Bioactive Peptide Profiling in Collagen Hydrolysates: Comparative Analysis Using Targeted and Untargeted Liquid Chromatography-Tandem Mass Spectrometry Quantification.

The investigation of collagen hydrolysates (CHs) is essential due to their widespread use in health, cosmetic, and therapeutic industries, attributing to the presence of bioactive dipeptides (DPs) and tripeptides (TPs). This study developed a novel targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method with propyl chloroformate (PCF) derivatization to measure three bioactive peptides-Hydroxyprolyl-glycine (Hyp-Gly), Glycyl-prolyl-hydroxyproline (Gly-Pro-Hyp), and Prolyl-hydroxyproline (Pro-Hyp)-in CHs, with strong correlation coefficients (0.992, 1.000, and 0.995, respectively) and low limits of detection (LODs) of 1.40, 0.14, and 1.16 µM, respectively. Untargeted data-dependent acquisition (DDA) analyses measured peptide size distribution, while amino acid analysis assessed nutritional content. The analysis of ten commercial CHs revealed similar amino acid profiles but varied peptide lengths, indicating diverse hydrolysis conditions. Products with higher proportions of smaller peptides showed elevated levels of the targeted bioactive peptides, suggesting that a smaller peptide size may increase bioactivity. These findings can inform the optimization of CH supplements, providing consumers with detailed peptide content for more informed choices. Data are available via ProteomeXchange with the identifier PXD051699.

Changes in Serum Protein-Peptide Patterns in Atopic Children Allergic to Plant Storage Proteins.

Next to cow's milk and eggs, plant foods, i.e., legumes, tree nuts and cereal grains, most often sensitise atopic children. Storage proteins constitutes the most relevant protein fraction of plant foods, causing primary sensitisation. They exhibit strong allergenic properties and immunogenicity. Our goal was to analyse sensitisation to 26 plant storage proteins in a group of 76 children aged 0-5 years with chronic symptoms of atopic dermatitis using Allergy Explorer ALEX2 and to discover changes in serum protein-peptide patterns in allergic patients with the use of MALDI-TOF-MS. We reported that 25% of children were allergic to 2S albumins, 19.7% to 7S globulins, 13.2% to 11S globulins and 1.3% to cereal prolamins. The most common allergenic molecules were Ara h 1 (18.4%), Ara h 2 (17.1%), Ara h 6 (15.8%) and Ara h 3 (11.8%) from peanuts, and the mean serum sIgE concentrations in allergic patients were 10.93 kUA/L, 15.353 kUA/L, 15.359 kUA/L and 9.038 kUA/L, respectively. In children allergic to storage proteins compared to the other patients (both allergic and non-allergic), the cell cycle control protein 50A, testis-expressed sequence 13B, DENN domain-containing protein 5A and SKI family transcriptional corepressor 2 were altered. Our results indicate that the IgE-mediated allergy to storage proteins is a huge problem in a group of young, atopic children, and show the potential of proteomic analysis in the prediction of primary sensitisation to plant foods. It is the next crucial step for understanding the molecular consequences of allergy to storage proteins.

Profiling of schizophrenia-associated serum peptides by MALDI-TOF-MS.

Schizophrenia is a psychiatric condition characterized by poor prognosis and severe symptoms that decrease the quality of life of patients. It is therefore important to develop rapid and reliable methods for early diagnosis. To achieve this aim, identification of accurate biomarkers will promote research into the mechanisms of schizophrenia and the design of effective diagnosis tools. Discriminative peptides in the serum of participants (277 schizophrenia patients and 294 healthy controls) were detected using the matrix-assisted laser desorption ionization time-of-flight tandem mass spectrometry (MALDI-TOF-MS). The diagnostic model for schizophrenia was validated using the ClinProTool software. Discrimination models were tested in the training set (200 schizophrenia patients and 200 healthy controls), and the robustness of the models was evaluated using the independent test set (77 cases and 94 controls). A total of 77 peaks were significantly different between schizophrenia patients and healthy controls with a signal-to-noise ratio of over 5. Among them, 35 peptides were down-regulated and 42 peptides were up-regulated in schizophrenia patients. With a cross-validation rate of 92.7% and a recognition capability rate of 96.5%, the supervised neural network comprising 25 discriminative peaks was found to be the most efficient model for schizophrenia diagnosis (sensitivity = 96.10%, specificity = 94.68%). Peptides at m/z = 2022.18 corresponded to complement C3f, and peptides at m/z = 1020.89, 1351.02, 1466.1 were identified as fragments of fibrinopeptide A. These two peptides may be potential biomarkers for schizophrenia in the Chinese population. The serum peptide levels present a potential clinical diagnostic tool for schizophrenia.

