From proteins to proteomes: large scale protein identification by two-dimensional electrophoresis and amino acid analysis

Label-free liquid chromatography-mass spectrometry comparison of the breast muscle proteome profiles in two fast-growing broilers

Poultry meat-production is increasing worldwide; leading to the selection of chickens for meat-production that show a fast growth. A label-free quantitative proteomic-approach and Western-blot were applied to investigate the dynamics of muscle protein under rapid growth conditions in two common fast-growing broiler genetic-lines (Ross 508 and AZ Extra Heavy Red-chicken). Muscle exudate from chicken Pectoralis major was used as substrate to unveil the proteome of these genetic-lines. Six-hundred forty-five proteins were identified in total from all samples, and after statistical-analysis 172 proteins were found to be differentially-expressed, clearly distinguishing the two chicken genetic-lines. Several of these differentially-expressed proteins were involved with the proteasome and glycolysis/gluconeogenesis-pathways. Changes in meat-quality traits were also observed, which were reflected in the proteomic-profile. Proteins involved in the ubiquitin-proteasome system were associated with the bigger muscle mass of Ross 508, while phosphoglucomutase 1 was associated with a possible higher capability of AZ Extra Heavy Red-chickens to cope with stressors. This pilot proteomic-approach applied on muscle exudate samples provided key evidence about the pathways and processes underlying these two chicken genetic-lines and their meat-quality parameters. We also identified potential biomarkers that could determine the peculiar production potentials (e.g. breast-growth) of these broilers-lines, which arise from differences in their genetic-backgrounds.

Direct Identification of Intact Proteins Using a Low-Resolution Mass Spectrometer with CIDn/ETnoD

Over the past decades, proteomics has become increasingly important and a heavily discussed topic. The identification of intact proteins remains a major focus in this field. While most intact proteins are analyzed using high-resolution mass spectrometry, identifying them through low-resolution mass spectrometry continues to pose challenges. In our study, we investigated the capability of identifying various intact proteins using collision-induced dissociation (CID) and electron transfer without dissociation (ETnoD). Using myoglobin as our test protein, stable product ions were generated with CID, and the identities of the product ions were identified with ETnoD. ETnoD uses a short activation time (AcT, 5 ms) to create sequential charge-reduced precursor ion (CRI). The charges of the fragments and their sequences were determined with corresponding CRI. The product ions can be selected for subsequent CID (termed CIDn) combined with ETnoD for further sequence identification and validation. We refer to this method as CIDn/ETnoD. The use of a multistage CID activation (CIDn) and ETnoD protocol has been applied to several intact proteins to obtain multiple sequence identifications.

Mass spectrometry-based proteomic approaches for salivary protein biomarkers discovery and dental caries diagnosis: A critical review

Dental caries is a multifactorial chronic disease resulting from the intricate interplay among acid-generating bacteria, fermentable carbohydrates, and several host factors such as saliva. Saliva comprises several proteins which could be utilized as biomarkers for caries prevention, diagnosis, and prognosis. Mass spectrometry-based salivary proteomics approaches, owing to their sensitivity, provide the opportunity to investigate and unveil crucial cariogenic pathogen activity and host indicators and may demonstrate clinically relevant biomarkers to improve caries diagnosis and management. The present review outlines the published literature of human clinical proteomics investigations on caries and extensively elucidates frequently reported salivary proteins as biomarkers. This review also discusses important aspects while designing an experimental proteomics workflow. The protein-protein interactions and the clinical relevance of salivary proteins as biomarkers for caries, together with uninvestigated domains of the discipline are also discussed critically.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Exploiting ion-mobility mass spectrometry for unraveling proteome complexity

Ion mobility spectrometry-mass spectrometry (IMS-MS) is experiencing rapid growth in proteomic studies, driven by its enhancements in dynamic range and throughput, increasing the quantitation precision, and the depth of proteome coverage. The core principle of ion mobility spectrometry is to separate ions in an inert gas under the influence of an electric field based on differences in drift time. This minireview provides an introduction to IMS operation modes and a description of advantages and limitations is presented. Moreover, the principles of trapped IMS-MS (TIMS-MS), including parallel accumulation-serial fragmentation are discussed. Finally, emerging applications linked to TIMS focusing on sample throughput (in clinical proteomics) and sensitivity (single-cell proteomics) are reviewed, and the possibilities of intact protein analysis are discussed.

Perspectives of Proteomics in Respiratory Allergic Diseases

Proteomics in respiratory allergic diseases has such a battery of techniques and programs that one would almost think there is nothing impossible to find, invent or mold. All the resources that we document here are involved in solving problems in allergic diseases, both diagnostic and prognostic treatment, and immunotherapy development. The main perspectives, according to this version, are in three strands and/or a lockout immunological system: (1) Blocking the diapedesis of the cells involved, (2) Modifications and blocking of paratopes and epitopes being understood by modifications to antibodies, antagonisms, or blocking them, and (3) Blocking FcεRI high-affinity receptors to prevent specific IgEs from sticking to mast cells and basophils. These tools and targets in the allergic landscape are, in our view, the prospects in the field. However, there are still many allergens to identify, including some homologies between allergens and cross-reactions, through the identification of structures and epitopes. The current vision of using proteomics for this purpose remains a constant; this is also true for the basis of diagnostic and controlled systems for immunotherapy. Ours is an open proposal to use this vision for treatment.

Recent advances in top-down proteome sample processing ahead of MS analysis

Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.

