Serum and plasma proteomics

Deep Learning Powers Protein Identification from Precursor MS Information

Proteome analysis currently heavily relies on tandem mass spectrometry (MS/MS), which does not fully utilize MS1 features, as many precursors remain unselected for MS/MS fragmentation, especially in the cases of low abundance samples and wide abundance dynamic range samples. Therefore, leveraging MS1 features as a complement to MS/MS has become an attractive option to improve the coverage of feature identification. Herein, we propose MonoMS1, an approach combining deep learning-based retention time, ion mobility, detectability prediction, and logistic regression-based scoring for MS1 feature identification. The approach achieved a significant increase in MS1 feature identification based on an E. coli data set. Application of MonoMS1 to data sets with wide dynamic range, such as human serum proteome samples, and with low sample abundance, such as single-cell proteome samples, enabled substantial complementation of MS/MS-based peptide and protein identification. This method opens a new avenue for proteomic analysis and can boost proteomic research on complex samples.

Interaction of Serum and Plasma Proteins with Polyelectrolyte Microparticles with Core/Shell and Shell-Only Structures

Polyelectrolyte microparticles (MPs) synthesized on calcium carbonate cores are considered a promising basis for new drug delivery systems. It is known that microparticles entering a physiological environment absorb proteins on their surface, which can change the properties of the microparticles and alter their functional activity. This study aimed to compare the compositions of the adsorbed protein layer formed on microparticles with the core/shell and shell structures obtained by layer-by-layer deposition. The difference in the microparticle structure was associated with changes in their surface topography and ζ-potential. These microparticles were incubated with human serum or plasma at 37°C for 24 h. The adsorbed proteins were eluted and analyzed by means of SDS-PAGE. The protein composition of the eluates was determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS); a total of 357 proteins were identified, and 183 of them were detected in all samples. Our results demonstrate that the relative abundance of proteins of different functional groups (immunoglobulins, complement proteins, and apolipoproteins) varied depending on the structure and surface characteristics of the polyelectrolyte microparticles and the incubation medium. Our findings expand the understanding of the influence of the physicochemical properties of the microparticles on their interaction with proteins, which can help to improve the design of microparticles for drug delivery.

Extracellular vesicles: an emerging tool for wild immunology

The immune system is crucial for defending organisms against pathogens and maintaining health. Traditionally, research in immunology has relied on laboratory animals to understand how the immune system works. However, there is increasing recognition that wild animals, due to their greater genetic diversity, lifespan, and environmental exposures, have much to contribute to basic and translational immunology. Unfortunately, logistical challenges associated with collecting and storing samples from wildlife, and the lack of commercially available species-specific reagents have hindered the advancement of immunological research on wild species. Extracellular vesicles (EVs) are cell-derived nanoparticles present in all body fluids and tissues of organisms spanning from bacteria to mammals. Human and lab animal studies indicate that EVs are involved in a range of immunological processes, and recent work shows that EVs may play similar roles in diverse wildlife species. Thus, EVs can expand the toolbox available for wild immunology research, helping to overcome some of the challenges associated with this work. In this paper, we explore the potential application of EVs to wild immunology. First, we review current understanding of EV biology across diverse organisms. Next, we discuss key insights into the immune system gained from research on EVs in human and laboratory animal models and highlight emerging evidence from wild species. Finally, we identify research themes in wild immunology that can immediately benefit from the study of EVs and describe practical considerations for using EVs in wildlife research.

Electrophoresis-Based Approach for Characterizing Dendrimer-Protein Interactions: A Proof-of-Concept Study

Improving the clinical translation of nanomedicine requires better knowledge about how nanoparticles interact with biological environments. As researchers are recognizing the importance of understanding the protein corona and characterizing how nanocarriers respond in biological systems, new tools and techniques are needed to analyze nanocarrier-protein interactions, especially for smaller size (<10 nm) nanoparticles like polyamidoamine (PAMAM) dendrimers. Here, we developed a streamlined, semiquantitative approach to assess dendrimer-protein interactions using a nondenaturing electrophoresis technique combined with mass spectrometry. With this protocol, we detect fluorescently tagged dendrimers and proteins simultaneously, enabling us to analyze when dendrimers migrate with proteins. We found that PAMAM dendrimers mostly interact with complement proteins, particularly C3 and C4a, which aligns with previously published data, verifying that our approach can be used to isolate and identify dendrimer-protein interactions.

Proteomics in Cardiovascular disease

This study focuses on recent advances in proteomics and provides an up-to-date use of this technology in identifying cardiovascular disease (CVD) biomarkers. A total of eight electronic databases (PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang, Vip, Sinomed, and CNKI) were searched and five were used for integrative analysis of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic ratio (DOR) and 1 secondary indicator area under the curve (AUC). This systematic review and integrative analysis summarized potential biomarkers previously identified by proteomics. The integrative analysis suggested that proteomics technology had high clinical value in CVD diagnosis. The findings provided new possible directions for the prevention or diagnosis of CVD.

Cell- and Serum-Derived Proteins Act as DAMPs to Activate RAW 264.7 Macrophage-like Cells on Silicone Implants

Protein adsorption after biomaterial implantation is the first stage of the foreign body response (FBR). However, the source(s) of the adsorbed proteins that lead to damaged associated molecular patterns (DAMPs) and induce inflammation have not been fully elucidated. This study examined the effects of different protein sources, cell-derived (from a NIH/3T3 fibroblast cell lysate) and serum-derived (from fetal bovine serum), which were compared to implant-derived proteins (after a 30 min subcutaneous implantation in mice) on activation of RAW 264.7 cells cultured in minimal (serum-free) medium. Both cell-derived and serum-derived protein sources when preadsorbed to either tissue culture polystyrene or medical-grade silicone induced RAW 264.7 cell activation. The combination led to an even higher expression of pro-inflammatory cytokine genes and proteins. Implant-derived proteins on silicone explants induced a rapid inflammatory response that then subsided more quickly and to a greater extent than the studies with in vitro cell-derived or serum-derived protein sources. Proteomic analysis of the implant-derived proteins identified proteins that included cell-derived and serum-derived, but also other proteinaceous sources (e.g., extracellular matrix), suggesting that the latter or nonproteinaceous sources may help to temper the inflammatory response in vivo. These findings indicate that both serum-derived and cell-derived proteins adsorbed to implants can act as DAMPs to drive inflammation in the FBR, but other protein sources may play an important role in controlling inflammation.

A Novel Peptidome Technology for the Diagnosis of Mild Cognitive Impairment and Alzheimer's Disease by Selected Reaction Monitoring

Background

With the aging of populations worldwide, Alzheimer's disease (AD) has become a concern due to its high prevalence and the continued lack of established treatments. Early diagnosis is required as a preventive intervention to modify the disease's progression. In our previous study, we performed peptidomic analysis of serum samples obtained from AD patients and age-matched healthy subjects to seek peptide biomarker candidates for AD by using BLOTCHIP-MS analysis, and identified four peptides as AD biomarker candidates.

Objective

The objective was to validate the serum biomarker peptides to distinguish mild cognitive impairment (MCI) and AD in comparison to cognitively healthy controls using a new peptidome technology, the Dementia Risk Test.

