Metagenomic next-generation sequencing reveals respiratory flora distribution in COVID-19

This retrospective study compared metagenomic next-generation sequencing (mNGS) and traditional culture for pathogen detection in 43 patients with lower respiratory tract infections (LRTI), including 34 COVID-19 cases (14 critical, 20 non-critical) and 9 non-COVID controls. mNGS demonstrated superior sensitivity (95.35% vs. 81.08%) and broader pathogen coverage, identifying 36.36% of bacteria and 74.07% of fungi detected by cultures. Concordance between methods was observed in 63% of cases. Severe COVID-19 patients exhibited reduced respiratory microbiota abundance, potentially linked to viral dominance or therapeutic interventions. Clinical outcomes correlated positively with inflammatory markers (procalcitonin/PCT, N-terminal pro-B-type natriuretic peptide/N-proBNP, neutrophils, lactate dehydrogenase/LDH, neutrophil-to-lymphocyte ratio/NLR) and negatively with lymphocytes, highlighting systemic inflammation's role in disease progression. While mNGS offers rapid, high-sensitivity pathogen profiling, limitations include small sample sizes, unresolved specificity concerns and unmeasured confounders. The study underscores mNGS as a promising tool for LRTI diagnosis in COVID-19, though larger prospective cohorts and standardized outcome metrics are needed to validate clinical utility, optimize interpretation, and address cost-effectiveness compared to conventional methods.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-10-29
DOI
https://doi.org/10.1038/s41598-025-21722-y
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Metagenomic next-generation sequencing reveals respiratory flora distribution in COVID-19

Shuo Yang, Hongchao Liu, Jing Li, Qi Liu et al.
Scientific Reports
Gut microbiota and health
article

Metagenomic next-generation sequencing reveals respiratory flora distribution in COVID-19

Shuo Yang, Hongchao Liu, Jing Li, Qi Liu, Chong Wang, He Wang, Liyan Cui, Sisi Ma
article en

Abstract

This retrospective study compared metagenomic next-generation sequencing (mNGS) and traditional culture for pathogen detection in 43 patients with lower respiratory tract infections (LRTI), including 34 COVID-19 cases (14 critical, 20 non-critical) and 9 non-COVID controls. mNGS demonstrated superior sensitivity (95.35% vs. 81.08%) and broader pathogen coverage, identifying 36.36% of bacteria and 74.07% of fungi detected by cultures. Concordance between methods was observed in 63% of cases. Severe COVID-19 patients exhibited reduced respiratory microbiota abundance, potentially linked to viral dominance or therapeutic interventions. Clinical outcomes correlated positively with inflammatory markers (procalcitonin/PCT, N-terminal pro-B-type natriuretic peptide/N-proBNP, neutrophils, lactate dehydrogenase/LDH, neutrophil-to-lymphocyte ratio/NLR) and negatively with lymphocytes, highlighting systemic inflammation's role in disease progression. While mNGS offers rapid, high-sensitivity pathogen profiling, limitations include small sample sizes, unresolved specificity concerns and unmeasured confounders. The study underscores mNGS as a promising tool for LRTI diagnosis in COVID-19, though larger prospective cohorts and standardized outcome metrics are needed to validate clinical utility, optimize interpretation, and address cost-effectiveness compared to conventional methods.

Scientific ReportsVol. 15(1)
Peking University (CN), Peking University Third Hospital (CN)
National Natural Science Foundation of China, National Science and Technology Major Project
Openalex Percentile: Top 72%
Gut microbiota and health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.