A Label-Free Quantitative Analysis for the Search of Proteomic Differences between Goat Breeds

The intensification and standardization of livestock farming are causing a decline in the number of animal breeds in many species, such as the goat. The availability of more studies on the potentiality of goat breeds could raise awareness of their importance, conservation and productive possibilities. Label-free quantitative analysis was applied in this study to investigate the proteomic differences between the autochthon Teramana and Saanen goats that could be useful for defining peculiar features of these breeds. A total of 2093 proteins were characterized in the muscle exudate proteome of the Teramana and Saanen breeds. A total of 41 proteins clearly separated the two breeds. Eukaryotic initiation factor proteins and aldehyde-dehydrogenase 7 family-member A1 were up-regulated in the autochthon breed and associated with its resilience, whereas catalase was down-regulated and associated with lower muscular mass. This study is the most detailed report of goat muscle proteome. Several differentially regulated proteins between the two breeds were identified, providing insights into functional pathways that define this organism and its biology.

Detergent-Assisted Protein Digestion-On the Way to Avoid the Key Bottleneck of Shotgun Bottom-Up Proteomics

Gel-free bottom-up shotgun proteomics is the principal methodological platform for the state-of-the-art proteome research. This methodology assumes quantitative isolation of the total protein fraction from a complex biological sample, its limited proteolysis with site-specific proteases, analysis of the resulted peptides with nanoscaled reversed-phase high-performance liquid chromatography-(tandem) mass spectrometry (nanoRP-HPLC-MS and MS/MS), protein identification by sequence database search and peptide-based quantitative analysis. The most critical steps of this workflow are protein reconstitution and digestion; therefore, detergents and chaotropic agents are strongly mandatory to ensure complete solubilization of complex protein isolates and to achieve accessibility of all protease cleavage sites. However, detergents are incompatible with both RP separation and electrospray ionization (ESI). Therefore, to make LC-MS analysis possible, several strategies were implemented in the shotgun proteomics workflow. These techniques rely either on enzymatic digestion in centrifugal filters with subsequent evacuation of the detergent, or employment of MS-compatible surfactants, which can be degraded upon the digestion. In this review we comprehensively address all currently available strategies for the detergent-assisted proteolysis in respect of their relative efficiency when applied to different biological matrices. We critically discuss the current progress and the further perspectives of these technologies in the context of its advances and gaps.

Evaluation of the Fecal Proteome in Healthy and Diseased Cheetahs (Acinonyx jubatus) Suffering from Gastrointestinal Disorders

Fecal proteomics allows for the identification of proteins and peptides present in stools and is useful in finding possible new biomarkers for diagnosing and/or monitoring gastrointestinal (GI) disorders. In the present study, we investigated the fecal proteome in healthy and diseased cheetahs (Acinonyx jubatus). Captive individuals of this species frequently show gastrointestinal disorders characterized by recurrent episodes of diarrhea, rare episodes of vomiting and weight loss, associated with Helicobacter spp. infection. Fecal proteomic evaluation has been performed by two-dimensional electrophoresis followed by liquid chromatography-tandem mass spectrometry. In healthy cheetahs, the results showed the presence of the following proteins: collagen alpha-1 (II) chain, transthyretin, IgG Fc-binding protein, titin, dystonin, isopentenyl-diphosphate Delta-isomerase 1, sodium/potassium-transporting ATPase subunit alpha-1 and protein disulfide-isomerase A6. The presence of albumin isoforms was found only in diseased cheetahs. The present paper reports the study of the fecal proteome in the cheetah, evidences some differences between healthy and diseased patients and confirms, once again, the potential of fecal proteomics for the study of the GI environment, with promising developments regarding the identification of new diagnostic/monitoring markers.

Influence of 30 and 60 Min of Hypobaric Hypoxia in Simulated Altitude of 15,000 ft on Human Proteome Profile

The human body reacts to hypobaric hypoxia, e.g., during a stay at high altitude, with several mechanisms of adaption. Even short-time exposition to hypobaric hypoxia leads to complex adaptions. Proteomics facilitates the possibility to detect changes in metabolism due to changes in proteins. The present study aims to identify time-dependent changes in protein expression due to hypobaric hypoxia for 30 and 60 min at a simulated altitude of 15,000 ft. N = 80 male subjects were randomized and assigned into four different groups: 40 subjects to ground control for 30 (GC30) and 60 min (GC60) and 40 subjects to 15,000 ft for 30 (HH30) and 60 min (HH60). Subjects in HH30 and HH60 were exposed to hypobaric hypoxia in a pressure chamber (total pressure: 572 hPa) equivalent to 15,000 ft for 30 vs. 60 min, respectively. Drawn blood was centrifuged and plasma frozen (−80 °C) until proteomic analysis. After separation of high abundant proteins, protein expression was analyzed by 2-DIGE and MALDI-TOF. To visualize the connected signaling cascade, a bio-informatical network analysis was performed. The present study was approved by the ethical committee of the University of Cologne, Germany. The study registry number is NCT03823677. In comparing HH30 to GC30, a total of seven protein spots had a doubled expression, and 22 spots had decreased gene expression. In a comparison of HH60 to GC60, a total of 27 protein spots were significantly higher expressed. HH60, as compared to GC30, revealed that a total of 37 spots had doubled expression. Vice versa, 12 spots were detected, which were higher expressed in GC30 vs. HH60. In comparison to GC, HH60 had distinct differences in the number of differential protein spots (noticeably more proteins due to longer exposure to hypoxia). There are indicators that changes in proteins are dependent on the length of hypobaric hypoxia. Some proteins associated with hemostasis were differentially expressed in the 60 min comparison.

