Microproteomic sample preparation

Single-tissue proteomics in Caenorhabditis elegans reveals proteins resident in intestinal lysosome-related organelles

The nematode intestine is the primary site for nutrient uptake and storage as well as the synthesis of biomolecules; lysosome-related organelles known as gut granules are important for many of these functions. Aspects of intestine biology are not well understood, including the export of the nutrients it imports and the molecules it synthesizes, as well as the complete functions and protein content of the gut granules. Here, we report a mass spectrometry (MS)-based proteomic analysis of the intestine of the Caenorhabditis elegans and of its gut granules. Overall, we identified approximately 5,000 proteins each in the intestine and the gonad and showed that most of these proteins can be detected in samples extracted from a single worm, suggesting the feasibility of individual-level genetic analysis using proteomes. Comparing proteomes and published transcriptomes of the intestine and the gonad, we identified proteins that appear to be synthesized in the intestine and then transferred to the gonad. To identify gut granule proteins, we compared the proteome of individual intestines deficient in gut granules to the wild type. The identified gut granule proteome includes proteins known to be exclusively localized to the granules and additional putative gut granule proteins. We selected two of these putative gut granule proteins for validation via immunohistochemistry, and our successful confirmation of both suggests that our strategy was effective in identifying the gut granule proteome. Our results demonstrate the practicability of single-tissue MS-based proteomic analysis in small organisms and in its future utility.

Microproteomic-Based Analysis of the Goat Milk Protein Synthesis Network and Casein Production Evaluation

Goat milk has been consumed by humans since ancient times and is highly nutritious. Its quality is mainly determined by its casein content. Milk protein synthesis is controlled by a complex network with many signal pathways. Therefore, the aim of our study is to clearly depict the signal pathways involved in milk protein synthesis in goat mammary epithelial cells (GMECs) using state-of-the-art microproteomic techniques and to identify the key genes involved in the signal pathway. The microproteomic analysis identified more than 2253 proteins, with 323 pathways annotated from the identified proteins. Knockdown of IRS1 expression significantly influenced goat casein composition (α, β, and κ); therefore, this study also examined the insulin receptor substrate 1 (IRS1) gene more closely. A total of 12 differential expression proteins (DEPs) were characterized as upregulated or downregulated in the IRS1-silenced sample compared to the negative control. The enrichment and signal pathways of these DEPs in GMECs were identified using GO annotation and KEGG, as well as KOG analysis. Our findings expand our understanding of the functional genes involved in milk protein synthesis in goats, paving the way for new approaches for modifying casein content for the dairy goat industry and milk product development.

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.

Digital Microfluidics for Microproteomic Analysis of Minute Mammalian Tissue Samples Enabled by a Photocleavable Surfactant

Proteome profiles of precious tissue samples have great clinical potential for accelerating disease biomarker discovery and promoting novel strategies for early diagnosis and treatment. However, tiny clinical tissue samples are often difficult to handle and analyze with conventional proteomic methods. Automated digital microfluidic (DMF) workflows facilitate the manipulation of size-limited tissue samples. Here, we report the assessment of a DMF microproteomics workflow enabled by a photocleavable surfactant for proteomic analysis of minute tissue samples. The surfactant 4-hexylphenylazosulfonate (Azo) was found to facilitate fast droplet movement on DMF and enhance the proteomics analysis. Comparisons of Azo and n-Dodecyl β-d-maltoside (DDM) using small samples of HeLa digest standards and MCF-7 cell digests revealed distinct differences at the peptide level despite similar results at the protein level. The DMF microproteomics workflow was applied for the sample preparation of ∼3 μg biopsies from murine brain tissue. A total of 1969 proteins were identified in three samples, including established neural biomarkers and proteins related to synaptic signaling. Going forward, we propose that the Azo-enabled DMF workflow has the potential to advance the practical clinical application of DMF for the analysis of size-limited tissue samples.