Methods

We enrolled 195 subjects with normal cognitive function (NC; n = 70), MCI (n = 55), and AD (n = 70), The concentrations of cognitive impairment marker peptides (Fibrinogen α chain (FAC), Fibrinogen β chain (FBC), Plasma protease C1 inhibitor (PPC1I), α2-HS-glycoprotein (AHSG)) were quantified by using a selected reaction monitoring assay based on liquid chromatography-MS/MS.

Results

The present study confirmed that three peptides, FAC, FBC, and PPC1I, were significantly upregulated during the onset of AD. This three-peptide set was both highly sensitive in determining AD (sensitivity: 85.7%, specificity: 95.7%, AUC: 0.900) and useful in distinguishing MCI (sensitivity: 61.8%, specificity: 98.6%, AUC: 0.824) from NC.

Conclusions

In this validation study, we confirmed the high diagnostic potential of the three peptides identified in our previous study as candidate serum biomarkers for AD. The Dementia Risk Test may be a powerful tool for detecting AD-related pathological changes.

Early stage of erythrocyte sedimentation rate test: Fracture of a high-volume-fraction gel

Erythrocyte sedimentation rate (ESR) is a clinical parameter used as a nonspecific marker for inflammation, and recent studies have shown that it is linked to the collapse of the gel formed by red blood cells (RBCs) at physiological hematocrits (i.e. RBC volume fraction). Previous research has suggested that the observation of a slower initial dynamics is related to the formation of fractures in the gel. Moreover, RBC gels present specific properties due to the anisotropic shape and flexibility of the RBCs. Namely, the onset of the collapse is reached earlier and the settling velocity of the gel increases with increasing attraction between the RBCs, while the gel of spherical particles shows the opposite trend. Here, we report experimental observations of the gel structure during the onset of the collapse. We suggest an equation modeling this initial process as fracturing of the gel. We demonstrate that this equation provides a model for the motion of the interface between blood plasma and the RBC gel, along the whole time span. We also observe that the increase in the attraction between the RBCs modifies the density of fractures in the gel, which explains why the gel displays an earlier onset when the aggregation energy between the RBCs increases. Our work uncovers the detailed physical mechanism underlying the ESR and provides insights into the fracture dynamics of an RBC gel. These results can improve the accuracy of clinical measurements.

Using trials of caloric restriction and bariatric surgery to explore the effects of body mass index on the circulating proteome

Thousands of proteins circulate in the bloodstream; identifying those which associate with weight and intervention-induced weight loss may help explain mechanisms of diseases associated with adiposity. We aimed to identify consistent protein signatures of weight loss across independent studies capturing changes in body mass index (BMI). We analysed proteomic data from studies implementing caloric restriction (Diabetes Remission Clinical trial) and bariatric surgery (By-Band-Sleeve), using SomaLogic and Olink Explore1536 technologies, respectively. Linear mixed models were used to estimate the effect of the interventions on circulating proteins. Twenty-three proteins were altered in a consistent direction after both bariatric surgery and caloric restriction, suggesting that these proteins are modulated by weight change, independent of intervention type. We also integrated Mendelian randomisation (MR) estimates of the effect of BMI on proteins measured by SomaLogic from a UK blood donor cohort as a third line of causal evidence. These MR estimates provided further corroborative evidence for a role of BMI in regulating the levels of six proteins including alcohol dehydrogenase-4, nogo receptor and interleukin-1 receptor antagonist protein. These results indicate the importance of triangulation in interrogating causal relationships; further study into the role of proteins modulated by weight in disease is now warranted.

Circulating Proteins as Diagnostic Markers in Gastric Cancer

Gastric cancer (GC) is a highly malignant disease affecting humans worldwide and has a poor prognosis. Most GC cases are detected at advanced stages due to the cancer lacking early detectable symptoms. Therefore, there is great interest in improving early diagnosis by implementing targeted prevention strategies. Markers are necessary for early detection and to guide clinicians to the best personalized treatment. The current semi-invasive endoscopic methods to detect GC are invasive, costly, and time-consuming. Recent advances in proteomics technologies have enabled the screening of many samples and the detection of novel biomarkers and disease-related signature signaling networks. These biomarkers include circulating proteins from different fluids (e.g., plasma, serum, urine, and saliva) and extracellular vesicles. We review relevant published studies on circulating protein biomarkers in GC and detail their application as potential biomarkers for GC diagnosis. Identifying highly sensitive and highly specific diagnostic markers for GC may improve patient survival rates and contribute to advancing precision/personalized medicine.

Proteomics for the Discovery of Clinical Delirium Biomarkers: A Systematic Review of Major Studies

Delirium represents a significant health care burden, diagnosed in more than 2 million elderly Americans each year. In the surgical population, delirium remains the most common complication among elderly patients, and is associated with longer hospital stays, higher costs of care, increased mortality, and functional impairment. The pathomechanism of disease is poorly understood, with current diagnostic approaches somewhat subjective and arbitrary, and definitive diagnostic biomarkers are currently lacking. Despite the recent interest in delirium research, biomarker discovery for it remains new. Most attempts to discover biomarkers are targeted studies that seek to assess the involvement of one or more members of a focused panel of candidates in delirium. For a more unbiased, system-biology view, we searched literature from Medical Literature Analysis and Retrieval System Online (MEDLINE), Cochrane Central, Web of Science, SCOPUS, and Dimensions between 2016 and 2021 for untargeted proteomic discovery studies for biomarkers of delirium conducted on human geriatric subjects. Two reviewers conducted an independent review of all search results and resolved discordance by consensus. From an overall search of 1172 publications, 8 peer-reviewed studies met our defined inclusion criteria. The 370 unique perioperative biomarkers identified in these reports are enriched in pathways involving activation of the immune system, inflammatory response, and the coagulation cascade. The most frequently identified biomarker was interleukin-6 (IL-6). By reviewing the distribution of protein biomarker candidates from these studies, we conclude that a panel of proteins, rather than a single biomarker, would allow for discriminating delirium cases from noncases. The paucity of hypothesis-generating studies in the peer-reviewed literature also suggests that a system-biology view of delirium pathomechanisms has yet to fully emerge.

Clinical applications of plasma proteomics and peptidomics: Towards precision medicine

In the context of precision medicine, disease treatment requires individualized strategies based on the underlying molecular characteristics to overcome therapeutic challenges posed by heterogeneity. For this purpose, it is essential to develop new biomarkers to diagnose, stratify, or possibly prevent diseases. Plasma is an available source of biomarkers that greatly reflects the physiological and pathological conditions of the body. An increasing number of studies are focusing on proteins and peptides, including many involving the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), and proteomics and peptidomics techniques are emerging as critical tools for developing novel precision medicine preventative measures. Excitingly, the emerging plasma proteomics and peptidomics toolbox exhibits a huge potential for studying pathogenesis of diseases (e.g., COVID-19 and cancer), identifying valuable biomarkers and improving clinical management. However, the enormous complexity and wide dynamic range of plasma proteins makes plasma proteome profiling challenging. Herein, we summarize the recent advances in plasma proteomics and peptidomics with a focus on their emerging roles in COVID-19 and cancer research, aiming to emphasize the significance of plasma proteomics and peptidomics in clinical applications and precision medicine.

