Bioinformatics tools for microbiome analysis and the prognosis prediction in sepsis patients

Abstract

With the advent of Next-Generation Sequencing (NGS), a plethora of novel opportunities has emerged across diverse biological and clinical research domains, facilitating a more streamlined, cost-effective, and precise examination of entire genetic sequences within organisms. This trans-formative impact has been particularly pronounced within the realm of infectious diseases, where the adoption of contemporary NGS methodologies, complemented by specialized bioinformatics tools, has become indispensable. The primary objectives of this study were to conceptualize and execute innovative bioinformatics strategies and methodologies specifically tailored to the analysis of microbiome data derived from NGS. This multifaceted endeavor encompassed three key compo-nents: 1) A comprehensive review of existing literature and software resources pertaining to the analysis of microbial communities from NGS datasets. This comprehensive survey served as the cor-nerstone for subsequent analyses and software development; 2) The conception, creation, and rig-orous testing of two distinct software tools designed for the analysis of 16S rRNA data. These tools harnessed the advantages of long-read sequencing and real-time experimental capabilities, result-ing in a notable enhancement in taxonomy accuracy and the potential to augment prognostic pre-dictions; and 3) An exhaustive metagenomic examination of respiratory samples aimed at assessing the association between the antibiotic resistance mechanisms identified from sequence data and mortality among sepsis patients. In summary, this research underscores the paramount importance of pioneering novel bioinformatics methodologies while simultaneously emphasizing the necessity of standardization and reproducibility. These imperatives are pivotal in fully harnessing the trans-formative potential of the NGS revolution in the infectious diseases research.