Magnetic Bead-based Weak Cation Exchange Research Articles

Proteome analysis reveals novel serum biomarkers for Henoch-Schönlein purpura in Chinese children

PurposeHenoch-Schönlein purpura (HSP) is diagnosed based on characteristic skin changes. This study aimed to identify the serum biomarkers of HSP in children. Experimental designWe performed proteomic analysis of serum samples from 38 paired pre- and posttherapy HSP patients and 22 healthy controls using a combination of magnetic bead-based weak cation exchange and MALDI-TOF MS. ClinProTools was used to screen the differential peaks. Then, LC–ESI–MS/MS was performed to identify the proteins. ELISA was used to verify the expression of whole protein in the serum of 92 HSP patients, 14 peptic ulcer disease (PUD) patients and 38 healthy controls, which were prospectively collected. Finally, logistic regression analysis was performed to analyze the diagnostic value of the above predictors and existing clinical indicators. ResultsSeven potential HSP serum biomarker peaks (m/z:1228.95, m/z:1781.22, m/z:1468.43, m/z:1619.53, m/z:1868.41, m/z:1694.05, m/z:1743.25) with higher expression in the pretherapy group and one peak (m/z:1947.41) with lower expression in the pretherapy group were all identified as peptide regions of albumin (ALB), complement C4-A precursor (C4A), tubulin beta chain (TUBB), isoform 1 of fibrinogen alpha chain (FGA), and ezrin (EZR). The expression of identified proteins was validated by ELISA. Multivariate logistic regression analysis showed that serum C4A EZR and ALB were independent risk factors for HSP, serum C4A and lgA were independent risk factors for HSPN, and serum D-dimer was an independent risk factor for abdominal HSP. Conclusions and clinical relevanceThese findings revealed the specific etiology of HSP from the perspective of serum proteomics. The identified proteins might serve as potential biomarkers for HSP and HSPN diagnoses. SignificanceHenoch-Schönlein purpura (HSP) is the most common systemic vasculitis in children, and its diagnosis depends primarily on characteristic skin changes. Early diagnosis of non-rash patients is difficult, especially for abdominal and renal types (Henoch-Schönlein purpura nephritis, HSPN). HSPN has poor outcomes, is diagnosed based on urinary protein and/or haematuria, and cannot be detected early in HSP. Patients with an earlier diagnosis of HSPN appear to have better renal outcomes. Our plasma proteomic analysis of HSP in children revealed that HSP patients could be distinguished from healthy controls and peptic ulcer disease patients using complement C4-A precursor (C4A), ezrin, and albumin. C4A and IgA could distinguish HSPN from HSP in the early stages, and D-dimer was a sensitive index used to distinguish abdominal HSP; identifying these biomarkers could promote the early diagnosis of HSP, especially pediatric HSPN and abdominal HSP, thereby improving precision therapy.

Isoform 1 of Fibrinogen Alpha Chain Precursor is a Potential Biomarker for Steroid-Induced Osteonecrosis of the Femoral Head.

Early diagnosis is crucial to increase the chances of conservation treatment for patients with steroid-induced osteonecrosis of the femoral head (SIONFH). This study aimed to identify serum peptides as potential biomarkers to diagnose SIONFH. The serum proteome of 32 SIONFH patients and 24 healthy controls are analyzed using magnetic bead-based weak cation exchange (MB-WCX) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS). Next, candidate biomarkers are identified using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Candidate biomarkers are then validated using ELISA and western blotting. 39 peaks are identified and the expression fold changes of seven peaks in the two groups are greater than 1.5. Three peaks (m/z: 1077.84Da; m/z: 1061.78Da; m/z: 1099.56Da) tend to be upregulated, while four peaks (m/z: 3973.92Da; m/z: 7766.53Da; m/z: 3957.31Da; m/z: 4212.02Da) tend to be down-regulated in SIONFH patients. The peak for a 1077.84Da peptide is identified as Isoform 1 of the Fibrinogen alpha chain precursor (FGA). ELISAs and western blot analyses reveal that the expression of FGA is significantly higher in SIONFH patients than healthy controls. FGA is overexpressed in SIONFH patients, and thus, is a novel potential biomarker for SIONFH.

