Search

Hundreds of compounds are detected during untargeted lipidomics analysis. The potential efficacy of lipids as disease markers makes it important to select the species with the most discriminative potential. Datasets based on a selected class of lipids allow the development of a high-quality diagnostic model using orthogonal projection on latent structure. The combination of selection of lipids by variable importance in projection and by Akaike information criteria makes it possible to build a reliable diagnostic model based on logistic regression., (© 2021 John Wiley & Sons, Ltd.)

The detection of viral RNA by polymerase chain reaction (PCR) is currently the main diagnostic tool for COVID-19 ( Eurosurveillance 2019, 25 (3), 1). The PCR-based test, however, shows limited sensitivity, especially in the early and late stages of disease development ( Nature 2020, 581, 465-469; J. Formosan Med. Assoc. 2020, 119 (6) 1123), and is relatively time-consuming. Fast and reliable complementary methods for detecting the viral infection would be of help in the current pandemic conditions. Mass spectrometry is one of such possibilities. We have developed a mass-spectrometry-based method for the detection of the SARS CoV-2 virus in nasopharynx epithelial swabs based on the detection of the viral nucleocapsid N protein. Our approach shows confident identification of the N protein in patient samples, even those with the lowest viral loads, and a much simpler preparation procedure. Our main protocol consists of virus inactivation by heating and the addition of isopropanol and tryptic digestion of the proteins sedimented from the swabs followed by MS analysis. A set of unique peptides, produced as a result of proteolysis of the nucleocapsid phosphoprotein of SARS-CoV-2, is detected. The obtained results can further be used to create fast parallel mass-spectrometric approaches for the detection of the virus in the nasopharyngeal mucosa, saliva, sputum and other physiological fluids.

The objectives of this study were to identify molecular features characteristic to arctic DOM from the Kolyma River basin and to elucidate structural imprints induced by a choice of the sorption technique. To achieve this goal, DOM was isolated from the Kolyma River basin with a use of three nonionic sorbents: Amberlite XAD-8 resin, PPL- and C18 - SPE cartridges, and one anion exchanging resin-diethylaminoethyl (DEAE) -cellulose. The structural studies were conducted with a use of electrospray ionization Fourier Transform Ion Cyclotron Resonance (ESI FT-ICR) mass spectrometry and liquid state (1)H NMR spectroscopy. The DOM isolates obtained with a use of PPL and C18 cartridges were characterized with higher content of aliphatic compounds as compared to XAD-8 and DEAE-isolates. In total, for all arctic DOM isolates we observed predominance of hydrogen saturated compounds with high H/C values of identified formulas from FT-ICR MS data. (1)H NMR spectroscopy studies have confirmed this trend and revealed high contribution of alkyl-chain protons into the spectral density of the arctic DOM reaching 43% for PPL isolates.

Oxidative and nitrosative stress leaves footprints in the plant chloroplast in the form of oxidatively modified proteins. Using a mass spectrometric approach, we identified 126 tyrosine and 12 tryptophan nitration sites in 164 nitrated proteolytic peptides, mainly from photosystem I (PSI), photosystem II (PSII), cytochrome b(6) /f and ATP-synthase complexes and 140 oxidation products of tyrosine, tryptophan, proline, phenylalanine and histidine residues. While a high number of nitration sites were found in proteins from four photosynthetic complexes indicating that the nitration belongs to one of the prominent posttranslational protein modifications in photosynthetic apparatus, amino acid oxidation products were determined mostly in PSII and to a lower extent in PSI. Exposure of plants to light stress resulted in an increased level of tyrosine and tryptophan nitration and tryptophan oxidation in proteins of PSII reaction center and the oxygen-evolving complex, as compared to low light conditions. In contrast, the level of nitration and oxidation of these amino acid residues strongly decreased for all light-harvesting proteins of PSII under the same conditions. Based on these data, we propose that oxidative modifications of proteins by reactive oxygen and nitrogen species might represent an important regulatory mechanism of protein turnover under light stress conditions, especially for PSII and its antenna proteins., (Copyright © 2010 John Wiley & Sons, Ltd.)

