Proteins In Body Fluids Research Articles

An Equine Protein Atlas Highlights Synovial Fluid Proteome Dynamics during Experimentally LPS-Induced Arthritis.

In human proteomics, substantial efforts are ongoing to leverage large collections of mass spectrometry (MS) fragment ion spectra into extensive spectral libraries (SL) as a resource for data independent acquisition (DIA) analysis. Currently, such initiatives in equine research are still missing. Here we present a large-scale equine SL, comprising 6394 canonical proteins and 89,329 unique peptides, based on data dependent acquisition analysis of 75 tissue and body fluid samples from horses. The SL enabled large-scale DIA-MS based quantification of the same samples to generate a quantitative equine protein distribution atlas to infer dominant proteins in different organs and body fluids. Data mining revealed 163 proteins uniquely identified in a specific type of tissue or body fluid, serving as a starting point to determine tissue-specific or tissue-type-specific proteins. We showcase the SL by highlighting proteome dynamics in equine synovial fluid samples during experimental lipopolysaccharide-induced arthritis. A fuzzy c-means cluster analysis pinpointed SERPINB1, ATRN, NGAL, LTF, MMP1, and LBP as putative biomarkers for joint inflammation. This SL provides an extendable resource for future equine studies employing DIA-MS.

Parallel reaction monitoring targeted mass spectrometry as a fast and sensitive alternative to antibody-based protein detection

The reliable, accurate and quantitative targeted detection of proteins is a key technology in molecular and cell biology and molecular diagnostics. The current golden standard for targeted protein detection in complex mixtures such as complete cell lysates or body fluids is immunoblotting, a technology that was developed in the late 1970s and has not undergone major changes since. Although widespread, this methodology suffers from several disadvantages, such as the inability to detect low-abundant proteins or specific posttranslational modifications, the requirement for highly specific antibodies, the lack of quantitative power and the often-tedious practical procedures. Mass spectrometry (MS) based targeted protein detection is an alternative technology that could circumvent these caveats. Here, we compare immunoblotting with targeted protein mass spectrometry using a parallel reaction monitoring (PRM) regime on the Orbitrap mass spectrometer. We show that PRM based MS has superior sensitivity and quantitative accuracy over immunoblotting. The limit of detection for proteolytic peptides of a purified target protein was found to be in the mid- to low-attomole range and approximately one order of magnitude higher when embedded in a complex biological matrix. The incorporation of synthetic heavy isotope labeled (AQUA) peptides as internal calibrants into the PRM workflow allows for even higher accuracy for both the relative and absolute quantitation of tryptic target peptides. In conclusion, PRM is a versatile and sensitive technology, which can overcome the shortcomings of immunoblotting. We argue that PRM based MS could become the method of choice for the targeted detection of proteins in complex cellular matrices or body fluids and may eventually replace standard methods such as Western blotting and ELISA in biomedical research and in the clinic.

Oxidative Modifications of Proteins and Lipids of Dried Semen, Urine, and Saliva Stains as a Function of Age in Forensic Context

Knowledge of the time of deposition is pivotal in forensic investigations. Recent studies show that changes in intrinsic fluorescence over time can be used to estimate the age of body fluids. These changes have been attributed to oxidative modifications caused by protein–lipid interactions. This pilot study aims to explore the impact of these modifications on body fluid fluorescence, enhancing the protein–lipid model system for age estimation. Lipid and protein oxidation markers, including protein carbonyls, dityrosine, advanced glycation end-products (AGEs), malondialdehyde (MDA), and 4-hydroxynonenal (HNE), were studied in aging semen, urine, and saliva over 21 days. Surface plasmon resonance imaging (SPRi), enzyme-linked immunosorbent assay (ELISA), and fluorescence spectroscopy were applied. Successful detection of AGE, dityrosine, MDA, and HNE occurred in semen and saliva via SPRi, while only dityrosine was detected in urine. Protein carbonyls were measured in all body fluids, but only in saliva was a significant increase observed over time. Additionally, protein fluorescence loss and fluorescent oxidation product formation were assessed, showing significant decreases in semen and saliva, but not in urine. Although optimization is needed for accurate quantification, this study reveals detectable markers for protein and lipid oxidation in aging body fluids, warranting further investigation.