HPLC–(Q)-TOF-MS-Based Study of Plasma Metabolic Profile Differences Associated with Age in Pediatric Population Using an Animal Model

A deep knowledge about the biological development of children is essential for appropriate drug administration and dosage in pediatrics. In this sense, the best approximation to study organ maturation is the analysis of tissue samples, but it requires invasive methods. For this reason, surrogate matrices should be explored. Among them, plasma emerges as a potential alternative since it represents a snapshot of global organ metabolism. In this work, plasma metabolic profiles from piglets of different ages (newborns, infants, and children) obtained by HPLC–(Q)-TOF-MS at positive and negative ionization modes were studied. Improved clustering within groups was achieved using multiblock principal component analysis compared to classical principal component analysis. Furthermore, the separation observed among groups was better resolved by using partial least squares-discriminant analysis, which was validated by bootstrapping and permutation testing. Thanks to univariate analysis, 13 metabolites in positive and 21 in negative ionization modes were found to be significant to discriminate the three groups of piglets. From these features, an acylcarnitine and eight glycerophospholipids were annotated and identified as metabolites of interest. The findings indicate that there is a relevant change with age in lipid metabolism in which lysophosphatidylcholines and lysophoshatidylethanolamines play an important role.

Circulating proteins as predictive and prognostic biomarkers in breast cancer

Breast cancer (BC) is the most common cancer and among the leading causes of cancer death in women. It is a heterogeneous group of tumours with numerous morphological and molecular subtypes, making predictions of disease evolution and patient outcomes difficult. Therefore, biomarkers are needed to help clinicians choose the best treatment for each patient. For the last years, studies have increasingly focused on biomarkers obtainable by liquid biopsy. Circulating proteins (from serum or plasma) can be used for inexpensive and minimally invasive determination of disease risk, early diagnosis, treatment adjusting, prognostication and disease progression monitoring. We provide here a review of the main published studies on serum proteins in breast cancer and elaborate on the potential of circulating proteins to be predictive and/or prognostic biomarkers in breast cancer.

A non-invasive method for concurrent detection of early-stage women-specific cancers

We integrated untargeted serum metabolomics using high-resolution mass spectrometry with data analysis using machine learning algorithms to accurately detect early stages of the women specific cancers of breast, endometrium, cervix, and ovary across diverse age-groups and ethnicities. A two-step approach was employed wherein cancer-positive samples were first identified as a group. A second multi-class algorithm then helped to distinguish between the individual cancers of the group. The approach yielded high detection sensitivity and specificity, highlighting its utility for the development of multi-cancer detection tests especially for early-stage cancers.

Loggerhead sea turtle Caretta caretta plasma biochemistry and proteome profile modulation during recovery

The aim of the study was to monitor and analyse injured and diseased loggerhead sea turtles (Caretta caretta) plasma proteome profiles and biochemistry parameters during their recovery period in rescue centre within different age and recovery period groups, and determine the potential biomarkers that can be used in diagnostics. The plasma biochemical parameters of total protein and glucose content, accompanied by aspartate aminotransferase (AST) and N-acetyl-cystein-activated creatinine kinase (CK-NAC) are highlighted as valuable and potential biomarkers of turtle's health status and condition. Using high throughput tandem mass tag (TMT)-based proteomic approach we identified 913 plasma proteins, 12 of which shown to be modulated in loggerheads age groups, and identified as a part of (i) platelet degranulation, (ii) neutrophil degranulation, and (iii) innate immune system pathways. The neurofascin (NFASC) is shown to be differentially abundant among all the age groups, and alpha-1-acid glycoprotein 2-like (ORM2) and alpha-1-antitrypsin-like (SERPINA1) proteins were recognized as members of all three above mentioned REACTOME pathways. Furthermore, 29 of plasma proteins were significantly differentially abundant in loggerheads age and recovery period groups. Out of 15 recognized pathways, those proteins were mostly included in three specific REACTOME pathways: (i) post-translational phosphorylation, (ii) regulation of Insulin-like Growth Factor (IGF) transport and uptake by Insulin-like Growth Factor Binding Proteins (IGFBPs), and (iii) platelet degranulation. The alpha-fetoprotein (AFP) was the only protein which showed statistically significant up-regulation patterns in all loggerhead age groups before release from the rescue centre, and the complement component 3 (C3) protein was the only protein modulated in all recovery period groups. Furthermore, C3 protein takes part in 9; and followed up with apolipoprotein A-I (APOA1) in 7; complement component 4 (C4), complement component 5 (C5) and kininogen-1 (KNG1) in 6 REACTOME pathways. Thereby, those proteins are highlighted and recommended as potential biomarkers of turtle's health status. Data are available via ProteomeXchange with identifier PXD029569. Finally, based on our results, we believe that comprehensive omics approach and routine plasma biochemical analysis, accompanied by proteins of acute phase, acid-base status and immune-response indicator analysis may significantly and reliably improve assessment of captive loggerheads rehabilitation and medication. SIGNIFICANCE: Monitoring and comparison of loggerhead sea turtles (C. caretta) blood plasma biochemistry parameters and plasma proteome profiles in relation to the age, and recovery period pointed out significantly differentially abundant proteins, along with certain biochemical parameter contents as potential biomarkers of turtle's fitness, health status and physiology.

Combination of strong anion exchange liquid chromatography with microchip capillary electrophoresis sodium dodecyl sulfate for rapid two-dimensional separations of complex protein mixtures

Two-dimensional separations provide a simple way to increase the resolution and peak capacity of complex protein separations. The feasibility of a recently developed instrumental approach for two-dimensional separations of proteins was evaluated. The approach is based on the general principle of two-dimensional gel electrophoresis. In the first dimension, semi-preparative strong anion exchange high-performance liquid chromatography is utilized and fractions are collected by means of a fraction collector. They are subsequently analyzed in the second dimension with microchip capillary electrophoresis sodium dodecyl sulfate. Microchip capillary electrophoresis provides the necessary speed (approximately 1 min/fraction) for short analysis. In this study, three different samples were investigated. Different constructs of soluble guanylyl cyclase were expressed in Sf9-cells using the baculovirus expression system. Cell lysates were analyzed and the resulting separations were compared. In our experimental setup, the soluble guanylyl cyclase was identified among hundreds of other proteins in these cell lysates, indicating its potential for screening, process control, or analysis. The results were validated by immunoblotting. Samples from Chinese hamster ovary cell culture before and after a purification step were investigated and approximately 9% less impurities could be observed. The separation patterns obtained for human plasma are closely similar to patterns obtained with two-dimensional gel electrophoresis and a total of 218 peaks could be observed. Overall, the approach was well applicable to all samples and, based on these results, further directions for improvements were identified. .

