Two-dimensional gel electrophoresis in proteomics: a tutorial. J Proteomics. 2011;74:1829-1841. [PMID: 21669304 DOI: 10.1016/j.jprot.2011.05.040]

Metaproteomics as a Powerful Tool for an Extensive Characterization of Ambient Bioaerosols

Bioaerosols are of great health and environmental concern. Current techniques for their characterization are generally designed to detect individual species or oppositely unspecific molecular tracers. Metaproteomics on the other hand features the possibility to cover a broad range of taxonomies in a single analysis. This work presents a successful application of metaproteomics to characterize the biological fraction of airborne particulate matter (PM). A bottom-up proteomic strategy was employed, including protein extraction by ultrasonication in aqueous buffer, in-solution tryptic digestion, and nanoflow liquid chromatography-high-resolution mass spectrometry analysis. Extraction parameters were optimized to enhance proteins' recovery. The method was validated on Escherichia coli extracts before its application on ambient PM10 samples collected over 12 weeks in Strasbourg, France. A total of 1,087 peptides were detected across all samples, with a weekly average of 223 ± 104 peptides corresponding to 111 ± 40 proteins. Peptides from species belonging to animals, plants, fungi, bacteria, and archaea kingdoms were inventoried. Many of them proved to be very relevant, as they were related to human allergens and pathogens, plant pathogens, or ecological indicators. In this work, the major benefits of metaproteomics, yet rather unexploited, as well as its pitfalls and challenges for a broader application in atmospheric chemistry, are discussed.

CRISPR-Based Biosensors for Medical Diagnosis: Readout from Detector-Dependence Detection Toward Naked Eye Detection

The detection of biomarkers (such as DNA, RNA, and protein) plays a vital role in medical diagnosis. The CRISPR-based biosensors utilize the CRISPR/Cas system for biometric recognition of targets and use biosensor strategy to read out biological signals without the employment of professional operations. Consequently, the CRISPR-based biosensors demonstrate great potential for the detection of biomarkers with high sensitivity and specificity. However, the signal readout still relies on specialized detectors, limiting its application in on-site detection for medical diagnosis. In this review, we summarize the principles and advances of the CRISPR-based biosensors with a focus on medical diagnosis. Then, we review the advantages and progress of CRISPR-based naked eye biosensors, which can realize diagnosis without additional detectors for signal readout. Finally, we discuss the challenges and further prospects for the development of CRISPR-based biosensors.

Whole protein sequencing and quantification without proteolysis, terminal residue cleavage, or purification: A computational model

Sequencing and quantification of whole proteins in a sample without separation, terminal residue cleavage, or proteolysis are modeled computationally. Similar to recent work on DNA sequencing (PNAS 113, 5233-5238, 2016), a high-volume conjugate is attached to every instance of amino acid (AA) type AAi, 1 ≤ i ≤ 20, in an unfolded whole protein, which is then translocated through a nanopore. From the volume excluded by 2L residues in a pore of length L nm (a proxy for the blockade current), a partial sequence containing AAi is obtained. Translocation is assumed to be unidirectional, with residues exiting the pore at a roughly constant rate of ~1/μs (Nature Biotechnology 41, 1130-1139, 2023). The blockade signal is sampled at intervals of 1 μs and digitized with a step precision of 70 nm3; the positions of the AAis are obtained from the positions of well-defined quantum jumps in the signal. This procedure is applied to all 20 standard AA types, the resulting 20 partial sequences are merged to obtain the whole protein sequence. The complexity of subsequence computation is O(N) for a protein with N residues. The method is illustrated with a sample protein from the human proteome (Uniprot id UP000005640_9606). A mixture of M' protein molecules (including multiple copies) can be sequenced by constructing an M' × 20 array of partial sequences from which proteins occurring multiple times are first isolated and their sequences obtained separately. The remaining M singly-occurring molecules are detected from M disjoint paths through the 20 columns of the reduced M × 20 array. Detection complexity is O(M20), which is nominally in polynomial time but practical only for small M; to use this method a sample may be subdivided into subsamples down to this level. Quantification of proteins can be done by sorting their computed sequences on the sequence strings and counting the number of duplicates. The possibility of translating this procedure into practice and related implementation issues are discussed.

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

This perspective article is concerned with the question of how proteomics, which is a core technique of systems biology that is deeply embedded in the multi-omics field of modern bioresearch, can help us better understand the molecular pathogenesis of complex diseases. As an illustrative example of a monogenetic disorder that primarily affects the neuromuscular system but is characterized by a plethora of multi-system pathophysiological alterations, the muscle-wasting disease Duchenne muscular dystrophy was examined. Recent achievements in the field of dystrophinopathy research are described with special reference to the proteome-wide complexity of neuromuscular changes and body-wide alterations/adaptations. Based on a description of the current applications of top-down versus bottom-up proteomic approaches and their technical challenges, future systems biological approaches are outlined. The envisaged holistic and integromic bioanalysis would encompass the integration of diverse omics-type studies including inter- and intra-proteomics as the core disciplines for systematic protein evaluations, with sophisticated biomolecular analyses, including physiology, molecular biology, biochemistry and histochemistry. Integrated proteomic findings promise to be instrumental in improving our detailed knowledge of pathogenic mechanisms and multi-system dysfunction, widening the available biomarker signature of dystrophinopathy for improved diagnostic/prognostic procedures, and advancing the identification of novel therapeutic targets to treat Duchenne muscular dystrophy.

Trends and challenges in microfluidic methods for protein manipulation-A review

Proteins are important molecules involved in an immensely large number of biological processes. Being capable of manipulating proteins is critical for developing reliable and affordable techniques to analyze and/or detect them. Such techniques would enable the production of therapeutic agents for the treatment of diseases or other biotechnological applications (e.g., bioreactors or biocatalysis). Microfluidic technology represents a potential solution to protein manipulation challenges because of the diverse phenomena that can be exploited to achieve micro- and nanoparticle manipulation. In this review, we discuss recent contributions made in the field of protein manipulation in microfluidic systems using different physicochemical principles and techniques, some of which are miniaturized versions of already established macro-scale techniques.