HSADab: A comprehensive database for human serum albumin

Human Serum Albumin (HSA), the most abundant protein in human body fluids, plays a crucial role in the transportation, absorption, metabolism, distribution, and excretion of drugs, significantly influencing their therapeutic efficacy. Despite the importance of HSA as a drug target, the available data on its interactions with external agents, such as drug-like molecules and antibodies, are limited, posing challenges for molecular modeling investigations and the development of empirical scoring functions or machine learning predictors for this target. Furthermore, the reported entries in existing databases often contain major inconsistencies due to varied experiments and conditions, raising concerns about data quality. To address these issues, a pioneering database, HSADab, was established through an extensive review of >30,000 scientific publications published between 1987 and 2023. The database encompasses over 5000 affinity data points at multiple temperatures and >130 crystal structures, including both ligand-bound and apo forms. The current HSADab resource (www.hsadab.cn) serves as a reliable foundation for validating molecular simulation protocols, such as traditional virtual screening workflows using docking, end-point, and al-chemical free energy techniques. Additionally, it provides a valuable data source for the implementation of machine learning predictors, including plasma protein binding models and plasma protein-based drug design models.

ESMSec: Prediction of Secreted Proteins in Human Body Fluids Using Protein Language Models and Attention.

The secreted proteins of human body fluid have the potential to be used as biomarkers for diseases. These biomarkers can be used for early diagnosis and risk prediction of diseases, so the study of secreted proteins of human body fluid has great application value. In recent years, the deep-learning-based transformer language model has transferred from the field of natural language processing (NLP) to the field of proteomics, leading to the development of protein language models (PLMs) for protein sequence representation. Here, we propose a deep learning framework called ESM Predict Secreted Proteins (ESMSec) to predict three types of proteins secreted in human body fluid. The ESMSec is based on the ESM2 model and attention architecture. Specifically, the protein sequence data are firstly put into the ESM2 model to extract the feature information from the last hidden layer, and all the input proteins are encoded into a fixed 1000 × 480 matrix. Secondly, multi-head attention with a fully connected neural network is employed as the classifier to perform binary classification according to whether they are secreted into each body fluid. Our experiment utilized three human body fluids that are important and ubiquitous markers. Experimental results show that ESMSec achieved average accuracy of 0.8486, 0.8358, and 0.8325 on the testing datasets for plasma, cerebrospinal fluid (CSF), and seminal fluid, which on average outperform the state-of-the-art (SOTA) methods. The outstanding performance results of ESMSec demonstrate that the ESM can improve the prediction performance of the model and has great potential to screen the secretion information of human body fluid proteins.

Histological, biochemical and immunohistochemical assessments of Roundup®, atrazine, and 2,4-D mixtures on tissue architecture, body fluid conditions, nitrotyrosine protein and Na+/K+-ATPase expressions in the American oyster, Crassostera virginica

Pesticides are widely used to control weeds and pests in agricultural settings but harm non-target aquatic organisms. In this study, our objective was to evaluate the effect of short-term exposure (one week) to environmentally relevant concentrations of pesticides mixture (low concentration: 0.4 μg/l atrazine, 0.5 μg/l Roundup®, and 0.5 μg/l 2,4-D; high concentration: 0.8 μg/l atrazine, 1 μg/l Roundup®, and 1 μg/l 2,4-D) on tissue architecture, body fluid conditions, and 3-nitrotyrosine protein (NTP) and Na+/K+-ATPase, expressions in tissues of American oyster (Crassostrea virginica) under controlled laboratory conditions. Histological analysis demonstrated the atrophy in the gills and digestive glands of oysters exposed to pesticides mixture. Periodic acid-Schiff (PAS) staining showed the number of hemocytes in connective tissue increased in low- and high-concentration pesticides exposure groups. However, pesticides treatment significantly (P < 0.05) decreased the amount of mucous secretion in the gills and digestive glands of oysters. The extrapallial fluid (i.e., body fluid) protein concentrations and glucose levels were dropped significantly (P < 0.05) in oysters exposed to high-concentration pesticides exposure groups. Moreover, immunohistochemical analysis showed significant upregulations of NTP and Na+/K+-ATPase expressions in the gills and digestive glands in pesticides exposure groups. Our results suggest that exposure to environmentally relevant pesticides mixture causes morphological changes in tissues and alters body fluid conditions and NTP and Na+/K+-ATPase expressions in tissues, which may lead to impaired physiological functions in oysters.