Erythrocyte sedimentation: Effect of aggregation energy on gel structure during collapse

The erythrocyte (or red blood cell) sedimentation rate (ESR) is commonly interpreted as a measure of cell aggregation and as a biomarker of inflammation. It is well known that an increase of fibrinogen concentration, an aggregation-inducing protein for erythrocytes, leads to an increase of the sedimentation rate of erythrocytes, which is generally explained through the formation and faster settling of large disjoint aggregates. However, many aspects of erythrocyte sedimentation conform well with the collapse of a particle gel rather than with the sedimentation of disjoint aggregates. Using experiments and cell-level numerical simulations, we systematically investigate the dependence of ESR on fibrinogen concentration and its relation to the microstructure of the gel-like erythrocyte suspension. We show that for physiological aggregation interactions, an increase in the attraction strength between cells results in a cell network with larger void spaces. This geometrical change in the network structure occurs due to anisotropic shape and deformability of erythrocytes and leads to an increased gel permeability and faster sedimentation. Our results provide a comprehensive relation between the ESR and the cell-level structure of erythrocyte suspensions and support the gel hypothesis in the interpretation of blood sedimentation.

Protein discrimination using erythrosin B-based GUMBOS in combination with UV-Vis spectroscopy and chemometrics

GUMBOS (Group of Uniform Materials Based on Organic Salts) have recently emerged as interesting materials for protein analysis due to their unique features and high tunability. In this regard, four novel erythrosin B (EB)-based GUMBOS were synthesized and their potential to discriminate among proteins with distinct properties (e.g., size, charge, and hydrophobicity) was assessed. These solid-phase materials were prepared using a single-step metathesis reaction between EB and various phosphonium and ammonium cations, namely tetrabutylphosphonium (P₄₄₄₄⁺), tributylhexadecylphosphonium (P₄₄₄₁₆⁺), tetrabutylammonium (N₄₄₄₄⁺), and benzyldimethylhexadecylammonium (BDHA⁺). Subsequently, the effect of pH (3.0, 4.5, and 6.0) and reaction time (5, 10, and 15 min) on the discriminatory power of synthesized GUMBOS was evaluated. Absorption spectra resulting from the interaction between EB-based GUMBOS and proteins were analyzed using partial least squares discriminant analysis (PLSDA). Unlike time, the pH value was determined to have influence over GUMBOS discrimination potential. Correct protein assignments varied from 86.5% to 100.0%, and the best discriminatory results were observed for [P₄₄₄₄]₂[EB] and [N₄₄₄₄]₂[EB] at pH 6.0. Additionally, these two GUMBOS allowed discrimination of protein mixtures containing different ratios of albumin and myoglobin, which appeared as individualized clusters in the PLSDA scores plots. Overall, this study showcases EB-based GUMBOS as simple synthetic targets to provide a label-free, cost-effective, rapid, and successful approach for discrimination of single proteins and their mixtures.

Evaluation of the Molecular Mechanisms of Sepsis Using Proteomics

Sepsis is a complex syndrome promoted by pathogenic and host factors; it is characterized by dysregulated host responses and multiple organ dysfunction, which can lead to death. However, its underlying molecular mechanisms remain unknown. Proteomics, as a biotechnology research area in the post-genomic era, paves the way for large-scale protein characterization. With the rapid development of proteomics technology, various approaches can be used to monitor proteome changes and identify differentially expressed proteins in sepsis, which may help to understand the pathophysiological process of sepsis. Although previous reports have summarized proteomics-related data on the diagnosis of sepsis and sepsis-related biomarkers, the present review aims to comprehensively summarize the available literature concerning “sepsis”, “proteomics”, “cecal ligation and puncture”, “lipopolysaccharide”, and “post-translational modifications” in relation to proteomics research to provide novel insights into the molecular mechanisms of sepsis.

A simple organic solvent precipitation method to improve detection of low molecular weight proteins

Mass spectrometry-based proteomics revolutionized global proteomic profiling. Although high molecular weight abundant proteins are readily sampled in global proteomics studies, less abundant low molecular weight proteins are often underrepresented. This includes biologically important classes of low molecular weight proteins including ligands, growth factors, peptide hormones and cytokines. Although extensive fractionation can facilitate achieving better coverage of proteome, it requires additional infrastructure, mass spectrometry time and labor. There is need for a simple method that can selectively deplete high molecular weight abundant proteins and enrich for low molecular weight less abundant proteins to improve their coverage in proteomics studies. We present a simple organic-solvent based protein precipitation method that selectively depletes high molecular weight proteins and enriches low molecular weight proteins in the soluble fraction. Using this strategy, we demonstrate identification of low molecular weight proteins that are generally underrepresented in proteomics datasets. In addition, we show the utility of this approach in identifying functional cleavage products from precursor proteins and low molecular weight short open reading frame proteins encoded by non-coding regions such as lncRNAs and UTRs. As the method does not require additional infrastructure, it can complement existing proteomics workflows to increase detection and coverage of low molecular weight proteins that are less abundant. This article is protected by copyright. All rights reserved.

Peptidomics: A Review of Clinical Applications and Methodologies

Improvements in both liquid chromatography (LC) and mass spectrometry (MS) instrumentation have greatly enhanced proteomic and small molecule metabolomic analysis in recent years. Less focus has been on the improved capability to detect and quantify small bioactive peptides, even though the exact sequences of the peptide species produced can have important biological consequences. Endogenous bioactive peptide hormones, for example, are generated by the targeted and regulated cleavage of peptides from their prohormone sequence. This process may include organ specific variants, as proglucagon is converted to glucagon in the pancreas but glucagon-like peptide-1 (GLP-1) in the small intestine, with glucagon raising, whereas GLP-1, as an incretin, lowering blood glucose. Therefore, peptidomics workflows must preserve the structure of the processed peptide products to prevent the misidentification of ambiguous peptide species. The poor in vivo and in vitro stability of peptides in biological matrices is a major factor that needs to be considered when developing methods to study them. The bioinformatic analysis of peptidomics data sets requires the inclusion of specific post-translational modifications, which are critical for the function of many bioactive peptides. This review aims to discuss and contrast the various extraction, analytical, and bioinformatics approaches used for human peptidomics studies in a multitude of matrices.

Dynamic interactions and intracellular fate of label-free, thin graphene oxide sheets within mammalian cells: role of lateral sheet size

Graphene oxide (GO) holds great potential for biomedical applications, however fundamental understanding of the way it interacts with biological systems is still lacking even though it is essential for successful clinical translation. In this study, we exploit intrinsic fluorescent properties of thin GO sheets to establish the relationship between lateral dimensions of the material, its cellular uptake mechanisms and intracellular fate over time. Label-free GO with distinct lateral dimensions, small (s-GO) and ultra-small (us-GO) were thoroughly characterised both in water and in biologically relevant cell culture medium. Interactions of the material with a range of non-phagocytic mammalian cell lines (BEAS-2B, NIH/3T3, HaCaT, 293T) were studied using a combination of complementary analytical techniques (confocal microscopy, flow cytometry and TEM). The uptake mechanism was initially interrogated using a range of pharmaceutical inhibitors and validated using polystyrene beads of different diameters (0.1 and 1 μm). Subsequently, RNA-Seq was used to follow the changes in the uptake mechanism used to internalize s-GO flakes over time. Regardless of lateral dimensions, both types of GO were found to interact with the plasma membrane and to be internalized by a panel of cell lines studied. However, s-GO was internalized mainly via macropinocytosis while us-GO was mainly internalized via clathrin- and caveolae-mediated endocytosis. Importantly, we report the shift from macropinocytosis to clathrin-dependent endocytosis in the uptake of s-GO at 24 h, mediated by upregulation of mTORC1/2 pathway. Finally, we show that both s-GO and us-GO terminate in lysosomal compartments for up to 48 h. Our results offer an insight into the mechanism of interaction of GO with non-phagocytic cell lines over time that can be exploited for the design of biomedically-applicable 2D transport systems.