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.

Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology

Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.

Mass spectrometry-based retina proteomics

A subfield of neuroproteomics, retina proteomics has experienced a transformative growth since its inception due to methodological advances in enabling chemical, biochemical, and molecular biology techniques. This review focuses on mass spectrometry's contributions to facilitate mammalian and avian retina proteomics to catalog and quantify retinal protein expressions, determine their posttranslational modifications, as well as its applications to study the proteome of the retina in the context of biology, health and diseases, and therapy developments.

Immunoproteomics and phage display in the context of leishmaniasis complexity

Leishmaniasis is defined as a complex of diseases caused by protozoan parasites of the genus Leishmania, which comprises 20 parasite species pathogenic to mammalians, such as humans and dogs. From a clinical point of view, and considering the diversity and biological complexity of the parasites, vectors, and vertebrate hosts, leishmaniasis is classified according to the distinct clinical manifestations, such as tegumentary (involving the cutaneous, mucosal, and cutaneous-diffuse forms) and visceral leishmaniasis. Many issues and challenges remain unaddressed, which could be attributed to the complexity and diversity of the disease. The current demand for the identification of new Leishmania antigenic targets for the development of multicomponent-based vaccines, as well as for the production of specific diagnostic tests, is evident. In recent years, biotechnological tools have allowed the identification of several Leishmania biomarkers that might potentially be used for diagnosis and have an application in vaccine development. In this Mini Review, we discuss the different aspects of this complex disease that have been addressed by technologies such as immunoproteomics and phage display. It is extremely important to be aware of the potential applications of antigens selected in different screening context, so that they can be used appropriately, so understanding their performance, characteristics, and self-limitations.

Fiber-Type Shifting in Sarcopenia of Old Age: Proteomic Profiling of the Contractile Apparatus of Skeletal Muscles

The progressive loss of skeletal muscle mass and concomitant reduction in contractile strength plays a central role in frailty syndrome. Age-related neuronal impairments are closely associated with sarcopenia in the elderly, which is characterized by severe muscular atrophy that can considerably lessen the overall quality of life at old age. Mass-spectrometry-based proteomic surveys of senescent human skeletal muscles, as well as animal models of sarcopenia, have decisively improved our understanding of the molecular and cellular consequences of muscular atrophy and associated fiber-type shifting during aging. This review outlines the mass spectrometric identification of proteome-wide changes in atrophying skeletal muscles, with a focus on contractile proteins as potential markers of changes in fiber-type distribution patterns. The observed trend of fast-to-slow transitions in individual human skeletal muscles during the aging process is most likely linked to a preferential susceptibility of fast-twitching muscle fibers to muscular atrophy. Studies with senescent animal models, including mostly aged rodent skeletal muscles, have confirmed fiber-type shifting. The proteomic analysis of fast versus slow isoforms of key contractile proteins, such as myosin heavy chains, myosin light chains, actins, troponins and tropomyosins, suggests them as suitable bioanalytical tools of fiber-type transitions during aging.

Protein Digestion for 2D-DIGE Analysis

In-gel digestion of protein spots derived from two-dimensional gels and their subsequent identification by mass spectrometry is involved in a multitude of mass spectrometry-driven proteomic experiments, including fluorescence two-dimensional difference gel electrophoresis (2D-DIGE). This type of proteomic methodology has been involved in the establishment of comparative proteome maps and in the identification of differentially expressed proteins and their isoforms in health and disease. Most in-gel digestion protocols follow a number of common steps including excision of the protein spots of interest, destaining, reduction and alkylation (for silver-stained gels), and dehydration and overnight digestion with the proteolytic enzyme of choice. While trypsin has been a mainstay of peptide digestion for many years, it does have its shortcomings, particularly related to incomplete peptide digestion, and this has led to a rise in popularity for other proteolytic enzymes either used alone or in combination. This chapter discusses the alternative enzymes available and describes the process of in-gel digestion using the enzyme trypsin.

Two-CyDye-Based 2D-DIGE Analysis of Aged Human Muscle Biopsy Specimens

The gradual loss of skeletal muscle mass during aging and associated decline in contractile strength can result in reduced fitness, frailty, and loss of independence. In order to better understand the molecular and cellular mechanisms that underlie sarcopenia of old age and the frailty syndrome, as well as identify novel therapeutic targets to treat age-related fiber wasting, it is crucial to develop a comprehensive biomarker signature of muscle aging. Fluorescence two-dimensional gel electrophoresis (2D-DIGE) in combination with sensitive mass spectrometry presents an ideal bioanalytical tool for biomarker discovery in biogerontology. This chapter outlines the application of the 2D-DIGE method for the comparative analysis of human biopsy specimens from middle-aged versus senescent individuals using a two-CyDye-based method.

Two-Dye Versus Three-Dye DIGE for Comparative Testis Tissue Proteomic Analysis

The global analysis of the proteome is an important tool in cell biology. Comparative proteomic evaluations can identify and compare the composition, dynamics, and modifications between different samples. Comparing tissue proteomes under different conditions is crucial for advancing the biomedical field. Fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) is a sensitive and robust biochemical method that can compare multiple protein samples over a broad dynamic range on the same analytical gel and can be used to establish differentially expressed protein profiles between different sample groups. 2D-DIGE involves fluorescently labeling protein samples with CyDye flours, via a two-dye or a three-dye system, pre-separation by isoelectric point, and molecular weight. DIGE circumvents gel-to-gel variability by multiplexing samples to a single gel and through the use of a pooled internal standard for normalization, thus enabling accurate high-resolution analysis of differences in protein abundance between samples. This chapter discusses 2D-DIGE as a comparative tissue proteomic technique and describes in detail the experimental steps required for comparative proteomic analysis employing both options of two-dye and three-dye DIGE minimal labeling.

