The Strategy for Peptidomic LC-MS/MS Data Analysis: The Case of Urinary Peptidome Study.

The study of urinary peptidome is an important area of research, which concerns the characterization of endogenous peptides, as well as the identification of biomarkers for a wide range of socially significant diseases. First of all, this relates to renal and genitourinary pathologies and/or pathologies associated with proteinuria, such as kidney diseases, bladder, prostate and ovarian cancers, diabetic nephropathy, and pre-eclampsia. Unlike proteins, peptides do not require proteolytic hydrolysis, can be analyzed in their native form and can provide certain information about occurring (patho)physiological processes. Mass spectrometry (MS)-based approaches are the most unbiased and sensitive instruments with high multiplexing capacity and provided most of the current information about endogenous urine peptides. However, despite the large number of urine peptidomic studies, there are certain issues related to the insufficient comparability of their results due to the lack of consistent approaches to their interpretation. Also the development of a custom project-specific protein library for endogenous peptides search and identification is another important point that should be noted in the context of high-throughput peptidomic analysis. Here we propose the custom-specific urinary protein database and the grouping of endogenous urinary peptides with overlapping sequences as useful tools, which can facilitate the acquisition and analysis of LC-MS peptidomic data, as well as the comparison of results of different studies, which should facilitate their more efficient further application.

Quantitative Proteomics of Maternal Blood Plasma in Isolated Intrauterine Growth Restriction.

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.

Integrating Proteomics and Lipidomics for Evaluating the Risk of Breast Cancer Progression: A Pilot Study.

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.

Targeted Blood Plasma Proteomics and Hemostasis Assessment of Post COVID-19 Patients with Acute Myocardial Infarction.

The molecular mechanisms underlying cardiovascular complications after the SARS-CoV-2 infection remain unknown. The goal of our study was to analyze the features of blood coagulation, platelet aggregation, and plasma proteomics in COVID-19 convalescents with AMI. The study included 66 AMI patients and 58 healthy volunteers. The groups were divided according to the anti-N IgG levels (AMI post-COVID (n = 44), AMI control (n = 22), control post-COVID (n = 31), and control (n = 27)). All participants underwent rotational thromboelastometry, thrombodynamics, impedance aggregometry, and blood plasma proteomics analysis. Both AMI groups of patients demonstrated higher values of clot growth rates, thrombus size and density, as well as the elevated levels of components of the complement system, proteins modifying the state of endothelium, acute-phase and procoagulant proteins. In comparison with AMI control, AMI post-COVID patients demonstrated decreased levels of proteins connected to inflammation and hemostasis (lipopolysaccharide-binding protein, C4b-binding protein alpha-chain, plasma protease C1 inhibitor, fibrinogen beta-chain, vitamin K-dependent protein S), and altered correlations between inflammation and fibrinolysis. A new finding is that AMI post-COVID patients opposite the AMI control group, are characterized by a less noticeable growth of acute-phase proteins and hemostatic markers that could be explained by prolonged immune system alteration after COVID-19.

Targeted MRM Quantification of Urinary Proteins in Chronic Kidney Disease Caused by Glomerulopathies.

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).

Potential Urine Proteomic Biomarkers for Focal Segmental Glomerulosclerosis and Minimal Change Disease.

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.

Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning.

The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors' samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.

Prognosis of Alzheimer's Disease Using Quantitative Mass Spectrometry of Human Blood Plasma Proteins and Machine Learning.

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.

Combined Impact of Magnetic Force and Spaceflight Conditions on Escherichia coli Physiology.

Changes in bacterial physiology caused by the combined action of the magnetic force and microgravity were studied in Escherichia coli grown using a specially developed device aboard the International Space Station. The morphology and metabolism of E. coli grown under spaceflight (SF) or combined spaceflight and magnetic force (SF + MF) conditions were compared with ground cultivated bacteria grown under standard (control) or magnetic force (MF) conditions. SF, SF + MF, and MF conditions provided the up-regulation of Ag43 auto-transporter and cell auto-aggregation. The magnetic force caused visible clustering of non-sedimenting bacteria that formed matrix-containing aggregates under SF + MF and MF conditions. Cell auto-aggregation was accompanied by up-regulation of glyoxylate shunt enzymes and Vitamin B12 transporter BtuB. Under SF and SF + MF but not MF conditions nutrition and oxygen limitations were manifested by the down-regulation of glycolysis and TCA enzymes and the up-regulation of methylglyoxal bypass. Bacteria grown under combined SF + MF conditions demonstrated superior up-regulation of enzymes of the methylglyoxal bypass and down-regulation of glycolysis and TCA enzymes compared to SF conditions, suggesting that the magnetic force strengthened the effects of microgravity on the bacterial metabolism. This strengthening appeared to be due to magnetic force-dependent bacterial clustering within a small volume that reinforced the effects of the microgravity-driven absence of convectional flows.

The Parallel Reaction Monitoring-Parallel Accumulation-Serial Fragmentation (prm-PASEF) Approach for Multiplexed Absolute Quantitation of Proteins in Human Plasma.

