Protein expression profiles in pediatric multiple sclerosis: potential biomarkers

2009 ◽  
Vol 15 (4) ◽  
pp. 455-464 ◽  
Author(s):  
KN Rithidech ◽  
L Honikel ◽  
M Milazzo ◽  
D Madigan ◽  
R Troxell ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Mass Spectrometry ◽  
Protein Expression ◽  
Expression Profiles ◽  
Low Frequency ◽  
Complement Factor ◽  
Protein Biomarkers ◽  
Two Dimensional Gel Electrophoresis ◽  
Pediatric Multiple Sclerosis ◽  
Proteomic Approach

The diagnosis of pediatric multiple sclerosis (MS) is challenging due to its low frequency and the overlap with other acquired childhood demyelinating disorders of the central nervous system. To identify potential protein biomarkers which could facilitate the diagnosis, we used two-dimensional gel electrophoresis (2-DE) in combination with mass spectrometry to identify proteins associated with pediatric MS. Plasma samples from nine children with MS and nine healthy subjects, matched in aggregate by age and gender, were analyzed for differences in their patterns of protein expression. We found 12 proteins that were significantly up regulated in the pediatric MS group: alpha-1-acid-glycoprotein 1, alpha-1-B-glycoprotein, transthyretin, apoliprotein-C-III, serum amyloid P component, complement factor-I, clusterin, gelsolin, hemopexin, kininogen-1, hCG1993037-isoform, and vitamin D-binding protein. These results show that 2-DE in combination with mass spectrometry is a highly sensitive technique for the identification of blood-based biomarkers. This proteomic approach could lead to a new panel of diagnostic and prognostic markers in pediatric MS.

scholarly journals Protein Expression Profiles in an Endosymbiotic Cyanobacterium Revealed by a Proteomic Approach

2006 ◽  
Vol 19 (11) ◽  
pp. 1251-1261 ◽  
Author(s):  
Martin Ekman ◽  
Petter Tollbäck ◽  
Johan Klint ◽  
Birgitta Bergman
Keyword(s):  
Mass Spectrometry ◽  
Protein Expression ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Calvin Cycle ◽  
Pentose Phosphate ◽  
Free Living ◽  
Two Dimensional Gel Electrophoresis ◽  
Proteomic Approach ◽  
Nostoc Strain

Molecular mechanisms behind adaptations in the cyano-bacterium (Nostoc sp.) to a life in endosymbiosis with plants are still not clarified, nor are the interactions between the partners. To get further insights, the proteome of a Nostoc strain, freshly isolated from the symbiotic gland tissue of the angiosperm Gunnera manicata Linden, was analyzed and compared with the proteome of the same strain when free-living. Extracted proteins were separated by two-dimensional gel electrophoresis and were identified by matrix-assisted laser desorption/ionization-time of flight mass spectrometry combined with tandem mass spectrometry. Even when the higher percentage of differentiated cells (heterocysts) in symbiosis was compensated for, the majority of the proteins detected in the symbiotic cyanobacteria were present in the free-living counterpart, indicating that most cellular processes were common for both stages. However, differential expression profiling revealed a significant number of proteins to be down-regulated or missing in the symbiotic stage, while others were more abundant or only expressed in symbiosis. The differential protein expression was primarily connected to i) cell envelope-associated processes, including proteins involved in exopolysaccharide synthesis and surface and membrane associated proteins, ii) to changes in growth and metabolic activities (C and N), including upregulation of nitrogenase and proteins involved in the oxidative pentose phosphate pathway and downregu-lation of Calvin cycle enzymes, and iii) to the dark, micro-aerobic conditions offered inside the Gunnera gland cells, including changes in relative phycobiliprotein concentrations. This is the first comprehensive analysis of proteins in the symbiotic state.

scholarly journals MicroRNA expression classification for pediatric multiple sclerosis identification

2021 ◽  
Author(s):  
Gabriella Casalino ◽  
Giovanna Castellano ◽  
Arianna Consiglio ◽  
Nicoletta Nuzziello ◽  
Gennaro Vessio
Keyword(s):  
Machine Learning ◽  
Multiple Sclerosis ◽  
Expression Profiles ◽  
Healthy Children ◽  
Multifactorial Diseases ◽  
Hyperactivity Disorder ◽  
Pediatric Multiple Sclerosis ◽  
Mirna Expression Profiles ◽  
Selection Algorithms ◽  
Expression Classification

Abstract MicroRNAs (miRNAs) are a set of short non-coding RNAs that play significant regulatory roles in cells. The study of miRNA data produced by Next-Generation Sequencing techniques can be of valid help for the analysis of multifactorial diseases, such as Multiple Sclerosis (MS). Although extensive studies have been conducted on young adults affected by MS, very little work has been done to investigate the pathogenic mechanisms in pediatric patients, and none from a machine learning perspective. In this work, we report the experimental results of a classification study aimed at evaluating the effectiveness of machine learning methods in automatically distinguishing pediatric MS from healthy children, based on their miRNA expression profiles. Additionally, since Attention Deficit Hyperactivity Disorder (ADHD) shares some cognitive impairments with pediatric MS, we also included patients affected by ADHD in our study. Encouraging results were obtained with an artificial neural network model based on a set of features automatically selected by feature selection algorithms. The results obtained show that models developed on automatically selected features overcome models based on a set of features selected by human experts. Developing an automatic predictive model can support clinicians in early MS diagnosis and provide new insights that can help find novel molecular pathways involved in MS disease.

