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Mass spectrometry (MS), a core technology for proteomics and metabolomics, is currently being developed for clinical applications. The identification of microorganisms in clinical samples using matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry (MALDI-TOF MS) is a representative MS-based proteomics application that is relevant to daily clinical practice. This technology has the advantages of convenience, speed, and accuracy when compared with conventional biochemical methods. MALDI-TOF MS can shorten the time used for microbial identification by about 1 day in routine workflows. Sample preparation from microbial colonies has been improved, increasing the accuracy and speed of identification. MALDI-TOF MS is also used for testing blood, cerebrospinal fluid, and urine, because it can directly identify the microorganisms in these liquid samples without prior culture or subculture. Thus, MALDI-TOF MS has the potential to improve patient prognosis and decrease the length of hospitalization and is therefore currently considered an essential tool in clinical microbiology. Furthermore, MALDI-TOF MS is currently being combined with other technologies, such as flow cytometry, to expand the scope of clinical applications.

Detection of SARS-CoV-2 using RT–PCR and other advanced methods can achieve high accuracy. However, their application is limited in countries that lack sufficient resources to handle large-scale testing during the COVID-19 pandemic. Here, we describe a method to detect SARS-CoV-2 in nasal swabs using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and machine learning analysis. This approach uses equipment and expertise commonly found in clinical laboratories in developing countries. We obtained mass spectra from a total of 362 samples (211 SARS-CoV-2-positive and 151 negative by RT–PCR) without prior sample preparation from three different laboratories. We tested two feature selection methods and six machine learning approaches to identify the top performing analysis approaches and determine the accuracy of SARS-CoV-2 detection. The support vector machine model provided the highest accuracy (93.9%), with 7% false positives and 5% false negatives. Our results suggest that MALDI-MS and machine learning analysis can be used to reliably detect SARS-CoV-2 in nasal swab samples.SARS-CoV-2 is reliably detected in nasal swab samples using mass spectrometry and machine learning analysis.

First introduced into clinical microbiology laboratories in Europe, MALDI-TOF MS is being rapidly embraced by laboratories around the globe. Although it has multiple applications, its widespread adoption in clinical microbiology relates to its use as an inexpensive, easy, fast, and accurate method for identification of grown bacteria and fungi based on automated analysis of the mass distribution of bacterial proteins. This review provides a historical perspective on this new technology. Modern applications in the clinical microbiology laboratory are reviewed with a focus on the most recent publications in the field. Identification of aerobic and anaerobic bacteria, mycobacteria, and fungi are discussed, as are applications for testing urine and positive blood culture bottles. The strengths and limitations of MALDI-TOF MS applications in clinical microbiology are also addressed. MALDI-TOF MS is a tool for rapid, accurate, and cost-effective identification of cultured bacteria and fungi in clinical microbiology. The technology is automated, high throughput, and applicable to a broad range of common as well as esoteric bacteria and fungi. MALDI-TOF MS is an incontrovertibly beneficial technology for the clinical microbiology laboratory.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can simultaneously record the lateral distribution of numerous biomolecules in tissue slices, but its sensitivity is restricted by limited ionization. We used a wavelength-tunable postionization laser to initiate secondary MALDI-like ionization processes in the gas phase. In this way, we could increase the ion yields for numerous lipid classes, liposoluble vitamins, and saccharides, imaged in animal and plant tissue with a 5-micrometer-wide laser spot, by up to two orders of magnitude. Critical parameters for initiation of the secondary ionization processes are pressure of the cooling gas in the ion source, laser wavelength, pulse energy, and delay between the two laser pulses. The technology could enable sensitive MALDI-MS imaging with a lateral resolution in the low micrometer range.

Objective Knee osteoarthritis (OA) is a heterogeneous, complex joint pathology of unknown aetiology. Biomarkers have been widely used to investigate OA but currently available biomarkers lack specificity and sensitivity. Therefore, novel biomarkers are needed to better understand the pathophysiological processes of OA initiation and progression. Methods Surface enhanced laser desorption/ionisation-time of flight-mass spectrometry proteomic technique was used to analyse protein expression levels in 284 serum samples from patients with knee OA classified according to Kellgren and Lawrence (K&L) score (0–4). OA serum samples were also compared to serum samples provided by healthy individuals (negative control subjects; NC; n=36) and rheumatoid arthritis (RA) patients (n=25). Proteins that gave similar signal in all K&L groups of OA patients were ignored, whereas proteins with increased or decreased levels of expression were selected for further studies. Results Two proteins were found to be expressed at higher levels in sera of OA patients at all four K&L scores compared to NC and RA, and were identified as V65 vitronectin fragment and C3fpeptide. Of the two remaining proteins, one showed increased expression (unknown protein at m/z of 3762) and the other (identified as connective tissue-activating peptide III protein) was decreased in K&L scores >2 subsets compared to NC, RA and K&L scores 0 or 1 subsets. Conclusion The authors detected four unexpected biomarkers (V65 vitronectin fragment, C3f peptide, CTAP-III and m/z 3762 protein) that could be relevant in the pathophysiological process of OA as having significant correlation with parameters reflecting local inflammation and bone remodelling, as well as decrease in cartilage turnover.