Top-Down Proteomics and Comparative 2D-DIGE Analysis

The combination of large-scale protein separation techniques, sophisticated mass spectrometry, and systems bioinformatics has led to the establishment of proteomics as a distinct discipline within the wider field of protein biochemistry. Both discovery proteomics and targeted proteomics are widely used in biological and biomedical research, whereby the analytical approaches can be broadly divided into proteoform-centric top-down proteomics versus peptide-centric bottom-up proteomics. This chapter outlines the scientific value of top-down proteomics and describes how fluorescence two-dimensional difference gel electrophoresis can be combined with the systematic analysis of crucial post-translational modifications. The concept of on-membrane digestion following the electrophoretic transfer of proteins and the usefulness of comparative two-dimensional immunoblotting are discussed.

Subcellular Fractionation for DIGE-Based Proteomics

Mass spectrometry-based protein methodologies have revolutionized the field of analytical biochemistry and enable the identification of hundreds to thousands of proteins in biological fluids, cell lines, and tissue. This methodology requires the initial separation of a protein constellation, and this has been successfully achieved using gel-based techniques, particularly that of fluorescence two-dimensional difference gel electrophoresis (2D-DIGE). However, given the complexity of the proteome, fractionation techniques may be required to optimize the detection of low-abundance proteins, which are often underrepresented but which may represent important players in health and disease. Such subcellular fractionation protocols typically utilize density-gradient centrifugation and have enabled the enrichment of crude microsomes, the cytosol, the plasmalemma, the nuclei, and the mitochondria. In this chapter, we describe the experimental steps involved in the enrichment of crude microsomes from the skeletal muscle using differential centrifugation and subsequent verification of enrichment by gel electrophoresis and immunoblotting, prior to comparative 2D-DIGE analysis.

Comparative 3-Sample 2D-DIGE Analysis of Skeletal Muscles

The skeletal muscle proteome consists of a large number of diverse protein species with a broad and dynamic concentration range. Since mature skeletal muscles are characterized by a distinctive combination of contractile cells with differing physiological and biochemical properties, it is essential to determine specific differences in the protein composition of fast, slow, and hybrid fibers. Fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) is a powerful comparative tool to analyze fiber type-specific differences between predominantly fast contracting versus slower twitching muscles. In this chapter, the application of the 2D-DIGE method for the comparative analysis of different subtypes of skeletal muscles is outlined in detail. A standardized proteomic workflow is described, involving sample preparation, protein extraction, differential fluorescence labeling using a 3-CyDye system, first-dimension isoelectric focusing, second-dimension slab gel electrophoresis, 2D-DIGE image analysis, protein digestion, and mass spectrometry.

Comparison of grain protein profiles of Brazilian cowpea (Vigna unguiculata) cultivars based on principal component analysis

This study aims to compare the grain protein profile of four Brazilian cowpea cultivars (BRS Aracê, BRS Itaim, BRS Pajeú, and BRS Xiquexique) by two-dimensional electrophoresis (2-DE) and principal component analysis (PCA). 2-DE efficiently separate cowpea protein profiles, showing high homogeneity among the four cultivars. In addition, the principal component analysis indicated that there is a difference in abundance of proteins among the cultivars. The cultivars BRS Aracê and BRS Xiquexique, both biofortified in iron and zinc, were separated from the cultivars BRS Itaim and BRS Pajeú. These results demonstrate that protein profiles can be used to discriminate cowpea varieties.

Graphical Abstract

A binary/digital approach to amino acid identification and its application to peptide sequencing and protein identification

A binary/digital method is proposed in theory for the identification of single amino acids (AAs) in the bulk or with a few molecules from a single binary measurement. Combined with Edman degradation (or other cleaving method), it can be used to sequence a peptide or identify the parent protein from a partial sequence. The approach is centered on the superspecificity property of transfer RNAs (tRNAs). Markedly different from conventional and recent single molecule (SM) sequencing methods based on analog measurements, it changes the analytical question 'Which AA is it?' to the much simpler one 'Is there an AA in the detection space?'. Each of 20 terminal residues cleaved from 20 copies of a peptide enters a different cavity with a unique tRNA; tRNA charging (or binding with AA) occurs only in the cavity with the cognate AA. The bound AA or the AA separated from the tRNA is detected with a single binary measurement; its identity is known from the position of the single high bit in the resulting 20-bit output. Alternatively, a 20-stage pipeline can be used with sparse samples. Detection of the bound AA can be done optically by tagging the AAs with a fluorescent dye, or of the freed AA electrically with a nanopore. Necessary conditions for accurate AA identification are satisfied in principle; related computations and simulation results are presented. A modified version that can be used for de novo sequencing in parallel of large numbers of peptides immobilized on a glass slide with the tRNAs carrying a fluorescent tag is also proposed. Both methods can be used for protein identification from partial sequences containing 2 or 3 AA types by using only the corresponding tRNAs. Experiments may be performed to validate them, followed by translation into practice with existing technology; potential implementation issues are discussed. Binary/digital amino acid identification for peptide sequencing.

Cotton proteomics: Dissecting the stress response mechanisms in cotton

The natural environment of plants comprises a complex set of biotic and abiotic stresses, and plant responses to these stresses are complex as well. Plant proteomics approaches have significantly revealed dynamic changes in plant proteome responses to stress and developmental processes. Thus, we reviewed the recent advances in cotton proteomics research under changing environmental conditions, considering the progress and challenging factors. Finally, we highlight how single-cell proteomics is revolutionizing plant research at the proteomics level. We envision that future cotton proteomics research at the single-cell level will provide a more complete understanding of cotton's response to stresses.