Background/Objectives: The development of blood tests for the early detection of individual predisposition to socially significant diseases remains a pressing issue. Methods: In this pilot study, multiple reaction monitoring mass spectrometry (MRM-MS) with a BAK-270 assay was applied for protein concentrations analysis in blood plasma from 21 healthy volunteers of the European cohort. Results: The levels of 138 plasma proteins were reliably and precisely quantified in no less than 50% of samples. The quantified proteins included 66 FDA-approved markers of cardiovascular diseases (CVD), and other potential biomarkers of pathologies such as cancer, diabetes mellitus, and Alzheimer's disease. The analysis of individual variations of the plasma proteins revealed significant differences between the male (11) and female (10) groups. In total, fifteen proteins had a significantly different concentration in plasma; this included four proteins that exhibited changes greater than ±1.5-fold, three proteins (RBP4, APCS, and TTR) with higher levels in males, and one (SHBG) elevated in females. The obtained results demonstrated considerable agreement with the data collected from 20 samples of a North American cohort, which were analyzed with the similar MRM assay. The most significant differences between the cohorts of the two continents were observed in the level of 42 plasma proteins (including 24 FDA markers), of which 17 proteins showed a ≥1.5-fold change, and included proteins increased in North Americans (APOB, CRTAC1, C1QB, C1QC, C9, CRP, HP, IGHG1, IGKV4-1, SERPING1, RBP4, and AZGP1), as well as those elevated in Europeans (APOF, CD5L, HBG2, SELPLG, and TNA). Conclusions: The results suggest a different contribution of specific (patho)physiological pathways (e.g., immune system and blood coagulation) to the development of socially significant diseases in Europeans and North Americans, and they should be taken into account when refining diagnostic panels. [ABSTRACT FROM AUTHOR]

Intrauterine growth restriction (IUGR) remains a significant concern in modern obstetrics, linked to high neonatal health problems and even death, as well as childhood disability, affecting adult quality of life. The role of maternal and fetus adaptation during adverse pregnancy is still not completely understood. This study aimed to investigate the disturbance in biological processes associated with isolated IUGR via blood plasma proteomics. The levels of 125 maternal plasma proteins were quantified by liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with corresponding stable isotope-labeled peptide standards (SIS). Thirteen potential markers of IUGR (Gelsolin, Alpha-2-macroglobulin, Apolipoprotein A-IV, Apolipoprotein B-100, Apolipoprotein(a), Adiponectin, Complement C5, Apolipoprotein D, Alpha-1B-glycoprotein, Serum albumin, Fibronectin, Glutathione peroxidase 3, Lipopolysaccharide-binding protein) were found to be inter-connected in a protein–protein network. These proteins are involved in plasma lipoprotein assembly, remodeling, and clearance; lipid metabolism, especially cholesterol and phospholipids; hemostasis, including platelet degranulation; and immune system regulation. Additionally, 18 proteins were specific to a particular type of IUGR (early or late). Distinct patterns in the coagulation and fibrinolysis systems were observed between isolated early- and late-onset IUGR. Our findings highlight the complex interplay of immune and coagulation factors in IUGR and the differences between early- and late-onset IUGR and other placenta-related conditions like PE. Understanding these mechanisms is crucial for developing targeted interventions and improving outcomes for pregnancies affected by IUGR. [ABSTRACT FROM AUTHOR]

Metastasis is a serious and often life-threatening condition, representing the leading cause of death among women with breast cancer (BC). Although the current clinical classification of BC is well-established, the addition of minimally invasive laboratory tests based on peripheral blood biomarkers that reflect pathological changes in the body is of utmost importance. In the current study, the serum proteome and lipidome profiles for 50 BC patients with (25) and without (25) metastasis were studied. Targeted proteomic analysis for concertation measurements of 125 proteins in the serum was performed via liquid chromatography–multiple reaction monitoring mass spectrometry (LC–MRM MS) using the BAK 125 kit (MRM Proteomics Inc., Victoria, BC, Canada). Untargeted label-free lipidomic analysis was performed using liquid chromatography coupled to tandem mass-spectrometry (LC–MS/MS), in both positive and negative ion modes. Finally, 87 serum proteins and 295 lipids were quantified and showed a moderate correlation with tumor grade, histological and biological subtypes, and the number of lymph node metastases. Two highly accurate classifiers that enabled distinguishing between metastatic and non-metastatic BC were developed based on proteomic (accuracy 90%) and lipidomic (accuracy 80%) features. The best classifier (91% sensitivity, 89% specificity, AUC = 0.92) for BC metastasis diagnostics was based on logistic regression and the serum levels of 11 proteins: alpha-2-macroglobulin, coagulation factor XII, adiponectin, leucine-rich alpha-2-glycoprotein, alpha-2-HS-glycoprotein, Ig mu chain C region, apolipoprotein C-IV, carbonic anhydrase 1, apolipoprotein A-II, apolipoprotein C-II and alpha-1-acid glycoprotein 1. [ABSTRACT FROM AUTHOR]