Matrix-assisted laser desorption–ionization mass spectrometry imaging in transmission-mode geometry (t-MALDI–MSI) can provide molecular information with a pixel size of 1 µm and smaller, which makes this label-free method highly interesting for characterizing the chemical composition of tissues and cells on a (sub)cellular level. However, a major hindrance for wider use of the technology is the reduced ion abundance at small pixel sizes. Here we mitigate this problem by use of laser-induced post-ionization (MALDI-2) and by adapting a t-MALDI-2 ion source to an Orbitrap mass analyzer. We demonstrate the crucial sensitivity and accuracy boosts that are achieved with this combination by visualizing the distribution of numerous phospho- and glycolipids in mouse cerebellum and kidney slices, and in cultured Vero B4 cells. With brain tissue, a pixel size of 600 nm was achieved. Our method could constitute a valuable new tool for research in cell biology and biomedicine.

Abstract Until recently, microbial identification in clinical diagnostic laboratories has mainly relied on conventional phenotypic and gene sequencing identification techniques. The development of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) devices has revolutionized the routine identification of microorganisms in clinical microbiology laboratories by introducing an easy, rapid, high throughput, low-cost, and efficient identification technique. This technology has been adapted to the constraint of clinical diagnostic laboratories and has the potential to replace and/or complement conventional identification techniques for both bacterial and fungal strains. Using standardized procedures, the resolution of MALDI-TOF MS allows accurate identification at the species level of most Gram-positive and Gram-negative bacterial strains with the exception of a few difficult strains that require more attention and further development of the method. Similarly, the routine identification by MALDI-TOF MS of yeast isolates is reliable and much quicker than conventional techniques. Recent studies have shown that MALDI-TOF MS has also the potential to accurately identify filamentous fungi and dermatophytes, providing that specific standardized procedures are established for these microorganisms. Moreover, MALDI-TOF MS has been used successfully for microbial typing and identification at the subspecies level, demonstrating that this technology is a potential efficient tool for epidemiological studies and for taxonomical classification. Use of MALDI-TOF mass spectrometry in routine microbial identification increased much during last years and it is time to summarize and review all available data, to help clinical microbiologist to use this quantum leap technology.

A growing appreciation of the importance of cellular metabolism and revelations concerning the extent of cell–cell heterogeneity demand metabolic characterization of individual cells. We present SpaceM, an open-source method for in situ single-cell metabolomics that detects >100 metabolites from >1,000 individual cells per hour, together with a fluorescence-based readout and retention of morpho-spatial features. We validated SpaceM by predicting the cell types of cocultured human epithelial cells and mouse fibroblasts. We used SpaceM to show that stimulating human hepatocytes with fatty acids leads to the emergence of two coexisting subpopulations outlined by distinct cellular metabolic states. Inducing inflammation with the cytokine interleukin-17A perturbs the balance of these states in a process dependent on NF-κB signaling. The metabolic state markers were reproduced in a murine model of nonalcoholic steatohepatitis. We anticipate SpaceM to be broadly applicable for investigations of diverse cellular models and to democratize single-cell metabolomics.SpaceM combines light microscopy and MALDI-imaging mass spectrometry to enable single-cell metabolic profiling of cultured cells. SpaceM reveals coexisting metabolic states of hepatocytes and aims to democratize single-cell metabolomics.

in mass spectrometry have enabled the investigation of various biological systems by directly analyzing diverse sets of biomolecules (i.e., proteins, lipids, and carbohydrates), thus making a significant impact on the life sciences field. Over the past decade, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been widely utilized as a rapid and reliable method for the identification of microorganisms. MALDI-TOF MS has come into widespread use despite its relatively low resolving power (full width at half maximum, FWHM: < 5,000) and its incompatibility with tandem MS analysis, features with which other high-resolution mass spectrometers are equipped. Microbial identification is achieved by searching databases containing mass spectra of peptides and proteins extracted from microorganisms of interest, using scoring algorithms to match analyzed spectra with reference spectra. In this paper, we give a brief overview of the diverse applications of rapid and robust MALDI-TOF MS-based techniques for microbial identification in a variety of fields, such as clinical diagnosis and environmental and food monitoring. We also describe the fundamental principles of MALDI-TOF MS. The general specifications of the two major MS-based microbial identification systems available in the global market (BioTyper® and VITEK® MS Plus) and the distribution of these instruments in Republic of Korea are also discussed. The current review provides an understanding of this emerging microbial identification and classification technology and will help bacteriologists and cell biologists take advantage of this powerful technique.

Mass spectrometry is a central analytical technique for protein research and for the study of biomolecules in general. Driven by the need to identify, characterize, and quantify proteins at ever increasing sensitivity and in ever more complex samples, a wide range of new mass spectrometry-based analytical platforms and experimental strategies have emerged. Here we review recent advances in mass spectrometry instrumentation in the context of current and emerging research strategies in protein science.