Personalized medicine using omics approaches in acute respiratory distress syndrome to identify biological phenotypes

In the last decade, research on acute respiratory distress syndrome (ARDS) has made considerable progress. However, ARDS remains a leading cause of mortality in the intensive care unit. ARDS presents distinct subphenotypes with different clinical and biological features. The pathophysiologic mechanisms of ARDS may contribute to the biological variability and partially explain why some pharmacologic therapies for ARDS have failed to improve patient outcomes. Therefore, identifying ARDS variability and heterogeneity might be a key strategy for finding effective treatments. Research involving studies on biomarkers and genomic, metabolomic, and proteomic technologies is increasing. These new approaches, which are dedicated to the identification and quantitative analysis of components from biological matrixes, may help differentiate between different types of damage and predict clinical outcome and risk. Omics technologies offer a new opportunity for the development of diagnostic tools and personalized therapy in ARDS. This narrative review assesses recent evidence regarding genomics, proteomics, and metabolomics in ARDS research.

Technique development of high-throughput and high-sensitivity sample preparation and separation for proteomics

Sample preparation and separation methods determine the sensitivity and the quantification accuracy of the proteomics analysis. This article covers a comprehensive review of the recent technique development of high-throughput and high-sensitivity sample preparation and separation methods in proteomics research.

'Omics' of suicidal behaviour: A path to personalised psychiatry

Psychiatric disorders, including suicide, are complex disorders that are affected by many different risk factors. It has been estimated that genetic factors contribute up to 50% to suicide risk. As the candidate gene approach has not identified a gene or set of genes that can be defined as biomarkers for suicidal behaviour, much is expected from cutting edge technological approaches that can interrogate several hundred, or even millions, of biomarkers at a time. These include the '-omic' approaches, such as genomics, transcriptomics, epigenomics, proteomics and metabolomics. Indeed, these have revealed new candidate biomarkers associated with suicidal behaviour. The most interesting of these have been implicated in inflammation and immune responses, which have been revealed through different study approaches, from genome-wide single nucleotide studies and the micro-RNA transcriptome, to the proteome and metabolome. However, the massive amounts of data that are generated by the '-omic' technologies demand the use of powerful computational analysis, and also specifically trained personnel. In this regard, machine learning approaches are beginning to pave the way towards personalized psychiatry.

Application of Mass Spectrometry-Based Proteomics to Barley Research

Barley (Hordeum vulgare) is the fourth most cultivated crop in the world in terms of production volume, and it is also the most important raw material of the malting and brewing industries. Barley belongs to the grass (Poaceae) family and plays an important role in food security and food safety for both humans and livestock. With the global population set to reach 9.7 billion by 2050, but with less available and/or suitable land for agriculture, the use of biotechnology tools in breeding programs are of considerable importance in the quest to meet the growing food gap. Proteomics as a member of the "omics" technologies has become popular for the investigation of proteins in cereal crops and particularly barley and its related products such as malt and beer. This technology has been applied to study how proteins in barley respond to adverse environmental conditions including abiotic and/or biotic stresses, how they are impacted during food processing including malting and brewing, and the presence of proteins implicated in celiac disease. Moreover, proteomics can be used in the future to inform breeding programs that aim to enhance the nutritional value and broaden the application of this crop in new food and beverage products. Mass spectrometry analysis is a valuable tool that, along with genomics and transcriptomics, can inform plant breeding strategies that aim to produce superior barley varieties. In this review, recent studies employing both qualitative and quantitative mass spectrometry approaches are explored with a focus on their application in cultivation, manufacturing, processing, quality, and the safety of barley and its related products.

Morphological observation and protein expression of fertile and abortive ovules in Castanea mollissima

Chinese chestnuts (Castanea mollissima Blume.) contain 12-18 ovules in one ovary, but only one ovule develops into a seed, indicating a high ovule abortion rate. In this study, the Chinese chestnut 'Huaihuang' was used to explore the possible mechanisms of ovule abortion with respect to morphology and proteomics. The morphology and microstructure of abortive ovules were found to be considerably different from those of fertile ovules at 20 days after anthesis (20 DAA). The fertile ovules had completely formed tissues, such as the embryo sac, embryo and endosperm. By contrast, in the abortive ovules, there were no embryo sacs, and wide spaces between the integuments were observed, with few nucelli. Fluorescence labelling of the nuclei and transmission electron microscopy (TEM) observations showed that cells of abortive ovules were abnormally shaped and had thickened cell walls, folded cell membranes, condensed cytoplasm, ruptured nuclear membranes, degraded nucleoli and reduced mitochondria. The iTRAQ (isobaric tag for relative and absolute quantitation) results showed that in the abortive ovules, low levels of soluble protein with small molecular weights were found, and most of differently expressed proteins (DEPs) were related to protein synthesis, accumulation of active oxygen free radical, energy synthesis and so on. These DEPs might be associated with abnormal ovules formation.

Identification of differential proteomics in Epstein-Barr virus-associated gastric cancer and related functional analysis

BACKGROUND

Epstein-Barr virus-associated gastric cancer (EBVaGC) is the most common EBV-related malignancy. A comprehensive research for the protein expression patterns in EBVaGC established by high-throughput assay remains lacking. In the present study, the protein profile in EBVaGC tissue was explored and related functional analysis was performed.