Peptidome profiles in melamine diet-induced bladder stones in C57BL/6 mice

The aim of this research was to detect potential serum biomarkers of melamine diet-induced bladder stones in C57BL/6 mice. Magnetic bead-based weak cationexchange chromatography (MB-WCX) and matrix-assisted laser desorption ionization-time of flight-mass spectrometry (MALDI-TOF-MS) were employed to detect serum biomarkers in 10 mice fed a melamine diet and 10 control mice. Seventeen peaks (fold change>1.5) with a mass to charge (m/z) value of 1000–10,000 Da were detected in the two groups. Among the significant peaks, five were upregulated and the other 12 were downregulated in the model group. Among the upregulated peaks, 2954.49 and 1710.49 were found to correspond to the peptide regions of NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 8(Ndufα8) and basigin, respectively, by liquid chromatography with electrospray ionization and tandem triple quadrupole mass spectrometry(LC-ESI-MS/MS). Western blot analysis was used to detect the expression of Ndufα8 and basigin in another 10 model mice and 10 control mice. The western blot results confirmed the LC-ESI-MS/MS data. The expression of serum basigin and Ndufα8 was partly dependent the concentration of melamine, but no time dependence. In conclusion, Ndufα8 and basigin may be potential serum biomarkers for the detection of melamine diet-induced bladder stones in C57BL/6 mice

RNA-Binding Motif Protein 6 is a Candidate Serum Biomarker for Pancreatic Cancer.

Early diagnosis is crucial to improve outcomes for pancreatic cancer patients (PC). The present study is designed to identify differently expressed peptides involved in PC as potential biomarkers. The serum proteome of 22 PC patients, 12 pancreatitis patients (PP), and 45 healthy controls (HC) are analyzed using magnetic bead-based weak cation exchange (MB-WCX) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Next, a supervised neural network (SNN) algorithm model is established by ClinProTools and the candidate biomarker identified using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Finally, the candidate biomarker is validated in tissue samples. The SNN algorithm model discriminates PC from HC with 92.97% sensitivity and 94.55% specificity. Seventy-six differentially expressed peptides are identified, seven of which are significantly different among PC, PP, and HC (p < 0.05). Only one peak (m/z: 1466.99) tends to be upregulated in samples from HC, PP, and PC, which is identified as region of RNA-binding motif protein 6 (RBM6). In subsequent tissue analysis, it is verified that RBM6 expression is significantly higher in PC tissues than paracancerous tissue. The results indicate that RBM6 might serve as a candidate diagnostic biomarker for PC. Methods used in this study could generate serum peptidome profiles of PC, PP, and HC, and present an approach to identify potential biomarkers for diagnosis of this malignancy.

Retraction Note to: Effects of a Terrified-Sound Stress on Serum Proteomic Profiling in Mice.

The serum proteomic profiles of mice exposed to terrified-sound-induced stress and after stress release were investigated. Serum samples from 32 mice were divided into four groups (n = 8 each) and analyzed using matrix-assisted laser desorption and ionization time-of-flight mass spectrometry techniques (MALDI-TOF MS) combined with magnetic bead-based weak cation-exchange chromatography. ClinProTools software identified several distinct markers that differed between the stressed and control groups and between the stress released and stressed released controls. Of 33 m/z peaks that differed among the four groups, 17 were significantly different (P < 0.05). Five peaks (m/z: 2793.37, 2924.86, 1979.90, 3492.49, 3880.24) showed significant differences in expression after exposure to terrified-sound stress and returned to control levels after stress release. These were sequence identified as peptide regions of dimethylaniline monooxygenase, myosin-9, uncharacterized protein in Rattus norvegicus, apolipoprotein C-I, and plasma serine protease inhibitor (Serpina 5). Our study provides the first evidence of significant changes in serum proteomic profiles in mice exposed to terrified-sound stress, which suggests that protein expression profiles are affected by the stress. Normal expression levels were restored after stress release, suggesting the activation of self-adjustment mechanisms for the recovery of protein expression levels altered by this stress.

The application of fuzzy statistics and linear discriminant analysis as criteria for optimizing the preparation of plasma for matrix-assisted laser desorption/ionization mass spectrometry peptide profiling

An alternative bioinformatics approach based on fuzzy theory statistics and linear discriminant analysis is proposed for the interpretation of MALDI MS spectra in peptide profiling. When applied, the methodology enables the establishment of a reproducible plasma preparation protocol appropriate for the evaluation of small data sets. The samples were collected from pregnant women affected by gestational diabetes mellitus (GDM), n=18 and control group, n=13. The following pre-treatment sets were tested: pipette tips with C18 stationary phase (ZipTip, Millipore and Omix, Agilent) and magnetic bead-based weak cation exchange chromatography kit (MB WCX, Bruker Daltonics). The spectra were recorded using a MALDI TOF mass spectrometer (UltrafleXtreme, Bruker Daltonics) for a mass range of m/z from 1000 to 10,000. The significant features were selected using the wrapper selection method, and two classification systems were tested: discriminant analysis (DA) and fuzzy inference system (FIS). ClinProTools software was employed to compare the usefulness of the proposed methodology. The study showed that the optimum results for MS spectra were obtained after the use of the ZipTip as pre-treatment method in plasma preparation. Chemometric analysis allowed the differentiation of the GDM group from the control with a high degree of accuracy: 0.7333 (DA) and 0.8065 (FIS).