Glomerulopathies with nephrotic syndrome that are resistant to therapy often progress to end-stage chronic kidney disease (CKD) and require timely and accurate diagnosis. Targeted quantitative urine proteome analysis by mass spectrometry (MS) with multiple-reaction monitoring (MRM) is a promising tool for early CKD diagnostics that could replace the invasive biopsy procedure. However, there are few studies regarding the development of highly multiplexed MRM assays for urine proteome analysis, and the two MRM assays for urine proteomics described so far demonstrate very low consistency. Thus, the further development of targeted urine proteome assays for CKD is actual task. Herein, a BAK270 MRM assay previously validated for blood plasma protein analysis was adapted for urine-targeted proteomics. Because proteinuria associated with renal impairment is usually associated with an increased diversity of plasma proteins being present in urine, the use of this panel was appropriate. Another advantage of the BAK270 MRM assay is that it includes 35 potential CKD markers described previously. Targeted LC-MRM MS analysis was performed for 69 urine samples from 46 CKD patients and 23 healthy controls, revealing 138 proteins that were found in ≥2/3 of the samples from at least one of the groups. The results obtained confirm 31 previously proposed CKD markers. Combination of MRM analysis with machine learning for data processing was performed. As a result, a highly accurate classifier was developed (AUC = 0.99) that enables distinguishing between mild and severe glomerulopathies based on the assessment of only three urine proteins (GPX3, PLMN, and A1AT or SHBG). [ABSTRACT FROM AUTHOR]

Primary focal segmental glomerulosclerosis (FSGS), along with minimal change disease (MCD), are diseases with primary podocyte damage that are clinically manifested by the nephrotic syndrome. The pathogenesis of these podocytopathies is still unknown, and therefore, the search for biomarkers of these diseases is ongoing. Our aim was to determine of the proteomic profile of urine from patients with FSGS and MCD. Patients with a confirmed diagnosis of FSGS (n = 30) and MCD (n = 9) were recruited for the study. For a comprehensive assessment of the severity of FSGS a special index was introduced, which was calculated as follows: the first score was assigned depending on the level of eGFR, the second score—depending on the proteinuria level, the third score—resistance to steroid therapy. Patients with the sum of these scores of less than 3 were included in group 1, with 3 or more—in group 2. The urinary proteome was analyzed using liquid chromatography/mass spectrometry. The proteome profiles of patients with severe progressive FSGS from group 2, mild FSGS from group 1 and MCD were compared. Results of the label free analysis were validated using targeted LC-MS based on multiple reaction monitoring (MRM) with stable isotope labelled peptide standards (SIS) available for 47 of the 76 proteins identified as differentiating between at least one pair of groups. Quantitative MRM SIS validation measurements for these 47 proteins revealed 22 proteins with significant differences between at least one of the two group pairs and 14 proteins were validated for both comparisons. In addition, all of the 22 proteins validated by MRM SIS analysis showed the same direction of change as at the discovery stage with label-free LC-MS analysis, i.e., up or down regulation in MCD and FSGS1 against FSGS2. Patients from the FSGS group 2 showed a significantly different profile from both FSGS group 1 and MCD. Among the 47 significantly differentiating proteins, the most significant were apolipoprotein A-IV, hemopexin, vitronectin, gelsolin, components of the complement system (C4b, factors B and I), retinol- and vitamin D-binding proteins. Patients with mild form of FSGS and MCD showed lower levels of Cystatin C, gelsolin and complement factor I. [ABSTRACT FROM AUTHOR]

