Mass Spectrometry in Clinical Diagnostics

2017 ◽  
Vol 58 ◽  
pp. 98-110 ◽  
Author(s):  
Joanna Piechowicz ◽  
Agnieszka Gajewska-Naryniecka ◽  
Maciej Kukula ◽  
Jerzy Wiśniewski ◽  
Andrzej Gamian
2000 ◽  
Vol 5 (4) ◽  
pp. 341-348 ◽  
Author(s):  
JAMES LEUSHNER ◽  
NORMAN H. L. CHIU

2020 ◽  
Vol 58 (6) ◽  
pp. 883-896 ◽  
Author(s):  
Muhammad Zubair Israr ◽  
Dennis Bernieh ◽  
Andrea Salzano ◽  
Shabana Cassambai ◽  
Yoshiyuki Yazaki ◽  
...  

AbstractBackgroundMatrix-assisted laser desorption ionisation (MALDI) mass spectrometry (MS) has been used for more than 30 years. Compared with other analytical techniques, it offers ease of use, high throughput, robustness, cost-effectiveness, rapid analysis and sensitivity. As advantages, current clinical techniques (e.g. immunoassays) are unable to directly measure the biomarker; rather, they measure secondary signals. MALDI-MS has been extensively researched for clinical applications, and it is set for a breakthrough as a routine tool for clinical diagnostics.ContentThis review reports on the principles of MALDI-MS and discusses current clinical applications and the future clinical prospects for MALDI-MS. Furthermore, the review assesses the limitations currently experienced in clinical assays, the advantages and the impact of MALDI-MS to transform clinical laboratories.SummaryMALDI-MS is widely used in clinical microbiology for the screening of microbial isolates; however, there is scope to apply MALDI-MS in the diagnosis, prognosis, therapeutic drug monitoring and biopsy imaging in many diseases.OutlookThere is considerable potential for MALDI-MS in clinic as a tool for screening, profiling and imaging because of its high sensitivity and specificity over alternative techniques.


2014 ◽  
Vol 80 (14) ◽  
pp. 4234-4241 ◽  
Author(s):  
Maria-Theresia Gekenidis ◽  
Patrick Studer ◽  
Simone Wüthrich ◽  
René Brunisholz ◽  
David Drissner

ABSTRACTA well-accepted method for identification of microorganisms uses matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) coupled to analysis software which identifies and classifies the organism according to its ribosomal protein spectral profile. The method, called MALDI biotyping, is widely used in clinical diagnostics and has partly replaced conventional microbiological techniques such as biochemical identification due to its shorter time to result (minutes for MALDI biotyping versus hours or days for classical phenotypic or genotypic identification). Besides its utility for identifying bacteria, MS-based identification has been shown to be applicable also to yeasts and molds. A limitation to this method, however, is that accurate identification is most reliably achieved on the species level on the basis of reference mass spectra, making further phylogenetic classification unreliable. Here, it is shown that combining tryptic digestion of the acid/organic solvent extracted (classical biotyping preparation) and resolubilized proteins, nano-liquid chromatography (nano-LC), and subsequent identification of the peptides by MALDI-tandem TOF (MALDI-TOF/TOF) mass spectrometry increases the discrimination power to the level of subspecies. As a proof of concept, using this targeted proteomics workflow, we have identified subspecies-specific biomarker peptides for threeSalmonellasubspecies, resulting in an extension of the mass range and type of proteins investigated compared to classical MALDI biotyping. This method therefore offers rapid and cost-effective identification and classification of microorganisms at a deeper taxonomic level.


2012 ◽  
Vol 105 ◽  
pp. 32-38 ◽  
Author(s):  
Uwe Christians ◽  
Jacek Klepacki ◽  
Touraj Shokati ◽  
Jost Klawitter ◽  
Jelena Klawitter

2021 ◽  
Author(s):  
Andrew T Rajczewski ◽  
Subina T Mehta ◽  
Dinh Duy An Ngyuen ◽  
Björn Andreas Grüning ◽  
James E Johnson ◽  
...  

