novo peptide sequences obtained showed a significant MS-BLAST score, so that further studies will be required.

Embryonic stem cell proteomics

Human embryonic stem cells potentially represent an unlimited source of cells and tissues for regenerative medicine. Understanding signaling events that drive proliferation and specialization of these cells into various differentiated derivatives is of utmost importance for controlling their behavior in vitro. Major progress has been made in unraveling these signaling events with large-scale studies at the transcriptional level, but analysis of protein expression, interaction and modification has been more limited, since it requires different strategies. Recent advances in mass spectrometry-based proteomics indicate that proteome characterization can contribute significantly to our understanding of embryonic stem cell biology. In this article, we review mass spectrometry-based studies of human and mouse embryonic stem cells and their differentiated progeny, as well as studies of conditioned media that have been reported to support self-renewal of the undifferentiated cells in the absence of the more commonly used feeder cells. In addition, we make concise comparisons with related transcriptome profiling reports.

Application of immobilized metal affinity chromatography in proteomics

It has been proved that the progress of proteomics is mostly determined by the development of advanced and sensitive protein separation technologies. Immobilized metal affinity chromatography (IMAC) is a powerful protein fractionation method used to enrich metal-associated proteins and peptides. In proteomics, IMAC has been widely employed as a prefractionation method to increase the resolution in protein separation. The combination of IMAC with other protein analytical technologies has been successfully utilized to characterize metalloproteome and post-translational modifications. In the near future, newly developed IMAC integrated with other proteomic methods will greatly contribute to the revolution of expression, cell-mapping and structural proteomics.

Proteomics meets genetics: SILAC labeling of Drosophila melanogaster larvae and cells for in vivo functional studies

Stable isotope labeling by amino acids in cell culture (SILAC) is an established and potent method for quantitative proteomics. When combined with high-resolution mass spectrometry (MS) and efficient algorithms for the analysis of quantitative MS data, SILAC has proven to be the strategy of choice for the in-depth characterization of functional states at the protein level. The fruit fly Drosophila melanogaster is one of the most widely used model systems for studies of genetics and developmental biology. Despite this, a global proteomic approach in Drosophila is rarely considered. Here, we describe an adaptation of SILAC for functional investigation of fruit flies by proteomics: We illustrate how to perform efficient SILAC labeling of cells in culture and whole fly larvae. The combination of SILAC, a highly accurate global protein quantification method, and of the fruit fly, the prime genetics and developmental model, represents a unique opportunity for quantitative proteomic studies in vivo.

Towards a comprehensive picture of the genetic landscape of complex traits

The formation of phenotypic traits, such as biomass production, tumor volume and viral abundance, undergoes a complex process in which interactions between genes and developmental stimuli take place at each level of biological organization from cells to organisms. Traditional studies emphasize the impact of genes by directly linking DNA-based markers with static phenotypic values. Functional mapping, derived to detect genes that control developmental processes using growth equations, has proven powerful for addressing questions about the roles of genes in development. By treating phenotypic formation as a cohesive system using differential equations, a different approach-systems mapping-dissects the system into interconnected elements and then map genes that determine a web of interactions among these elements, facilitating our understanding of the genetic machineries for phenotypic development. Here, we argue that genetic mapping can play a more important role in studying the genotype-phenotype relationship by filling the gaps in the biochemical and regulatory process from DNA to end-point phenotype. We describe a new framework, named network mapping, to study the genetic architecture of complex traits by integrating the regulatory networks that cause a high-order phenotype. Network mapping makes use of a system of differential equations to quantify the rule by which transcriptional, proteomic and metabolomic components interact with each other to organize into a functional whole. The synthesis of functional mapping, systems mapping and network mapping provides a novel avenue to decipher a comprehensive picture of the genetic landscape of complex phenotypes that underlie economically and biomedically important traits.