Application of quantitative proteomics to investigate fruit ripening and eating quality

The consumption of fruit and vegetables play an important role in human nutrition, dietary diversity and health. Fruit and vegetable industries impart significant impact on our society, economy, and environment, contributing towards sustainable development in both developing and developed countries. The eating quality of fruit is determined by its appearance, color, firmness, flavor, nutritional components, and the absence of defects from physiological disorders. However, all of these components are affected by many pre- and postharvest factors that influence fruit ripening and senescence. Significant efforts have been made to maintain and improve fruit eating quality by expanding our knowledge of fruit ripening and senescence, as well as by controlling and reducing losses. Innovative approaches are required to gain better understanding of the management of eating quality. With completion of the genome sequence for many horticultural products in recent years and development of the proteomic research technique, quantitative proteomic research on fruit is changing rapidly and represents a complementary research platform to address how genetics and environment influence the quality attributes of various produce. Quantiative proteomic research on fruit is advancing from protein abundance and protein quantitation to gene-protein interactions and post-translational modifications of proteins that occur during fruit development, ripening and in response to environmental influences. All of these techniques help to provide a comprehensive understanding of eating quality. This review focuses on current developments in the field as well as limitations and challenges, both in broad term and with specific examples. These examples include our own research experience in applying quantitative proteomic techniques to identify and quantify the protein changes in association with fruit ripening, quality and development of disorders, as well as possible control mechanisms.

Histological and Top-Down Proteomic Analyses of the Visual Pathway in the Cuprizone Demyelination Model

A change in visual perception is a frequent early symptom of multiple sclerosis (MS), the pathoaetiology of which remains unclear. Following a slow demyelination process caused by 12 weeks of low-dose (0.1%) cuprizone (CPZ) consumption, histology and proteomics were used to investigate components of the visual pathway in young adult mice. Histological investigation did not identify demyelination or gliosis in the optic tracts, pretectal nuclei, superior colliculi, lateral geniculate nuclei or visual cortices. However, top-down proteomic assessment of the optic nerve/tract revealed a significant change in the abundance of 34 spots in high-resolution two-dimensional (2D) gels. Subsequent liquid chromatography-tandem mass spectrometry (LC-TMS) analysis identified alterations in 75 proteoforms. Literature mining revealed the relevance of these proteoforms in terms of proteins previously implicated in animal models, eye diseases and human MS. Importantly, 24 proteoforms were not previously described in any animal models of MS, eye diseases or MS itself. Bioinformatic analysis indicated involvement of these proteoforms in cytoskeleton organization, metabolic dysregulation, protein aggregation and axonal support. Collectively, these results indicate that continuous CPZ-feeding, which evokes a slow demyelination, results in proteomic changes that precede any clear histological changes in the visual pathway and that these proteoforms may be potential early markers of degenerative demyelinating conditions.

Current Insights on the Impact of Proteomics in Respiratory Allergies

Respiratory allergies affect humans worldwide, causing extensive morbidity and mortality. They include allergic rhinitis (AR), asthma, pollen food allergy syndrome (PFAS), aspirin-exacerbated respiratory disease (AERD), and nasal polyps (NPs). The study of respiratory allergic diseases requires new technologies for early and accurate diagnosis and treatment. Omics technologies provide the tools required to investigate DNA, RNA, proteins, and other molecular determinants. These technologies include genomics, transcriptomics, proteomics, and metabolomics. However, proteomics is one of the main approaches to studying allergic disorders' pathophysiology. Proteins are used to indicate normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. In this field, the principal goal of proteomics has been to discover new proteins and use them in precision medicine. Multiple technologies have been applied to proteomics, but that most used for identifying, quantifying, and profiling proteins is mass spectrometry (MS). Over the last few years, proteomics has enabled the establishment of several proteins for diagnosing and treating respiratory allergic diseases.

The Use of Bacteriophages in Biotechnology and Recent Insights into Proteomics

Phages have certain features, such as their ability to form protein-protein interactions, that make them good candidates for use in a variety of beneficial applications, such as in human or animal health, industry, food science, food safety, and agriculture. It is essential to identify and characterize the proteins produced by particular phages in order to use these viruses in a variety of functional processes, such as bacterial detection, as vehicles for drug delivery, in vaccine development, and to combat multidrug resistant bacterial infections. Furthermore, phages can also play a major role in the design of a variety of cheap and stable sensors as well as in diagnostic assays that can either specifically identify specific compounds or detect bacteria. This article reviews recently developed phage-based techniques, such as the use of recombinant tempered phages, phage display and phage amplification-based detection. It also encompasses the application of phages as capture elements, biosensors and bioreceptors, with a special emphasis on novel bacteriophage-based mass spectrometry (MS) applications.

Comparative Proteomics of Mulberry Leaves at Different Developmental Stages Identify Novel Proteins Function Related to Photosynthesis

Mulberry leaves at different positions are different in photosynthetic rate, nutrient substance and feeding impact to silkworms. Here, we investigated the proteomic differences of the first (L1), sixth (L6), and twentieth (L20) mulberry leaves at different stem positions (from top to the base) using a label-free quantitative proteomics approach. L1 contained less developed photosynthetic apparatus but was more active in protein synthesis. L20 has more channel proteins and oxidoreductases relative to L6. Proteins that detected in all measured leaves were classified into three groups according to their expression patterns in L1, L6, and L20. The protein group that displayed the maximum amount in L6 has the highest possibility that function related to photosynthesis. Nine function unknown proteins belong to this group were further analyzed in the light responsive expression, evolutionary tree and sub-cellular localization analysis. Based on the results, five proteins were suggested to be involved in photosynthesis. Taken together, these results reveal the molecular details of different roles of mulberry leaves at different developmental stages and contribute to the identification of five proteins that might function related to photosynthesis.