Proteomics analysis of circulating small extracellular vesicles: Focus on the contribution of EVs to tumor metabolism

The term small extracellular vesicle (sEV) is a comprehensive term that includes any type of cell-derived, membrane-delimited particle that has a diameter < 200 nm, and which includes exosomes and smaller microvesicles. sEVs transfer bioactive molecules between cells and are crucial for cellular homeostasis and particularly during tumor development, where sEVs provide important contributions to the formation of the premetastic niche and to their altered metabolism. sEVs are thus legitimate targets for intervention and have also gained increasing interest as an easily accessible source of biomarkers because they can be rapidly isolated from serum/plasma and their molecular cargo provides information on their cell-of origin. To target sEVs that are specific for a given cell/disease it is essential to identify EV surface proteins that are characteristic of that cell/disease. Mass-spectrometry based proteomics is widely used for the identification and quantification of sEV proteins. The methods used for isolating the sEVs, preparing the sEV sample for proteomics analysis, and mass spectrometry analysis, can have a strong influence on the results and requires careful consideration. This review provides an overview of the approaches used for sEV proteomics and discusses the inherent compromises regarding EV purity versus depth of coverage. Additionally, it discusses the practical applications of the methods to unravel the involvement of sEVs in regulating the metabolism of pancreatic ductal adenocarcinoma (PDAC). The metabolic reprogramming in PDAC includes enhanced glycolysis, elevated glutamine metabolism, alterations in lipid metabolism, mitochondrial dysfunction and hypoxia, all of which are crucial in promoting tumor cell growth. A thorough understanding of these metabolic adaptations is imperative for the development of targeted therapies to exploit PDAC's vulnerabilities.

Data-Dependent Acquisition with Precursor Coisolation Improves Proteome Coverage and Measurement Throughput for Label-Free Single-Cell Proteomics

We combined efficient sample preparation and ultra-low-flow liquid chromatography with a newly developed data acquisition and analysis scheme termed wide window acquisition (WWA) to quantify >3,000 proteins from single cells in rapid label-free analyses. WWA employs large isolation windows to intentionally co-isolate and co-fragment adjacent precursors along with the selected precursor. Optimized WWA increased the number of MS2-identified proteins by ≈40 % relative to standard data-dependent acquisition. For a 40-min LC gradient operated at ≈15 nL/min, we identified an average of 3,524 proteins per single-cell-sized aliquot of protein digest. Reducing the active gradient to 20 min resulted in a modest 10 % decrease in proteome coverage. Using this platform, we compared protein expression between single HeLa cells having an essential autophagy gene, atg9a, knocked out, with their isogenic WT parental line. Similar proteome coverage was observed, and 268 proteins were significantly up- or downregulated. Protein upregulation primarily related to innate immunity, vesicle trafficking and protein degradation.

Bottom-Up Proteomics: Advancements in Sample Preparation

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. LC–MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, it is prone to errors and has low reproducibility and throughput. In-solution digestion and filter-aided sample preparation are the typical and widely used methods. In the past decade, novel methods to improve and facilitate the entire sample preparation process or integrate sample preparation and fractionation have been reported to reduce time, increase throughput, and improve reproducibility. In this review, we have outlined the current methods used for sample preparation in proteomics, including on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping. Additionally, we have summarized and discussed current devices and methods for integrating different steps of sample preparation and peptide fractionation.

Mass Spectrometry-Based Proteomics Workflows in Cancer Research: The Relevance of Choosing the Right Steps

The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography-mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS acquisition methods, statistical treatment, and bioinformatics to understand the biological meaning of the findings and set predictive classifiers. As the choice of best options might not be straightforward, we herein review and assess past and current proteomics approaches for the discovery of new cancer biomarkers. Moreover, we review major bioinformatics tools for interpreting and visualizing proteomics results and suggest the most popular machine learning techniques for the selection of predictive biomarkers. Finally, we consider the approximation of proteomics strategies for clinical diagnosis and prognosis by discussing current barriers and proposals to circumvent them.

Proteomic Landscape of Human Spermatozoa: Optimized Extraction Method and Application

Human spermatozoa proteomics exposed to some physical, biological or chemical stressors is being explored. However, there is a lack of optimized sample preparation methods to achieve in-depth protein coverage for sperm cells. Meanwhile, it is not clear whether antibiotics can regulate proteins to affect sperm quality. Here, we systematically compared a total of six different protein extraction methods based the combination of three commonly used lysis buffers and physical lysis strategies. The urea buffer combined with ultrasonication (UA-ultrasonication) produced the highest protein extraction rate, leading to the deepest coverage of human sperm proteome (5685 protein groups) from healthy human sperm samples. Since the antibiotics, amoxicillin and clarithromycin, have been widely used against H. pylori infection, we conduct a longitudinal study of sperm proteome via data-independent acquisition tandem mass spectrometry (DIA-MS/MS) on an infected patient during on and off therapy with these two drugs. The semen examination and morphological analysis were performed combined with proteomics analysis. Our results indicated that antibiotics may cause an increase in the sperm concentration and the rate of malformed sperm and disrupt proteome expression in sperm. This work provides an optimized extraction method to characterize the in-depth human sperm proteome and to extend its clinical applications.

