Background: Metagenomic sequencing of microbial cell-free DNA (cfDNA) in blood and urine is increasingly used as a tool for unbiased infection screening. The sensitivity of metagenomic cfDNA sequencing assays is determined by the efficiency by which the assay recovers microbial cfDNA vs host-specific cfDNA. We hypothesized that the choice of methods used for DNA isolation, DNA sequencing library preparation, and sequencing would affect the sensitivity of metagenomic cfDNA sequencing.
Methods: We characterized the fragment length biases inherent to select DNA isolation and library preparation procedures and developed a model to correct for these biases. We analyzed 305 cfDNA sequencing data sets, including publicly available data sets and 124 newly generated data sets, to evaluate the dependence of the sensitivity of metagenomic cfDNA sequencing on pre-analytical variables.
Results: Length bias correction of fragment length distributions measured from different experimental procedures revealed the ultrashort (<100 bp) nature of microbial-, mitochondrial-, and host-specific urinary cfDNA. The sensitivity of metagenomic sequencing assays to detect the clinically reported microorganism differed by more than 5-fold depending on the combination of DNA isolation and library preparation used.
Conclusions: Substantial gains in the sensitivity of microbial and other short fragment recovery can be achieved by easy-to-implement changes in the sample preparation protocol, which highlights the need for standardization in the liquid biopsy field.
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http://dx.doi.org/10.1093/clinchem/hvab142 | DOI Listing |
Front Cell Infect Microbiol
December 2024
Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Background: Targeted next-generation sequencing (tNGS) has become a trending tool in the field of infection diagnosis, but concerns are also raising about its performance compared with metagenomic next-generation sequencing (mNGS). This study aims to explore the clinical feasibility of a tNGS panel for respiratory tract infection diagnosis and compare it with mNGS in the same cohort of inpatients.
Methods: 180 bronchoalveolar lavage fluid samples were collected and sent to two centers for mNGS and tNGS blinded tests, respectively.
Front Cell Infect Microbiol
December 2024
Department of Infectious Diseases, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Objective: The aim of this study was to assess the clinical value of metagenomic next-generation sequencing (mNGS) of blood samples for the identification of disseminated tuberculosis (DTB).
Methods: A total of 48 individuals suspected of DTB were enrolled. All patients underwent mNGS of peripheral blood and conventional microbiological tests.
Ann Clin Microbiol Antimicrob
December 2024
The Centre for Clinical Microbiology, University College London, London, UK.
Introduction: Colonisation and infection with Carbapenem-resistant Enterobacterales (CRE) in healthcare settings poses significant risks, especially for vulnerable patients. Genomic analysis can be used to trace transmission routes, supporting antimicrobial stewardship and informing infection control strategies. Here we used genomic analysis to track the movement and transmission of CREs within clinical and environmental samples.
View Article and Find Full Text PDFAnn Clin Microbiol Antimicrob
December 2024
Department of Pediatric Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, 3333 Binsheng Road, Binjiang District, Hangzhou, Zhejiang, China.
Background: Antimicrobial resistance (AMR) poses a significant threat to pediatric health; therefore, precise identification of pathogens as well as AMR is imperative. This study aimed at comprehending antibiotic resistance patterns among critically ill children with infectious diseases admitted to pediatric intensive care unit (PICU) and to clarify the impact of drug-resistant bacteria on the prognosis of children.
Methods: This study retrospectively collected clinical data, identified pathogens and AMR from 113 children's who performed metagenomic next-generation sequencing for pathogen and antibiotic resistance genes identification, and compared the clinical characteristic difference and prognostic effects between children with and without AMR detected.
NAR Genom Bioinform
December 2024
Center for Bioinformatics and Computational Genomics, Georgia Institute of Technology, 225 North Avenue NW, Atlanta, GA, 30332, USA.
Dimension reduction (DR or embedding) algorithms such as t-SNE and UMAP have many applications in big data visualization but remain slow for large datasets. Here, we further improve the UMAP-like algorithms by (i) combining several aspects of t-SNE and UMAP to create a new DR algorithm; (ii) replacing its rate-limiting step, the K-nearest neighbor graph (K-NNG), with a Hierarchical Navigable Small World (HNSW) graph; and (iii) extending the functionality to DNA/RNA sequence data by combining HNSW with locality sensitive hashing algorithms (e.g.
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