The effects of sequencing strategies on Metagenomic pathogen detection using bronchoalveolar lavage fluid samples

Ziyang Li; Zhe Guo; Weimin Wu; Li Tan; Qichen Long; Han Xia; Min Hu

Heliyon (Jul 2024)

The effects of sequencing strategies on Metagenomic pathogen detection using bronchoalveolar lavage fluid samples

Ziyang Li,
Zhe Guo,
Weimin Wu,
Li Tan,
Qichen Long,
Han Xia,
Min Hu

Affiliations

Ziyang Li: Department of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Center for Clinical Molecular Diagnostics, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
Zhe Guo: Department of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Center for Clinical Molecular Diagnostics, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
Weimin Wu: Department of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Center for Clinical Molecular Diagnostics, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
Li Tan: Department of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Center for Clinical Molecular Diagnostics, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
Qichen Long: Department of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Center for Clinical Molecular Diagnostics, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
Han Xia: School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China; MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
Min Hu: Department of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Center for Clinical Molecular Diagnostics, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Corresponding author. Department of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.

Journal volume & issue: Vol. 10, no. 13
p. e33429

Abstract

Read online

Objectives: Metagenomic next-generation sequencing (mNGS) is a powerful tool for pathogen detection. The accuracy depends on both wet lab and dry lab procedures. The objective of our study was to assess the influence of read length and dataset size on pathogen detection. Methods: In this study, 43 clinical BALF samples, which tested positive via clinical mNGS and were consistent with the diagnosis, were subjected to re-sequencing on the Illumina NovaSeq 6000 platform. The raw re-sequencing data, consisting of 100 million (M) paired-end 150 bp (PE150) reads, were divided into simulated datasets with eight different data sizes (5 M, 10 M, 15 M, 20 M, 30 M, 50 M, 75 M, 100 M) and five different read lengths (single-end 50 bp (SE50), SE75, SE100, PE100, and PE150). Both Kraken2 and IDseq bioinformatics pipelines were employed to analyze the previously diagnosed pathogens in the simulated data. Detection of pathogens was based on read counts ranging from 1 to 10 and RPM values ranging from 0.2 to 2. Results: Our results revealed that increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection. However, a larger data sizes for mNGS require higher economic costs and longer turnaround time for data analysis. Our findings indicate 20 M reads being sufficient for SE75 mode to achieve high recall rates. Additionally, high nucleic acid loads in samples can lead to increased stability in pathogen detection efficiency, reducing the impact of sequencing strategies. The choice of bioinformatics pipelines had a significant impact on recall rates achieved in pathogen detection. Conclusions: Increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection but increase the economic and time costs of sequencing and data analysis. Currently, the 20 M reads in SE75 mode may be the best sequencing option.

Published in Heliyon

ISSN: 2405-8440 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Science: Science (General); Social Sciences: Social sciences (General)
Website: https://www.cell.com/heliyon/home

About the journal

Abstract

Keywords