Early recognition of the risk of Alzheimer's disease (AD) onset is a global challenge that requires the development of reliable and affordable screening methods for wide-scale application. Proteomic studies of blood plasma are of particular relevance; however, the currently proposed differentiating markers are poorly consistent. The targeted quantitative multiple reaction monitoring (MRM) assay of the reported candidate biomarkers (CBs) can contribute to the creation of a consistent marker panel. An MRM-MS analysis of 149 nondepleted EDTA–plasma samples (MHRC, Russia) of patients with AD (n = 47), mild cognitive impairment (MCI, n = 36), vascular dementia (n = 8), frontotemporal dementia (n = 15), and an elderly control group (n = 43) was performed using the BAK 125 kit (MRM Proteomics Inc., Canada). Statistical analysis revealed a significant decrease in the levels of afamin, apolipoprotein E, biotinidase, and serum paraoxonase/arylesterase 1 associated with AD. Different training algorithms for machine learning were performed to identify the protein panels and build corresponding classifiers for the AD prognosis. Machine learning revealed 31 proteins that are important for AD differentiation and mostly include reported earlier CBs. The best-performing classifiers reached 80% accuracy, 79.4% sensitivity and 83.6% specificity and were able to assess the risk of developing AD over the next 3 years for patients with MCI. Overall, this study demonstrates the high potential of the MRM approach combined with machine learning to confirm the significance of previously identified CBs and to propose consistent protein marker panels. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has exposed a number of key challenges that need to be urgently addressed. Mass spectrometric studies of blood plasma proteomics provide a deep understanding of the relationship between the severe course of infection and activation of specific pathophysiological pathways. Analysis of plasma proteins in whole blood may also be relevant for the pandemic as it requires minimal sample preparation.The frozen whole blood samples were used to analyze 203 plasma proteins using multiple reaction monitoring (MRM) mass spectrometry and stable isotope-labeled peptide standards (SIS). A total of 131 samples (FRCC, Russia) from patients with mild (n=41), moderate (n=39) and severe (n=19) COVID-19 infection and healthy controls (n=32) were analyzed.Levels of 94 proteins were quantified and compared. Significant differences between all of the groups were revealed for 44 proteins. Changes in the levels of 61 reproducible COVID-19 markers (SERPINA3, SERPING1, ORM1, HRG, LBP, APOA1, AHSG, AFM, ITIH2, etc.) were consistent with studies performed with serum/plasma samples. The best-performing classifier built with 10 proteins achieved the best combination of ROC-AUC (0.97–0.98) and accuracy (0.90–0.93) metrics and distinguished patients from controls, as well as patients by severity.Here, for the first time, frozen whole blood samples were used for proteomic analysis and assessment of the status of patients with COVID-19. The results obtained with frozen whole blood samples are consistent with those from plasma and serum. [ABSTRACT FROM AUTHOR]

Lung cancer remains the most prevalent cause of cancer mortality worldwide mainly due to insufficient availability of early screening methods for wide-scale application. Exhaled breath condensate (EBC) is currently considered as one of the promising targets for early screening and is particularly attractive due to its absolutely noninvasive collection and possibility for long-term frozen storage. EBC proteome analysis can provide valuable information about the (patho)physiological changes in the respiratory system and may help to identify in time a high risk of lung cancer. Mass spectrometry (MS) profiling of EBC proteome seems to have no alternative in obtaining the most extensive data and characteristic marker panels for screening. This special report summarizes the data of several proteomic studies of EBC in normal and lung cancer (from 2012 to 2021, PubMed), focuses on the possible reasons for the significant discrepancy in the results, and discusses some aspects for special attention in further studies. The significant discrepancy in the results of various studies primarily highlights the need to create standardized protocols for the collection and preparation of EBC for proteomic analysis. The application of quantitative and targeted LC-MS/MS based approaches seems to be the most promising in further EBC proteomic studies. [ABSTRACT FROM AUTHOR]

Cervicovaginal fluid (CVF) is a valuable source of clinical information about the female reproductive tract in both nonpregnant and pregnant women. The aim of this study is to specify the CVF proteome at different stages of cervix neoplastic transformation by label‐free quantitation approach based on liquid chromatography tandem mass spectrometry (LC‐MS/MS) method. The proteome composition of CVF from 40 women of reproductive age with human papillomavirus (HPV)‐associated cervix neoplastic transformation (low‐grade squamous intraepithelial lesion [LSIL], high‐grade squamous intraepithelial lesion [HSIL], and CANCER) was investigated. Hierarchical clustering and principal component analysis (PCA) of the proteomic data obtained by a label‐free quantitation approach show the distribution of the sample set between four major clusters (no intraepithelial lesion or malignancy [NILM], LSIL, HSIL and CANCER) depending on the form of cervical lesion. Multisample ANOVA with subsequent Welch's t test resulted in 117 that changed significantly across the four clinical stages, including 27 proteins significantly changed in cervical cancer. Some of them were indicated as promising biomarkers previously (ACTN4, VTN, ANXA1, CAP1, ANXA2, and MUC5B). CVF proteomic data from the discovery stage were analyzed by the partial least squares‐discriminant analysis (PLS‐DA) method to build a statistical model, allowing to differentiate severe dysplasia (HSIL and CANCER) from the mild/normal stage (NILM and LSIL), and receiver operating characteristic (ROC) area under the curve (AUC) were obtained on an independent set of 33 samples. The sensitivity of the model was 77%, and the specificity was 94%; AUC was equal to 0.87. CVF proteome proved to be reflect the stage of cervical epithelium neoplastic process. [ABSTRACT FROM AUTHOR]