scholarly journals Novel circulating protein biomarkers for thyroid cancer determined through data-independent acquisition mass spectrometry

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9507
Author(s):  
Dandan Li ◽  
Jie Wu ◽  
Zhongjuan Liu ◽  
Ling Qiu ◽  
Yimin Zhang
Keyword(s):  
Mass Spectrometry ◽  
Area Under The Curve ◽  
High Sensitivity ◽  
Factor H ◽  
Complement Factor ◽  
Protein Biomarkers ◽  
Serum Samples ◽  
Data Independent Acquisition ◽  
Median Serum ◽  
And Control

Background Distinguishing between different types of thyroid cancers (TC) remains challenging in clinical laboratories. As different tumor types require different clinical interventions, it is necessary to establish new methods for accurate diagnosis of TC. Methods Proteomic analysis of the human serum was performed through data-independent acquisition mass spectrometry for 29 patients with TC (stages I–IV): 13 cases of papillary TC (PTC), 10 cases of medullary TC (MTC), and six cases follicular TC (FTC). In addition, 15 patients with benign thyroid nodules (TNs) and 10 healthy controls (HCs) were included in this study. Subsequently, 17 differentially expressed proteins were identified in 291 patients with TC, including 247 with PTC, 38 with MTC, and six with FTC, and 69 patients with benign TNs and 176 with HC, using enzyme-linked immunosorbent assays. Results In total, 517 proteins were detected in the serum samples using an Orbitrap Q-Exactive-plus mass spectrometer. The amyloid beta A4 protein, apolipoprotein A-IV, gelsolin, contactin-1, gamma-glutamyl hydrolase, and complement factor H-related protein 1 (CFHR1) were selected for further analysis. The median serum CFHR1 levels were significantly higher in the MTC and FTC groups than in the PTC and control groups (P < 0.001). CFHR1 exhibited higher diagnostic performance in distinguishing patients with MTC from those with PTC (P < 0.001), with a sensitivity of 100.0%, specificity of 85.08%, area under the curve of 0.93, and detection cut-off of 0.92 ng/mL. Conclusion CFHR1 may serve as a novel biomarker to distinguish PTC from MTC with high sensitivity and specificity.

scholarly journals New insights into Trypanosoma cruzi evolution and genotyping based on system-wide protein expression profiles (PhyloQuant)

2020 ◽  
Author(s):  
Simon Ngao Mule ◽  
Andrè Guillherme da Costa Martins ◽  
Livia Rosa-Fernandes ◽  
Gilberto Santos de Oliveira ◽  
Carla Monadeli Rodrigues ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Trypanosoma Cruzi ◽  
Protein Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Shotgun Proteomics ◽  
Close Correlation ◽  
Evolutionary Relationships ◽  
Trypanosome Species ◽  
Protein Expression Profiles

AbstractThe etiological agent of Chagas disease, Trypanosoma cruzi, is subdivided into seven genetic subdivisions termed discrete typing units (DTUs), TcI-TcVI and Tcbat. The relevance of T. cruzi genetic diversity to the variable clinical course of the disease, virulence, pathogenicity, drug resistance, transmission cycles and ecological distribution justifies the concerted efforts towards understanding the population structure of T. cruzi strains. In this study, we introduce a novel approach termed ‘phyloquant’ to infer the evolutionary relationships and assignment of T. cruzi strains to their DTUs based on differential protein expression profiles evidenced by bottom up large scale mass spectrometry-based quantitative proteomic features. Mass spectrometry features analyzed using parsimony (MS1, iBAQ and LFQ) showed a close correlation between protein expression and T. cruzi DTUs and closely related trypanosome species. Although alternative topologies with minor differences between the three MS features analyzed were demonstrated, we show congruence to well accepted evolutionary relationships of T. cruzi DTUs; in all analyses TcI and Tcbat were sister groups, and the parental nature of genotype TcII and the hybrid genotypes TcV/TcVI were corroborated. Character mapping of genetic distance matrices based on phylogenetics and phyloquant clustering showed statistically significant correlations. We propose the first quantitative shotgun proteomics approach as a complement strategy to the genetic-based assignment of T. cruzi strains to DTUs and evolutionary inferences. Moreover, this approach allows for the identification of differentially regulated and strain/DTU/species-specific proteins, with potential application in the identification of strain/DTU specific biomarkers and candidate therapeutic targets. In addition, the correlation between multi-gene protein expression and divergence of trypanosome species was evaluated, adding another level to understand the genetic subdivisions among T. cruzi DTUs.

scholarly journals Proteomic profiles of unilateral cryptorchidism in pigs at different ages using MALDI-TOF mass spectrometry and in-gel digestion coupled with mass spectrometry (GeLC-MS/MS) approaches