METHODS

Epstein-Barr virus-encoded RNA (EBER) in situ hybridization (ISH) was applied to EBV detection in GC cases. Data-independent acquisition (DIA) mass spectrometry (MS) was performed for proteomics assay of EBVaGC. Functional analysis of identified proteins was conducted with bioinformatics methods. Immunohistochemistry (IHC) staining was employed to detect protein expression in tissue.

RESULTS

The proteomics study for EBVaGC was conducted with 7 pairs of GC cases. A total of 137 differentially expressed proteins in EBV-positive GC group were identified compared with EBV-negative GC group. A PPI network was constructed for all of them, and several proteins with relatively high interaction degrees could be the hub genes in EBVaGC. Gene enrichment analysis showed they might be involved in the biological pathways related to energy and biochemical metabolism. Combined with GEO datasets, a highly associated protein (GBP5) with EBVaGC was screened out and validated with IHC staining. Further analyses demonstrated that GBP5 protein might be associated with clinicopathological parameters and EBV infection in GC.

CONCLUSIONS

The newly identified proteins with significant differences and potential central roles could be applied as diagnostic markers of EBVaGC. Our study would provide research clues for EBVaGC pathogenesis as well as novel targets for the molecular-targeted therapy of EBVaGC.

Applied Proteomics in 'One Health'

‘One Health’ summarises the idea that human health and animal health are interdependent and bound to the health of ecosystems. The purpose of proteomics methodologies and studies is to determine proteins present in samples of interest and to quantify changes in protein expression during pathological conditions. The objectives of this paper are to review the application of proteomics technologies within the One Health concept and to appraise their role in the elucidation of diseases and situations relevant to One Health. The paper develops in three sections. Proteomics Applications in Zoonotic Infections part discusses proteomics applications in zoonotic infections and explores the use of proteomics for studying pathogenetic pathways, transmission dynamics, diagnostic biomarkers and novel vaccines in prion, viral, bacterial, protozoan and metazoan zoonotic infections. Proteomics Applications in Antibiotic Resistance part discusses proteomics applications in mechanisms of resistance development and discovery of novel treatments for antibiotic resistance. Proteomics Applications in Food Safety part discusses the detection of allergens, exposure of adulteration, identification of pathogens and toxins, study of product traits and characterisation of proteins in food safety. Sensitive analysis of proteins, including low-abundant ones in complex biological samples, will be achieved in the future, thus enabling implementation of targeted proteomics in clinical settings, shedding light on biomarker research and promoting the One Health concept.

Proteomic and molecular evidences of Il1rl2, Ric8a, Krt18 and Hsp90b1 modulation during experimental hepatic fibrosis and pomegranate supplementation

The inspection of variations in the proteomic aspects conspire the biomarker discovery in diagnostics of peculiar diseases. Recent developments in high-throughput proteomic techniques have provided leverage in the discovery of biomarkers during the etiology of various diseases. We identified potential biomarkers by utilizing proteomics, bioinformatics and gene expression studies. Meticulous assessment of collagen and hydroxyproline levels along with the glycogen and protein carbonyl levels exhibited deterioration in the N' - Nitrosodiethylamine (NDEA) administered rat livers and subsequent salubrious effect of pomegranate juice. The immunohistochemical inspection of iNOS and nitrite estimation indicated the peccant fibrotic alterations. 2D proteome profiling and MALDI-TOF MS/MS furthered the significant biomarkers to be analyzed for the gene ontology by PANTHER, cluster analysis by DAVID and network simulation by STRING 10.0. Several genes found relevant after MALDI analysis were evaluated by real-time PCR (RTPCR). Our data revealed CYP2b15, HSP70, TRFE, HPT, Il1rl2, Ric8a, Krt18, Hsp90b1 and iNOS as novel biomarkers for the mechanism of pomegranate against liver fibrosis. It can be inferred that NDEA-induced liver fibrosis actuates various biological pathways by the identified biomarkers and pomegranate juice modifies them.

Proteomic Advances in Milk and Dairy Products

Proteomics is a new area of study that in recent decades has provided great advances in the field of medicine. However, its enormous potential for the study of proteomes makes it also applicable to other areas of science. Milk is a highly heterogeneous and complex fluid, where there are numerous genetic variants and isoforms with post-translational modifications (PTMs). Due to the vast number of proteins and peptides existing in its matrix, proteomics is presented as a powerful tool for the characterization of milk samples and their products. The technology developed to date for the separation and characterization of the milk proteome, such as two-dimensional gel electrophoresis (2DE) technology and especially mass spectrometry (MS) have allowed an exhaustive characterization of the proteins and peptides present in milk and dairy products with enormous applications in the industry for the control of fundamental parameters, such as microbiological safety, the guarantee of authenticity, or the control of the transformations carried out, aimed to increase the quality of the final product.