Mass Spectrometric-Based Proteomics for Biomarker Discovery in Osteosarcoma: Current Status and Future Direction

Due to a lack of novel therapies and biomarkers, the clinical outcomes of osteosarcoma patients have not significantly improved for decades. The advancement of mass spectrometry (MS), peptide quantification, and downstream pathway analysis enables the investigation of protein profiles across a wide range of input materials, from cell culture to long-term archived clinical specimens. This can provide insight into osteosarcoma biology and identify candidate biomarkers for diagnosis, prognosis, and stratification of chemotherapy response. In this review, we provide an overview of proteomics studies of osteosarcoma, indicate potential biomarkers that might be promising therapeutic targets, and discuss the challenges and opportunities of mass spectrometric-based proteomics in future osteosarcoma research.

Infrared Laser Ablation Microsampling for Small Volume Proteomics

Infrared (IR) laser ablation was used to remove localized tissue regions from which proteins were extracted and processed with a low volume sample preparation workflow for bottom-up proteomics by liquid chromatography tandem mass spectrometry (LC-MS/MS). A polytetrafluoroethylene (PTFE) coated glass slide with 2 mm diameter microwells was used to capture ablated rat brain tissue for in situ protein digestion with submicroliter solution volumes. The resulting peptides were analyzed with LC-MS/MS for protein identification and label-free quantification. The method was used to identify an average of 600, 1350, and 1900 proteins from ablation areas of 0.01, 0.04, and 0.1 mm², respectively, from a 50 μm thick rat brain tissue section. Differential proteomics of 0.01 mm² regions captured from cerebral cortex and corpus callosum was accomplished to demonstrate the capabilities of the approach.

Human peripheral blood mononuclear cells: A review of recent proteomic applications

Human peripheral blood mononuclear cells (PBMCs) represent a sentinel blood sample which reacts to different pathophysiological stimuli in the form of immunological responses/immunophenotypic changes. The study of molecular content of PBMCs can provide better understanding of immune processes giving the possibility of monitoring the health conditions of the host organism. Proteomic analysis of PBMCs can achieve mentioned goal as important immune-related biomarkers are easily accessible for analysis. PBMCs have been gaining attention in different research areas including preclinical or clinical investigations. In this review, recent applications of proteomic analysis of PBMCs are described and discussed. Approaches are divided based on different proteomic workflows such as in-gel, in-solution and on-filter modes. The effect of various diseases such as autoimmune, cancer, neurodegenerative, viral, metabolic, and various immune stimulations such as radiation, vaccine, corticosteroids over PBMCs proteome, are described with emphasis on promising protein biomarker candidates. This article is protected by copyright. All rights reserved.

Approaching Sites of Action of Temozolomide for Pharmacological and Clinical Studies in Glioblastoma

Temozolomide (TMZ), together with bulk resection and focal radiotherapy, is currently a standard of care for glioblastoma. Absorption, distribution, metabolism, and excretion (ADME) parameters, together with the mode of action of TMZ, make its biochemical and biological action difficult to understand. Accurate understanding of the mode of action of TMZ and the monitoring of TMZ at its anatomical, cellular, and molecular sites of action (SOAs) would greatly benefit precision medicine and the development of novel therapeutic approaches in combination with TMZ. In the present perspective article, we summarize the known ADME parameters and modes of action of TMZ, and we review the possible methodological options to monitor TMZ at its SOAs. We focus our descriptions of methodologies on mass spectrometry-based approaches, and all related considerations are taken into account regarding the avoidance of artifacts in mass spectrometric analysis during sampling, sample preparation, and the evaluation of results. Finally, we provide an overview of potential applications for precision medicine and drug development.