Proteome Analysis of Whole-Body Responses in Medaka Experimentally Exposed to Fish-Killing Dinoflagellate Karenia mikimotoi

Karenia mikimotoi is a well-known harmful algal bloom species. Blooms of this dinoflagellate have become a serious threat to marine life, including fish, shellfish, and zooplanktons and are usually associated with massive fish death. Despite the discovery of several toxins such as gymnocins and gymnodimines in K. mikimotoi, the mechanisms underlying the ichthyotoxicity of this species remain unclear, and molecular studies on this topic have never been reported. The present study investigates the fish-killing mechanisms of K. mikimotoi through comparative proteomic analysis. Marine medaka, a model fish organism, was exposed to K. mikimotoi for a three-part time period (LT25, LT50 and LT90). Proteins extracted from the whole fish were separated by using two-dimensional gel electrophoresis, and differentially expressed proteins were identified with reference to an untreated control. The change in fish proteomes over the time-course of exposure were analyzed. A total of 35 differential protein spots covering 19 different proteins were identified, of which most began to show significant change in expression levels at the earliest stage of intoxication. Among the 19 identified proteins, some are closely related to the oxidative stress responses, energy metabolism, and muscle contraction. We propose that oxidative stress-mediated muscle damage might explain the symptoms developed during the ichthyotoxicity test, such as gasping for breath, loss of balance, and body twitching. Our findings lay the foundations for more in-depth studies of the mechanisms of K. mikimotoi's ichthyotoxicity.

Proteomics: Concepts and applications in human medicine

Proteomics is the complete evaluation of the function and structure of proteins to understand an organism’s nature. Mass spectrometry is an essential tool that is used for profiling proteins in the cell. However, biomarker discovery remains the major challenge of proteomics because of their complexity and dynamicity. Therefore, combining the proteomics approach with genomics and bioinformatics will provide an understanding of the information of biological systems and their disease alteration. However, most studies have investigated a small part of the proteins in the blood. This review highlights the types of proteomics, the available proteomic techniques, and their applications in different research fields.

Proteomics of Multiple Sclerosis: Inherent Issues in Defining the Pathoetiology and Identifying (Early) Biomarkers

Multiple Sclerosis (MS) is a demyelinating disease of the human central nervous system having an unconfirmed pathoetiology. Although animal models are used to mimic the pathology and clinical symptoms, no single model successfully replicates the full complexity of MS from its initial clinical identification through disease progression. Most importantly, a lack of preclinical biomarkers is hampering the earliest possible diagnosis and treatment. Notably, the development of rationally targeted therapeutics enabling pre-emptive treatment to halt the disease is also delayed without such biomarkers. Using literature mining and bioinformatic analyses, this review assessed the available proteomic studies of MS patients and animal models to discern (1) whether the models effectively mimic MS; and (2) whether reasonable biomarker candidates have been identified. The implication and necessity of assessing proteoforms and the critical importance of this to identifying rational biomarkers are discussed. Moreover, the challenges of using different proteomic analytical approaches and biological samples are also addressed.

Differentially expressed proteins in platelets derived from patients with hypertension

Hypertension (HTN) causes end-organ damage and is a major cause of morbidity and mortality globally. Recent studies suggested blood cells participate in the maintenance of HTN. Platelets—anucleated cell fragments derived from megakaryocytes—exert diverse functions, including their well-characterized role in the formation of hemostatic clots. However, platelets from patients with HTN exhibit altered membrane lipid and protein compositions that impact platelet function and lead to formation of aggregates and vascular obstructions. Here, for the first time, we have identified, by proteomic analyses, the most relevant 11 proteins that show the greatest difference in their expression in platelets derived from patients with HTN, in comparison with those from normotensive individuals. These proteins are involved in cytoskeletal organization and the coagulation cascade that contributes to platelet activation, release of granule contents, and aggregation, which culminate in thrombus formation. These results have important implications in our understanding of the molecular mechanisms associated with the development of HTN, and in consequence, the development of new strategies to counteract the cardiovascular disorders associated with constitutive activation of platelets in HTN.

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.

Neurodegenerative Proteinopathies in the Proteoform Spectrum-Tools and Challenges

Proteinopathy refers to a group of disorders defined by depositions of amyloids within living tissue. Neurodegenerative proteinopathies, including Alzheimer's disease, Parkinson's disease, Creutzfeldt-Jakob disease, and others, constitute a large fraction of these disorders. Amyloids are highly insoluble, ordered, stable, beta-sheet rich proteins. The emerging theory about the pathophysiology of neurodegenerative proteinopathies suggests that the primary amyloid-forming proteins, also known as the prion-like proteins, may exist as multiple proteoforms that contribute differentially towards the disease prognosis. It is therefore necessary to resolve these disorders on the level of proteoforms rather than the proteome. The transient and hydrophobic nature of amyloid-forming proteins and the minor post-translational alterations that lead to the formation of proteoforms require the use of highly sensitive and specialized techniques. Several conventional techniques, like gel electrophoresis and conventional mass spectrometry, have been modified to accommodate the proteoform theory and prion-like proteins. Several new ones, like imaging mass spectrometry, have also emerged. This review aims to discuss the proteoform theory of neurodegenerative disorders along with the utility of these proteomic techniques for the study of highly insoluble proteins and their associated proteoforms.

Biological Applications for LC-MS-Based Proteomics

Since its inception, liquid chromatography-mass spectrometry (LC-MS) has been continuously improved upon in many aspects, including instrument capabilities, sensitivity, and resolution. Moreover, the costs to purchase and operate mass spectrometers and liquid chromatography systems have decreased, thus increasing affordability and availability in sectors outside of academic and industrial research. Processing power has also grown immensely, cutting the time required to analyze samples, allowing more data to be feasibly processed, and allowing for standardized processing pipelines. As a result, proteomics via LC-MS has become popular in many areas of biological sciences, forging an important seat for itself in targeted and untargeted assays, pure and applied science, the laboratory, and the clinic. In this chapter, many of these applications of LC-MS-based proteomics and an outline of how they can be executed will be covered. Since the field of personalized medicine has matured alongside proteomics, it has also come to rely on various mass spectrometry methods and will be elaborated upon as well. As time goes on and mass spectrometry evolves, there is no doubt that its presence in these areas, and others, will only continue to grow.

Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages

Insights into the modes of action (MoAs) of xenobiotics are of utmost importance for the definition of adverse outcome pathways (AOPs), which are essential for a mechanism-based risk assessment. A well-established strategy to reveal MoAs of xenobiotics is the use of omics. However, often an even more comprehensive approach is needed, which can be achieved using multi-omics. Since the immune system plays a central role in the defense against foreign substances and pathogens, with the innate immune system building a first barrier, we systematically reviewed multi-omics studies investigating the effects of xenobiotics on macrophages. Surprisingly, only nine publications were identified, combining proteomics with transcriptomics or metabolomics. We summarized pathways and single proteins, transcripts, or metabolites, which were described to be affected upon treatment with xenobiotics in the reviewed studies, thus revealing a broad range of effects. In summary, we show that macrophages are a relevant model system to investigate the toxicological effects induced by xenobiotics. Furthermore, the multi-omics approaches led to a more comprehensive overview compared to only one omics layer with slight advantages for combinations that complement each other directly, e.g., proteome and metabolome.

Bringing New Methods to the Seed Proteomics Platform: Challenges and Perspectives

For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins, and carbohydrates in their seeds, distinctly dominate modern agriculture, thus play an essential role in food industry and fuel production. Therefore, seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, seed development and germination as well as age- and stress-related alterations in seed vigor, longevity, nutritional value, and safety can be addressed by a broad panel of analytical, biochemical, and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes accompanying plant development, senescence, and response to biotic or abiotic stress. Among individual post-genomic methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. During the recent decades, multiple methodological advances were introduced in different branches of life science, although only some of them were established in seed proteomics so far. Therefore, here we discuss main methodological approaches already employed in seed proteomics, as well as those still waiting for implementation in this field of plant research, with a special emphasis on sample preparation, data acquisition, processing, and post-processing. Thereby, the overall goal of this review is to bring new methodologies emerging in different areas of proteomics research (clinical, food, ecological, microbial, and plant proteomics) to the broad society of seed biologists.

Mechanisms of Insecticidal Action of Metarhizium anisopliae on Adult Japanese Pine Sawyer Beetles (Monochamus alternatus)

Pine wilt disease, caused by Bursaphelenchus xylophilus (pine wood nematode), leads to severe environmental and economic damage. Here, we report the results of experiments on the biological control of pine wilt disease through termination of the insect vector of the nematode and the mechanism of the insecticidal action of Metarhizium anisopliae JEF-279 against Monochamus alternatus (Japanese pine sawyer). A combined treatment with a fungal conidia suspension and a fungal protease-containing culture filtrate caused 75.8% mortality of the insect vector. Additionally, the presence of destruxins was confirmed in the dead Japanese pine sawyer adults, and half of the 10 protein spots in proteomic analysis were identified as an actin related to muscle contraction. Based on proteomic and microscopic analyses, the infection cycle of the Japanese pine sawyer by M. anisopliae JEF-279 was inferred to proceed in the following sequence: (1) host adhesion and germination, (2) epicuticle degradation, (3) growth as blastospore, (4) killing by various fungal toxins (insecticidal metabolites), (5) immune response as defense mechanism, and (6) hyphal extrusion and conidiation. Consequently, the combined fungal conidia suspension and protease-containing culture filtrate treatment may be applied as an insecticidal agent, and flaccid paralysis is likely a major mechanism underlying the insecticidal action of M. anisopliae JEF-279 on host insects.

Proteomics-Based Methodologies for the Detection and Quantification of Seafood Allergens

Seafood is considered one of the main food allergen sources by the European Food Safety Authority (EFSA). It comprises several distinct groups of edible aquatic animals, including fish and shellfish, such as crustacean and mollusks. Recently, the EFSA recognized the high risk of food allergy over the world and established the necessity of developing new methodologies for its control. Consequently, accurate, sensitive, and fast detection methods for seafood allergy control and detection in food products are highly recommended. In this work, we present a comprehensive review of the applications of the proteomics methodologies for the detection and quantification of seafood allergens. For this purpose, two consecutive proteomics strategies (discovery and targeted proteomics) that are applied to the study and control of seafood allergies are reviewed in detail. In addition, future directions and new perspectives are also provided.

Proteomic Strategies to Evaluate the Impact of Farming Conditions on Food Quality and Safety in Aquaculture Products

This review presents the primary applications of various proteomic strategies to evaluate the impact of farming conditions on food quality and safety in aquaculture products. Aquaculture is a quickly growing sector that represents 47% of total fish production. Food quality, dietary management, fish welfare, the stress response, food safety, and antibiotic resistance, which are covered by this review, are among the primary topics in which proteomic techniques and strategies are being successfully applied. The review concludes by outlining future directions and potential perspectives.

Detecting protein and post-translational modifications in single cells with iDentification and qUantification sEparaTion (DUET)

While technologies for measuring transcriptomes in single cells have matured, methods for measuring proteins and their post-translational modification (PTM) states in single cells are still being actively developed. Unlike nucleic acids, proteins cannot be amplified, making detection of minute quantities from single cells difficult. Here, we develop a strategy to detect targeted protein and its PTM isoforms in single cells. We barcode the proteins from single cells by tagging them with oligonucleotides, pool barcoded cells together, run bulk gel electrophoresis to separate protein and its PTM isoform and quantify their abundances by sequencing the oligonucleotides associated with each protein species. We used this strategy, iDentification and qUantification sEparaTion (DUET), to measure histone protein H2B and its monoubiquitination isoform, H2Bub, in single yeast cells. Our results revealed the heterogeneities of H2B ubiquitination levels in single cells from different cell-cycle stages, which is obscured in ensemble measurements.

