Dataset Information

Simple Protein Analysis by Droplet Paper Spray Ionization Mass Spectrometry with Polyolefin Silica-Based Paper.

ABSTRACT: Paper spray ionization mass spectrometry (PSI MS) has emerged as a notable method for the rapid analysis of biological samples. However, the typical cellulose-based paper tip is incompatible with protein detection due to the strong interaction between cellulose hydroxyl groups and proteins. In this study, we utilized a commercially available polyolefin-based synthetic paper, Teslin^®, as an alternative PSI substrate for simple protein analysis. We have named this method "droplet PSI" MS, as the aqueous protein solution droplet retains its shape on the Teslin^® paper tip. For droplet PSI, no further chemical pretreatment was necessary for the Teslin^® substrate; the only required preparation was shaping the Teslin^® paper into a triangular tip. In droplet PSI MS, protein ion signals were instantly detected from a protein solution droplet upon applying a spray solvent in situ along with high voltage (HV). When compared with conventional PSI MS, our method demonstrated superior sensitivity. The droplet PSI MS utilizing Teslin^® also showcased flexibility in real-time observation of protein alterations induced by an acid additive. Additionally, the effects of spray solvent composition and the application method were discussed.

SUBMITTER: An SJ

PROVIDER: S-EPMC10647424 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Simple Protein Analysis by Droplet Paper Spray Ionization Mass Spectrometry with Polyolefin Silica-Based Paper.

An Sung Jun SJ Kal Youngjoo Y Jeong Minjoo M Kang Sumin S Kwak Byeongho B Kim Hyunsoo H Ryu Shihyeon S Cha Sangwon S

Molecules (Basel, Switzerland) 20231030 21

Paper spray ionization mass spectrometry (PSI MS) has emerged as a notable method for the rapid analysis of biological samples. However, the typical cellulose-based paper tip is incompatible with protein detection due to the strong interaction between cellulose hydroxyl groups and proteins. In this study, we utilized a commercially available polyolefin-based synthetic paper, Teslin<sup>®</sup>, as an alternative PSI substrate for simple protein analysis. We have named this method "droplet PSI" M ...[more]

PMID: 37959759

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Project description:This study performs a chemical investigation of blood plasma samples from patients with and without fibromyalgia, combined with some of the symptoms and their levels of intensity used in the diagnosis of this disease. The symptoms evaluated were: visual analogue pain scale (VAS); fibromyalgia impact questionnaire (FIQ); Hamilton anxiety rating scale (HAM); Tampa Scale for Kinesiophobia (TAMPA); quality of life Questionnaire-physical and mental health (QL); and Pain Catastrophizing Scale (CAT). Plasma samples were analyzed by paper spray ionization mass spectrometry (PSI-MS). Spectral data were organized into datasets and related to each of the symptoms measured. The datasets were submitted to multivariate classification using supervised models such as principal component analysis with linear discriminant analysis (PCA-LDA), successive projections algorithm with linear discriminant analysis (SPA-LDA), genetic algorithm with linear discriminant analysis (GA-LDA) and their versions with quadratic discriminant analysis (PCA/SPA/GA-QDA) and support vector machines (PCA/SPA/GA-SVM). These algorithm combinations were performed aiming the best class separation. Good discrimination between the controls and fibromyalgia samples were observed using PCA-LDA, where the spectral data associated with the CAT symptom achieved 100% classification sensitivity, and associated with the VAS symptom achieved 100% classification specificity, with both symptoms at the moderate level of intensity. The spectral variable at 579 m/z was found to be substantially significant for classification according to the PCA loadings. According to the human metabolites database, this variable can be associated with a LysoPC compound, which comprises a class of metabolites already evidenced in other studies for fibromyalgia diagnosis. This study proposed an investigation of spectral data combined with clinical data to compare the classification ability of different datasets. The good classification results obtained confirm this technique is as a good analytical tool for the detection of fibromyalgia, and provides theoretical support for other studies about fibromyalgia diagnosis.

Dataset Information

Simple Protein Analysis by Droplet Paper Spray Ionization Mass Spectrometry with Polyolefin Silica-Based Paper.

Publications

Simple Protein Analysis by Droplet Paper Spray Ionization Mass Spectrometry with Polyolefin Silica-Based Paper.

Similar Datasets

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