Proteome analysis using machine learning approaches and its applications to diseases

With the tremendous developments in the fields of biological and medical technologies, huge amounts of data are generated in the form of genomic data, images in medical databases or as data on protein sequences, and so on. Analyzing this data through different tools sheds light on the particulars of the disease and our body's reactions to it, thus, aiding our understanding of the human health. Most useful of these tools is artificial intelligence and deep learning (DL). The artificially created neural networks in DL algorithms help extract viable data from the datasets, and further, to recognize patters in these complex datasets. Therefore, as a part of machine learning, DL helps us face all the various challenges that come forth during protein prediction, protein identification and their quantification. Proteomics is the study of such proteins, their structures, features, properties and so on. As a form of data science, Proteomics has helped us progress excellently in the field of genomics technologies. One of the major techniques used in proteomics studies is mass spectrometry (MS). However, MS is efficient with analysis of large datasets only with the added help of informatics approaches for data analysis and interpretation; these mainly include machine learning and deep learning algorithms. In this chapter, we will discuss in detail the applications of deep learning and various algorithms of machine learning in proteomics.

Identification and Immunological Characterization of Somatic Proteins from Adults of Toxocara cati by Proteomics Technique

Background:

Toxocara cati is considered as one of the main etiological agents of toxocariasis with global and regional importance. As there is no information on proteomics of T. cati, herein, we reported the results obtained by proteomic analysis of somatic proteins extract, using a mass spectrometry (LC–MS/MS) approach.

Methods:

Somatic extract fractions were separated by two-dimensional SDS-PAGE and were electro blotted on to PVDF membranes for immunoblot analysis, then collected the immunogenic spots which response of antibodies of the paratenic hosts (mice) to the antigens (Mashhad, 2017), and analyzed by LC–MS/MS. The LC-MS/MS data were analyzed by Mascot database, Taxonomy Toxocara, and common contaminants, in Omics Center, Biotechnology Medical University of Graz (Austria, 2018).

Result:

The protein spots were isolated between 15–140 kDa ranges using 3–10 non-linear IPG strips and Brilliant Blue Coomassie. Ten proteins were characterized as immunogenic proteins, seven of them were identified and three of them were unknown proteins.

Conclusion:

This study provided additional information about the somatic antigens of T. cati, which can lead to the development of new strategies for novel immuno-modulators, drug targets, subunit vaccines and immunodiagnostic kits for toxocariasis.

Comparative Proteomic Study Shows the Expression of Hint-1 in Pituitary Adenomas

Pituitary adenomas (PAs) can be unpredictable and aggressive tumors. No reliable markers of their biological behavior have been found. Here, a proteomic analysis was applied to identify proteins in the expression profile between invasive and non-invasive PAs to search for possible biomarkers. A histopathological and immunohistochemical (adenohypophyseal hormones, Ki-67, p53, CD34, VEGF, Flk1 antibodies) analysis was done; a proteomic map was evaluated in 64 out of 128 tumors. There were 107 (84%) invasive and 21 (16%) non-invasive PAs; 80.5% belonged to III and IV grades of the Hardy–Vezina classification. Invasive PAs (n = 56) showed 105 ± 43 spots; 86 ± 32 spots in non-invasive PAs (n = 8) were observed. The 13 most prominent spots were selected and 11 proteins related to neoplastic process in different types of tumors were identified. Hint1 (Histidine triad nucleotide-binding protein 1) high expression in invasive PA was found (11.8 ± 1.4, p = 0.005), especially at high index (>10; p = 0.0002). High Hint1 expression was found in invasive VEGF positive PA (13.8 ± 2.3, p = 0.005) and in Flk1 positive PA (14.04 ± 2.28, p = 0.006). Hint1 is related to human tumorigenesis by its interaction with signaling pathways and transcription factors. It could be related to invasive behavior in PAs. This is the first report on Hint expression in PAs. More analysis is needed to find out the possible role of Hint in these tumors.

Enzymes as a Reservoir of Host Defence Peptides

Host defence peptides (HDPs) are powerful modulators of cellular responses to various types of insults caused by pathogen agents. To date, a wide range of HDPs, from species of different kingdoms including bacteria, plant and animal with extreme diversity in structure and biological activity, have been described. Apart from a limited number of peptides ribosomally synthesized, a large number of promising and multifunctional HDPs have been identified within protein precursors, with properties not necessarily related to innate immunity, consolidating the fascinating hypothesis that proteins have a second or even multiple biological mission in the form of one or more bio-active peptides. Among these precursors, enzymes constitute certainly an interesting group, because most of them are mainly globular and characterized by a fine specific internal structure closely related to their catalytic properties and also because they are yet little considered as potential HDP releasing proteins. In this regard, the main aim of the present review is to describe a panel of HDPs, identified in all canonical classes of enzymes, and to provide a detailed description on hydrolases and their corresponding HDPs, as there seems to exist a striking link between these structurally sophisticated catalysts and their high content in cationic and amphipathic cryptic peptides.

Fish Pathology Research and Diagnosis in Aquaculture of Farmed Fish; a Proteomics Perspective

One of the main constraints in aquaculture production is farmed fish vulnerability to diseases due to husbandry practices or external factors like pollution, climate changes, or even the alterations in the dynamic of product transactions in this industry. It is though important to better understand and characterize the intervenients in the process of a disease outbreak as these lead to huge economical losses in aquaculture industries. High-throughput technologies like proteomics can be an important characterization tool especially in pathogen identification and the virulence mechanisms related to host-pathogen interactions on disease research and diagnostics that will help to control, prevent, and treat diseases in farmed fish. Proteomics important role is also maximized by its holistic approach to understanding pathogenesis processes and fish responses to external factors like stress or temperature making it one of the most promising tools for fish pathology research.