Intelligent salivary biosensors for periodontitis: in vitro simulation of oral oxidative stress conditions.

One of the most common oral diseases affecting millions of people worldwide is periodontitis. Usually, proteins in body fluids are used as biomarkers of diseases. This study focused on hydrogen peroxide, lipopolysaccharide (LPS), and lactic acid as salivary non-protein biomarkers for oxidative stress conditions of periodontitis. Electrochemical analysis of artificial saliva was done using Gamry with increasing hydrogen peroxide, bLPS, and lactic acid concentrations. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) were conducted. From EIS data, change in capacitance and CV plot area were calculated for each test condition. Hydrogen peroxide groups had a decrease in CV area and an increase in percentage change in capacitance, lipopolysaccharide groups had a decrease in CV area and a decrease in percentage change in capacitance, and lactic acid groups had an increase of CV area and an increase in percentage change in capacitance with increasing concentrations. These data showed a unique combination of electrochemical properties for the three biomarkers. Scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) employed to observe the change in the electrode surface and elemental composition data present on the sensor surface also showed a unique trend of elemental weight percentages. Machine learning models using hydrogen peroxide, LPS, and lactic acid electrochemical data were applied for the prediction of risk levels of periodontitis. The detection of hydrogen peroxide, LPS, and lactic acid by electrochemical biosensors indicates the potential to use these molecules as electrochemical biomarkers and use the data for ML-driven prediction tool for the periodontitis risk levels.

Neurofilament light chain but not glial fibrillary acidic protein is a potential biomarker of overt hepatic encephalopathy in patients with cirrhosis

Introduction and ObjectivesHepatic encephalopathy (HE) is a frequent complication of cirrhosis and may cause cerebral damage. Neurodegenerative diseases can induce the release of neuroproteins like neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in body fluids, including blood plasma. We investigated whether NfL and GFAP could serve as potential diagnostic plasma biomarkers for overt HE (oHE). Materials and MethodsWe included 85 patients from three prospective cohorts with different stages of liver disease and HE severity. The following patients were included: 1) 34 patients with primary sclerosing cholangitis (PSC) with compensated disease; 2) 17 patients with advanced liver disease without oHE before elective transjugular intrahepatic portosystemic shunt (TIPS) placement; 3) 17 intensive care unit (ICU) patients with oHE and 17 ICU patients without cirrhosis or oHE. Plasma NfL and GFAP were measured using single molecule assays. ResultsICU oHE patients had higher NfL concentrations compared to pre-TIPS patients or ICU controls (p < 0.05, each). Median GFAP concentrations were equal in the ICU oHE and pre-TIPS patients or ICU controls. Plasma NfL and GFAP concentrations correlated with Model for End-Stage Liver Disease (MELD) scores (R = 0.58 and R = 0.40, p < 0.001, each). ConclusionsPlasma NfL deserves further evaluation as potential diagnostic biomarker for oHE and correlates with the MELD score.

A structure‐based fluid biomarker for the differential diagnosis of early‐stage neurodegenerative diseases measured by the immuno‐infrared‐sensor (iRS)