Magnetic-molecularly imprinted polymers in electrochemical sensors and biosensors

Magnetic particles, as well as molecularly imprinted polymers, have revolutionized separation and bioanalytical methodologies in the 1980s due to their wide range of applications. Today, biologically modified magnetic particles are used in many scientific and technological applications and are integrated in more than 50,000 diagnostic instruments for the detection of a huge range of analytes. However, the main drawback of this material is their stability and high cost. In this work, we review recent advances in the synthesis and characterization of hybrid molecularly imprinted polymers with magnetic properties, as a cheaper and robust alternative for the well-known biologically modified magnetic particles. The main advantages of these materials are, besides the magnetic properties, the possibility to be stored at room temperature without any loss in the activity. Among all the applications, this work reviews the direct detection of electroactive analytes based on the preconcentration by using magnetic-MIP integrated on magneto-actuated electrodes, including food safety, environmental monitoring, and clinical and pharmaceutical analysis. The main features of these electrochemical sensors, including their analytical performance, are summarized. This simple and rapid method will open the way to incorporate this material in different magneto-actuated devices with no need for extensive sample pretreatment and sophisticated instruments.

Variation of body condition and plasma energy substrates with life stage, sex, and season in wild-sampled nurse sharks Ginglymostoma cirratum

Reported here are the relationships among morphological (i.e., body condition) and biochemical (i.e., plasma concentrations of triglycerides, cholesterol, free fatty acids, and ketone bodies and ketone body ratios) parameters related to energy storage and use, as well as the variation of such parameters, for 107 free-ranging nurse sharks Ginglymostoma cirratum sampled off South Florida. Immature G. cirratum exhibited a higher variance in body condition, plasma free fatty acid concentrations and ketone body ratios compared to adults. Mature female G. cirratum had significantly higher body condition than mature males, driven by a seasonal increase in mature female body condition during the wet season. Mature male G. cirratum showed a decrease in the ketone body β-hydroxybutyric acid during the dry season. Taken together, this study provides a baseline assessment of body condition and internal physiological state for a data-poor marine species and demonstrates significant ontogenetic, sexual and seasonal variation in G. cirratum energetic state. As concluded by other studies of energy metabolism in free-ranging sharks, this research highlights the importance of considering intraspecific patterns and sampling context for inferring the drivers of variation.

[Research progress and application of retention time prediction method based on deep learning]

In "shotgun" proteomics strategy, the proteome is explained by analyzing tryptic digested peptides using liquid chromatography-mass spectrometry. In this strategy, the retention time of peptides in liquid chromatography separation can be predicted based on the peptide sequence. This is a useful feature for peptide identification. Therefore, the prediction of the retention time has attracted much research attention. Traditional methods calculate the physical and chemical properties of the peptides based on their amino acid sequence to obtain the retention time under certain chromatography conditions; however, these methods cannot be directly adopted for other chromatography conditions, nor can they be used across laboratories or instrument platforms. To solve this problem, in recent years, deep learning was introduced to proteomics research for retention time prediction. Deep learning is an advanced machine-learning method that has extraordinary capability to learn complex relationships from large-scale data. By stacking multiple hidden neural networks, deep learning can ingest raw data without manually designed features. Transfer learning is an important method in deep learning. It improves the learning process a new task through the transfer of knowledge from an already-learned related task. Transfer learning allows models trained using large datasets to be utilized across conditions by fine-tuning on smaller datasets, instead of retraining the whole model. Many retention time prediction methods have been developed. In the process of training the model, the sequences of peptides are encoded to represent peptide information. Deep learning considers the relationship between the characteristics of the peptides and their corresponding retention times without the need for manual input of the physical and chemical properties of the peptides. Compared with traditional methods, deep learning methods have higher accuracy and can be easily used under different chromatography conditions by transfer learning. If there are not enough datasets to train a new model, a trained model from other datasets can be used as a replacement after calibration with small datasets obtained from these chromatography conditions. While the retention times of modified peptides can also be predicted, the predictions are inadequate for complex modifications such as glycosylation, and this is one of the main problems to be solved. The predicted retention times were used to control the quality of peptide identification. With high accuracy, the predicted retention times can be considered as actual retention times. Therefore, the difference between predicted and observed retention times can serve as an effective and unbiased quantitative metric for evaluating the quality of peptide-spectrum matches (PSMs) reported using different peptide identification methods. Combined with fragment ion intensity prediction, retention time prediction is used to generate spectral libraries for data-independent acquisition (DIA)-based mass spectrometry analysis. Generally, DIA methods identify peptides using specific spectrum libraries obtained from data-dependent acquisition (DDA) experiments. As a result, only peptides detected in the DDA experiments can be present in the libraries and detected in DIA. Furthermore, it takes a lot of time and effort to build libraries from DDA experiments, and typically, they cannot be adopted across different laboratories or instrument platforms. In contrast, the pseudo spectral libraries generated by retention times and fragment ion intensity prediction can overcome these shortcomings. The pseudo spectral libraries generate theoretical spectra of all possible peptides without the need for DDA experiments. This paper reviews the research progress of deep learning methods in the prediction of retention time and in related applications in order to provide references for retention time prediction and protein identification. At the same time, the development direction and application trend of retention time prediction methods based on deep learning are discussed.

Green synthesis as a simple and rapid route to protein modified magnetic nanoparticles for use in the development of a fluorometric molecularly imprinted polymer-based assay for detection of myoglobin

We have developed a low-cost molecularly imprinted polymer (MIP)-based fluorometric assay to directly quantify myoglobin in a biological sample. The assay uses a previously unreported method for the development of microwave-assisted rapid synthesis of aldehyde functionalized magnetic nanoparticles, in just 20 min. The aldehyde functionalized nanoparticles have an average size of 7.5 nm ± 1.8 and saturation magnetizations of 31.8 emu g-1 with near-closed magnetization loops, confirming their superparamagnetic properties. We have subsequently shown that protein tethering was possible to the aldehyde particles, with 0.25 ± 0.013 mg of myoglobin adsorbed to 20 mg of the nanomaterial. Myoglobin-specific fluorescently tagged MIP (F-MIP) particles were synthesized and used within the assay to capture myoglobin from a test sample. Excess F-MIP was removed from the sample using protein functionalized magnetic nanoparticles (Mb-SPION), with the remaining sample analyzed using fluorescence spectroscopy. The obtained calibration plot of myoglobin showed a linear correlation ranging from 60 pg ml-1 to 6 mg ml-1 with the limit of detection of 60 pg ml-1. This method was successfully used to detect myoglobin in spiked fetal calf serum, with a recovery rate of more than 93%.

