Temperature Dependence of Desorbed Ions and Neutrals and Ionization Mechanism of Matrix-Assisted Laser Desorption/Ionization

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022

The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.

Novel Ag-modified vanadate nanosheets for determination of small organic molecules with laser desorption ionization mass spectrometry

Laser desorption ionization mass spectrometry (LDI-MS) aroused intensive concerns for the merits of label-free and high-throughput analysis. Here, we designed a silver nanoparticles (AgNP)-modified indium vanadate nanosheets with doping samarium (AgNP@InVO4:Sm) nanosheets. The developed AgNP@InVO4:Sm nanosheets (AIVON) were synthesized based on the microemulsion-mediated solvothermal method and ultraviolet-assisted in situ formation of AgNP, then for the first time applied as a matrix in LDI-MS analysis. With the advantages including enhanced MS signal, little matrix-related background, high reproducibility, and good salt tolerance, AIVON exhibited much better prospect than non-modified indium vanadate nanosheets with doping samarium (IVON) and traditional organic matrix, thus allowing sensitive MS detection for a wide range of low-molecular-weight (LMW) molecules. Moreover, by coupling with headspace sampling thin-film microextraction (TFME), a kind of representative pollutant chlorophenols were identified and quantified via AIVON-assisted LDI-MS in environmental and biological samples. Volatile LMW pollutants could be preconcentrated after TFME, hence a sensitive and rapid assay with negligible sample matrix effect was realized by using AIVON-assisted LDI-MS. It is anticipated that this novel nano-matrix AIVON and the proposed TFME coupling detection strategy were of competitive merits for LDI-MS analysis in the fields of environment, biomedicine, and agriculture.

Experimental and Computational Study of Aminoacridines as MALDI(-)-MS Matrix Materials for the Analysis of Complex Samples

Monoaminoacridines (1-, 2-, 3-, 4-, and 9-aminoacridine) were studied for suitability as matrices in the negative ion mode matrix-assisted laser desorption/ionization mass spectrometry (MALDI(-)-MS) analysis of various samples. This is the first study to examine 1-, 2-, and 4-aminoacridine as potential matrix material candidates for MALDI(-)-MS. In addition, spectral (UV-Vis absorption and fluorescence), proton transfer-related (basicity and autoprotolysis), and crystallization properties of these compounds were characterized experimentally and/or computationally. For testing the capabilities of these aminoacridines as matrix materials, four samples related to cultural heritage materials-stearic acid, colophony resin, dyer's madder dye, and a resinous case-study sample from a shipwreck-were analyzed with MALDI(-)-MS. A novel algorithm (implemented as an executable Python script) for MS data analysis was developed to compare the five matrix materials and to help mass spectrometrists rapidly identify peaks originating from the sample and matrix material. It was determined that all five of the studied aminoacridines can successfully be used as matrix materials in MALDI(-)-MS analysis. As an interesting finding, in several cases, the best mass spectra were obtained by using a relatively small amount of matrix material mixed with an excess amount of sample. 3- and 4-aminoacridine outperformed the other aminoacridines in the ease of obtaining acceptable spectra, average number of ions identified in the mass spectra, and low dependence of the sample-to-matrix mass ratio on experimental results.

Validation of MALDI-MS imaging data of selected membrane lipids in murine brain with and without laser postionization by quantitative nano-HPLC-MS using laser microdissection

MALDI mass spectrometry imaging (MALDI-MSI) is a widely used technique to map the spatial distribution of molecules in sectioned tissue. The technique is based on the systematic generation and analysis of ions from small sample volumes, each representing a single pixel of the investigated sample surface. Subsequently, mass spectrometric images for any recorded ion species can be generated by displaying the signal intensity at the coordinate of origin for each of these pixels. Although easily equalized, these recorded signal intensities, however, are not necessarily a good measure for the underlying amount of analyte and care has to be taken in the interpretation of MALDI-MSI data. Physical and chemical properties that define the analyte molecules’ adjacencies in the tissue largely influence the local extraction and ionization efficiencies, possibly leading to strong variations in signal intensity response. Here, we inspect the validity of signal intensity distributions recorded from murine cerebellum as a measure for the underlying molar distributions. Based on segmentation derived from MALDI-MSI measurements, laser microdissection (LMD) was used to cut out regions of interest with a homogenous signal intensity. The molar concentration of six exemplary selected membrane lipids from different lipid classes in these tissue regions was determined using quantitative nano-HPLC-ESI-MS. Comparison of molar concentrations and signal intensity revealed strong deviations between underlying concentration and the distribution suggested by MSI data. Determined signal intensity response factors strongly depend on tissue type and lipid species.