AbstractBackgroundNeurodegenerative diseases like Alzheimer’s (AD) and Parkinson’s disease (PD) are accompanied by misfolding of the key proteins into beta‐sheet enriched structures resulting in high neurotoxicity in early phases. We have developed a diagnostic immuno‐infrared‐sensor (iRS) that monitors the secondary structure distribution of these key proteins (Abeta for AD, alpha‐synuclein for PD) as an early detectable biomarker before the clinical manifestation, which is shown exemplarily for AD.1 MethodThe iRS combines the secondary‐structure‐specific infrared spectroscopy in a flow system based attenuated total reflection (ATR) set‐up with methods of immuno‐detection by surface‐immobilized antibodies. The antibodies specifically capture disease‐related target proteins (e.g., Abeta) from complex media (cerebrospinal fluid or blood plasma) for measurements. The readout is the amide‐I band, which directly reflects the secondary structure distribution of the captured proteins in body fluids and thus, indicates the protein misfolding: The lower the amide‐I frequency, the higher the content of misfolded Abeta species in the sample present.2 ResultThe structure biomarker for Abeta has been validated in multiple independent clinical studies with strong correlation to CSF biomarkers and PET scans.1,3‐5 Especially, very early preclinical AD could be identified in symptom‐free individuals before plaque formation, up to 17 years before the diagnosis.6 ConclusionThe results demonstrate a highly specific and sensitive immune‐assay capable of tracking structural changes of Abeta before clinical manifestation of AD. In addition, alpha‐synuclein and TDP‐43 misfolding indicate PD and ALS in current discovery studies, providing a tool for differential diagnosis at early stages.

A-122 Fluid Type (STILL) Matters: An Analysis of Quality Control Material Suitability for Measuring Eleven Body Fluid Analytes in the Clinical Laboratory

Abstract Background Measuring the concentration of albumin, amylase, bilirubin, cholesterol, creatinine, glucose, lactate dehydrogenase (LDH), lipase, total protein(TP), triglycerides, and urea nitrogen(UN) in body fluids(BFs) provides important information to aid in clinical decision-making. The range of expected values of these analytes in BFs may not match serum, and the distribution by fluid type is not well described. Quality control (QC) materials are designed to reflect clinically relevant concentrations in blood. Hence, the measuring ranges for assays modified for BF testing vary in suitability. Laboratorians and manufacturers would benefit from understanding the overlap in BF and serum analyte concentrations. The aim of this study was to characterize the range of BF analyte concentrations compared to serum and assess the suitability of QC materials used on these assays. Methods A retrospective analysis was performed for the following analytes in BFs with reportable ranges(including maximum dilution factor): albumin = 0.2–12.0 g/dL(×2), amylase = 3–14 000 U/L(×100), bilirubin = 0.1–72.2 mg/dL(×2), cholesterol = 4–8000 mg/dL(×10), creatinine = 0.1–92.0 mg/dL(×4), glucose = 2–3375 mg/dL(×5), LDH = 10–9000 U/L(×10), lipase = 3–300 000 U/L(×1000), TP = 0.2–36.0 g/dL(×3), triglycerides = 4–8850 mg/dL(×10), and UN = 2–300 mg/dL(×3). Chemistry tests were run on a cobas® 6000 c501 (Roche Diagnostics,Indiana). Patient analyte concentration and fluid type results reported between 9/16/2019 and 1/27/2022 at all Mayo Clinic locations were extracted from an institutional database of electronic medical record data. Serum results were included for comparison. Descriptive statistical analyses (median and range) were performed with R (version 4.2.2)/R Studio(version 2022.12.0). QC materials for BF testing were purchased from Bio-Rad (Multilevel Qual, Levels 1 and 3; Hercules, CA, USA). Target concentrations are reported. Results Conclusion BF median (range) concentrations are similar or higher for bilirubin, creatinine, glucose, lipase, and UN. Serum QC material is likely appropriate for these assays in BFs. BF median(range) concentrations are lower for albumin, cholesterol, TP, and triglycerides suggesting that serum QC material may not be well suited for BFs. The need for extended dilutions may impact BF amylase and lipase.

A multi-task positive-unlabeled learning framework to predict secreted proteins in human body fluids

Body fluid biomarkers are very important, because they can be detected in a non-invasive or minimally invasive way. The discovery of secreted proteins in human body fluids is an essential step toward proteomic biomarker identification for human diseases. Recently, many computational methods have been proposed to predict secreted proteins and achieved some success. However, most of them are based on a manual negative dataset, which is usually biased and therefore limits the prediction performances. In this paper, we first propose a novel positive-unlabeled learning framework to predict secreted proteins in a single body fluid. The secreted protein discovery in a single body fluid is transformed into multiple binary classifications and solved via multi-task learning. Also, an effective convolutional neural network is employed to reduce the overfitting problem. After that, we then improve this framework to predict secreted proteins in multiple body fluids simultaneously. The improved framework adopts a globally shared network to further improve the prediction performances of all body fluids. The improved framework was trained and evaluated on datasets of 17 body fluids, and the average benchmarks of 17 body fluids achieved an accuracy of 89.48%, F1 score of 56.17%, and PRAUC of 58.93%. The comparative results demonstrate that the improved framework performs much better than other state-of-the-art methods in secreted protein discovery.