Fresh Molecular Concepts to Extend the Lifetimes of Old Antimicrobial Drugs

Antimicrobial drug development generally initiates with target identification and mode of action studies. Often, emergence of resistance and/or undesired side effects that are discovered only after prolonged clinical use, result in discontinuation of clinical use. Since the cost and time required for improvement of existing drugs are considerably lower than those required for the development of novel drugs, academic and pharmaceutical company researchers pursue this direction. In this account we describe selected examples of how chemical probes generated from antimicrobial drugs and chemical and enzymatic modifications of these drugs have been used to modify modes of action, block mechanisms of resistance, or reduce side effects, improving performance. These examples demonstrate how new and comprehensive mechanistic insights can be translated into fresh concepts for development of next-generation antimicrobial agents.

Quantitative proteomic profiling of Cervicovaginal fluid from pregnant women with term and preterm birth

Background

Preterm birth (PTB) is one of major causes of perinatal mortality and neonatal morbidity, but knowledge of its complex etiology is still limited. Here we present cervicovaginal fluid (CVF) protein profiles of pregnant women who subsequently delivered at spontaneous preterm or term, aiming to identify differentially expressed CVF proteins in PTB and term birth.

Methods

The CVF proteome of women who sequentially delivered at preterm and term was analyzed using isobaric tags for relative and absolute quantitation (iTRAQ) coupled with two-dimensional nanoflow liquid chromatography-tandem mass spectrometry (2D-nLC-MS/MS). We compared the CVF proteome of PTB (n = 5) and control subjects (term birth, n = 7) using pooled control CVF (term birth, n = 20) as spike-in standard.

Results

We identified 1294 CVF proteins, of which 605 were newly identified proteins. Of 990 proteins quantified in both PTB and term birth, 52 proteins were significantly up/down-regulated in PTB compared to term birth. The differentially expressed proteins were functionally associated to immune response, endopeptidase inhibitors and structural constituent of cytoskeleton. Finally, we confirm the down-regulation of SERPINB7 (a serine-type protease inhibitor) in PTB compared to control by Western blot.

Conclusions

Taken together, our study provide quantitative CVF proteome profiles of pregnant women who ultimately delivered at preterm and term. These promising results could help to improve the understanding of PTB etiology and to discover biomarkers for asymptomatic PTB.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12953-021-00171-1.

Extracellular Vesicles in Musculoskeletal Pathologies and Regeneration

The incidence of musculoskeletal diseases is steadily increasing with aging of the population. In the past years, extracellular vesicles (EVs) have gained attention in musculoskeletal research. EVs have been associated with various musculoskeletal pathologies as well as suggested as treatment option. EVs play a pivotal role in communication between cells and their environment. Thereby, the EV cargo is highly dependent on their cellular origin. In this review, we summarize putative mechanisms by which EVs can contribute to musculoskeletal tissue homeostasis, regeneration and disease, in particular matrix remodeling and mineralization, pro-angiogenic effects and immunomodulatory activities. Mesenchymal stromal cells (MSCs) present the most frequently used cell source for EV generation for musculoskeletal applications, and herein we discuss how the MSC phenotype can influence the cargo and thus the regenerative potential of EVs. Induced pluripotent stem cell-derived mesenchymal progenitor cells (iMPs) may overcome current limitations of MSCs, and iMP-derived EVs are discussed as an alternative strategy. In the last part of the article, we focus on therapeutic applications of EVs and discuss both practical considerations for EV production and the current state of EV-based therapies.

Affinity Proteomics Assays for Cardiovascular and Atherosclerotic Disease Biomarkers

Systematic exploration of the dynamic human plasma proteome enables the discovery of novel protein biomarkers. Using state-of-the-art technologies holds the promise to facilitate a better diagnosis and risk prediction of diseases. Cardiovascular disease (CVD) pathophysiology is characterized for unbalancing of processes such as vascular inflammation, endothelial dysfunction, or lipid profiles among others. Such processes have a direct impact on the dynamic and complex composition of blood and hence the plasma proteome. Therefore, the study of the plasma proteome comprises an excellent exploratory source of biomarker research particularly for CVD. We describe the protocol for performing the discovery of protein biomarker candidates using the suspension bead array technology. The process does not require depletion steps to remove abundant proteins and consumes only a few microliters of sample from the body fluid of interest. The approach is scalable to measure many analytes as well as large numbers of samples. Moreover, we describe a bead-assisted antibody-labeling process that helps to develop quantitative assays for validation purposes and facilitate the translation of the identified candidates into clinical studies.

Serum Prevents Interactions between Antimicrobial Amphiphilic Aminoglycosides and Plasma Membranes

Antimicrobial cationic amphiphiles have broad-spectrum activity, and microbes do not readily develop resistance to these agents, highlighting their clinical and industrial potential. Cationic amphiphiles perturb the integrity of membranes leading to cell death, and the lack of discrimination between microbial and mammalian plasma membranes is thought to be one of the main barriers of using these agents for the treatment of systemic infections. Here, we describe the synthesis and study of 20 antimicrobial cationic amphiphiles that are derivatives of the aminoglycoside nebramine with different numbers of alkyl chain ethers that differ in length and degree of unsaturation. We determined antifungal activities and evaluated hemoglobin release from red blood cells as a measure of membrane selectivity and analyzed how serum influences these activities. Microscopic images revealed morphological transformations of red blood cells from the normal double-disc shape to empty ghost cells upon treatment with the cationic amphiphiles. Antifungal activity, hemolysis, and morphological changes in red blood cells decreased as the percentage of serum in the culture medium was increased. In images of red blood cells treated with fluorescently labeled amphiphilic nebramine probes, the accumulation of the cationic amphiphiles in the membranes decreased as serum concentration increased. This suggests that, in addition to its known effect of preventing the deformability of red blood cells, serum prevents interactions between cationic amphiphiles and the plasma membrane. The results of this study indicate that biological activities of cationic amphiphiles are abrogated in serum. Thus, these agents are suitable for external and industrial uses but probably not for effective treatment of systemic infections.

An Integrated Quantitative Proteomics Workflow for Cancer Biomarker Discovery and Validation in Plasma

Blood plasma is one of the most widely used samples for cancer biomarker discovery research as well as clinical investigations for diagnostic and therapeutic purposes. However, the plasma proteome is extremely complex due to its wide dynamic range of protein concentrations and the presence of high-abundance proteins. Here we have described an optimized, integrated quantitative proteomics pipeline combining the label-free and multiplexed-labeling-based (iTRAQ and TMT) plasma proteome profiling methods for biomarker discovery, followed by the targeted approaches for validation of the identified potential marker proteins. In this workflow, the targeted quantitation of proteins is carried out by multiple-reaction monitoring (MRM) and parallel-reaction monitoring (PRM) mass spectrometry. Thus, our approach enables both unbiased screenings of biomarkers and their subsequent selective validation in human plasma. The overall procedure takes only ~2 days to complete, including the time for data acquisition (excluding database searching). This protocol is quick, flexible, and eliminates the need for a separate immunoassay-based validation workflow in blood cancer biomarker investigations. We anticipate that this plasma proteomics workflow will help to accelerate the cancer biomarker discovery program and provide a valuable resource to the cancer research community.