The Coronavirus Disease 2019 (COVID19) global pandemic has had a profound, lasting impact on the world's population. A key aspect to providing care for those with COVID19 and checking its further spread is early and accurate diagnosis of infection, which has been generally done via methods for amplifying and detecting viral RNA molecules. Detection and quantitation of peptides using targeted mass spectrometry-based strategies has been proposed as an alternative diagnostic tool due to direct detection of molecular indicators from non-invasively collected samples as well as the potential for high-throughput analysis in a clinical setting; many studies have revealed the presence of viral peptides within easily accessed patient samples. However, evidence suggests that some viral peptides could serve as better indicators of COVID19 infection status than others, due to potential misidentification of peptides derived from human host proteins, poor spectral quality, high limits of detection etc. In this study we have compiled a list of 636 peptides identified from Sudden Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples, including from in vitro and clinical sources. These datasets were rigorously analyzed using automated, Galaxy-based workflows containing tools such as PepQuery, BLAST-P, and the Multi-omic Visualization Platform as well as the open-source tools MetaTryp and Proteomics Data Viewer (PDV). Using PepQuery for confirming peptide spectrum matches, we were able to narrow down the 639 peptide possibilities to 87 peptides which were most robustly detected and specific to the SARS-CoV-2 virus. The specificity of these sequences to coronavirus taxa was confirmed using Unipept and BLAST-P. Through stringent p-value cutoff combined with manual verification of peptide spectrum match quality, 4 peptides derived from the nucleocapsid phosphoprotein and membrane protein were found to be most robustly detected across all cell culture and clinical samples, including those collected non-invasively. We propose that these peptides would be of the most value for clinical proteomics applications seeking to detect COVID-19 from a variety of sample types. We also contend that samples taken from the upper respiratory tract and oral cavity have the highest potential for diagnosis of SARS-CoV-2 infection from easily collected patient samples using mass spectrometry-based proteomics assays.


2019 ◽  
Vol 65 (4) ◽  
pp. 510-513 ◽  
Author(s):  
Felix Leung ◽  
Livia S Eberlin ◽  
Kristina Schwamborn ◽  
Ron M A Heeren ◽  
Nicholas Winograd ◽  
...  

2013 ◽  
Vol 420 ◽  
pp. 11-22 ◽  
Author(s):  
Hui Ye ◽  
Erin Gemperline ◽  
Lingjun Li

2019 ◽  
Vol 92 (1) ◽  
pp. 183-202 ◽  
Author(s):  
Devin J. Swiner ◽  
Sierra Jackson ◽  
Benjamin J. Burris ◽  
Abraham K. Badu-Tawiah

Catalysts ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 833 ◽  
Author(s):  
Rosulek ◽  
Darebna ◽  
Pompach ◽  
Slavata ◽  
Novak

A large number of different enzyme immobilization techniques are used in the field of life sciences, clinical diagnostics, or biotechnology. Most of them are based on a chemically mediated formation of covalent bond between an enzyme and support material. The covalent bond formation is usually associated with changes of the enzymes’ three-dimensional structure that can lead to reduction of enzyme activity. The present work demonstrates a potential of an ambient ion-landing technique to effectively immobilize enzymes on conductive supports for direct matrix-assisted laser desorption/ionization (MALDI) mass spectrometry analyses of reaction products. Ambient ion landing is an electrospray-based technique allowing strong and stable noncovalent and nondestructive enzyme deposition onto conductive supports. Three serine proteolytic enzymes including trypsin, α-chymotrypsin, and subtilisin A were immobilized onto conductive indium tin oxide glass slides compatible with MALDI mass spectrometry. The functionalized MALDI chips were used for in situ time-limited proteolysis of proteins and protein–ligand complexes to monitor their structural changes under different conditions. The data from limited proteolysis using MALDI chips fits to known or predicted protein structures. The results show that functionalized MALDI chips are sensitive, robust, and fast and might be automated for general use in the field of structural biology.


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