Detection, Differentiation and Subtyping of Botulinum Neurotoxins in Clinical Samples with Mass Spectrometry

2011 ◽  
pp. 83-97 ◽  
Author(s):  
John R. Barr ◽  
Suzanne R. Kalb ◽  
James L. Pirkle
Keyword(s):  
Mass Spectrometry ◽  
Clinical Samples ◽  
Botulinum Neurotoxins

scholarly journals Label-Free Mass Spectrometry-Based Quantification of Linker Histone H1 Variants in Clinical Samples

2020 ◽  
Vol 21 (19) ◽  
pp. 7330
Author(s):  
Roberta Noberini ◽  
Cristina Morales Torres ◽  
Evelyn Oliva Savoia ◽  
Stefania Brandini ◽  
Maria Giovanna Jodice ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Histone H1 ◽  
Histone Variants ◽  
Linker Histone ◽  
Clinical Samples ◽  
Label Free ◽  
Complex Samples ◽  
Linker Histone H1 ◽  
Ideal Tool ◽  
Free Quantification

Epigenetic aberrations have been recognized as important contributors to cancer onset and development, and increasing evidence suggests that linker histone H1 variants may serve as biomarkers useful for patient stratification, as well as play an important role as drivers in cancer. Although traditionally histone H1 levels have been studied using antibody-based methods and RNA expression, these approaches suffer from limitations. Mass spectrometry (MS)-based proteomics represents the ideal tool to accurately quantify relative changes in protein abundance within complex samples. In this study, we used a label-free quantification approach to simultaneously analyze all somatic histone H1 variants in clinical samples and verified its applicability to laser micro-dissected tissue areas containing as low as 1000 cells. We then applied it to breast cancer patient samples, identifying differences in linker histone variants patters in primary triple-negative breast tumors with and without relapse after chemotherapy. This study highlights how label-free quantitation by MS is a valuable option to accurately quantitate histone H1 levels in different types of clinical samples, including very low-abundance patient tissues.

Tissue 2-Hydroxyglutarate and Preoperative Seizures in Patients With Diffuse Gliomas

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012893
Author(s):  
Makoto Ohno ◽  
Yoshiharu Hayashi ◽  
Hiroaki Aikawa ◽  
Mitsuhiro Hayashi ◽  
Yasuji Miyakita ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Resolution Mass Spectrometry ◽  
Characteristic Curve ◽  
Structural Similarity ◽  
Tumor Location ◽  
Clinical Samples ◽  
Histopathological Diagnosis ◽  
Diffuse Glioma ◽  
Who Grade ◽  
Cutoff Value

ObjectiveMutant isocitrate dehydrogenase (IDH) 1/2 gene products gain a new ability to produce D-2-hydroxyglutarate (D2HG). IDH1/2 mutations are thought to be associated with seizures owing to the structural similarity between D2HG and glutamate. However, the effects of D2HG on seizures in clinical settings are not fully understood. We, therefore, sought to investigate the relationship between tissue 2-hydroxyglutarate (2HG) concentration and preoperative seizures using clinical samples.MethodsWe included consecutive 104 patients with diffuse glioma who underwent surgery from August 2008 to May 2016 and whose clinical presentation and IDH1/2 status were identified. The presence of preoperative seizures, tumor location, histopathological diagnosis, IDH1/2 status, and 1p/19q codeletion were assessed from the patient charts. Tissue 2HG concentration was measured using liquid chromatography–tandem mass spectrometry. To evaluate 2HG distribution without artefactual tissue disruption, we applied matrix-assisted laser desorption/ionization high resolution mass spectrometry imaging (MALDI–MSI) in 12 patients’ surgically resected samples. We assessed the correlation of preoperative seizures with tissue 2HG concentration, IDH1/2 status, WHO grade, and 1p/19q codeletion.ResultsTissue 2HG concentration was higher in IDH1/2 mutant tumors (IDH-Mut) than in IDH1/2 wildtype tumors (IDH-WT) (median: 4860 ng/mg vs 75 ng/mg) (p < 0.0001). MALDI–MSI could detect 2HG signals in IDH-Mut, but not in IDH-WT. Preoperative seizures were observed in 64.3% patients with IDH-Mut and 21.0% patients with IDH-WT (p < 0.0001). The optimal cutoff value of tissue 2HG concentration for predicting preoperative seizures was 1190 ng/mg, as calculated by the receiver operating characteristic curve. Increased preoperative seizure risk was only observed in tumors with 2HG concentration above the cutoff value among IDH-Mut (IDH-Mut with above the cutoff value: 71.4 % vs IDH-Mut with below the cutoff value: 28.6 %, p = 0.031). Multivariate analysis, including IDH1/2 mutation status, tissue 2HG concentration, WHO grade and 1p/19q codeletion, revealed that only increased tissue 2HG concentration was associated with preoperative seizures (odds ratio 5.86, 95% confidence interval 1.02–48.5, p = 0.048).ConclusionsWe showed that high tissue 2HG concentration was associated with preoperative seizures, suggesting that excess 2HG increases risk of preoperative seizures in IDH1/2 mutant tumors.