Enhanced Cellular Transduction of Nanoparticles Resistant to Rapidly Forming Plasma Protein Coronas

Nanoparticles (NPs) are increasingly being developed as biomedical platforms for drug/nucleic acid delivery and imaging. However, in biological fluids, NPs interact with a wide range of proteins that form a coating known as protein corona. Coronae can critically influence self-interaction and binding of other molecules, which can affect toxicity, promote cell activation, and inhibit general or specific cellular uptake. Glycosaminoglycan (GAG)-binding enhanced transduction (GET) is developed to efficiently deliver a variety of cargoes intracellularly; employing GAG-binding peptides, which promote cell targeting, and cell penetrating peptides (CPPs) which enhance endocytotic cell internalization. Herein, it is demonstrated that GET peptide coatings can mediate sustained intracellular transduction of magnetic NPs (MNPs), even in the presence of serum or plasma. NP colloidal stability, physicochemical properties, toxicity and cellular uptake are investigated. Using label-free snapshot proteomics, time-resolved profiles of human plasma coronas formed on functionalized GET-MNPs demonstrate that coronae quickly form (<1 min), with their composition relatively stable but evolving. Importantly GET-MNPs present a subtly different corona composition to MNPs alone, consistent with GAG-binding activities. Understanding how NPs interact with biological systems and can retain enhanced intracellular transduction will facilitate novel drug delivery approaches for cell-type specific targeting of new nanomaterials.

Putative serum protein biomarkers for epsilon toxin exposure in mouse model using LC-MS/MS analysis

Epsilon toxin (ETX), produced by Clostridium perfringens Type B or type D strains, is a potential biological and toxin warfare (BTW) agent, largely for its very high toxicity. The toxin is implicated in several animal diseases. Using LC-MS/MS analysis, we report here elucidation of putative serum maker proteins for ETX exposure with an objective of the early diagnosis of intoxication. Of 166 consensus proteins (488 peptides), showing ETX-induced alterations, 119 proteins exhibited increase and 47 proteins showed decreased abundance in serum, as revealed by SWATH (DIA) acquisition on LC-MS/MS and label free quantitative analysis of control and test samples. Complement and coagulation cascade, nitrogen metabolism, negative regulation of peptidase activity, and response to ROS were among the biological processes and pathways perturbed by the ETX exposure. Interaction network indicated enzyme inhibitor activity, detoxification of ROS, and steroid binding functions were the major interaction networks for the proteins with increased abundance, while, hemostasis and structural molecule activity were the prominent networks for the down-regulated proteins. Validation studies were carried out by immunoprecipitation, ELISA, and Western blot analysis of selected proteins to demonstrate diagnostic potential of the putative marker proteins of ETX exposure.

Revival of Krebs-Ringer balanced salt solution for the investigation of polymorphonuclear leukocytes and Pseudomonas aeruginosa biofilm interaction

To study the interaction between aggregating bacteria and polymorphonuclear leukocytes (PMNs) in vitro, the chosen medium must favor both the isolated PMNs and the bacteria. To investigate the best-suited medium for the in vitro survival of isolated unactivated human PMNs, we compared three different mammalian cell media: Krebs-Ringer balanced salt solution (BSS), Hanks' BSS (HBSS) and Roswell Park Memorial Institute (RPMI) 1640. The death of PMNs was estimated by the release of lactate dehydrogenase activity. Furthermore, two types of serum, human (HS) and fetal bovine (FBS), were compared at different concentrations (0%, 2%, 5%, 10%) and at three different time points (2, 4, 20 h). We show that Krebs-Ringer BSS prolonged the survival of PMNs compared to HBSS and RPMI 1640 and that the addition of 10% FBS significantly enhanced the long-term survival (20 h) compared to HS. Furthermore, we observed aggregation of Pseudomonas aeruginosa when grown in the presence of either a mixture of histones, histone H3, arginine or lysine. In this study, we show that the use of Krebs-Ringer BSS is highly relevant for the study of the interaction of bacteria and PMNs in relation to novel treatment strategies of biofilm infections due to the reproduction of bacterial aggregation as seen in chronic bacterial infections.

Alzheimer's Disease Diagnosis Using Misfolding Proteins in Blood

Alzheimer's disease (AD) is pathologically characterized by a long progressive phase of neuronal changes, including accumulation of extracellular amyloid-β (Aβ) and intracellular neurofibrillary tangles, before the onset of observable symptoms. Many efforts have been made to develop a blood-based diagnostic method for AD by incorporating Aβ and tau as plasma biomarkers. As blood tests have the advantages of being highly accessible and low cost, clinical implementation of AD blood tests would provide preventative screening to presymptomatic individuals, facilitating early identification of AD patients and, thus, treatment development in clinical research. However, the low concentration of AD biomarkers in the plasma has posed difficulties for accurate detection, hindering the development of a reliable blood test. In this review, we introduce three AD blood test technologies emerging in South Korea, which have distinctive methods of heightening detection sensitivity of specific plasma biomarkers. We discuss in detail the multimer detection system, the self-standard analysis of Aβ biomarkers quantified by interdigitated microelectrodes, and a biomarker ratio analysis comprising Aβ and tau.

Albumin-driven disassembly of lipidic nanoparticles: the specific case of the squalene-adenosine nanodrug

In the field of nanomedicine, nanostructured nanoparticles (NPs) made of self-assembling prodrugs emerged in the recent years with promising properties. In particular, squalene-based drug nanoparticles have already shown their efficiency through in vivo experiments. However, a complete pattern of their stability and interactions in the blood stream is still lacking. In this work we assess the behavior of squalene-adenosine (SQAd) nanoparticles - whose neuroprotective effect has already been demonstrated in murine models - in the presence of fetal bovine serum (FBS) and of bovine serum albumin (BSA), the main protein of blood plasma. Extensive physicochemical characterizations were performed using Small Angle Neutron Scattering (SANS), cryogenic transmission electron microscopy (Cryo-TEM), circular dichroism (CD), steady-state fluorescence spectroscopy (SSFS) and isothermal titration calorimetry (ITC) as well as in silico by means of ensemble docking simulations with human serum albumin (HSA). Significant changes in the colloidal stability of the nanoparticles in the presence of serum albumin were observed. SANS, CD and SSFS analyses demonstrated an interaction between SQAd and BSA, with a partial disassembly of the nanoparticles in the presence of BSA and the formation of a complex between SQAd and BSA. The interaction free energy of SQAd nanoparticles with BSA derived from ITC experiments, is about -8 kcal mol^-1 which is further supported in silico by ensemble docking simulations. Overall, our results show that serum albumin partially disassembles SQAd nanoparticles by extracting individual SQAd monomers from them. As a consequence, the SQAd nanoparticles would act as a circulating reservoir in the blood stream. The approach developed in this study could be extended to other soft organic nanoparticles.

In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics

Data-independent acquisition (DIA) is an emerging technology for quantitative proteomic analysis of large cohorts of samples. However, sample-specific spectral libraries built by data-dependent acquisition (DDA) experiments are required prior to DIA analysis, which is time-consuming and limits the identification/quantification by DIA to the peptides identified by DDA. Herein, we propose DeepDIA, a deep learning-based approach to generate in silico spectral libraries for DIA analysis. We demonstrate that the quality of in silico libraries predicted by instrument-specific models using DeepDIA is comparable to that of experimental libraries, and outperforms libraries generated by global models. With peptide detectability prediction, in silico libraries can be built directly from protein sequence databases. We further illustrate that DeepDIA can break through the limitation of DDA on peptide/protein detection, and enhance DIA analysis on human serum samples compared to the state-of-the-art protocol using a DDA library. We expect this work expanding the toolbox for DIA proteomics.

