Kimberly Y Kartowikromo, Jessica S Pizzo, Iffat Jerin, Ahmed M Hamid
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引用次数: 0
Abstract
Infectious diseases remain a leading global health concern, requiring rapid, precise, and cost-effective diagnostic approaches. Traditional diagnostic methods, such as culture-based techniques, serological assays, and molecular diagnostics, often have sensitivity, specificity, and time efficiency limitations. The emergence of mass spectrometry (MS)-based technologies, particularly matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) MS, has revolutionized clinical microbiology by enabling rapid microbial identification. However, MALDI-TOF MS has limitations, such as its limited ability to differentiate closely related species and database constraints, necessitating the development of more advanced methodologies. Ion mobility (IM)-MS has emerged as a promising analytical tool that enhances pathogen identification by separating ions based on their size, mass, shape, and charge. IM-MS has demonstrated significant potential in clinical microbiology by improving the characterization of bacterial, viral, and fungal infections. This review discusses the significance of infectious disease diagnosis in public health and the impact of timely and accurate identification on treatment outcomes. In addition, it provides a comprehensive analysis of IM-MS, detailing its principles, integration with omics technologies and machine learning, and its applications in infectious disease diagnosis. The review also explores the advantages of IM-MS over conventional techniques, highlights key studies demonstrating its effectiveness, and discusses future perspectives for enhancing its role in clinical diagnostics, precision medicine, and public health surveillance.
期刊介绍:
PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.