Proteomics and Leishmaniasis: Potential Clinical Applications

Leishmaniases are diseases caused by protozoan parasites of the genus Leishmania. They are endemic in 98 countries, affect around 12 million people worldwide and may present several distinct clinical forms. Unfortunately, there are only a few drugs available for treatment of leishmaniasis, which are toxic and not always effective. Different parasite species and different clinical forms require optimization of the treatment or more specific therapies, which are not available. The emergence of resistance is also a matter of concern. Besides, diagnosis can sometimes be complicated due to atypical manifestations and associations with other pathologies. In this review, proteomic data are presented and discussed in terms of their application in important issues in leishmaniasis such as parasite resistance to chemotherapy, diagnosis of active disease in patients and dogs, markers for different clinical forms, identification of virulence factors, and their potential use in vaccination. It is shown that proteomics has contributed to the discovery of potential biomarkers for prognosis, diagnosis, therapeutics, monitoring of disease progression, treatment follow-up and identification of vaccine candidates for specific diseases. However, the authors believe its capabilities have not yet been fully explored for routine clinical analysis for several reasons, which will be presented in this review.

Purification and Proteomic Analysis of Alphavirus Particles from Sindbis Virus Grown in Mammalian and Insect Cells

Current mass spectrometry (MS) methods and new instrumentation now allow for more accurate identification of proteins in low abundance than previous protein fractionation and identification methods. It was of interest if this method could serve to define the virus proteome of a membrane-containing virus. To evaluate the efficacy of mass spec to determine the proteome of medically important viruses, Sindbis virus (SINV), the prototypical alphavirus was chosen for evaluation. This model system was chosen specifically because the alphaviruses contain members which are human pathogens, this virus is well defined biochemically and structurally, and grows to high titers in both vertebrate and non-vertebrate host cells. The SINV proteome was investigated using this method to determine if host proteins are specifically packaged into infectious virions. It was also of interest if the SINV proteome, when grown in multiple host cells representing vertebrate and mosquito hosts, incorporated specific host proteins from all hosts. Observation of recurrent or distinctive proteins in the virus proteome aided in the determination of proteins incorporated into the virion as opposed to those bound to the particle exterior. Mass spectrometry analysis identified the total protein content of purified virions within limits of detection. The most significant finding was that in addition to the host proteins, SINV non-structural protein 2 (nsP2) was detected within virions grown in all host cells examined. This analysis identified host factors not previously associated with alphavirus entry, replication, or egress, identifying at least one host factor integrally involved in alphavirus replication. Key to the success of this analysis is the method of virus purification which must deliver measurably infectious virus free of high levels of contaminants. For SINV and other members of the alphavirus family, this is accomplished by isopycnic centrifugation through potassium tartrate, followed by a high salt wash.

The Development of a Personalised Training Framework: Implementation of Emerging Technologies for Performance

Over the last decade, there has been considerable interest in the individualisation of athlete training, including the use of genetic information, alongside more advanced data capture and analysis techniques. Here, we explore the evidence for, and practical use of, a number of these emerging technologies, including the measurement and quantification of epigenetic changes, microbiome analysis and the use of cell-free DNA, along with data mining and machine learning. In doing so, we develop a theoretical model for the use of these technologies in an elite sport setting, allowing the coach to better answer six key questions: (1) To what training will my athlete best respond? (2) How well is my athlete adapting to training? (3) When should I change the training stimulus (i.e., has the athlete reached their adaptive ceiling for this training modality)? (4) How long will it take for a certain adaptation to occur? (5) How well is my athlete tolerating the current training load? (6) What load can my athlete handle today? Special consideration is given to whether such an individualised training framework will outperform current methods as well as the challenges in implementing this approach.

Differential proteome analysis of diabetes mellitus type 2 and its pathophysiological complications

The prevalence of Diabetes Mellitus Type 2 (DM 2) is increasing every passing year due to some global changes in lifestyles of people. The exact underlying mechanisms of the progression of this disease are not yet known. However recent advances in the combined omics more particularly in proteomics and genomics have opened a gateway towards the understanding of predetermined genetic factors, progression, complications and treatment of this disease. Here we shall review the recent advances in proteomics that have led to an early and better diagnostic approaches in controlling DM 2 more importantly the comparison of structural and functional protein biomarkers that are modified in the diseased state. By applying these advanced and promising proteomic strategies with bioinformatics applications and bio-statistical tools the prevalence of DM 2 and its associated disorders i-e nephropathy and retinopathy are expected to be controlled.

Current Status and Future Opportunities of Omics Tools in Mycotoxin Research

Mycotoxins are toxic secondary metabolites of low molecular weight produced by filamentous fungi, such as Aspergillus, Fusarium, and Penicillium spp. Mycotoxins are natural contaminants of agricultural commodities and their prevalence may increase due to global warming. Dangerous mycotoxins cause a variety of health problems not only for humans, but also for animals. For instance, they possess carcinogenic, immunosuppressive, hepatotoxic, nephrotoxic, and neurotoxic effects. Hence, various approaches have been used to assess and control mycotoxin contamination. Significant challenges still exist because of the complex heterogeneous nature of food composition. The potential of combined omics approaches such as metabolomics, genomics, transcriptomics, and proteomics would contribute to our understanding about pathogen fungal crosstalk as well as strengthen our ability to identify, isolate, and characterise mycotoxins pre and post-harvest. Multi-omics approaches along with advanced analytical tools and chemometrics provide a complete annotation of such metabolites produced before/during the contamination of crops. We have assessed the merits of these individual and combined omics approaches and their promising applications to mitigate the issue of mycotoxin contamination. The data included in this review focus on aflatoxin, ochratoxin, and patulin and would be useful as benchmark information for future research.