Design of a Prediction Model for the Differentiation of Pasteurized Milk from Heated ESL Milk by Peptide Profiling.

This study designs a prediction model to differentiate pasteurized milk from heated extended shelf life (ESL) milk based on milk peptides. For this purpose, quantitative peptide profiles of a training set of commercial samples including pasteurized (n = 20), pasteurized-ESL (n = 13), and heated-ESL (n = 16) milk are recorded by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Seven peptides are selected as putative markers, and cutoff levels and performance measures of each marker are defined by receiver operating characteristic (ROC) analysis. The accuracy of these peptides in the training set range between 71% and 90%. A prediction model is established based on the combined cutoff levels and evaluated by an independent blind test set. The processing method of 19 out of 20 unknown milk samples is predicted correctly achieving 95% accuracy. Five peptides of the prediction model are identified as αS1 -casein182-199 (m/z 2014.0), αS1 -casein180-199 (m/z 2216.1), αS1 -casein1-24 (m/z 2910.6), ß-casein108-125 (m/z 2126.0), and ß-casein106-125 (m/z 2391.2) indicating thermal release and the action of plasmin and cathepsins. Thus, the present study demonstrates that the milk peptide profile reflects even minor differences in production parameters.

Serum peptide profiling for potential biomarkers in early diagnosis of Escherichia coli bloodstream infection.

BACKGROUND: Bacterial bloodstream infection (BSI) remains an important cause of morbidity and mortality, which is a widespread and uncontrolled inflammatory response. There are some cytokines for the auxiliary diagnosis, such as procalcitonin (PCT), C reactive protein (CRP), and interleukin 6 (IL-6), which are not sufficient. This study was aimed to explore a new method of diagnosing bacterial BSI and to find some new biomarkers that could differentiate bloodstream infected patients from healthy people. METHODS: An animal model was used to find relevant changes of peptides in the serum and was validated in clinical samples. Mice (25-27 g) were randomized to infection with Escherichia coli ATCC25922 or phosphate buffer saline. The serum samples were purified by weak cation exchange beads and the serum peptide profiling was established by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Statistical analysis and diagnostic modeling were conducted on BioExplorer. Amino acid sequences of the candidate peptides were identified by nano-liquid chromatography electrospray ionization-tandem mass spectrometry and relevant proteins were recognized on the Uniprot database. The identified proteins were confirmed via enzyme-linked immunosorbent assay on clinical samples. RESULTS: Five peptide peaks (m/z 1941, 2924.1, 3962.1, 4126.9 and 5514) were found as candidate biomarkers for E. coli infection, and the diagnostic model discriminated E. coli infected patients from healthy controls with an accuracy of 92.2%. Peptide peaks m/z 1941, 2924.1 and 4126.9 were identified as the fragments of Serotransferrin (TRF), Complement C3 and Serum amyloid A-1 protein (SAA1), respectively, but only C3 and SAA1 showed significant difference in clinical samples. CONCLUSION: MALDI-TOF MS could be a new method to find the changes of serum peptides after infection, C3 and SAA1 could be new biomarkers in diagnosing BSI.

MALDI-TOF-MS analysis in discovery and identification of serum proteomic patterns of ovarian cancer.

BACKGROUND: Due to high mortality and lack of efficient screening, new tools for ovarian cancer (OC) diagnosis are urgently needed. To broaden the knowledge on the pathological processes that occur during ovarian cancer tumorigenesis, protein-peptide profiling was proposed. METHODS: Serum proteomic patterns in samples from OC patients were obtained using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF). Eighty nine serum samples (44 ovarian cancer and 45 healthy controls) were pretreated using solid-phase extraction method. Next, a classification model with the most discriminative factors was identified using chemometric algorithms. Finally, the results were verified by external validation on an independent test set of samples. RESULTS: Main outcome of this study was an identification of potential OC biomarkers by applying liquid chromatography coupled with tandem mass spectrometry. Application of this novel strategy enabled the identification of four potential OC serum biomarkers (complement C3, kininogen-1, inter-alpha-trypsin inhibitor heavy chain H4, and transthyretin). The role of these proteins was discussed in relation to OC pathomechanism. CONCLUSIONS: The study results may contribute to the development of clinically useful multi-component diagnostic tools in OC. In addition, identifying a novel panel of discriminative proteins could provide a new insight into complex signaling and functional networks associated with this multifactorial disease.