An Enzymatic Multiplexed Impedimetric Sensor Based on α-MnO2/GQD Nano-Composite for the Detection of Diabetes and Diabetic Foot Ulcer Using Micro-Fluidic Platform

Diabetes is widely considered as a silent killer which affects the internal organs and ultimately has drastic impacts on our day-to-day activities. One of the fatal outcomes of diabetes is diabetic foot ulcer (DFU); which, when becomes chronic, may lead to amputation. The incorporation of nanotechnology in developing bio-sensors enables the detection of desired biomarkers, which in our study are glucose and L-tyrosine; which gets elevated in patients suffering from diabetes and DFUs, respectively. Herein, we report the development of an enzymatic impedimetric sensor for the multi-detection of these biomarkers using an electrochemical paper-based analytical device (µ-EPADs). The structure consists of two working electrodes and a counter electrode. One working electrode is modified with α-MnO2-GQD/tyrosinase hybrid to aid L-tyrosine detection, while the other electrode is coated with α-MnO2-GQD/glucose oxidase hybrid for glucose monitoring. Electrochemical impedance spectroscopy has been employed for the quantification of glucose and L-tyrosine, within a concentration range of 50–800 mg/dL and 1–500 µmol/L, respectively, using a sample volume of approximately 200 µL. The impedance response exhibited a linear relationship over the analyte concentration range with detection limits of ~58 mg/dL and ~0.3 µmol/L for glucose and tyrosine respectively, with shelf life ~1 month. The sensing strategy was also translated to Arduino-based device applications by interfacing the µ-EPADs with miniaturized electronics.

High-Throughput Sequencing of Circulating MicroRNAs in Plasma and Serum during Pregnancy Progression

Although circulating microRNAs (miRNAs) in maternal blood may play an important role in regulation of pregnancy progression and serve as non-invasive biomarkers for different gestation complications, little is known about their profile in blood during normally developing pregnancy. In this study we evaluated the miRNA profiles in paired plasma and serum samples from pregnant women without health or gestational abnormalities at three time points using high-throughput sequencing technology. Sequencing revealed that the percentage of miRNA reads in plasma and serum decreased by a third compared to first and second trimesters. We found two miRNAs in plasma (hsa-miR-7853-5p and hsa-miR-200c-3p) and 10 miRNAs in serum (hsa-miR-203a-5p, hsa-miR-495-3p, hsa-miR-4435, hsa-miR-340-5p, hsa-miR-4417, hsa-miR-1266-5p, hsa-miR-4494, hsa-miR-134-3p, hsa-miR-5008-5p, and hsa-miR-6756-5p), that exhibit level changes during pregnancy (p-value adjusted < 0.05). In addition, we observed differences for 36 miRNAs between plasma and serum (p-value adjusted < 0.05), which should be taken into consideration when comparing the results between studies performed using different biosample types. The results were verified by analysis of three miRNAs using qRT-PCR (p < 0.05). The present study confirms that the circulating miRNA profile in blood changes during gestation. Our results set the basis for further investigation of molecular mechanisms, involved in regulation of pregnancy, and the search for biomarkers of gestation abnormalities.

Targeted liquid chromatography-tandem mass spectrometry analysis of proteins: Basic principles, applications, and perspectives

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is now the main analytical method for the identification and quantification of peptides and proteins in biological samples. In modern research, identification of biomarkers and their quantitative comparison between samples are becoming increasingly important for discovery, validation, and monitoring. Such data can be obtained following specific signals after fragmentation of peptides using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) methods, with high specificity, accuracy, and reproducibility. In addition, these methods allow measurement of the amount of post-translationally modified forms and isoforms of proteins. This review article describes the basic principles of MRM assays, guidelines for sample preparation, recent advanced MRM-based strategies, applications and illustrative perspectives of MRM/PRM methods in clinical research and molecular biology.

Automation of single-cell proteomic sample preparation

Molecular heterogeneity exists at different spatial scales in biological samples and is an important parameter in the development of pathologies and resistances to therapies. When aiming to reach molecular heterogeneity of cells at extremely low spatial scales, single-cell analysis can be the ultimate choice. Proteomics performed in bulk population of cells (macroproteomics) is prone to mask molecular heterogeneity. Mass spectrometry-based single cell proteomics (SCP-MS) is the right solution to overcome this issue. Three main problems can be identified using SCP-MS: (i) analytical loss during sample preparation, (ii) inefficient microinjection/delivery of proteins/peptides from samples to MS and (iii) low analytical throughput. Technologies for automation of SCP have recently gained attention to improve methods accuracy, sensitivity, throughput and in-depth and low-biased proteome analysis. In this minireview, we therefore overview the state-of-the-art of automation of SCP-MS sample preparation approaches.