Clinical Applications of Omics Technologies on ZHENG Differentiation Research in Traditional Chinese Medicine

Traditional Chinese medicine (TCM) ZHENG is the basic concept of TCM theory. The effectiveness of TCM treatment depends on the accuracy of ZHENG differentiation. ZHENG differentiation, using the "four diagnostic methods," has the drawbacks of subjectivity and variability. Following development of omics technologies, which study the functional activities of human body from a system-wide perspective, it has been more and more applied in study of objectivity differentiating TCM ZHENG and understanding its biological mechanisms. This paper reviewed the literatures of clinical TCM ZHENG differentiation researches, underlying omics technologies, and indicated the increased trends of related articles with four kinds of omics technologies, including genomics, transcriptomics, proteomics and metabolomics, and the correlations between ZHENG differentiation and findings in omics studies. Moreover, the paper summarized the typical omics application in common studied diseases and TCM ZHENGs and discussed the main problems and countermeasure of ZHENG differentiation researches. The work here may provide a reference for further research of TCM ZHENG differentiation using omics technologies.

Ligand-directed profiling: applications to target drug discovery in cancer

BACKGROUND

Generation of targeted therapy remains a major challenge in medicine. The development of drugs that can discriminate between tumor cells and non-malignant cells would improve efficacy and reduce general side effects. Phage display allows identification of specific supramolecular complexes that can target therapeutic compounds or imaging agents, both in vitro and in vivo. The use of phage display to identify molecules expressed on the surface of human cancer cells without bias, as well as to provide initial steps toward identification of a ligand/receptor-based map of the human microvasculature, has broad implications for drug discovery in general, especially for cancer therapy.

OBJECTIVE/METHOD

In this review, we discuss the use of phage display technology as a ligand-directed targeting strategy and its applications to drug discovery.

CONCLUSION

Compared to other existing drug discovery platforms, phage display technology has the advantage to provide valuable clues pointing to target proteins in an unbiased biological context. The result from various display library screenings indicates that in many cases the selected peptide motifs mimic biological ligands. Analysis of peptide motifs targeting a receptor provides a basis for rational drug design of targeted peptidomimetics.

Ripples in the pond--using a systems approach to decipher the cellular functions of membrane microdomains

Membrane microdomains such as lipid rafts and caveolae regulate a myriad of cellular functions including cell signalling, protein trafficking, cell viability, and cell movement. They have been implicated in diseases such as cancer, diabetes and Alzheimer's disease, highlighting the essential role they play in cell processes. Despite much research and debate on the size, composition and dynamics of membrane microdomains, the molecular mechanism(s) of their action remain poorly understood. Most studies have dealt solely with the content and properties of the membrane microdomain as an entity in itself. However, recent work shows that membrane microdomain disruption has wide ranging effects on other subcellular compartments, and the cell as a whole. Hence we propose that a systems approach incorporating many cellular attributes such as subcellular localisation is required in order to understand the global impact of microdomains on cell function. Although analysis of sub-proteome changes already provides additional insight, we further propose biological network analysis of functional proteomics data to capture effects at the systems level. In this review, we highlight the use of protein-protein interactions networks and mixed networks to portray and visualize the relationships between proteins within and between subcellular fractions. Such a systems analysis will be required to improve our understanding of the full cellular function of membrane microdomains.

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Intraneuronal β-amyloid and its interactions with proteins and subcellular organelles

Amyloidogenic aggregation and misfolding of proteins are linked to neurodegeneration. The mechanism of neurodegeneration in Alzheimer's disease, which gives rise to severe neuronal death and memory loss, is not yet fully understood. The amyloid hypothesis remains the most accepted theory for the pathomechanism of the disease. It was suggested that β-amyloid accumulation may play a key role in initiating the neurodegenerative processes. The recent intracellular β-amyloid (iAβ) hypothesis emphasizes the primary role of iAβ to initiate the disease by interaction with cytoplasmic proteins and cell organelles, thereby triggering apoptosis. Sophisticated methods (proteomics, protein microarray, and super resolution microscopy) have been used for studying iAβ interactions with proteins and membraneous structures. The present review summarizes the studies on the origin of iAβ and the base of its neurotoxicity: interactions with cytosolic proteins and several cell organelles such as endoplasmic reticulum, endosomes, lysosomes, ribosomes, mitochondria, and the microtubular system.