Plasma Exosome Analysis for Protein Mutation Identification Using a Combination of Raman Spectroscopy and Deep Learning.

Protein mutation detection using liquid biopsy can be simply performed periodically, making it easy to detect the occurrence of newly emerging mutations rapidly. However, it has low diagnostic accuracy since there are more normal proteins than mutated proteins in body fluids. To increase the diagnostic accuracy, we analyzed plasma exosomes using nanoplasmonic spectra and deep learning. Exosomes, a promising biomarker, are abundant in plasma and stably carry intact proteins originating from mother cells. However, the mutated exosomal proteins cannot be detected sensitively because of the subtle changes in their structure. Therefore, we obtained Raman spectra that provide molecular information about structural changes in mutated proteins. To extract the unique features of the protein from complex Raman spectra, we developed a deep-learning classification algorithm with two deep-learning models. Consequently, controls with wild-type proteins and patients with mutated proteins were classified with high accuracy. As a proof of concept, we discriminated the lung cancer patients with mutations in the epidermal growth factor receptor (EGFR), L858R, E19del, L858R + T790M, and E19del + T790M, from controls with an accuracy of 0.93. Moreover, the protein mutation status of the patients with primary (E19del, L858R) and secondary (+T790M) mutations was clearly monitored. Overall, our technique is expected to be applied as a novel method for companion diagnostic and treatment monitoring.

Urine‐based liquid biopsy in bladder cancer: Opportunities and challenges

AbstractBladder cancer (BLCA) is a most common urological tumours with high rate of recurrence, which needs long‐term of follow‐up. To date, diagnosis and surveillance of BLCA still rely on cystoscopy, an invasive and expensive method that increases the difficulty for routine follow‐up. Therefore, exploring new biomarkers or tests is an effective way to improve the current clinical management of BLCA. Recent years, liquid biopsy has received increasing attention, especially for its great potential for clinical application in the non‐invasive detection of tumours. In addition, liquid biopsy involves a wide range of biomarkers, including DNA, RNA, proteins, extracellular vesicles and metabolites in blood, urine or other body fluids. For BLCA, urine is a most ideal body fluid to achieve non‐invasive diagnosis and surveillance. Here, we address recent developments of urine‐based biomarkers or tests for clinical diagnostic challenges in BLCA, such as early detection, minimal residual, recurrence monitoring and therapeutic response. Meanwhile, the many challenges of urine biomarkers that need to be overcome are also discussed.

Rapid Detection of SARS-CoV-2 Spike RBD Protein in Body Fluid: Based on Special Calcium Ion-Mediated Gold Nanoparticles Modified by Bromide Ions.

The receptor-binding domain of the SARS-CoV-2 spike mediates the key to binding the virus to the host receptor, but capturing the molecular signal of this spike RBD remains a formidable challenge. Here, we report a new surface-enhanced Raman spectroscopy (SERS) approach, which used gold nanoparticles prepared by low-speed constant-temperature centrifugation by bromine and calcium ions in two cleaning steps as the enhanced substrate to rapidly and accurately detect spike RBD large protein molecules in body fluids. The detection signal was extremely stable, and the orientation of the spike RBD on the enhanced substrate surface was also determined. This approach was specific in distinguishing different SARS-CoV-2 variants of spike RBD, including Delta, Beta, Gamma, and Omicron. Additionally, the enhanced substrate can identify biologically active or inactive spike RBD. This two-step cleaning enhanced substrate opens up opportunities not only for early diagnostics of SARS-CoV-2 virus but also for developing targeted drugs against viruses.