Proteomic Lung Analysis of Mice with Ventilator-Induced Lung Injury (VILI) Using iTRAQ-Based Quantitative Proteomics

Ventilator-induced lung injury (VILI) has implications for mortality from acute lung injury (ALI) and for acute respiratory distress syndrome (ARDS) patients; the complicated mechanisms of VILI have not been well defined. To discover new biomarkers and mechanisms of VILI, isobaric Tag for Relative and Absolute Quantitation (iTRAQ)-based quantitative proteomics were applied to identify differentially expressed proteins in mice treated with high tidal volume ventilation (HV), low tidal volume ventilation (LV) and lipopolysaccharide (LPS). A total of 14 dysregulated proteins showed the same change trend both in the LV and HV group and no change in the LPS group, and most importantly, the fold change of these proteins increased with the increase of volume ventilation, which indicates these proteins may be considered as potential markers specific for VILI. Ingenuity pathway analysis (IPA) canonical pathways analysis identified the top 4 canonical pathways, including the extrinsic prothrombin activation pathway, coagulation systems, the intrinsic prothrombin activation pathway and the acute phase response, suggesting that these pathways, as associated with these proteins' expression, may be important therapeutic targets for reducing VILI. These findings will provide a new perspective for understanding the pathogenesis of VILI in the future.

Utilizing proteomics to understand and define hypertension: where are we and where do we go?

INTRODUCTION

Hypertension is a complex and multifactorial cardiovascular disorder. With different mechanisms contributing to a different extent to an individual's blood pressure, the discovery of novel pathogenetic principles of hypertension is challenging. However, there is an urgent and unmet clinical need to improve prevention, detection, and therapy of hypertension in order to reduce the global burden associated with hypertension-related cardiovascular diseases. Areas covered: Proteomic techniques have been applied in reductionist experimental models including angiotensin II infusion models in rodents and the spontaneously hypertensive rat in order to unravel mechanisms involved in blood pressure control and end organ damage. In humans proteomic studies mainly focus on prediction and detection of organ damage, particularly of heart failure and renal disease. While there are only few proteomic studies specifically addressing human primary hypertension, there are more data available in hypertensive disorders in pregnancy, such as preeclampsia. We will review these studies and discuss implications of proteomics on precision medicine approaches. Expert commentary: Despite the potential of proteomic studies in hypertension there has been moderate progress in this area of research. Standardized large-scale studies are required in order to make best use of the potential that proteomics offers in hypertension and other cardiovascular diseases.

Applications of transcriptomics and proteomics in understanding fish immunity

With the development of intensive aquaculture, economic losses increasingly result from fish mortality due to pathogen infection. In recent years, a growing number of researchers have used transcriptomic and proteomic analyses to study fish immune responses to exogenous pathogen infection. Integrating transcriptomic and proteomic analyses provides a better understanding of the fish immune system including gene expression, regulation, and the intricate biological processes underlying immune responses against infection. This review focuses on the recent advances in the fields of transcriptomics and proteomics, which have contributed to our understanding of fish immunity to exogenous pathogens.

A computational framework for complex disease stratification from multiple large-scale datasets

BACKGROUND

Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states.

METHODS

The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification.

RESULTS

We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes.

CONCLUSIONS

This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.

Association of Proteomics Changes with Al-Sensitive Root Zones in Switchgrass

In this paper, we report on aluminum (Al)-induced root proteomic changes in switchgrass. After growth in a hydroponic culture system supplemented with 400 μM of Al, plants began to show signs of physiological stress such as a reduction in photosynthetic rate. At this time, the basal 2-cm long root tips were harvested and divided into two segments, each of 1-cm in length, for protein extraction. Al-induced changes in proteomes were identified using tandem mass tags mass spectrometry (TMT-MS)-based quantitative proteomics analysis. A total of 216 proteins (approximately 3.6% of total proteins) showed significant differences between non-Al treated control and treated groups with significant fold change (twice the standard deviation; FDR adjusted p-value < 0.05). The apical root tip tissues expressed more dramatic proteome changes (164 significantly changed proteins; 3.9% of total proteins quantified) compared to the elongation/maturation zones (52 significantly changed proteins, 1.1% of total proteins quantified). Significantly changed proteins from the apical 1-cm root apex tissues were clustered into 25 biological pathways; proteins involved in the cell cycle (rotamase FKBP 1 isoforms, and CDC48 protein) were all at a reduced abundance level compared to the non-treated control group. In the root elongation/maturation zone tissues, the identified proteins were placed into 18 pathways, among which proteins involved in secondary metabolism (lignin biosynthesis) were identified. Several STRING protein interaction networks were developed for these Al-induced significantly changed proteins. This study has identified a large number of Al-responsive proteins, including transcription factors, which will be used for exploring new Al tolerance genes and mechanisms. Data are available via ProteomeXchange with identifiers PXD008882 and PXD009125.