Why Has Metabolomics So Far Not Managed to Efficiently Contribute to the Improvement of Assisted Reproduction Outcomes? The Answer through a Review of the Best Available Current Evidence

Metabolomics emerged to give clinicians the necessary information on the competence, in terms of physiology and function, of gametes, embryos, and the endometrium towards a targeted infertility treatment, namely, assisted reproduction techniques (ART). Our minireview aims to investigate the current status of the use of metabolomics in assisted reproduction, the potential flaws in its use, and to propose specific solutions towards the improvement of ART outcomes through the use of the intervention. We used published reports assessing the role of metabolomic investigation of the endometrium, oocytes, and embryos in improving clinical outcomes in women undergoing ART. We initially found that there is no evidence to support that fertility outcomes can be improved through metabolomics profiling. In contrast, it may be helpful for understanding and appraising the nutritional environment of oocytes and embryos. The causes include the different infertility populations, the difference between animals and humans, technical limitations, and the great heterogeneity in the variables employed. Suggested steps include the standardization of variables of the method itself, the universal creation of a panel where all biomarkers are stored concerning specific infertile populations with different phenotypes or etiologies, specific bioinformatics contribution, significant computing power for data processing, and importantly, properly conducted trials.

Exosomes: Potential Disease Biomarkers and New Therapeutic Targets

Exosomes are extracellular vesicles released by cells, both constitutively and after cell activation, and are present in different types of biological fluid. Exosomes are involved in the pathogenesis of diseases, such as cancer, neurodegenerative diseases, pregnancy disorders and cardiovascular diseases, and have emerged as potential non-invasive biomarkers for the detection, prognosis and therapeutics of a myriad of diseases. In this review, we describe recent advances related to the regulatory mechanisms of exosome biogenesis, release and molecular composition, as well as their role in health and disease, and their potential use as disease biomarkers and therapeutic targets. In addition, the advantages and disadvantages of their main isolation methods, characterization and cargo analysis, as well as the experimental methods used for exosome-mediated drug delivery, are discussed. Finally, we present potential perspectives for the use of exosomes in future clinical practice.

hnRNP A/B Proteins: An Encyclopedic Assessment of Their Roles in Homeostasis and Disease

The hnRNP A/B family of proteins is canonically central to cellular RNA metabolism, but due to their highly conserved nature, the functional differences between hnRNP A1, A2/B1, A0, and A3 are often overlooked. In this review, we explore and identify the shared and disparate homeostatic and disease-related functions of the hnRNP A/B family proteins, highlighting areas where the proteins have not been clearly differentiated. Herein, we provide a comprehensive assembly of the literature on these proteins. We find that there are critical gaps in our grasp of A/B proteins' alternative splice isoforms, structures, regulation, and tissue and cell-type-specific functions, and propose that future mechanistic research integrating multiple A/B proteins will significantly improve our understanding of how this essential protein family contributes to cell homeostasis and disease.

CD3+, CD8+, CD4+ and FOXP3+ T Cells in the Immune Microenvironment of Small Bowel Neuroendocrine Tumors

The role of inflammation in neuroendocrine tumors is poorly known. The purpose of this study was to characterize the densities of CD3⁺, CD8⁺, CD4⁺ and FOXP3⁺ T cells in small bowel neuroendocrine tumors (SB-NETs), SB-NET lymph node metastases and gastric neuroendocrine tumors (G-NETs) to assess the prognostic role of immune cell infiltrates in SB-NETs. The final cohort included 113 SB-NETs, 75 SB-NET lymph node metastases and 19 G-NETs from two Finnish hospitals. CD3⁺- and CD8⁺-based immune cell score (ICS), and other T cell densities were evaluated. Survival analyses of SB-NETs and SB-NET lymph node metastases were performed with the Kaplan-Meier method and Cox regression adjusted for confounders. The primary outcome was disease-specific survival (DSS). No significant difference in DSS was seen between low and high ICS groups in SB-NETs at 5 years (92.6% vs. 87.8%) or 10 years (53.8% vs. 79.4%), p = 0.507, or in SB-NET lymph node metastases at 5 years (88.9% vs. 90.4%) or 10 years (71.1% vs. 59.8%), p = 0.466. Individual densities of the examined T cell types showed no correlation with prognosis either. SB-NETs and lymph node metastases had similar inflammatory cell profiles, whereas in G-NETs CD3⁺ and CD8⁺ T cells were particularly more abundant. In SB-NETs, ICS or T cell densities showed no correlation with prognosis.