Profiling of age-related changes in the tibialis anterior muscle proteome of the mdx mouse model of dystrophinopathy

X-linked muscular dystrophy is a highly progressive disease of childhood and characterized by primary genetic abnormalities in the dystrophin gene. Senescent mdx specimens were used for a large-scale survey of potential age-related alterations in the dystrophic phenotype, because the established mdx animal model of dystrophinopathy exhibits progressive deterioration of muscle tissue with age. Since the mdx tibialis anterior muscle is a frequently used model system in muscular dystrophy research, we employed this particular muscle to determine global changes in the dystrophic skeletal muscle proteome. The comparison of mdx mice aged 8 weeks versus 22 months by mass-spectrometry-based proteomics revealed altered expression levels in 8 distinct protein species. Increased levels were shown for carbonic anhydrase, aldolase, and electron transferring flavoprotein, while the expressions of pyruvate kinase, myosin, tropomyosin, and the small heat shock protein Hsp27 were found to be reduced in aged muscle. Immunoblotting confirmed age-dependent changes in the density of key muscle proteins in mdx muscle. Thus, segmental necrosis in mdx tibialis anterior muscle appears to trigger age-related protein perturbations due to dystrophin deficiency. The identification of novel indicators of progressive muscular dystrophy might be useful for the establishment of a muscle subtype-specific biomarker signature of dystrophinopathy.

Proteomic profiling of follicular and papillary thyroid tumors

OBJECTIVE

Thyroid proteomics is a new direction in thyroid cancer research aiming at etiological understanding and biomarker identification for improved diagnosis.

METHODS

Two-dimensional electrophoresis was applied to cytosolic protein extracts from frozen thyroid samples (ten follicular adenomas, nine follicular carcinomas, ten papillary carcinomas, and ten reference thyroids). Spots with differential expression were revealed by image and multivariate statistical analyses, and identified by mass spectrometry.

RESULTS

A set of 25 protein spots significant for discriminating between the sample groups was identified. Proteins identified for nine of these spots were studied further including 14-3-3 protein beta/alpha, epsilon, and zeta/delta, peroxiredoxin 6, selenium-binding protein 1, protein disulfide-isomerase precursor, annexin A5 (ANXA5), tubulin alpha-1B chain, and α1-antitrypsin precursor. This subset of protein spots carried the same predictive power in differentiating between follicular carcinoma and adenoma or between follicular and papillary carcinoma, as compared with the larger set of 25 spots. Protein expression in the sample groups was demonstrated by western blot analyses. For ANXA5 and the 14-3-3 proteins, expression in tumor cell cytoplasm was demonstrated by immunohistochemistry both in the sample groups and an independent series of papillary thyroid carcinomas.

CONCLUSION

The proteins identified confirm previous findings in thyroid proteomics, and suggest additional proteins as dysregulated in thyroid tumors.

Connexin multi-site phosphorylation: mass spectrometry-based proteomics fills the gap

Connexins require an integrated network for protein synthesis, assembly, gating, internalization, degradation and feedback control that are necessary to regulate the biosynthesis, and turnover of gap junction channels. At the most fundamental level, the introduction of sequence-altering, modifications introduces changes in protein conformation, activity, charge, stability and localization. Understanding the sites, patterns and magnitude of protein post-translational modification, including phosphorylation, is absolutely critical. Historically, the examination of connexin phosphorylation has been placed within the context that one or small number of sites of modification strictly corresponds to one molecular function. However, the release of high-profile proteomic datasets appears to challenge this dogma by demonstrating connexins undergo multiple levels of multi-site phosphorylation. With the growing prominence of mass spectrometry in biology and medicine, we are now getting a glimpse of the richness of connexin phosphate signals. Having implications to health and disease, this review provides an overview of technologies in the context of targeted and discovery proteomics, and further discusses how these techniques are being applied to "fill the gaps" in understanding of connexin post-translational control. This article is part of a Special Issue entitled: The Communicating junctions, roles and dysfunctions.