A serious problem during intensive care and nursing of premature infants is the invasiveness of many examination methods. Urine is an excellent source of potential biomarkers due to the safety of the collection procedure. The purpose of this study was to determine the features specific for the urine proteome of preterm newborns and their changes under respiratory pathologies of infectious and non-infectious origin. The urine proteome of 37 preterm neonates with respiratory diseases and 10 full-term newborns as a control group were investigated using the LC-MS/MS method. The total number of identified proteins and unique peptides was 813 and 3672 respectively. In order to further specify the defined infant-specific dataset these proteins were compared with urine proteome of healthy adults (11 men and 11 pregnant women) resulting in 94 proteins found only in infants. Pairwise analysis performed for label-free proteomic data revealed 36 proteins which reliably distinguished newborns with respiratory disorders of infectious genesis from those with non-infectious pathologies, including: proteins involved in cell adhesion (CDH-2,-5,-11, NCAM1, TRY1, DSG2), metabolism (LAMP1, AGRN, TPP1, GPX3, APOD, CUBN, IDH1), regulation of enzymatic activity (SERPINA4, VASN, GAPDH), inflammatory and stress response (CD55, CD 93, NGAL, HP, TNFR, LCN2, AGT, S100P, SERPINA1/C1/B1/F1). [ABSTRACT FROM AUTHOR]

Urinary proteins serve as indicators of various conditions in human normal physiology and disease pathology. Using mass spectrometry proteome analysis, the permanent constituent of the urine was examined in the Mars-500 experiment (520 days isolation of healthy volunteers in a terrestrial complex with an autonomous life support system). Seven permanent proteins with predominant distribution in the liver and blood plasma as well as extracellular localization were identified. Analysis of the overrepresentation of the molecular functions and biological processes based on Gene Ontology revealed that the functional association among these proteins was low. The results showed that the identified proteins may be independent markers of the various conditions and processes in healthy humans and that they can be used as standards in determination of the concentration of other proteins in the urine. [ABSTRACT FROM AUTHOR]