The feature selection approach for evaluation of potential rheumatoid arthritis markers using MALDI-TOF datasets.

BACKGROUND: The selection of the most representative mass profiles, in rheumatoid arthritis (RA) serum samples was developed. This allows for selection and identification of potential biomarkers in RA serum samples. METHODS: The RA and controls samples were analyzed using MALDI-TOF. Two different protein elution procedures utilizing ZipTips (E1 and E2) were examined. The statistical evaluation of data was performed using different feature selection (FS) methods in combination with different classifiers, while identification of selected masses was performed using MALDI-TOF-TOF. RESULTS: Utilization of proposed statistical strategy allowed for the selection of different masses according to FS method and elution procedure. Obtained masses were further subjected for targeted identification. The panel of proteins were identified as potential markers. The role of these proteins was discussed in relation to pathomechanism of RA. CONCLUSION: Application of advanced biostatistical analysis of obtained MALDI-TOF datasets, resulted with targeted selection of potential RA biomarkers. Five proteins were identified due the E1 procedure, and six proteins were identified due the E2 procedure, respectively. The panel of identified proteins suggest that presented statistical methodology and proteomic strategy was correct and gave valid results. Obtained results may contribute to development of clinically useful multicomponent diagnostic tool.

Mass spectrometry hyphenated techniques for the analysis of volatiles and peptides in soft cheese: Useful tools for the shelf life optimization.

In order to assess the product quality and shelf life of an Italian soft cream cheese under different storage conditions, the volatile and peptide profiles evolution were tested. Volatiles were sampled directly from the head space of cheese packaging by solid-phase microextraction and analyzed by GC-MS. Peptide profiles were obtained by nanoLC-MS/MS, following a novel bioinformatics approach based on scoring distribution associated to the protein hits originating from the database search. In particular, a refined identification by focusing on selected time segments corresponding to the most intense peaks was carried out. A total of 40 compounds including acids, aldehydes, ketones, lactones, alcohols, esters, hydrocarbons, terpene, sulfur, and aromatic compounds were detected. Significant differences in their abundance during the storage in different packagings were observed, as well as an evolution of peptides mainly belonging to αS1-casein. The results demonstrated the usefulness of the above-mentioned hyphenated techniques for the determination of the soft cheese shelf life under different storage conditions.

Identification of Serum Peptidome Signatures of Non-Small Cell Lung Cancer.

Due to high mortality rates of lung cancer, there is a need for identification of new, clinically useful markers, which improve detection of this tumor in early stage of disease. In the current study, serum peptide profiling was evaluated as a diagnostic tool for non-small cell lung cancer patients. The combination of the ZipTip technology with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for the analysis of peptide pattern of cancer patients (n = 153) and control subjects (n = 63) was presented for the first time. Based on the observed significant differences between cancer patients and control subjects, the classification model was created, which allowed for accurate group discrimination. The model turned out to be robust enough to discriminate a new validation set of samples with satisfactory sensitivity and specificity. Two peptides from the diagnostic pattern for non-small cell lung cancer (NSCLC) were identified as fragments of C3 and fibrinogen α chain. Since ELISA test did not confirm significant differences in the expression of complement component C3, further study will involve a quantitative approach to prove clinical utility of the other proteins from the proposed multi-peptide cancer signature.

Peptidomics for Studying Limited Proteolysis.