Verification of male infertility biomarkers in seminal plasma by multiplex selected reaction monitoring assay

Seminal plasma is a promising biological fluid to use for noninvasive clinical diagnostics of male reproductive system disorders. To verify a list of prospective male infertility biomarkers, we developed a multiplex selected reaction monitoring assay and measured the relative abundance of 31 proteins in 30 seminal plasma samples from normal, nonobstructive azoospermia and post-vasectomy individuals. Median levels of some proteins were decreased by more than 100-fold in nonobstructive azoospermia or post-vasectomy samples, in comparison with normal samples. To follow up the most promising candidates and measure their concentrations in seminal plasma, heavy isotope-labeled internal standards were synthesized and used to reanalyze 20 proteins in the same set of samples. Concentrations of candidate proteins in normal seminal plasma were found in the range 0.1-1000 μg/ml but were significantly decreased in nonobstructive azoospermia and post-vasectomy. These data allowed us to select, for the first time, biomarkers to discriminate between normal, nonobstructive azoospermia, and post-vasectomy (simulated obstructive azoospermia) seminal plasma samples. Some testis-specific proteins (LDHC, TEX101, and SPAG11B) performed with absolute or nearly absolute specificities and sensitivities. Cell-specific classification of protein expression indicated that Sertoli or germ cell dysfunction, but not Leydig cell dysfunction, was observed in nonobstructive azoospermia seminal plasma. The proposed panel of biomarkers, pending further validation, could lead to a clinical assay that can eliminate the need for testicular biopsy to diagnose the category of male infertility, thus providing significant benefits to patients as well as decreased costs associated with the differential diagnosis of azoospermia.

Biomarkers of immunosuppressant organ toxicity after transplantation: status, concepts and misconceptions

INTRODUCTION

A major challenge in transplantation is improving long-term organ transplant and patient survival. Immunosuppressants protect the transplant organ from alloimmune reactions, but sometimes also exhibit limiting side effects. The key to improving long-term outcome following transplantation is the selection of the correct immunosuppressive regimen for an individual patient for minimizing toxicity while maintaining immunosuppressive efficacy.

AREAS COVERED

Proteomics and metabolomics have the potential to develop sensitive and specific diagnostic tools for monitoring early changes in cell signal transduction, regulation and biochemical pathways. Here, we review the steps required for the development of molecular markers from discovery, mechanistic and clinical qualification to regulatory approval, and present a critical discussion of the current status of molecular marker development as relevant for the management and individualization of immunosuppressive drug regimens.

EXPERT OPINION

Although metabolomics and proteomics-based studies have yielded several candidate molecular markers, most published studies are poorly designed, statistically underpowered and/or often have not gone beyond the discovery stage. Most molecular marker candidates are still at an early stage. Due to the high complexity of and the resources required for diagnostic marker development, initiatives and consortia organized and supported by funding agencies and regulatory agencies will be critical.

Frozen tissue can provide reproducible proteomic results of subcellular fractionation

Differential detergent fractionation (DDF) is frequently used to partition fresh cells and tissues into distinct compartments. We have tested whether DDF can reproducibly extract and fractionate cellular protein components from frozen tissues. Frozen kidneys were sequentially extracted with three different buffer systems. Analysis of the three fractions with liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified 1693 proteins, some of which were common to all fractions and others of which were unique to specific fractions. Normalized spectral index (SI(N)) values obtained from these data were compared to evaluate both the reproducibility of the method and the efficiency of enrichment. SI(N) values between replicate fractions demonstrated a high correlation, confirming the reproducibility of the method. Correlation coefficients across the three fractions were significantly lower than those for the replicates, supporting the capability of DDF to differentially fractionate proteins into separate compartments. Subcellular annotation of the proteins identified in each fraction demonstrated a significant enrichment of cytoplasmic, cell membrane, and nuclear proteins in the three respective buffer system fractions. We conclude that DDF can be applied to frozen tissue to generate reproducible proteome coverage discriminating subcellular compartments. This demonstrates the feasibility of analyzing cellular compartment-specific proteins in archived tissue samples with the simple DDF method.

Shotgun proteomics identifies proteins specific for acute renal transplant rejection

PURPOSE

Acute rejection (AR) remains the primary risk factor for renal transplant outcome; development of non-invasive diagnostic biomarkers for AR is an unmet need.

EXPERIMENTAL DESIGN

We used shotgun proteomics applying LC-MS/MS and ELISA to analyze a set of 92 urine samples, from patients with AR, stable grafts (STA), proteinuria (NS), and healthy controls.