Proteomic Exploration of Plasma Exosomes and Other Small Extracellular Vesicles in Pediatric Hodgkin Lymphoma: A Potential Source of Biomarkers for Relapse Occurrence

Exosomes and other small extracellular vesicles (EVs) are potential sources of cancer biomarkers. Plasma-derived EVs have not yet been studied in pediatric Hodgkin lymphoma (HL), for which predictive biomarkers of relapse are greatly needed. In this two-part proteomic study, we used two-dimensional difference gel electrophoresis (2D-DIGE) followed by liquid chromatography–tandem mass spectrometry (LC–MS/MS) to analyze EV proteins of plasma collected at diagnosis from children with nodular sclerosis HL, relapsed or not. EVs isolated using membrane affinity had radii ranging from 20 to 130 nm and contained the programmed cell death 6-interacting (ALIX) and the tumor susceptibility gene 101 (TSG101) proteins, whereas calnexin (CANX) was not detected. 2D-DIGE identified 16 spots as differentially abundant between non-relapsed and relapsed HL (|fold change| ≥ 1.5, p < 0.05). LC–MS/MS identified these spots as 11 unique proteins, including five more abundant in non-relapsed HL (e.g., complement C4b, C4B; fibrinogen γ chain, FGG) and six more abundant in relapsed HL (e.g., transthyretin, TTR). Shotgun LC–MS/MS on pooled EV proteins from non-relapsed HL identified 161 proteins, including 127 already identified in human exosomes (ExoCarta data). This EV cargo included 89 proteins not yet identified in exosomes from healthy plasma. Functional interrogation by the Database for Annotation, Visualization and Integrated Discovery (DAVID) revealed that the EV proteins participate in platelet degranulation and serine-type endopeptidase activity as the most significant Gene Ontology (GO) biological process and molecular function (p < 0.01).

State-of-the-Art Methods and Emerging Fluid Biomarkers in the Diagnostics of Dementia-A Short Review and Diagnostic Algorithm

The most common neurodegenerative dementias include Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). The correct etiology-based diagnosis is pivotal for clinical management of these diseases as well as for the suitable timing and choosing the accurate disease-modifying therapies when these become available. Enzyme-linked immunosorbent assay (ELISA)-based methods, detecting altered levels of cerebrospinal fluid (CSF) Tau, phosphorylated Tau, and Aβ-42 in AD, allowed the wide use of this set of biomarkers in clinical practice. These analyses demonstrate a high diagnostic accuracy in AD but suffer from a relatively restricted usefulness due to invasiveness and lack of prognostic value. In recent years, the development of novel advanced techniques has offered new state-of-the-art opportunities in biomarker discovery. These include single molecule array technology (SIMOA), a tool for non-invasive analysis of ultra-low levels of central nervous system-derived molecules from biofluids, such as CSF or blood, and real-time quaking (RT-QuIC), developed to analyze misfolded proteins. In the present review, we describe the history of methods used in the fluid biomarker analyses of dementia, discuss specific emerging biomarkers with translational potential for clinical use, and suggest an algorithm for the use of new non-invasive blood biomarkers in clinical practice.

Urinary Proteomics Reveals Promising Biomarkers in Menstrually Related and Post-Menopause Migraine

Migraine is an invalidating neuro-vascular disorder largely spread in the world population. Currently, its pathophysiology is not yet completely understood. The purpose of this study was to investigate the urinary proteome of women suffering from menstrually related migraine (MM) and post-menopause migraine (PM) in comparison with non-headache women as controls, to search potential biomarkers of these migraine sub-types. Urine samples were analyzed by mono-dimensional gel electrophoresis (SDS-PAGE) and two-dimensional gel electrophoresis (2DE) coupled to liquid chromatography-mass spectrometry (LC-MS/MS). Twenty-one urinary proteins were found significantly dysregulated in MM and PM (p < 0.05). The STRING Analysis database revealed interaction between 15 proteins, which were mainly involved in the immune and inflammatory response. Seven of the most considerable proteins were further quantified by western blot: protein S100A8 (S10A8), up-regulated in MM, uromodulin (UROM), alpha-1-microglobulin (AMBP), gelsolin (GELS), prostaglandin-H2 D-isomerase (PTGDS), over-expressed in PM, apolipoprotein A-I (APOA1), and transthyretin (TTHY), respectively down- and up-regulated in both migraineur groups vs controls. These candidate biomarkers might be involved in the neurophysiological network of MM and PM, thus helping to better understand the pathophysiology of these migraine forms. If validated in large-scale studies, this protein cluster could become a distinctive target for clinical applications in migraine diagnosis and treatment.