Limited proteolysis is a pivotal mechanism regulating protein functions. Identifying physiologically or pathophysiologically relevant cleavage sites helps to develop molecular tools that can be used for diagnostics or therapeutics. During proteolysis of secretory and membrane proteins, part of the cleaved protein is liberated and destined to undergo degradation but should retain original cleavage sites created by proteolytic enzymes. We profiled endogenous peptides accumulated for 4 h in media conditioned by primary cultured rat cardiac fibroblasts. A total of 3916 redundant peptide sequences from 94 secretory proteins and membrane proteins served to identify limited cleavage sites, both annotated and unannotated, for signal peptide or propeptide removal, peptide hormone processing, ectodomain shedding, and regulated intramembrane proteolysis. Incorrectly predicted signal cleavage sites are found in typical proteins such as extracellular matrix proteins and the peptide hormone precursor adrenomedullin ADM. The revealed signal peptide cleavage site for ADM was experimentally verified by identifying the major molecular form of flanking proadrenomedullin N-terminal peptide. We suggest that profiling of endogenous peptides, like transcriptome sequence reads, makes sense in regular cells such as fibroblasts and that peptidomics provides insight into proteolysis-regulated protein functions.

Peptide profiling of the route from Mahoney to Sabin, and return.

In order to define poliovirus (PV) neurovirulence at the molecular level, we comparatively analyze the primary amino acid sequence of Mahoney, a neurovirulent PV strain, versus (i) Sabin, an attenuated PV strain, and (ii) IS1, a PV isolate obtained in temporal association to a paralysis event from a polio vaccinated subject. We identify and describe 12 pentapeptides that, originally present in the Mahoney sequence, are changed in the non-neurovirulent Sabin strain, and, successively, restored in IS1 strain.

Analysis of peptidome profiling of serum from patients with early onset symptoms of ischemic stroke.

BACKGROUND: We sought to identify new serum biomarkers for the early diagnosis of ischemic stroke. METHODS: We collected 63 serum samples from patients with neurologic disease (45 patients with ischemic stroke, 18 patients with other neurologic disorders, and 56 healthy controls). Serum peptides were extracted using immobilized copper ion chromatography on a robotic platform. Mass spectra were acquired by matrix-assisted laser desorption/ionization-time of flight mass spectrometry using an Autoflex II spectrometer (Bruker Daltonics, Billerica, MA). Statistical analyses were performed with Clinprotools 2.2 software (Bruker Daltonics) and SPSS software (version 15.0; SPSS, Inc., Chicago, IL). RESULTS: No peptide biomarker or panel of peptide biomarkers was identified to differentiate between ischemic stroke and other neurologic disease, but ischemic stroke patients were differentiated from healthy controls with a single feature of the peptidome (sensitivity 88.6%; specificity 96.4%). CONCLUSIONS: Analysis of peptidome profiling of serum could be a useful tool in the search for early diagnostic biomarkers of ischemic stroke.

Comprehensive species- and processing-specific peptide profiling of pasteurized, extended shelf-life and ultra-high temperature milk from cow, goat, sheep, buffalo, and mare.

The present study aimed to identify endogenous milk peptides for species differentiation independent of heat exposure. Thus, comprehensive milk peptide profiles from five species and three types of heat treatments were analyzed by micro-flow liquid chromatography ion mobility quadrupole time-of-flight mass spectrometry (microLC-IM-QTOF) with subsequent database search leading to ≥ 3000 identified peptides. In the milks, 1154 peptides were unique for cow, 712 for sheep, 466 for goat, 197 for buffalo, and 69 for mare. Most peptides were detected in extended-shelf life (ESL) milk (2010), followed by ultra-high temperature (UHT) processed (1474) and pasteurized milk (1459 peptides), with 693 peptides present in all milk types. A blind test set of 64 samples confirmed eight species-specific, but heat-independent marker peptides in milk from cow, seven from goat, six from sheep, nine from buffalo, and three from mare. The generated peptide profiles can also be used to identify species- and heat-specific markers.

Peptidomics Profile, Bioactive Peptides Identification and Biological Activities of Six Different Cheese Varieties.