RATIONALE Peptides and proteins are among the most important components of living systems. Different attempts have been made to experimentally model the formation of peptides from amino acid monomers in investigation of the origin of life. Detailed characterization of peptides formed under various conditions in such reactions is very important for understanding processes of abiogenic peptide formation. METHODS We used liquid chromatography coupled with tandem mass spectrometry (MS/MS) for an accurate study of homo-peptides formed in a model reaction: glutamic acid oligomerization catalyzed by 1,1'-carbonyldiimidazole in aqueous solution with 1 M of sodium or potassium chloride and without any salts. We used de novo sequencing software for peptide identification. In addition we propose an approach that uses more spectral information for de novo sequencing then standard methods. RESULTS Peptides up to 9 amino acids long were found in the experiments with KCl, while in experiments with NaCl and without salts only peptides of up to 7 amino acids were detected. Due to high salt concentrations in samples a high number of singly charged peptide ions with up to 4 substitutions of hydrogen atoms by sodium or potassium atoms were observed. De novo sequencing software provided correct identifications even for peptide ions with substitutions. CONCLUSIONS Multiple substitutions of hydrogen by alkali metal atoms in peptide ions strongly change their fragmentation patterns. Proposed approach for de novo sequencing was found very effective, even for ions with substitutions. So, it may be useful in more complicated cases like sequencing abiogenic peptides consisting of different amino acids. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) mass spectrum of natural organic matter (NOM) contains several thousand peaks with dozens of molecules matching the same nominal mass. Such a complexity poses a significant challenge for automatic data interpretation, in which the most difficult task is molecular formula assignment, especially in the case of heavy and/or multielement ions. In this study, a new universal algorithm for automatic treatment of FTICR mass spectra of NOM and humic substances based on total mass difference statistics (TMDS) has been developed and implemented. The algorithm enables a blind search for unknown building blocks (instead of a priori known Ones) by revealing repetitive patterns present in spectra. In this respect, it differs from all previously developed approaches. This algorithm was implemented in designing FIRAN-software for fully automated analysis of mass data with high peak density. The specific feature of FIRAN is its ability to assign formulas to heavy and/or multielement molecules using "virtual elements" approach. To verify the approach, it was used for processing mass spectra of sodium polystyrene sulfonate (PSS, Mw = 2200 Da) and polymethacrylate (PMA, Mw = 3290 Da) which produce heavy multielement and multiply- charged ions. Application of ThDS identified unambiguously monomers present in the polymers consistent with their structure: C8H7SO3Na for PSS and C4H8O2 for PMA. It also allowed unambiguous formula assignment to all multiply-charged peaks including the heaviest peak in PMA spectrum at mass 4025.6625 with charge state 6- (mass bias -0.33 ppm). Application of the TMDS-algorithm to processing data on the Suwannee River FA has proven its unique capacities in analysis of spectra with high peak density: it has not only identified the known small building blocks in the structure of FA such as CH2, H2, C2H2O, O but the heavier unit at 154.027 amu. The latter was identified for the first time and assigned a formula C7H6O4 consistent with the structure of dihydroxyl-benzoic acids. The presence of these compounds in the structure of FA has so far been numerically suggested but never proven directly. It was concluded that application of the TMDS-algorithm opens new horizons in unfolding molecular complexity of NOM and other natural products. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the leading cause of dementia among the elderly. Neuropathologically, AD is characterized by the deposition of a 39- to 42-amino acid long β-amyloid (Aβ) peptide in the form of senile plaques. Several post-translational modifications (PTMs) in the N-terminal domain have been shown to increase the aggregation and cytotoxicity of Aβ, and specific Aβ proteoforms (e.g., Aβ with isomerized D7 (isoD7-Aβ)) are abundant in the senile plaques of AD patients. Animal models are indispensable tools for the study of disease pathogenesis, as well as preclinical testing. In the presented work, the accumulation dynamics of Aβ proteoforms in the brain of one of the most widely used amyloid-based mouse models (the 5xFAD line) was monitored. Mass spectrometry (MS) approaches, based on ion mobility separation and the characteristic fragment ion formation, were applied. The results indicated a gradual increase in the Aβ fraction of isoD7-Aβ, starting from approximately 8% at 7 months to approximately 30% by 23 months of age. Other specific PTMs, in particular, pyroglutamylation, deamidation, and oxidation, as well as phosphorylation, were also monitored. The results for mice of different ages demonstrated that the accumulation of Aβ proteoforms correlate with the formation of Aβ deposits. Although the mouse model cannot be a complete analogue of the processes occurring in the human brain in AD, and several of the observed parameters differ significantly from human values supposedly due to the limited lifespan of the model animals, this dynamic study provides evidence on at least one of the possible mechanisms that can trigger amyloidosis in AD, i.e., the hypothesis on the relationship between the accumulation of isoD7-Aβ and the progression of AD-like pathology. [ABSTRACT FROM AUTHOR]

Ferritins comprise a conservative family of proteins found in all species and play an essential role in resistance to redox stress, immune response, and cell differentiation. Sponges (Porifera) are the oldest Metazoa that show unique plasticity and regenerative potential. Here, we characterize the ferritins of two cold-water sponges using proteomics, spectral microscopy, and bioinformatic analysis. The recently duplicated conservative HdF1a/b and atypical HdF2 genes were found in the Halisarca dujardini genome. Multiple related transcripts of HpF1 were identified in the Halichondria panicea transcriptome. Expression of HdF1a/b was much higher than that of HdF2 in all annual seasons and regulated differently during the sponge dissociation/reaggregation. The presence of the MRE and HRE motifs in the HdF1 and HdF2 promotor regions and the IRE motif in mRNAs of HdF1 and HpF indicates that sponge ferritins expression depends on the cellular iron and oxygen levels. The gel electrophoresis combined with specific staining and mass spectrometry confirmed the presence of ferric ions and ferritins in multi-subunit complexes. The 3D modeling predicts the iron-binding capacity of HdF1 and HpF1 at the ferroxidase center and the absence of iron-binding in atypical HdF2. Interestingly, atypical ferritins lacking iron-binding capacity were found in genomes of many invertebrate species. Their function deserves further research. [ABSTRACT FROM AUTHOR]