Epitope Imprinting Technology: Progress, Applications, and Perspectives toward Artificial Antibodies

Epitope imprinting is a promising tool to generate antibody-like specific recognition sites. Recently, because of the ease of obtaining templates, the flexibility in selecting monomers, their resistance to harsh environments, and the high specificity toward targets, epitope-imprinted materials have attracted much attention in various fields, such as bioanalysis, clinical therapy, and pharmacy. Here, the discussion is focused on the current representative epitope imprinting technologies, including epitope bulk imprinting and epitope surface imprinting. Moreover, the application of epitope-imprinted materials to the recognition of peptides, proteins, and cells is reviewed. Finally, the remaining challenges arising from the intrinsic properties of epitope imprinting are discussed, and future development in the field is prospected.

Common Repository of FBS Proteins (cRFP) To Be Added to a Search Database for Mass Spectrometric Analysis of Cell Secretome

We propose to use cRFP (common Repository of FBS Proteins) in the MS (mass spectrometry) raw data search of cell secretomes. cRFP is a small supplementary sequence list of highly abundant fetal bovine serum proteins added to the reference database in use. The aim behind using cRFP is to prevent the contaminant FBS proteins from being misidentified as other proteins in the reference database, just as we would use cRAP (common Repository of Adventitious Proteins) to prevent contaminant proteins present either by accident or through unavoidable contacts from being misidentified as other proteins. We expect it to be widely used in experiments where the proteins are obtained from serum-free media after thorough washing of the cells, or from a complex media such as SILAC, or from extracellular vesicles directly.

Non-coding RNAs in regulating gastric cancer metastasis

Gastric cancer is one of the leading causes of cancer-related deaths worldwide, and mortality remains high, especially in East Asia. At present, the main method to diagnose gastric cancer is pathological biopsy. At the time of diagnosis, most patients have been diagnosed with advanced cancer and metastasis. The treatment of gastric cancer patients is mainly radical surgical resection and chemoradiotherapy, while patients with metastatic tumor have great challenges to radical surgery and are prone to drug resistance. Metastasis is an important factor affecting tumor development. In addition, evidence accumulated in the literature indicates that non-coding RNA plays a key role in tumor metastasis. This article reviews the role of ncRNAs in gastric cancer metastasis and discusses the regulatory mechanism in the development and treatment of gastric cancer.

Elucidation of protein biomarkers in plasma and urine for epsilon toxin exposure in mouse model

Epsilon toxin (ETX) is the major virulence determinant of C. perfringens type B or type D strains, causing diseases in animals, besides being a listed biological and toxin warfare (BTW) agent. Keeping in mind the high lethality and the rapid onset of clinical manifestations, early diagnosis of epsilon toxin exposure is of paramount importance for implementation of appropriate medical countermeasures. Using a 2DE-MS approach, the present study is the first comprehensive proteomic elucidation of ETX-induced protein markers in the mouse model, providing putative targets for early diagnosis of ETX exposure. A total of 52 unique proteins showing ETX-induced modulations were identified in plasma and urine samples. Fibrinogen, apolipoprotein, serum amyloid protein, plasminogen, serum albumin, glutathione peroxidase, transferrin, major urinary protein 2, haptoglobin, transthyretin, and vitamin D-binding protein were among the proteins observed in more than one dataset with altered abundance after the ETX-intoxication. The predicted localization, function, and interaction of the ETX-modulated proteins in the plasma and urine indicated involvement of multiple pathways; extracellular proteins, followed by macromolecular complexes associated with blood coagulation and plasminogen activating cascade, being the most prominent among others. The putative markers elucidated here warrants further validation and can be of immense value for the early diagnosis of ETX exposure.

Early Proteome Shift and Serum Bioactivity Precede Diesel Exhaust-induced Impairment of Cardiovascular Recovery in Spontaneously Hypertensive Rats

Single circulating factors are often investigated to explain air pollution-induced cardiovascular dysfunction, yet broader examinations of the identity and bioactivity of the entire circulating milieu remain understudied. The purpose of this study was to determine if exposure-induced cardiovascular dysfunction can be coupled with alterations in both serum bioactivity and the circulating proteome. Two cohorts of Spontaneously Hypertensive Rats (SHRs) were exposed to 150 or 500 μg/m³ diesel exhaust (DE) or filtered air (FA). In Cohort 1, we collected serum 1 hour after exposure for proteomics analysis and bioactivity measurements in rat aortic endothelial cells (RAECs). In Cohort 2, we assessed left ventricular pressure (LVP) during stimulation and recovery from the sympathomimetic dobutamine HCl, one day after exposure. Serum from DE-exposed rats had significant changes in 66 serum proteins and caused decreased NOS activity and increased VCAM-1 expression in RAECs. While rats exposed to DE demonstrated increased heart rate at the start of LVP assessments, heart rate, systolic pressure, and double product fell below baseline in DE-exposed rats compared to FA during recovery from dobutamine, indicating dysregulation of post-exertional cardiovascular function. Taken together, a complex and bioactive circulating milieu may underlie air pollution-induced cardiovascular dysfunction.

The computational and experimental studies on a 1, 2, 3-triazole compound and its special binding to three kinds of blood proteins

A newly synthesized compound, ethyl 5-phenyl-2-(p-tolyl)-2H-1, 2, 3-triazole-4-carboxylate (EPPC) may be considered as a drug candidate and was exploited to study the structural and spectral properties by using quantum chemical calculation and multiple spectroscopic techniques. The results on theoretical spectrum of EPPC were consistent with experimental spectrum in great degree. In addition, EPPC has been as a special probe and investigated on the interactions with three kinds of blood proteins including human serum albumin (HSA), human immunoglobulin (HIgG) and bovine hemoglobin (BHb) by using UV-Vis, fluorescence spectroscopy and molecular modeling, respectively. Changes in various fluorescence and UV-Vis spectra were observed upon ligand binding along with a remarkable degree of fluorescence enhancement on complex formation under physiological condition with binding constant about 10⁵ order of magnitudes, which caused the variations of conformation and microenvironment of these proteins in aqueous solution. The obtained results from the thermodynamic parameters calculated according to the van't Hoff equation indicated that the entropy change ΔS° and enthalpy change ΔH° were found to be 0.168 KJ/mol K and 22.154 KJ/mol for EPPC-HSA system, 0.284 KJ/mol K and 54.408 KJ/mol for EPPC-HIgG system, and 0.228 KJ/mol K and 37.548 KJ/mol for EPPC-BHb system, respectively, which demonstrated that the primary binding pattern is determined by hydrophobic interaction. The results of docking and molecular dynamics simulation using three proteins crystal models revealed that EPPC could bind to three proteins well into hydrophobic cavity, which showed good consistence with the spectroscopic measurements.Communicated by Ramaswamy H. Sarma.