Integrating omics to unravel the stress-response mechanisms in probiotic bacteria: Approaches, challenges, and prospects

Identifying the stress-response mechanism of probiotic bacteria has always captivated the interest of food producers. It is crucial to identify probiotic bacteria that have increased stress tolerance to survive during production, processing, and storage of food products. However, in order to achieve high resistance to environmental factors, there is a need to better understand stress-induced responses and adaptive mechanisms. With advances in bacterial genomics, there has been an upsurge in the application of other omic platforms such as transcriptomics, proteomics, metabolomics, and some more recent ones such as interactomics, fluxomics, and phenomics. These omic technologies have revolutionized the functional genomics and their application. There have been several studies implementing various omic technologies to investigate the stress responses of probiotic bacteria. Integrated omics has the potential to provide in-depth information about the mechanisms of stress-induced responses in bacteria. However, there remain challenges in integrating information from different omic platforms. This review discusses current omic techniques and challenges faced in integrating various omic platforms with focus on their use in stress-response studies.

Proteomics and lipidomics in the human brain

Proteomics and lipidomics are powerful tools to the large-scale study of proteins and lipids, respectively. Several methods can be employed with particular benefits and limitations in the study of human brain. This is a review of the rationale use of current techniques with particular attention to limitations and pitfalls inherent to each one of the techniques, and more importantly, to their use in the study of post-mortem brain tissue. These aspects are cardinal to avoid false interpretations, errors and unreal expectancies. Other points are also stressed as exemplified in the analysis of human neurodegenerative diseases which are manifested by disease-, region-, and stage-specific modifications commonly in the context of aging. Information about certain altered protein clusters and proteins oxidatively damaged is summarized for Alzheimer and Parkinson diseases.

Thirty Minutes of Hypobaric Hypoxia Provokes Alterations of Immune Response, Haemostasis, and Metabolism Proteins in Human Serum

Hypobaric hypoxia (HH) during airline travel induces several (patho-) physiological reactions in the human body. Whereas severe hypoxia is investigated thoroughly, very little is known about effects of moderate or short-term hypoxia, e.g. during airline flights. The aim of the present study was to analyse changes in serum protein expression and activation of signalling cascades in human volunteers staying for 30 min in a simulated altitude equivalent to airline travel. After approval of the local ethics committee, 10 participants were exposed to moderate hypoxia (simulation of 2400 m or 8000 ft for 30 min) in a hypobaric pressure chamber. Before and after hypobaric hypoxia, serum was drawn, centrifuged, and analysed by two-dimensional gel electrophoresis (2-DIGE) and matrix-assisted laser desorption/ionization followed by time-of-flight mass spectrometry (MALDI-TOF). Biological functions of regulated proteins were identified using functional network analysis (GeneMania®, STRING®, and Perseus® software). In participants, oxygen saturation decreased from 98.1 ± 1.3% to 89.2 ± 1.8% during HH. Expression of 14 spots (i.e., 10 proteins: ALB, PGK1, APOE, GAPDH, C1QA, C1QB, CAT, CA1, F2, and CLU) was significantly altered. Bioinformatic analysis revealed an association of the altered proteins with the signalling cascades "regulation of haemostasis" (four proteins), "metabolism" (five proteins), and "leukocyte mediated immune response" (five proteins). Even though hypobaric hypoxia was short and moderate (comparable to an airliner flight), analysis of protein expression in human subjects revealed an association to immune response, protein metabolism, and haemostasis.

The maternal plasma proteome changes as a function of gestational age in normal pregnancy: a longitudinal study

OBJECTIVE

Pregnancy is accompanied by dramatic physiological changes in maternal plasma proteins. Characterization of the maternal plasma proteome in normal pregnancy is an essential step for understanding changes to predict pregnancy outcome. The objective of this study was to describe maternal plasma proteins that change in abundance with advancing gestational age and determine biological processes that are perturbed in normal pregnancy.

STUDY DESIGN

A longitudinal study included 43 normal pregnancies that had a term delivery of an infant who was appropriate for gestational age without maternal or neonatal complications. For each pregnancy, 3 to 6 maternal plasma samples (median, 5) were profiled to measure the abundance of 1125 proteins using multiplex assays. Linear mixed-effects models with polynomial splines were used to model protein abundance as a function of gestational age, and the significance of the association was inferred via likelihood ratio tests. Proteins considered to be significantly changed were defined as having the following: (1) >1.5-fold change between 8 and 40 weeks of gestation; and (2) a false discovery rate-adjusted value of P < .1. Gene ontology enrichment analysis was used to identify biological processes overrepresented among the proteins that changed with advancing gestation.

RESULTS

The following results were found: (1) Ten percent (112 of 1125) of the profiled proteins changed in abundance as a function of gestational age; (2) of the 1125 proteins analyzed, glypican-3, sialic acid-binding immunoglobulin-type lectin-6, placental growth factor, C-C motif-28, carbonic anhydrase 6, prolactin, interleukin-1 receptor 4, dual-specificity mitogen-activated protein kinase 4, and pregnancy-associated plasma protein-A had more than a 5-fold change in abundance across gestation (these 9 proteins are known to be involved in a wide range of both physiological and pathological processes, such as growth regulation, embryogenesis, angiogenesis immunoregulation, inflammation etc); and (3) biological processes associated with protein changes in normal pregnancy included defense response, defense response to bacteria, proteolysis, and leukocyte migration (false discovery rate, 10%).

CONCLUSION

The plasma proteome of normal pregnancy demonstrates dramatic changes in both the magnitude of changes and the fraction of the proteins involved. Such information is important to understand the physiology of pregnancy and the development of biomarkers to differentiate normal vs abnormal pregnancy and determine the response to interventions.