RESULTS

A total of 1446 urinary proteins (UP) were identified along with a number of nonspecific proteinuria-specific, renal transplantation specific and AR-specific proteins. Relative abundance of identified UP was measured by protein-level spectral counts adopting a weighted fold-change statistic, assigning increased weight for more frequently observed proteins. We have identified alterations in a number of specific UP in AR, primarily relating to MHC antigens, the complement cascade and extra-cellular matrix proteins. A subset of proteins (uromodulin, SERPINF1 and CD44), have been further cross-validated by ELISA in an independent set of urine samples, for significant differences in the abundance of these UP in AR.

CONCLUSIONS AND CLINICAL RELEVANCE

This label-free, semi-quantitative approach for sampling the urinary proteome in normal and disease states provides a robust and sensitive method for detection of UP for serial, non-invasive clinical monitoring for graft rejection after kidney transplantation.

Systems biology: the next frontier for bioinformatics

Biochemical systems biology augments more traditional disciplines, such as genomics, biochemistry and molecular biology, by championing (i) mathematical and computational modeling; (ii) the application of traditional engineering practices in the analysis of biochemical systems; and in the past decade increasingly (iii) the use of near-comprehensive data sets derived from 'omics platform technologies, in particular "downstream" technologies relative to genome sequencing, including transcriptomics, proteomics and metabolomics. The future progress in understanding biological principles will increasingly depend on the development of temporal and spatial analytical techniques that will provide high-resolution data for systems analyses. To date, particularly successful were strategies involving (a) quantitative measurements of cellular components at the mRNA, protein and metabolite levels, as well as in vivo metabolic reaction rates, (b) development of mathematical models that integrate biochemical knowledge with the information generated by high-throughput experiments, and (c) applications to microbial organisms. The inevitable role bioinformatics plays in modern systems biology puts mathematical and computational sciences as an equal partner to analytical and experimental biology. Furthermore, mathematical and computational models are expected to become increasingly prevalent representations of our knowledge about specific biochemical systems.

Integrated multifunctional microfluidics for automated proteome analyses

Proteomics is a challenging field for realizing totally integrated microfluidic systems for complete proteome processing due to several considerations, including the sheer number of different protein types that exist within most proteomes, the large dynamic range associated with these various protein types, and the diverse chemical nature of the proteins comprising a typical proteome. For example, the human proteome is estimated to have >10(6) different components with a dynamic range of >10(10). The typical processing pipeline for proteomics involves the following steps: (1) selection and/or extraction of the particular proteins to be analyzed; (2) multidimensional separation; (3) proteolytic digestion of the protein sample; and (4) mass spectral identification of either intact proteins (top-down proteomics) or peptide fragments generated from proteolytic digestions (bottom-up proteomics). Although a number of intriguing microfluidic devices have been designed, fabricated and evaluated for carrying out the individual processing steps listed above, work toward building fully integrated microfluidic systems for protein analysis has yet to be realized. In this chapter, information will be provided on the nature of proteomic analysis in terms of the challenges associated with the sample type and the microfluidic devices that have been tested to carry out individual processing steps. These include devices such as those for multidimensional electrophoretic separations, solid-phase enzymatic digestions, and solid-phase extractions, all of which have used microfluidics as the functional platform for their implementation. This will be followed by an in-depth review of microfluidic systems, which are defined as units possessing two or more devices assembled into autonomous systems for proteome processing. In addition, information will be provided on the challenges involved in integrating processing steps into a functional system and the approaches adopted for device integration. In this chapter, we will focus exclusively on the front-end processing microfluidic devices and systems for proteome processing, and not on the interface technology of these platforms to mass spectrometry due to the extensive reviews that already exist on these types of interfaces.