Development of Tier 2 LC-MRM-MS protein quantification methods for liquid biopsies

In the pursuit of personalized diagnostics and tailored treatments, quantitative protein tests contribute to a more precise definition of health and disease. The development of new quantitative protein tests should be driven by an unmet clinical need and performed in a collaborative effort that involves all stakeholders. With regard to the analytical part, mass spectrometry (MS)-based platforms are an excellent tool for quantification of specific proteins in body fluids, for example focused on cancer. The obtained readouts have great potential in determining tumor aggressiveness to facilitate treatment decisions, and can furthermore be used to monitor patient response. Internationally standardized TNM classifications of malignant tumors are beneficial for diagnosis, however treatment outcome and survival of cancer patients is poorly predicted. To this end, the importance of the tumor microenvironment has endorsed the introduction of the tumor-stroma ratio as a prognostic parameter in solid primary tumor types. Currently, the stromal content of tumor tissues is determined via routine diagnostic pathology slides. With the development of liquid chromatography (LC)-MS methods we aim at quantification of tumor-stroma specific proteins in body fluids. In this mini-review the analytical aspect of this developmental trajectory is further detailed.

Surface modification of silicate, borosilicate, and phosphate bioactive glasses to improve/control protein adsorption: PART II

Bioactive glasses (BGs) are characterized by high biocompatibility and bioactivity and are particularly promising for bone tissue regeneration. Once implanted, the BGs interact with the environment and adsorb chemical moieties and biomolecules. Proteins in body fluids are critical for the success of implants, because the adsorption of specific proteins can either promote or inhibit the adhesion of surrounding tissue or other factors such as bacteria. Controlling protein adsorption by tailoring the surface properties of implanted biomaterials is fundamental. This can determine the fate of the implant. In the current study, four BG compositions (two silicates, one borosilicate, and one phosphate glass) and three model proteins (fibronectin, chimeric avidin, and streptavidin) were considered. Each BG was surface pretreated, and the adsorption of fluorescently labeled fibronectin, chimeric avidin, or streptavidin was monitored. Untreated surfaces were used as controls. The amount and spatial distribution of each protein were estimated by confocal microscopy in fluorescence modality, followed by protein clustering analysis. Although streptavidin was not adsorbed efficiently on any of the considered substrates, BGs were successfully coated with fibronectin and chimeric avidin. Both proteins showed different affinities and surface distributions as functions of the implemented pretreatment on each substrate.

Effects of elevated temperature on 8-OHdG expression in the American oyster (Crassostrea virginica): Induction of oxidative stress biomarkers, cellular apoptosis, DNA damage and γH2AX signaling pathways

Global temperature is increasing due to anthropogenic activities and the effects of elevated temperature on DNA lesions are not well documented in marine organisms. The American oyster (Crassostrea virginica, an edible and commercially important marine mollusk) is an ideal shellfish species to study oxidative DNA lesions during heat stress. In this study, we examined the effects of elevated temperatures (24, 28, and 32 °C for one-week exposure) on heat shock protein-70 (HSP70, a biomarker of heat stress), 8‑hydroxy-2′-deoxyguanosine (8-OHdG, a biomarker of pro-mutagenic DNA lesion), double-stranded DNA (dsDNA), γ-histone family member X (γH2AX, a molecular biomarker of DNA damage), caspase-3 (CAS-3, a key enzyme of apoptotic pathway) and Bcl-2-associated X (BAX, an apoptosis regulator) protein and/or mRNA expressions in the gills of American oysters. Immunohistochemical and qRT-PCR results showed that HSP70, 8-OHdG, dsDNA, and γH2AX expressions in gills were significantly increased at high temperatures (28 and 32 °C) compared with control (24°C). In situ TUNEL analysis showed that the apoptotic cells in gill tissues were increased in heat-exposed oysters. Interestingly, the enhanced apoptotic cells were associated with increased CAS-3 and BAX mRNA and/or protein expressions, along with 8-OHdG levels in gills after heat exposure. Moreover, the extrapallial (EP) fluid (i.e., extracellular body fluid) protein concentrations were lower; however, the EP glucose levels were higher in heat-exposed oysters. Taken together, these results suggest that heat shock-driven oxidative stress alters extracellular body fluid conditions and induces cellular apoptosis and DNA damage, which may lead to increased 8-OHdG levels in cells/tissues in oysters.