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Nathamon Yimpring ◽  
Sittiruk Roytrakul ◽  
Janthima Jaresitthikunchai ◽  
Narumon Phaonakrop ◽  
Sucheewin Krobthong ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Expression ◽  
Western Blot ◽  
Blot Analysis ◽  
Western Blot Analysis ◽  
Expression Profiles ◽  
Tumor Necrosis Factor Receptor ◽  
Principal Component ◽  
Peptide Mass ◽  
Different Ages

Abstract Background Cryptorchidism is a condition that occurs when one or both testes fail to descend into the scrotum. It is a common congenital disorder, causing economic loss in pig production. However, there have been only limited studies of differential protein expression profiles in undescended testes (UDTs) in the abdomen and descended testes (DTs) in cryptorchid pigs, especially at the peptidome and proteome levels. The present study aimed to analyze the peptidome of UDTs and DTs in unilateral cryptorchid pigs aged 1–2, 6, 15 and 20 weeks and in normal testes of healthy pigs aged 1–2 and 12 weeks, using peptide mass fingerprinting and three-dimensional principal component analysis (3D-PCA) with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, and to identify potential protein candidates, using in-gel digestion coupled with mass spectrometry (GeLC-MS/MS). Western blot analysis was used to verify protein expression. Protein sequence was affirmed by liquid chromatography–tandem mass spectrometry. Results A PCA plot showed a discrete cluster for each sample group. Peptide mass fingerprints (PMFs) demonstrated unique peptide fragments in UDTs at different ages. A number of markedly expressed proteins from GeLC-MS/MS were identified, including the multifunctional tumor necrosis factor receptor superfamily member 18 (TNFRSF18), in DTs at 1–2 and 6 weeks and in UDTs at 15 and 20 weeks of age. Using western blot analysis, high expression of TNFRSF18 was observed in the UDTs at 15 weeks. Using the STITCH database, this protein was found to be related to apoptosis, corresponding to the previous report in the UDTs at the same age. Conclusions The present study revealed the specific PMFs and clusters for porcine cryptorchidism, and a novel protein, TNFRSF18, associated with the disease mechanism. These results could provide further insights into the pathogenesis of the disease.

A Potential Biomarker Panel of Multiple Myeloma Identified Using Label-Free Mass Spectrometry-Based Quantitative Proteomics

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2890-2890
Author(s):  
Attaya Suvannasankha ◽  
Colin D. Crean ◽  
Heather M. Sahm ◽  
Rafat Abonour ◽  
Sherif Farag ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Multiple Myeloma ◽  
Protein Expression ◽  
Plasma Cells ◽  
Expression Profiles ◽  
Peptide Identification ◽  
Clinical Samples ◽  
Normal Plasma ◽  
Potential Biomarker ◽  
Significant Difference

Abstract Abstract 2890 Background: Multiple myeloma is an incurable and fatal hematologic malignancy. Recent gene microarray studies showed distinct gene expression profiles defining MM subgroups and their association with cytogenetic abnormalities and treatment outcome. However, aside from transcriptional control, a variety of post-transcriptional/post-translational modifications likely play an important role in regulating protein expression and function, and ultimately may prove informative for predicting tumor behavior. Objectives: We hypothesize that the protein profile in MM cells is different than normal plasma cells. Methodology: Normal plasma cells and myeloma cells were isolated using CD138 immune magnetic beads from bone marrow aspirates from healthy volunteers or patients with newly diagnosed MM, respectively. CD138+ cells were frozen and subsequently analyzed in one batch. Proteins were digested by trypsin. Tryptic peptides were injected onto an HPLC system and analyzed on a Thermo-Fisher LTQ mass spectrometer. Peptide identification and quantification were carried out using proprietary algorithms. Identified proteins were categorized into priority groups based on the quality of the peptide identification by tandem mass spectrometry. Proteins with significant changes in expression level were further analyzed by bioinformatics tools for the determination of the biological significance. Results: In the discovery phase of this study, 433 proteins were identified and their expression levels were quantitatively compared. 169 of these proteins demonstrated a significant difference between normal plasma cells and MM cells. Among the significantly changed proteins, 18 were identified and quantified with high confidence, and were therefore chosen for further validation. The identified proteins are known to be involved in the glycolysis/gluconeogenesis pathway, the oxidative phosphorylation pathway, cysteine metabolism and the pentose phosphate pathway. None of these proteins are known to be of prognostic value or being currently targeted for therapy in MM. A high-throughput LC/MS-based multiple-reaction-monitoring (MRM) assay for quantitative validation of these candidates with clinical samples is ongoing. To date, using the MRM assay, we were able to detect MRM peptides for 13 of the 18 targeted proteins in clinical samples. The quantification of these peptides will be further confirmed using a separate set of clinical samples. Conclusion: Significant differences in protein expression were observed between MM and normal plasma cells. The study presents an important step toward using proteomics as a tool to develop diagnostic and/or prognostic biomarkers in the clinical setting. However, both follow-up analytical and clinical validations are required before they can serve as disease-specific biomarkers. Disclosures: Abonour: Celgene: Membership on an entity's Board of Directors or advisory committees.

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