Mass spectrometry (MS)-based quantitative proteomic methods have become some of the major tools for protein biomarker discovery and validation. The recently developed parallel reaction monitoring-parallel accumulation-serial fragmentation (prm-PASEF) approach on a Bruker timsTOF Pro mass spectrometer allows the addition of ion mobility as a new dimension to LC-MS-based proteomics and increases proteome coverage at a reduced analysis time. In this study, a prm-PASEF approach was used for the multiplexed absolute quantitation of proteins in human plasma using isotope-labeled peptide standards for 125 plasma proteins, over a broad (104-106) dynamic range. Optimization of LC and MS parameters, such as accumulation time and collision energy, resulted in improved sensitivity for more than half of the targets (73 out of 125 peptides) by increasing the signal-to-noise ratio by a factor of up to 10. Overall, 41 peptides showed up to a 2-fold increase in sensitivity, 25 peptides showed up to a 5-fold increase in sensitivity, and 7 peptides showed up to a 10-fold increase in sensitivity. Implementation of the prm-PASEF method allowed absolute protein quantitation (down to 1.13 fmol) in human plasma samples. A comparison of the concentration values of plasma proteins determined by MRM on a QTRAP instrument and by prm-PASEF on a timsTOF Pro revealed an excellent correlation (R2 = 0.97) with a slope of close to 1 (0.99), demonstrating that prm-PASEF is well suited for "absolute" quantitative proteomics.

Effects of Siberian fir terpenes extract Abisil on antioxidant activity, autophagy, transcriptome and proteome of human fibroblasts.

BACKGROUND: Abisil is an extract of Siberian fir terpenes with antimicrobial and wound healing activities. Previous studies revealed that Abisil has geroprotective, anti-tumorigenic, and anti-angiogenic effects. Abisil decreased the expression of cyclin D1, E1, A2, and increased the phosphorylation rate of AMPK. OBJECTIVE: In the present study, we analyzed the effect of Abisil on autophagy, the mitochondrial potential of embryonic human lung fibroblasts. We evaluated its antioxidant activity and analyzed the transcriptomic and proteomic effects of Abisil treatment. RESULTS: Abisil treatment resulted in activation of autophagy, reversal of rotenone-induced elevation of reactive oxygen species (ROS) levels and several-fold decrease of mitochondrial potential. Lower doses of Abisil (25 µg/ml) showed a better oxidative effect than high doses (50 or 125 µg/ml). Estimation of metabolic changes after treatment with 50 µg/ml has not shown any changes in oxygen consumption rate, but extracellular acidification rate decreased significantly. Abisil treatment (5 and 50 µg/ml) of MRC5-SV40 cells induced a strong transcriptomic shift spanning several thousand genes (predominantly, expression decrease). Among down-regulated genes, we noticed an over-representation of genes involved in cell cycle progression, oxidative phosphorylation, and fatty acid biosynthesis. Additionally, we observed predominant downregulation of genes encoding for kinases. Proteome profiling also revealed that the content of hundreds of proteins is altered after Abisil treatment (mainly, decreased). These proteins were involved in cell cycle regulation, intracellular transport, RNA processing, translation, mitochondrial organization. CONCLUSIONS: Abisil demonstrated antioxidant and autophagy stimulating activity. Treatment with Abisil results in the predominant downregulation of genes involved in the cell cycle and oxidative phosphorylation.

miRNAs and Their Gene Targets-A Clue to Differentiate Pregnancies with Small for Gestational Age Newborns, Intrauterine Growth Restriction, and Preeclampsia.

Despite the differences in the clinical manifestations of major obstetric syndromes, such as preeclampsia (PE) and intrauterine growth restriction (IUGR), their pathogenesis is based on the dysregulation of proliferation, differentiation, and invasion of cytotrophoblast cells that occur in the developing placenta, decidual endometrium, and myometrial parts of the spiral arteries. To understand the similarities and differences in the molecular mechanisms of PE and IUGR, samples of the placental bed and placental tissue were analyzed using protein mass spectrometry and the deep sequencing of small RNAs, followed by validation of the data obtained by quantitative RT-PCR in real time. A comparison of the transcriptome and proteomic profiles in the samples made it possible to conclude that the main changes in the molecular profile in IUGR occur in the placental bed, in contrast to PE, in which the majority of molecular changes occurs in the placenta. In placental bed samples, significant changes in the ratio of miRNA and its potential target gene expression levels were revealed, which were unique for IUGR (miR-30c-5p/VIM, miR-28-3p/VIM, miR-1-3p/ANXA2, miR-30c-5p/FBN1; miR-15b-5p/MYL6), unique for PE (miR-185-3p/FLNA), common for IUGR and PE (miR-30c-5p/YWHAZ and miR-654-3p/FGA), but all associated with abnormality in the hemostatic and vascular systems as well as with an inflammatory process at the fetal‒maternal interface.