Redox State of Human Serum Albumin in Multiple Sclerosis: A Pilot Study

Like in many other pathologies, oxidative stress is involved in the development of neurodegenerative disorders. Human serum albumin (HSA) is the main protein in different body fluids including cerebrospinal fluid (CSF). By its redox state in terms of cysteine-34, albumin serves as marker for oxidative burden. We aimed to evaluate the redox state of HSA in patients with multiple sclerosis in serum and CSF in comparison to controls to identify possible correlations with disease activity and severity. Samples were stored at -70 °C until analysis by HPLC for the determination of albumin redox state in terms of the fractions of human mercaptalbumin (HMA), human nonmercaptalbumin1 (HNA1), and human nonmercaptalbumin2 (HNA2). Albumin in CSF showed significantly higher fractions of the reduced form HMA and decreased HNA1 and HNA2. There was no difference between albumin redox states in serum of patients and controls. In CSF of patients HNA2 showed a trend to higher fractions compared to controls. Albumin redox state in serum was associated with physical disability in remission while albumin redox state in CSF was related to disease activity. Thus, albumin redox state in serum and CSF of patients in relation to disease condition merits further investigation.

Proteomics in Inherited Metabolic Disorders.

Inherited metabolic disorders (IMD) are rare medical conditions caused by genetic defects that interfere with the body's metabolism. The clinical phenotype is highly variable and can present at any age, although it more often manifests in childhood. The number of treatable IMDs has increased in recent years, making early diagnosis and a better understanding of the natural history of the disease more important than ever. In this review, we discuss the main challenges faced in applying proteomics to the study of IMDs, and the key advances achieved in this field using tandem mass spectrometry (MS/MS). This technology enables the analysis of large numbers of proteins in different body fluids (serum, plasma, urine, saliva, tears) with a single analysis of each sample, and can even be applied to dried samples. MS/MS has thus emerged as the tool of choice for proteome characterization and has provided new insights into many diseases and biological systems. In the last 10 years, sequential window acquisition of all theoretical fragmentation spectra mass spectrometry (SWATH-MS) has emerged as an accurate, high-resolution technique for the identification and quantification of proteins differentially expressed between healthy controls and IMD patients. Proteomics is a particularly promising approach to help obtain more information on rare genetic diseases, including identification of biomarkers to aid early diagnosis and better understanding of the underlying pathophysiology to guide the development of new therapies. Here, we summarize new and emerging proteomic technologies and discuss current uses and limitations of this approach to identify and quantify proteins. Moreover, we describe the use of proteomics to identify the mechanisms regulating complex IMD phenotypes; an area of research essential to better understand these rare disorders and many other human diseases.

Low Level of Advanced Glycation End Products in Serum of Patients with Allergic Rhinitis and Chronic Epstein-Barr Virus Infection at Different Stages of Virus Persistence.

Advanced glycation end products (AGEs) are formed in a nonenzymatic reaction of the reducing sugars with amino groups of proteins, lipids, and nucleic acids of different tissues and body fluids. A relatively small number of studies have been conducted on the role of AGEs in allergic inflammation. In this study, patients with allergic rhinitis (AR) were examined for the presence of Epstein-Barr virus and the content of fluorescent and nonfluorescent AGEs. We have also determined the level of a unique epitope (AGE10) which was recently identified in human serum using monoclonal antibodies against synthetic melibiose-derived AGE (MAGE). The levels of AGE10 determined with an immunoenzymatic method revealed no significant difference in the patients' blood with intermittent AR and chronic EBV persistence in the active and latent phases. It has been shown that there is a statistically significantly smaller amount of AGEs and pentosidine in groups of patients, both with and without viremia, than in healthy subjects. In turn, higher levels of immune complexes than of AGE10 were detected in the groups of patients, in contrast to the control group, which had lower levels of complexes than AGE10 concentration. In patients with active infection, there is even more complexes than of noncomplexed AGE10 antigen. The lower level of AGE in allergic rhinitis patient sera may also be due, besides complexes, to allergic inflammation continuously activating the cells, which effectively remove glycation products from the body.