The synthetic cannabinoid JWH-018 modulates Saccharomyces cerevisiae energetic metabolism

Synthetic cannabinoids are a group of novel psychoactive substances with similar properties to Δ9-THC. Among the vast number of synthetic cannabinoids, designed to be tested in clinical trials, JWH-018 was the first novel psychoactive substance found in the recreational drug marketplace. The consumption of JWH-018 shows typical effects of CB1 agonists including sedation, cognitive dysfunction, tachycardia, postural hypotension, dry mouth, ataxia and psychotropic effects, but appeared to be more potent than Δ9-THC. However, studies on human cells have shown that JWH-018 toxicity depends on the cellular line used. Despite these studies, the underlying molecular mechanisms to JWH-018 action has not been clarified yet. To understand the impact of JWH-018 at molecular and cellular level, we used Saccharomyces cerevisiae as a model. The results showed an increase in yeast growth rate in the presence of this synthetic cannabinoid due to an enhancement in the glycolytic flux at expense of a decrease in pentose phosphate pathway, judging by 2D-Gel proteomic analysis, qRT-PCR experiments and ATP measurements. Overall, our results provide insights into molecular mechanisms of JWH-018 action, also indicating that Saccharomyces cerevisiae is a good model to study synthetic cannabinoids.

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis

Proteomic technologies are powerful methodologies that can aid our understanding of mechanisms of action in biological systems by providing a global view of the impact of a disease, treatment, or other condition on the proteome as a whole. This report provides a detailed protocol for the extraction, quantification, precipitation, digestion, labeling, and subsequent data analysis of protein samples. Our optimized TMT labeling protocol requires a lower tag-label concentration and achieves consistently reliable data. We have used this protocol to evaluate protein expression profiles in a variety of mouse tissues (i.e., heart, skeletal muscle, and brain) as well as cells cultured in vitro. In addition, we demonstrate how to evaluate thousands of proteins from the resulting dataset.

Optimization of Protein Extraction Method for 2DE Proteomics of Goat's Milk

Two-dimensional electrophoretic (2DE)-based proteomics remains a powerful tool for allergenomic analysis of goat's milk but requires effective extraction of proteins to accurately profile the overall causative allergens. However, there are several current issues with goat's milk allergenomic analysis, and among these are the absence of established standardized extraction method for goat's milk proteomes and the complexity of goat's milk matrix that may hamper the efficacy of protein extraction. This study aimed to evaluate the efficacies of three different protein extraction methods, qualitatively and quantitatively, for the 2DE-proteomics, using milk from two commercial dairy goats in Malaysia, Saanen, and Jamnapari. Goat's milk samples from both breeds were extracted by using three different methods: a milk dilution in urea/thiourea based buffer (Method A), a triphasic separation protocol in methanol/chloroform solution (Method B), and a dilution in sulfite-based buffer (Method C). The efficacies of the extraction methods were assessed further by performing the protein concentration assay and 1D and 2D SDS-PAGE profiling, as well as identifying proteins by MALDI-TOF/TOF MS/MS. The results showed that method A recovered the highest amount of proteins (72.68% for Saanen and 71.25% for Jamnapari) and produced the highest number of protein spots (199 ± 16.1 and 267 ± 10.6 total spots for Saanen and Jamnapari, respectively) with superior gel resolution and minimal streaking. Six milk protein spots from both breeds were identified based on the positive peptide mass fingerprinting matches with ruminant milk proteins from public databases, using the Mascot software. These results attest to the fitness of the optimized protein extraction protocol, method A, for 2DE proteomic and future allergenomic analysis of the goat's milk.

Bioinformatics Resources for Plant Abiotic Stress Responses: State of the Art and Opportunities in the Fast Evolving -Omics Era

Abiotic stresses are among the principal limiting factors for productivity in agriculture. In the current era of continuous climate changes, the understanding of the molecular aspects involved in abiotic stress response in plants is a priority. The rise of -omics approaches provides key strategies to promote effective research in the field, facilitating the investigations from reference models to an increasing number of species, tolerant and sensitive genotypes. Integrated multilevel approaches, based on molecular investigations at genomics, transcriptomics, proteomics and metabolomics levels, are now feasible, expanding the opportunities to clarify key molecular aspects involved in responses to abiotic stresses. To this aim, bioinformatics has become fundamental for data production, mining and integration, and necessary for extracting valuable information and for comparative efforts, paving the way to the modeling of the involved processes. We provide here an overview of bioinformatics resources for research on plant abiotic stresses, describing collections from -omics efforts in the field, ranging from raw data to complete databases or platforms, highlighting opportunities and still open challenges in abiotic stress research based on -omics technologies.

Quantitative proteomic and phosphoproteomic profiling of ischemic myocardial stunning in swine

Despite decades of research on the pathophysiology of myocardial stunning, protein changes and/or phosphorylation status underlying alterations in cardiac function/structure remain inadequately understood. Here, we utilized comprehensive and quantitative proteomic and phosphoproteomic approaches to explore molecular mechanisms of myocardial stunning in swine. The closed-chest swine (n = 5 pigs) were subjected to a 10-min left anterior descending coronary artery (LAD) occlusion producing regional myocardial stunning. Tissues from the ischemic LAD region and a remote nonischemic area of the left ventricle were collected 1 h after reperfusion. Ion current-based proteomics (IonStar) and quantitative phosphoproteomics were employed in parallel to identify alterations in protein level and site-specific phosphorylation changes. A novel swine heart protein database exhibiting high accuracy and low redundancy was developed here to facilitate comprehensive study. Further informatic investigations identified potential protein-protein interactions in stunned myocardium. In total, we quantified 2,099 protein groups and 4,699 phosphorylation sites with only 0.4% missing values. Proteomic analyses revealed downregulation of contractile function and extracellular matrix remodeling. Meanwhile, alterations in phosphorylation linked with contractile dysfunction and apoptotic cell death were uncovered. NetworKIN/STRING analysis predicted regulatory kinases responsible for altered phosphosites, such as protein kinase C-mediated phosphorylation of cardiac troponin I-S199 and CaMKII-mediated phosphorylation of phospholamban-T17. In summary, the ion current-based proteomics and phosphoproteomics reliably identified novel alterations in protein content and phosphorylation contributing to contractile dysfunction, extracellular matrix (ECM) damage, and programmed cell death in stunned myocardium, which corroborate well with our physiological observations. Moreover, this work developed a comprehensive database of the swine heart proteome, a highly valuable resource for future translational research in porcine models with cardiovascular diseases.NEW & NOTEWORTHY We first used ion current-based proteomics and phosphoproteomics to reliably identify novel alterations in protein expression and phosphorylation contributing to contractile dysfunction, extracellular matrix (ECM) damage, and programmed cell death in stunned myocardium and developed a comprehensive swine heart-specific proteome database, which provides a valuable resource for future research in porcine models of cardiovascular diseases.