Platform for establishing interlaboratory reproducibility of selected reaction monitoring-based mass spectrometry peptide assays

Mass spectrometry (MS) is an attractive alternative to quantification of proteins by immunoassays, particularly for protein biomarkers of clinical relevance. Reliable quantification requires that the MS-based assays are robust, selective, and reproducible. Thus, the development of standardized protocols is essential to introduce MS into clinical research laboratories. The aim of this study was to establish a complete workflow for assessing the transferability and reproducibility of selected reaction monitoring (SRM) assays between clinical research laboratories. Four independent laboratories in North America, using identical triple-quadrupole mass spectrometers (Quantum Ultra, Thermo), were provided with standard protocols and instrumentation settings to analyze unknown samples and internal standards in a digested plasma matrix to quantify 51 peptides from 39 human proteins using a multiplexed SRM assay. The interlaboratory coefficient of variation (CV) was less than 10% for 25 of 39 peptides quantified (12 peptides were not quantified based upon hydrophobicity) and exhibited CVs less than 20% for the remaining peptides. In this report, we demonstrate that previously developed research platforms for SRM assays can be improved and optimized for deployment in clinical research environments.

Ecological adaptation of diverse honey bee (Apis mellifera) populations

Background

Honey bees are complex eusocial insects that provide a critical contribution to human agricultural food production. Their natural migration has selected for traits that increase fitness within geographical areas, but in parallel their domestication has selected for traits that enhance productivity and survival under local conditions. Elucidating the biochemical mechanisms of these local adaptive processes is a key goal of evolutionary biology. Proteomics provides tools unique among the major ‘omics disciplines for identifying the mechanisms employed by an organism in adapting to environmental challenges.

Results

Through proteome profiling of adult honey bee midgut from geographically dispersed, domesticated populations combined with multiple parallel statistical treatments, the data presented here suggest some of the major cellular processes involved in adapting to different climates. These findings provide insight into the molecular underpinnings that may confer an advantage to honey bee populations. Significantly, the major energy-producing pathways of the mitochondria, the organelle most closely involved in heat production, were consistently higher in bees that had adapted to colder climates. In opposition, up-regulation of protein metabolism capacity, from biosynthesis to degradation, had been selected for in bees from warmer climates.

Conclusions

Overall, our results present a proteomic interpretation of expression polymorphisms between honey bee ecotypes and provide insight into molecular aspects of local adaptation or selection with consequences for honey bee management and breeding. The implications of our findings extend beyond apiculture as they underscore the need to consider the interdependence of animal populations and their agro-ecological context.

Mass spectrometric identification of dystrophin isoform Dp427 by on-membrane digestion of sarcolemma from skeletal muscle

Although the membrane cytoskeletal protein dystrophin of 427kDa and its tightly associated glycoprotein complex are drastically affected in muscular dystrophy, recent large-scale proteomic investigations did not identify full-length dystrophin in muscle preparations and were unable to determine its molecular fate in dystrophinopathy. Because conventional two-dimensional gel electrophoresis underrepresents many low-abundance and membrane-associated protein species and in-gel trypsination is often hampered by an inefficient digestion of certain target proteins, here we have applied direct on-membrane digestion of one-dimensional blots of the sarcolemma-enriched fraction and the isolated dystrophin-glycoprotein complex. This method succeeded in the mass spectrometric identification of dystrophin isoform Dp427 and associated glycoproteins as well as sarcolemmal dysferlin. In addition, protein bands representing established signature molecules of cross-contaminating membrane systems, such as the voltage-sensing dihydropyridine receptor of transverse tubules, the ryanodine receptor Ca2+-release channel of triad junctions, and the Ca2+-ATPase of the sarcoplasmic reticulum, were identified by mass spectrometry. Thus, proteomic approaches using on-membrane digestion might be suitable for future studies of low-abundance proteins, integral proteins, peripheral membrane proteins, and high-molecular-mass proteins. On-membrane digestion has the potential to develop into the method of choice for studying these classes of proteins, whose presence is otherwise missed by conventional gel electrophoresis-based proteomics.