Vertical Transmission of SARS-CoV-2 in Second Trimester Associated with Severe Neonatal Pathology.

The effects of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in women on the gestation course and the health of the fetus, particularly in the first and second trimesters, remain very poorly explored. This report describes a case in which the normal development of pregnancy was complicated immediately after the patient had experienced Coronavirus disease 2019 (COVID-19) at the 21st week of gestation. Specific conditions included critical blood flow in the fetal umbilical artery, fetal growth restriction (1st percentile), right ventricular hypertrophy, hydropericardium, echo-characteristics of hypoxic-ischemic brain injury (leukomalacia in periventricular area) and intraventricular hemorrhage at the 25th week of gestation. Premature male neonate delivered at the 26th week of gestation died after 1 day 18 h due to asystole. The results of independent polymerase chain reaction (PCR), mass spectrometry and immunohistochemistry analyses of placenta tissue, umbilical cord blood and child blood jointly indicated vertical transmission of SARS-CoV-2 from mother to the fetus, which we conclude to be the major cause for the development of maternal vascular malperfusion in the studied case.

The Dynamics of ß-Amyloid Proteoforms Accumulation in the Brain of a 5xFAD Mouse Model of Alzheimer's Disease.

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 ß-amyloid (Aß) 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 Aß, and specific Aß proteoforms (e.g., Aß with isomerized D7 (isoD7-Aß)) 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 Aß 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 Aß fraction of isoD7-Aß, 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 Aß proteoforms correlate with the formation of Aß 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-Aß and the progression of AD-like pathology.

Mass-Spectrometric Detection of SARS-CoV-2 Virus in Scrapings of the Epithelium of the Nasopharynx of Infected Patients via Nucleocapsid N Protein.

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.

Proteome Profiling of the Exhaled Breath Condensate after Long-Term Spaceflights.

Comprehensive studies of the effects of prolonged exposure to space conditions and the overload experienced during landing on physiological and biochemical changes in the human body are extremely important in the context of planning long-distance space flights, which can be associated with constant overloads and various risk factors for significant physiological changes. Exhaled breath condensate (EBC) can be considered as a valuable subject for monitoring physiological changes and is more suitable for long-term storage than traditional monitoring subjects such as blood and urine. Herein, the EBC proteome changes due to the effects of spaceflight factors are analyzed. Thirteen EBC samples were collected from five Russian cosmonauts (i) one month before flight (background), (ii) immediately upon landing modules in the field (R0) after 169-199 days spaceflights, and (iii) on the seventh day after landing (R+7). Semi-quantitative label-free EBC proteomic analysis resulted in 164 proteins, the highest number of which was detected in EBC after landing (R0). Pathways enrichment analysis using the GO database reveals a large group of proteins which take part in keratinization processes (CASP14, DSG1, DSP, JUP, and so on). Nine proteins (including KRT2, KRT9, KRT1, KRT10, KRT14, DCD, KRT6C, KRT6A, and KRT5) were detected in all three groups. A two-sample Welch's t-test identified a significant change in KRT2 and KRT9 levels after landing. Enrichment analysis using the KEGG database revealed the significant participation of detected proteins in pathogenic E. coli infection (ACTG1, TUBA1C, TUBA4A, TUBB, TUBB8, and YWHAZ), which may indicate microbiota changes associated with being in space. This assumption is confirmed by microbial composition analysis. In general, the results suggest that EBC can be used for noninvasive monitoring of health status and respiratory tract pathologies during spaceflights, and that the obtained data are important for the development of medicine for use in extreme situations. Data are available from ProteomeXchange using the identifier PXD014191.

The Effects of Spaceflight Factors on the Human Plasma Proteome, Including Both Real Space Missions and Ground-Based Experiments.

The aim of the study was to compare proteomic data on the effects of spaceflight factors on the human body, including both real space missions and ground-based experiments. LC-MS/MS-based proteomic analysis of blood plasma samples obtained from 13 cosmonauts before and after long-duration (169-199 days) missions on the International Space Station (ISS) and for five healthy men included in 21-day-long head-down bed rest (HDBR) and dry immersion experiments were performed. The semi-quantitative label-free analysis revealed significantly changed proteins: 19 proteins were significantly different on the first (+1) day after landing with respect to background levels; 44 proteins significantly changed during HDBR and 31 changed in the dry immersion experiment. Comparative analysis revealed nine common proteins (A1BG, A2M, SERPINA1, SERPINA3, SERPING1, SERPINC1, HP, CFB, TF), which changed their levels after landing, as well as in both ground-based experiments. Common processes, such as platelet degranulation, hemostasis, post-translational protein phosphorylation and processes of protein metabolism, indicate common pathogenesis in ground experiments and during spaceflight. Dissimilarity in the lists of significantly changed proteins could be explained by the differences in the dynamics of effective development in the ground-based experiments. Data are available via ProteomeXchange using the identifier PXD013305.

Label-free cervicovaginal fluid proteome profiling reflects the cervix neoplastic transformation.

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.