Seasonal proteome variation in intertidal shrimps under a natural setting: Connecting molecular networks with environmental fluctuations

The ability of intertidal organisms to maintain their performance via molecular and physiological adjustments under low tide, seasonal fluctuations and extreme events ultimately determines population viability. Analyzing this capacity in the wild is extremely relevant since intertidal communities are under increased climate variability owing to global changes. We addressed the seasonal proteome signatures of a key intertidal species, the shrimp Palaemon elegans, in a natural setting. Shrimps were collected during spring and summer seasons at low tides and were euthanized in situ. Environmental variability was also assessed using hand-held devices and data loggers. Muscle samples were taken for 2D gel electrophoresis and protein identification through mass spectrometry. Proteome data revealed that 55 proteins (10.6% of the proteome) significantly changed between spring and summer collected shrimps, 24 of which were identified. These proteins were mostly involved in cytoskeleton remodelling, energy metabolism and transcription regulation. Overall, shrimps modulate gene expression leading to metabolic and structural adjustments related to seasonal differences in the wild (i.e. abiotic variation and possibly intrinsic cycles of reproduction and growth). This potentially promotes performance and fitness as suggested by the higher condition index in summer-collected shrimps. However, inter-individual variation (% coefficient of variation) in protein levels was quite low (min-max ranges were 0.6-8.3% in spring and 1.2-4.8% in summer), possibly suggesting reduced genetic diversity or physiological canalization. Protein plasticity is relevant to cope with present and upcoming environmental variation related to anthropogenic forcing (e.g. global change, pollution) but low inter-individual variation may limit evolutionary potential of shrimp populations.

Proteomic and phosphoproteomic analyses reveal several events involved in the early stages of bovine herpesvirus 1 infection

Herpesviruses are predicted to express more than 80 proteins during their infection cycle. The proteins synthesized by the immediate early genes and early genes target signaling pathways in host cells that are essential for the successful initiation of a productive infection and for latency. In this study, proteomic and phosphoproteomic tools showed the occurrence of changes in Madin-Darby bovine kidney cells at the early stage of the infection by bovine herpesvirus 1 (BoHV-1). Proteins that had already been described in the early stage of infection for other herpesviruses but not for BoHV-1 were found. For example, stathmin phosphorylation at the initial stage of infection is described for the first time. In addition, two proteins that had not been described yet in the early stages of herpesvirus infections in general were ribonuclease/angiogenin inhibitor and Rab GDP dissociation inhibitor beta. The biological processes involved in these cellular responses were repair and replication of DNA, splicing, microtubule dynamics, and inflammatory responses. These results reveal pathways that might be used as targets for designing antiviral molecules against BoHV-1 infection.

Regulation of the leaf proteome by inoculation of Populus × canescens with two Paxillus involutus isolates differing in root colonization rates

During ectomycorrhizal symbioses, up to 30% of the carbon produced in leaves may be translocated to the fungal partner. Given that the leaf response to root colonization is largely unknown, we performed a leaf proteome analysis of Populus × canescens inoculated in vitro with two isolates of Paxillus involutus significantly differing in root colonization rates (65 ± 7% vs 14 ± 7%), together with plant growth and leaf biochemistry analyses to determine the response of plant leaves to ectomycorrhizal root colonization. The isolate that more efficiently colonized roots (isolate H) affected 9.1% of the leaf proteome compared with control plants. Simultaneously, ectomycorrhiza in isolate H-inoculated plants led to improved plant growth and an increased abundance of leaf proteins involved in protein turnover, stress response, carbohydrate metabolism, and photosynthesis. The protein increment was also correlated with increases in chlorophyll, foliar carbon, and carbohydrate contents. Although inoculation of P. × canescens roots with the other P. involutus isolate (isolate L, characterized by a low root colonization ratio) affected 6.8% of the leaf proteome compared with control plants, most proteins were downregulated. The proteomic signals of increased carbohydrate biosynthesis were not detected, and carbohydrate, carbon, and leaf pigment levels and plant biomass did not differ from the noninoculated plants. Our results revealed that the upregulation of the photosynthetic protein abundance and levels of leaf carbohydrate are positively related to rates of root colonization. Upregulation of photosynthetic proteins, chlorophyll, and leaf carbohydrate levels in ectomycorrhizal plants was positively related to root colonization rates and resulted in increased carbon translocation and sequestration underground.

Bottlenecks in Proteomics: An Update

Mass spectrometry (MS) is the core for advanced methods in proteomic experiments. When effectively used, proteomics may provide extensive information about proteins and their post-translational modifications, as well as their interaction partners. However, there are also many problems that one can encounter during a proteomic experiment, including, but not limited to sample preparation, sample fractionation, sample analysis, data analysis & interpretation and biological significance. Here we discuss some of the problems that researchers should be aware of when performing a proteomic experiment.