Several recent published studies reported that cheese consumption may protect against the onset of cardiovascular diseases and type-2 diabetes due to the presence of bioactive peptides. In the present work, six cheese varieties (the Egyptian traditional cheeses Karish, Domiati and Ras as well as Feta-type, Gouda and Edam cheeses) were characterized for their peptidomics profiles with high-resolution mass spectrometry, biological activities and content in bioactive peptides. The highest ACE-inhibitory and DPP-IV-inhibitory activities were found in Gouda cheese, which also displayed the highest antioxidant activity. A total of 809 peptides originating from the major milk proteins were identified, and 82 of them were bioactive. Most of them showed ACE-inhibitory, antioxidant and DPP-IV-inhibitory activities. The highest amount of the in vivo anti-hypertensive tripeptides VPP and IPP was found in Gouda cheese (39.19 ± 1.26 and 17.72 ± 0.89 mg/100 g of cheese, respectively), whereas the highest amount of APFPE was detected in Edam cheese (509.13 ± 20.44 mg/100 g of cheese). These results suggest that the intake of Edam, Domiati and, especially, Gouda cheeses may result in a possible anti-hypertensive effect in hypertensive subjects.

Differences between peptide profiles of extensive hydrolysates and their influence on functionality for the management of cow's milk allergy: A short review.

Extensively hydrolyzed formulas (eHFs) are recommended for the dietary management of cow's milk protein allergy (CMPA) in non-exclusively breastfed infants. Studies show that peptide profiles differ between eHFs. This short review aims to highlight the variability in peptides and their ability to influence allergenicity and possibly the induction of tolerance by different eHFs. The differences between eHFs are determined by the source of the protein fraction (casein or whey), peptide size-distribution profile and residual ß-lactoglobulin which is the most immunogenic and allergenic protein in bovine milk for human infants as it is not present in human breastmilk. These differences occur from the hydrolyzation process which result in variable IgE reactivity against cow's milk allergen epitopes by subjects with CMPA and differences in the Th1, Th2 and pro-inflammatory cytokine responses elicited. They also have different effects on gut barrier integrity. Results suggest that one particular eHF-casein had the least allergenic potential due to its low residual allergenic epitope content and demonstrated the greatest effect on restoring gut barrier integrity by its effects on mucin 5AC, occludin and Zona Occludens-1 in human enterocytes. It also increased the production of the tolerogenic cytokines Il-10 and IFN-γ. In addition, recent studies documented promising effects of optional functional ingredients such as pre-, pro- and synbiotics on the management of cow's milk allergy and induction of tolerance, in part via the induction of the production of short chain fatty acids. This review highlights differences in the residual allergenicity, peptide size distribution, presence of optional functional ingredients and overall functionality of several well-characterized eHFs which can impact the management of CMPA and the ability to induce immune tolerance to cow's milk protein.

Activity-based Protein Profiling of Serine Hydrolase Superfamily Enzymes.

Activity-based protein profiling (ABPP) is a chemoproteomics platform to assess the functional state of enzymes in complex biological systems. Over the two decades, ABPP has emerged from a gel-based to gel-free platform, for in-depth proteome analysis with enhanced resolution, sensitivity for target detection, and discovery of small molecule inhibitors. The gel-free format of ABPP coupled with advanced mass spectrometry is highly sensitive and provides more comprehensive knowledge for the targeted enzyme family than the gel-based method. ABPP strategy is applied across microbe, plant, and animal models. It can be performed both in vitro and in vivo studies, and there is no limitation on sample origin. Here, we report an ultrasensitive, gel-free format of ABPP called active site peptide profiling. This protocol describes the identification of authentic functional proteins, by tagging their active sites in a native biological system. It is high throughput in nature and helps enrich even low abundance functional proteins. Since protein identification is virtually based on a single peptide, the identified peptide should be a unique peptide to identify its parent protein. It can be performed in a facile manner and offers to consolidate identification of protein targets as well as the site of probe modification. We have validated this approach using a fluorophosphonate (FP) serine hydrolase probe in the native proteome of the cereal crop Oryza sativa. Graphic abstract: Serine hydrolase active site peptide profiling.

MALDI-TOF MS Characterisation of the Serum Proteomic Profile in Insulin-Resistant Normal-Weight Individuals.

Insulin resistance (IR) is one of the most common metabolic disorders worldwide and is involved in the development of diseases, such as diabetes and cardiovascular diseases, affecting civilisations. The possibility of understanding the molecular mechanism and searching for new biomarkers useful in assessing IR can be achieved through modern research techniques such as proteomics. This study assessed the protein-peptide profile among normal-weight patients with IR to understand the mechanisms and to define new risk biomarkers. The research involved 21 IR and 43 healthy, normal-weight individuals, aged 19-65. Serum proteomic patterns were obtained using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry. The proposed methodology identified six proteins differentiating normal weight IR and insulin sensitive individuals. They were fibrinogen alpha chain, serum albumin, kininogen-1, complement C3, serotransferrin, and Ig gamma-1 chain, which could potentially be related to inflammation. However, further investigation is required to confirm their correlation with IR.