A simple equation to correct for gadolinium interference on plasma selenium measurement using inductively coupled plasma mass spectrometry

2020 ◽  
Vol 57 (3) ◽  
pp. 234-241
Author(s):  
Scott Wilschefski ◽  
Matthew Baxter ◽  
Gertruida Pool
Keyword(s):  
Mass Spectrometry ◽  
Inductively Coupled Plasma ◽  
Clinical Samples ◽  
Resonance Imaging ◽  
Simple Method ◽  
Plasma Selenium ◽  
Inductively Coupled ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Delays In Diagnosis

Background The measurement of selenium in human plasma is useful to assess deficiency or toxicity. The presence of gadolinium in clinical samples following administration of certain contrast agents used for magnetic resonance imaging can cause a significant positive bias in selenium results when measured using quadrupole inductively coupled plasma mass spectrometry (Q-ICP-MS). Methods A mathematical equation to correct for gadolinium interference was assessed using both patient samples and commercial quality control/external quality assurance (QC/EQA) materials spiked with gadolinium. Samples were analysed using an Agilent 7900 ICP-MS operated in ‘narrow peak’ (half-mass) mode. Accuracy was evaluated by comparing corrected selenium results with target concentrations. Results Corrected results were found to be accurate at all gadolinium concentrations tested (2, 4, 10 and 20 mg/L). Average recoveries ranged from 97.4 to 106.5%. Results for QC/EQA materials were within specified target ranges. Within-run imprecision was <3%, and between-run imprecision was <4.3%, demonstrating robustness. Conclusions The correction equation described here is a simple method to correct for gadolinium interference on plasma selenium measurement using ICP-MS. This approach eliminates the need for specimen recollections, and improves patient care by reducing laboratory turnaround times and preventing delays in diagnosis/treatment.

scholarly journals 383P A mass spectrometry-based assay for molecular profiling of gliomas and its validation on real-world clinical samples

2020 ◽  
Vol 31 ◽  
pp. S404-S405
Author(s):  
T. Wang ◽  
F. Tao ◽  
X. Li ◽  
Q. Duan ◽  
S. Chen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Real World ◽  
Molecular Profiling ◽  
Clinical Samples

From the Mouse to the Mass Spectrometer:  Detection and Differentiation of the Endoproteinase Activities of Botulinum Neurotoxins A−G by Mass Spectrometry

2005 ◽  
Vol 77 (13) ◽  
pp. 3916-3924 ◽  
Author(s):  
Anne E. Boyer ◽  
Hercules Moura ◽  
Adrian R. Woolfitt ◽  
Suzanne R. Kalb ◽  
Lisa G. McWilliams ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometer ◽  
Botulinum Neurotoxins

scholarly journals Discovery of Species-unique Peptide Biomarkers of Bacterial Pathogens by Tandem Mass Spectrometry-based Proteotyping

2020 ◽  
Vol 19 (3) ◽  
pp. 518-528 ◽  
Author(s):  
Roger Karlsson ◽  
Annika Thorsell ◽  
Margarita Gomila ◽  
Francisco Salvà-Serra ◽  
Hedvig E. Jakobsson ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Infectious Diseases ◽  
Respiratory Tract ◽  
Respiratory Tract Infections ◽  
Clinical Laboratory ◽  
Bacterial Pathogens ◽  
Clinical Samples ◽  
Tandem Ms ◽  
Adequate Treatment ◽  
Tract Infections

Mass spectrometry (MS) and proteomics offer comprehensive characterization and identification of microorganisms and discovery of protein biomarkers that are applicable for diagnostics of infectious diseases. The use of biomarkers for diagnostics is widely applied in the clinic and the use of peptide biomarkers is increasingly being investigated for applications in the clinical laboratory. Respiratory-tract infections are a predominant cause for medical treatment, although, clinical assessments and standard clinical laboratory protocols are time-consuming and often inadequate for reliable diagnoses. Novel methods, preferably applied directly to clinical samples, excluding cultivation steps, are needed to improve diagnostics of infectious diseases, provide adequate treatment and reduce the use of antibiotics and associated development of antibiotic resistance. This study applied nano-liquid chromatography (LC) coupled with tandem MS, with a bioinformatics pipeline and an in-house database of curated high-quality reference genome sequences to identify species-unique peptides as potential biomarkers for four bacterial pathogens commonly found in respiratory tract infections (RTIs): Staphylococcus aureus; Moraxella catarrhalis; Haemophilus influenzae and Streptococcus pneumoniae. The species-unique peptides were initially identified in pure cultures of bacterial reference strains, reflecting the genomic variation in the four species and, furthermore, in clinical respiratory tract samples, without prior cultivation, elucidating proteins expressed in clinical conditions of infection. For each of the four bacterial pathogens, the peptide biomarker candidates most predominantly found in clinical samples, are presented. Data are available via ProteomeXchange with identifier PXD014522. As proof-of-principle, the most promising species-unique peptides were applied in targeted tandem MS-analyses of clinical samples and their relevance for identifications of the pathogens, i.e. proteotyping, was validated, thus demonstrating their potential as peptide biomarker candidates for diagnostics of infectious diseases.

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.

A novel mass spectrometry method based on competitive non-covalent interaction for the detection of biomarkers

2018 ◽  
Vol 54 (76) ◽  
pp. 10726-10729 ◽  
Author(s):  
Jing Han ◽  
Yafeng Li ◽  
Lingpeng Zhan ◽  
Jinjuan Xue ◽  
Jie Sun ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Clinical Samples ◽  
Spectrometry Method ◽  
Sensitive Analysis ◽  
Mass Spectrometry Method ◽  
Covalent Interaction ◽  
Detection Of Biomarkers ◽  
Mass Tag

We report a novel MS platform based on competitive non-covalent interaction between ssDNA and a competitive mass tag towards AuNPs for the detection of biomarkers, which could be applicable to the sensitive analysis of clinical samples.

scholarly journals Measurement of glucose and fructose in clinical samples using gas chromatography/mass spectrometry

2010 ◽  
Vol 43 (1-2) ◽  
pp. 198-207 ◽  
Author(s):  
Paulin N. Wahjudi ◽  
Mary E. Patterson ◽  
Shu Lim ◽  
Jennifer K. Yee ◽  
Catherine S. Mao ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Gas Chromatography Mass Spectrometry ◽  
Clinical Samples ◽  
Chromatography Mass Spectrometry
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