Effects of a Terrified-Sound Stress on Serum Proteomic Profiling in Mice.

The serum proteomic profiles of mice exposed to terrified-sound-induced stress and after stress release were investigated. Serum samples from 32 mice were divided into four groups (n = 8 each) and analyzed using matrix-assisted laser desorption and ionization time-of-flight mass spectrometry techniques (MALDI-TOF MS) combined with magnetic bead-based weak cation-exchange chromatography. ClinProTools software identified several distinct markers that differed between the stressed and control groups and between the stress released and stressed released controls. Of 33 m/z peaks that differed among the four groups, 17 were significantly different (P < 0.05). Five peaks (m/z: 2793.37, 2924.86, 1979.90, 3492.49, 3880.24) showed significant differences in expression after exposure to terrified-sound stress and returned to control levels after stress release. These were sequence identified as peptide regions of dimethylaniline monooxygenase, myosin-9, uncharacterized protein in Rattus norvegicus, apolipoprotein C-I, and plasma serine protease inhibitor (Serpina 5). Our study provides the first evidence of significant changes in serum proteomic profiles in mice exposed to terrified-sound stress, which suggests that protein expression profiles are affected by the stress. Normal expression levels were restored after stress release, suggesting the activation of self-adjustment mechanisms for the recovery of protein expression levels altered by this stress.

Screening and identification of apolipoprotein A-I as a potential hepatoblastoma biomarker in children, excluding inflammatory factors.

The aim of the present study was to identify a child hepatoblastoma serum biomarker that is unaffected by inflammatory factors, with the ultimate aim of finding an effective method for the early diagnosis of hepatoblastoma. The magnetic bead-based weak cation exchange chromatography technique was used to process serum harvested from 30 children with hepatoblastoma, 20 children with systemic inflammatory response syndrome (SIRS) and 20 healthy children. Proteins differentially expressed in SIRS were excluded from consideration as biomarkers for hepatoblastoma. Proteins differentially expressed in hepatoblastoma and healthy controls were screened using surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS). Target proteins were purified by SDS-PAGE, and matrix-assisted laser desorption/ionization (MALDI)-TOF-MS was used to determine their amino acid sequences. Protein matches were searched in the SwissProt database. Quantitative polymerase chain reaction (qPCR) and ELISA were employed to confirm the expression of target proteins. Following screening to exclude inflammatory factors, SELDI-TOF-MS revealed a protein with a mass-to-charge ratio of 9,348 Da that was expressed at significantly lower levels in the serum of children with hepatoblastoma compared with healthy controls (P<0.01). Sequence analysis identified this protein as apolipoprotein A-1 (Apo A-I). qPCR and ELISA confirmed that the expression of Apo A-I mRNA and protein were significantly lower in children with hepatoblastoma compared with healthy controls (P<0.05). These results indicate that Apo A-I is a non-inflammatory protein marker for hepatoblastoma with the potential for use in early diagnosis of hepatoblastoma. In addition, the present study demonstrates the feasibility of proteomic screening for the identification of proteins that can serve as markers for a specific tumor.

Proteomic Profiling of Invasive Ductal Carcinoma (IDC) using Magnetic Beads‐based Serum Fractionation and MALDI‐TOF MS

To reveal the serum proteomic profiling of intraductal carcinoma (IDC) patients in China, establish a serum proteome fractionation technique for choosing magnetic beads for proteomic analysis in breast cancer research; and identify differentially expressed peptides (m/z; P < 0.0001) as potential biomarkers of early IDCs. We used two different kinds of magnetic beads (magnetic bead-based weak cation exchange chromatography (MB-WCX) and immobilized metal ion affinity chromatography (MB-IMAC-Cu)) to analyze 32 patients with early stage (stages I-II) IDC and 32 healthy control serum samples for proteomic profiling by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The mass spectra, analyzed using ClinProTools software, distinguished between IDC patients and healthy individuals based on k-nearest neighbor genetic algorithm. The serum samples purified in the MB-WCX group provided better proteomic patterns than the MB-IMAC-Cu group. The samples purified by MB-WCX had better average peak numbers, higher peak intensities, and better capturing ability of low abundance proteins or peptides in serum samples. In addition, the MB-WCX and MB-IMAC-Cu purification methods, followed MALDI-TOF MS identification and use of ClinProTools software accurately distinguished patients with early stage IDC from healthy individuals. Serum proteomic profiling by MALDI-TOF MS is a novel potential tool for the clinical diagnosis of patients with IDC in China.