Preeclampsia (PE) is a severe pregnancy complication, which may be considered as a systemic response in the second half of pregnancy to physiological failures in the first trimester, and can lead to very serious consequences for the health of the mother and fetus. Since PE is often associated with proteinuria, urine proteomic assays may represent a powerful tool for timely diagnostics and appropriate management. High resolution mass spectrometry was applied for peptidome analysis of 127 urine samples of pregnant women with various hypertensive complications: normotensive controls (n = 17), chronic hypertension (n = 16), gestational hypertension (n = 15), mild PE (n = 25), severe PE (n = 25), and 29 patients with complicated diagnoses. Analysis revealed 3869 peptides, which mostly belong to 116 groups with overlapping sequences. A panel of 22 marker peptide groups reliably differentiating PE was created by multivariate statistics, and included 15 collagen groups (from COL1A1, COL3A1, COL2A1, COL4A4, COL5A1, and COL8A1), and single loci from alpha-1-antitrypsin, fibrinogen, membrane-associated progesterone receptor component 1, insulin, EMI domain-containing protein 1, lysine-specific demethylase 6B, and alpha-2-HS-glycoprotein each. ROC analysis of the created model resulted in 88% sensitivity, 96.8% specificity, and receiver operating characteristic curve (AUC) = 0.947. Obtained results confirm the high diagnostic potential of urinary peptidome profiling for pregnancy hypertensive disorders diagnostics. [ABSTRACT FROM AUTHOR]

The mass spectrometry‐based molecular profiling can be used for better differentiation between normal and cancer tissues and for the detection of neoplastic transformation, which is of great importance for diagnostics of a pathology, prognosis of its evolution trend, and development of a treatment strategy. The aim of the present study is the evaluation of tissue classification approaches based on various data sets derived from the molecular profile of the organic solvent extracts of a tissue. A set of possibilities are considered for the orthogonal projections to latent structures discriminant analysis: all mass spectrometric peaks over 300 counts threshold, subset of peaks selected by ranking with support vector machine algorithm, peaks selected by random forest algorithm, peaks with the statistically significant difference of the intensity determined by the Mann‐Whitney U test, peaks identified as lipids, and both identified and significantly different peaks. The best predictive potential is obtained for OPLS‐DA model built on nonpolar glycerolipids (Q2 = 0.64, area under curve [AUC] = 0.95); the second one is OPLS‐DA model with lipid peaks selected by random forest algorithm (Q2 = 0.58, AUC = 0.87). Moreover, models based on particular molecular classes are more preferable from biological point of view, resulting in new explanatory mechanisms of pathophysiology and providing a pathway analysis. Another promising features for OPLS‐DA modeling are phosphatidylethanolamines (Q2 = 0.48, AUC = 0.86). [ABSTRACT FROM AUTHOR]

Abstract: We explored a possibility of using atmospheric pressure ionization techniques like corona discharge chemical ionization and surface thermoionization for distinguishing the chiral chemical compounds in situ. In both cases of ionization techniques we used home built ion sources coupled with non-modified ThermoFinnigan interfaces. For the proof-of-principle demonstration of recognition of molecule chirality in situ we used dimethyltartrate as a model chiral substance. We demonstrated that both ionization methods produce dimers and trimers of the dimethyltartrate molecules with pronounced chiral discrimination effects. In the case of corona discharge ionization we detected H3O+ and H2O+ based dimers and trimers. K+ based dimers and trimers dominated the mass spectra in the case of thermoionization. Homochiral domination in the potassiumated dimers and H2O+ based dimers can be attributed to inherited chirality effect from the trimers. We showed that addition of the water molecules to dimers strongly influenced the effect of chirality on dimer stability by making heterochiral dimer more stable than homochiral in case of addition of one water molecule and removing the influence of chirality on dimers stability by addition of two or more water molecules. The experimental observations agree well with the results of the quantum chemical calculation obtained for dimers containing different number of water molecules. [Copyright &y& Elsevier]