Association between Venom Immunotherapy and Changes in Serum Protein-Peptide Patterns.

Venom immunotherapy (VIT) is administered to allergic patients to reduce the risk of dangerous systemic reactions following an insect sting. To better understand the mechanism of this treatment and its impact on the human organism, we analysed serum proteomic patterns obtained at five time-points from Hymenoptera-venom-allergic patients undergoing VIT. For statistical analyses, patients were additionally divided into two groups (high responders and low responders) according to serum sIgG4 levels. VIT was found to be associated with changes in seven proteins: the fibrinogen alpha chain, complement C4-A, complement C3, filamin-B, kininogen-1, myosin-9 and inter-alpha-trypsin inhibitor heavy chain H1. The number of discriminative m/z (mass-to-charge ratio) features increased up to the 90th day of VIT, which may be associated with the development of immunity after the administration of increased venom doses. It may also suggest that during VIT, there may occur processes involved not only in protein synthesis but also in protein degradation (caused by proteolytic venom components). The results are consistent with measured serum sIgG4 levels, which increased from 2.04 mgA/I at baseline to 7.25 mgA/I at 90 days. Moreover, the major proteomic changes were detected separately in the high responder group. This may suggest that changes in protein-peptide profiles reflect the actual response to VIT.

Novel Biomarkers of Mastitis in Goat Milk Revealed by MALDI-TOF-MS-Based Peptide Profiling.

Mastitis is the most common infection of dairy goats impairing milk production and quality, which is usually recognized by mammary gland visual inspection and palpation. Subclinical forms of the disease are also widely represented, which lack the typical signs of the clinical ones but are still associated with reduced production and safety for human consumption of milk, generally presenting a high bacterial count. In order to obtain novel analytical tools for rapid and non-invasive diagnosis of mastitis in goats, we analyzed milk samples from healthy, subclinical and clinical mastitic animals with a MALDI-TOF-MS-based peptidomic platform, generating disease group-specific spectral profiles whose signal intensity and mass values were analyzed by statistics. Peculiar spectral signatures of mastitis with respect to the control were identified, while no significant spectral differences were observed between clinical and subclinical milk samples. Discriminant signals were assigned to specific peptides through nanoLC-ESI-Q-Orbitrap-MS/MS experiments. Some of these molecules were predicted to have an antimicrobial activity based on their strong similarity with homolog bioactive compounds from other mammals. Through the definition of a panel of peptide biomarkers, this study provides a very rapid and low-cost method to routinely detect mastitic milk samples even though no evident clinical signs in the mammary gland are observed.

MALDI-TOF-MS Analysis in the Identification of Urine Proteomic Patterns of Gestational Trophoblastic Disease.

Gestational trophoblastic disease (GTD) is a group of highly aggressive, rare tumors. Human chorionic gonadotropin is a common biomarker used in the diagnosis and monitoring of GTD. To improve our knowledge of the pathology of GTD, we performed protein-peptide profiling on the urine of patients affected with gestational trophoblastic neoplasm (GTN). We analyzed urine samples from patients diagnosed with GTN (n = 26) and from healthy pregnant and non-pregnant controls (n = 17) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Ions were examined in a linear mode over a m/z range of 1000⁻10,000. All GTN urine samples were analyzed before and after treatment and compared with those of the controls. The statistical analyses included multivariate classification algorithms as well as ROC curves. Urine sample analyses revealed there were significant differences in the composition of the ions between the evaluated groups. Comparing the pre-treatment and group with the pregnant controls, we identified two discriminatory proteins: hemoglobin subunit α (m/z = 1951.81) and complement C4A (m/z = 1895.43). Then, comparing urine samples from the post-treatment cases with those from the non-pregnant controls, we identified the peptides uromodulin fragments (m/z = 1682.34 and 1913.54) and complement C4A (m/z = 1895.43).