Primary Study of Lymph Node Metastasis‐Related Serum Biomarkers in Breast Cancer

The aim of this study was to detect the pretreatment serum protein profiles of breast cancer patients by mass spectrometry (MS) to screen candidate tumor biomarkers, which will supply a simple, accurate, and minimally invasive method to predict the axillary lymph node metastasis of breast cancer. We used magnetic bead-based weak cation-exchange chromatography followed by matrix-assisted laser desorption and ionization time-of-flight MS to detect proteins in the sera of 54 cases of axillary node-negative breast cancer, 47 cases of axillary node-positive breast cancer, and 101 healthy controls. The protein profiles were analyzed to screen tumor biomarkers and lymph node metastasis-associated proteins to establish and verify a diagnostic model. Comparison of the protein profiles between the two cancer groups resulted in a total of 111 discriminate m/z peaks that were associated with breast cancer. Furthermore, 40 discriminate m/z peaks were detected between breast cancer patients with and without axillary node metastases. Four protein m/z peaks at 5,643, 4,651, 2,377, and 2,240 were used to construct a diagnosis model, and cross-validation indicated that breast cancer with and without axillary node metastasis was identified with 87.04% sensitivity (47/54), 87.23% specificity (41/47), and 87.13% accuracy (88/101). These proteins could potentially be used as predictive biomarkers to distinguish between breast cancer patients with or without lymph node metastasis.

Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry Combined with Magnetic Beads for Detecting Serum Protein Biomarkers in Parkinson’s Disease

Background: Biomarkers for neurodegenerative diseases are essential to facilitate disease diagnosis. Application of proteomics has greatly hastened the search for novel biomarkers. In this study, new potential biomarkers were discovered, and a diagnostic pattern was established for idiopathic Parkinson’s disease (PD) by using proteomic technology. Methods: Serum proteins from PD patients and controls were captured by magnetic bead-based weak cation exchange. The molecular weight of the proteins in bead-binding fraction was detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Biomarker Wizard 3.1 and Biomarker Patterns Software were used for data analysis and constructing a model of biomarkers. A blinded testing set was used to validate the model. Results: A total of 17 discriminating m/z peaks related to PD were identified. The model based on the 5 biomarkers generated an excellent separation between PD and healthy controls with 98.36% for the sensitivity and 83.05% for the specificity. Blind test data demonstrated the model could recognize patients with PD with a sensitivity of 85.0% and a specificity of 70.0%. Conclusions: The preliminary data suggested a potential application of MALDI-TOF-MS combined with magnetic beads. The model comprising 5 promising biomarkers can differentiate individuals with PD and the healthy subjects precisely.

Proteomic profiling of renal allograft rejection in serum using magnetic bead–based sample fractionation and MALDI-TOF MS

Proteomics is one of the emerging techniques for biomarker discovery. Biomarkers can be used for early noninvasive diagnosis and prognosis of diseases and treatment efficacy evaluation. In the present study, the well-established research systems of ClinProt Micro solution incorporated unique magnetic bead sample preparation technology, which, based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), have become very successful in bioinformatics due to its outstanding performance and reproducibility for discovery disease-related biomarker. We collected fasting blood samples from patients with biopsy-confirmed acute renal allograft rejection (n = 12), chronic rejection (n = 12), stable graft function (n = 12) and also from healthy volunteers (n = 13) to study serum peptidome patterns. Specimens were purified with magnetic bead-based weak cation exchange chromatography and analyzed with a MALDI-TOF mass spectrometer. The results indicated that 18 differential peptide peaks were selected as potential biomarkers of acute renal allograft rejection, and 6 differential peptide peaks were selected as potential biomarkers of chronic rejection. A Quick Classifier Algorithm was used to set up the classification models for acute and chronic renal allograft rejection. The algorithm models recognize 82.64% of acute rejection and 98.96% of chronic rejection episodes, respectively. We were able to identify serum protein fingerprints in small sample sizes of recipients with renal allograft rejection and establish the models for diagnosis of renal allograft rejection. This preliminary study demonstrated that proteomics is an emerging tool for early diagnosis of renal allograft rejection and helps us to better understand the pathogenesis of disease process.