Proteomic Profiling of the Dystrophin-Deficient MDX Heart Reveals Drastically Altered Levels of Key Metabolic and Contractile Proteins

Although Duchenne muscular dystrophy is primarily classified as a neuromuscular disease, cardiac complications play an important role in the course of this X-linked inherited disorder. The pathobiochemical steps causing a progressive decline in the dystrophic heart are not well understood. We therefore carried out a fluorescence difference in-gel electrophoretic analysis of 9-month-old dystrophin-deficient versus age-matched normal heart, using the established MDX mouse model of muscular dystrophy-related cardiomyopathy. Out of 2,509 detectable protein spots, 79 2D-spots showed a drastic differential expression pattern, with the concentration of 3 proteins being increased, including nucleoside diphosphate kinase and lamin-A/C, and of 26 protein species being decreased, including ATP synthase, fatty acid binding-protein, isocitrate dehydrogenase, NADH dehydrogenase, porin, peroxiredoxin, adenylate kinase, tropomyosin, actin, and myosin light chains. Hence, the lack of cardiac dystrophin appears to trigger a generally perturbed protein expression pattern in the MDX heart, affecting especially energy metabolism and contractile proteins.

MSQuant, an open source platform for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics critically depends on algorithms for data interpretation. A current bottleneck in the rapid advance of proteomics technology is the closed nature and slow development cycle of vendor-supplied software solutions. We have created an open source software environment, called MSQuant, which allows visualization and validation of peptide identification results directly on the raw mass spectrometric data. MSQuant iteratively recalibrates MS data thereby significantly increasing mass accuracy leading to fewer false positive peptide identifications. Algorithms to increase data quality include an MS(3) score for peptide identification and a post-translational modification (PTM) score that determines the probability that a modification such as phosphorylation is placed at a specific residue in an identified peptide. MSQuant supports relative protein quantitation based on precursor ion intensities, including element labels (e.g., (15)N), residue labels (e.g., SILAC and ICAT), termini labels (e.g., (18)O), functional group labels (e.g., mTRAQ), and label-free ion intensity approaches. MSQuant is available, including an installer and supporting scripts, at http://msquant.sourceforge.net .

Recent progress of proteomics in critical illness

Critical illness, such as sepsis or septic shock with multiple organ dysfunction syndrome, is the leading cause of morbidity and mortality in intensive care units. The complexity of critical illness requires a robust methodology to explore the underlying mechanisms. Proteomics represents a powerful postgenomic biotechnology used for simultaneous examination of a large number of proteins or the proteome. Recent progress in proteomic techniques allows thorough evaluation of molecular changes associated with critical illness, thereby permitting to identify novel biomarkers and therapeutic targets. This review provides an update on the recent progress and potential of rapidly evolving proteomics approach to facilitate new discoveries in the field of critical care medicine.

Contributions of quantitative proteomics to understanding membrane microdomains

Membrane microdomains, e.g., lipid rafts and caveolae, are crucial cell surface organelles responsible for many cellular signaling and communication events, which makes the characterization of their proteomes both interesting and valuable. They are large cellular complexes comprised of specific proteins and lipids, yet they are simple enough in composition to be amenable to modern LC/MS/MS methods for proteomics. However, the proteomic characterization of membrane microdomains by traditional qualitative mass spectrometry is insufficient for distinguishing true components of the microdomains from copurifying contaminants or for evaluating dynamic changes in the proteome compositions. In this review, we discuss the contributions quantitative proteomics has made to our understanding of the biology of membrane microdomains.

Blood-related proteomics

Blood-related proteomics is an emerging field, recently gaining momentum. Indeed, a wealth of data is now available and a plethora of groups has contributed to add pieces to the jigsaw puzzle of protein complexity within plasma and blood cells. In this review article we purported to sail across the mare magnum of the actual knowledge in this research endeavour. The main strides in proteomic investigations on red blood cells, platelets, plasma and white blood cells are hereby presented in a chronological order. Moreover, a glance is given at prospective studies which promise to shift the focus of attention from the end product to its provider, the donor, in a sort of Kantian "Copernican revolution". A well-rounded portrait of the usefulness of proteomics in blood-related research is accurately given. In particular, proteomic tools could be adopted to follow the main steps of the blood-banking production processes (a comparison of collection methods, pathogen inactivation techniques, storage protocols). Thus proteomics has been recently transformed from a mere basic-research extremely-expensive toy into a dramatically-sensitive and efficient eye-lens to either delve into the depths of the molecular mechanisms of blood and blood components or to establish quality parameters in the blood-banking production chain totally anew.