Using MALDI-TOF MS coupled with a high-mass detector to directly analyze intact proteins in thyroid tissues

Identification of Escherichia coli strains using MALDI-TOF MS combined with long short-term memory neural networks

The current study aims to develop a new technique for the precise identification of Escherichia coli strains, utilizing matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with a long short-term memory (LSTM) neural network. A total of 48 Escherichia coli strains were isolated and cultured on tryptic soy agar medium for 24 hours for the generation of MALDI-TOF MS spectra. Eight hundred MALDI-TOF MS spectra were obtained per strain, resulting in a database of 38,400 spectra. Fifty percent of the data was utilized for LSTM neural network training, with fine-tuned parameters for strain-level identification. The other half served as the test set to assess model performance. Traditional PCA dimension reduction of MALDI-TOF MS spectra indicated 47 out of 48 strains to be unclassifiable. In contrast, the LSTM neural network demonstrated remarkable efficacy. After 20 training epochs, the model achieved a loss value of 0.0524, an accuracy of 0.999, a precision of 0.985, and a recall of 0.982. When tested on the unseen data, the model attained an overall accuracy of 92.24%. The integration of MALDI-TOF MS and LSTM neural network markedly enhances the identification of Escherichia coli strains. This innovative approach offers an effective and accurate tool for MALDI-TOF MS-based strain-level identification, thus expanding the analytical capabilities of microbial diagnostics.

Inhibiting Protein Aggregation Using Cellulose Nanocrystal in MALDI-TOF MS Analysis: Improving the Sensitivity and Repeatability of Intact Protein in Pueraria

Protein aggregation can induce low sensitivity and poor repeatability of matrix-assisted laser desorption/ionization time-of-fight mass spectrometry (MALDI-TOF MS) analysis for intact protein. Herein, we introduced a strategy to decrease protein aggregation in the sample solution by using cellulose nanocrystal (CNC). The results indicated that protein granule size was effectively reduced by adding CNC to the sample solution. Through MALDI-TOF MS analysis, the signal-to-noise ratio of [M + H]+ peak increased 2-fold, and the detection of limit was <10 μg/mL for intact protein. The CNC also contributed to excellent point-to-point repeatability for MALDI-TOF MS analysis with the coefficient of variation (CV) of 10.0% with CNC vs 48.9% without CNC in Hb solution. Also, the repeatability of Pueraria protein ion signals was improved by using CNC, and the CV with and without CNC was 16.1% and 39.6%, respectively. Moreover, protein ion intensity exhibited great linear relationship (y = 53.04x - 3.474, R2 = 0.9936) with the concentrations (ranging from 0.1 to 10 mg/mL) when using CNC. Further investigation revealed that m/z 19,000 and m/z 21,000 peaks of Pueraria could be used for the adulteration analysis and post-translational modification research, demonstrating our method has the potential for broad applications.

Mass Spectrometric (MS) Analysis of Proteins and Peptides

The human genome is sequenced and comprised of ~30,000 genes, making humans just a little bit more complicated than worms or flies. However, complexity of humans is given by proteins that these genes code for because one gene can produce many proteins mostly through alternative splicing and tissue-dependent expression of particular proteins. In addition, post-translational modifications (PTMs) in proteins greatly increase the number of gene products or protein isoforms. Furthermore, stable and transient interactions between proteins, protein isoforms/proteoforms and PTM-ed proteins (protein-protein interactions, PPI) add yet another level of complexity in humans and other organisms. In the past, all of these proteins were analyzed one at the time. Currently, they are analyzed by a less tedious method: mass spectrometry (MS) for two reasons: 1) because of the complexity of proteins, protein PTMs and PPIs and 2) because MS is the only method that can keep up with such a complex array of features. Here, we discuss the applications of mass spectrometry in protein analysis.

Derivatization Strategy for Simultaneous Molecular Imaging of Phospholipids and Low-Abundance Free Fatty Acids in Thyroid Cancer Tissue Sections

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has been applied in many fields for detecting and imaging a variety of metabolites. In cancer research, this fast-growing imaging method also helps to elucidate the connection between the changes of metabolites in the microenvironment and the proliferation and survival of cancer cells. Free fatty acids (FFAs) are a vital building block of phospholipids (PLs) that can serve as a second cellular messenger and provide nutrients in the cancer microenvironment. The metabolism process of FFAs and PLs is highly relevant to the initiation and progression of different cancers. To better understand the metabolism process in cancer tissues, simultaneously detecting and imaging FFAs and PLs is essential. Despite the crucial developments that have been performed in the field of lipids imaging, FFAs and PLs have rarely been detected and imaged simultaneously in positive ion mode with good detection sensitivity. In this work, an on-tissue derivatization method was used to add a permanently quaternary amine onto FFAs; then, the FFAs and PLs were simultaneously imaged in positive ion mode. The derivatized FFAs are suitable for detection in positive ion mode. In comparison with the traditional matrix and the previous derivatization method, our derivatization reagent has a higher sensitivity for imaging FFAs. In addition, for simultaneous imaging analysis of FFAs and PLs, the number of imaged FFAs and PLs is greater than that with the previous on-tissue derivatization method. This high-sensitivity on-tissue derivatization method was applied to detect and image PLs and fatty acids in thyroid cancer tissues. In the MSI experiment, FFA derivatives and PLs were imaged while molecular localization and tissue integrity were maintained. Meanwhile, the correlation between PLs and FFAs was also studied, and the results showed that the correlations between saturated FFAs of C16:0 and C18:0 and PLs are better than the correlations of unsaturated FFAs with PLs.