AUTHOR=Yang Jing , Zhang Qiang , Zhang Jun , Ouyang Yan , Sun Zepeng , Liu Xinlong , Qaio Feng , Xu Li-Qun , Niu Yunfei , Li Jian 

TITLE=Exploring the Change of Host and Microorganism in Chronic Obstructive Pulmonary Disease Patients Based on Metagenomic and Metatranscriptomic Sequencing

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2022.818281

DOI=10.3389/fmicb.2022.818281

ISSN=1664-302X

ABSTRACT=Background
Chronic obstructive pulmonary disease (COPD) is a universal respiratory disease resulting from the complex interactions between genes and environment condition. The process of COPD is deteriorated by repeated episodes of exacerbations, which are the primary reason for COPD-related morbidity and mortality. Bacterial pathogens are commonly identified in patients’ respiratory tracts both in the stable state and during acute exacerbations, with significant changes in the prevalence of airway bacteria occurring during acute exacerbations of COPD. Therefore, studies integrating perturbations in microbial composition with host inflammatory responses will be necessary to develop a mechanistic link between the airway microbiome and chronic pulmonary inflammation in COPD patients.
Methods
We performed metatranscriptomic and metagenomic sequencing on sputum samples for twelve AECOPD patients before treatment and for four of them after treatment (after discharge for two months). Sequencing reads were classified by Kraken2, and the host gene expression was analyzed by Hisat2 and Htseq. The correlation between genes was obtained by the Spearman correlation coefficient. Mann-Whitney U test was applied to identify microbes that exhibit significantly different distribution in two groups. 
Results
At the phyla level, the top 5 dominant phyla were Firmicutes, Actinobacteria, Proteobacteria, Bacteroidetes, and Fusobacteria. The proportion of dominant gates in metagenomic data was similar in metatranscriptomic data. There were significant differences in the abundance of specific microorganisms at the class level between the two methods. No significant difference between AECOPD and after treatment was found. Among them, the different expression levels of 5 host genes were significantly increased after treatment and were involved in immune response and inflammatory pathways, which were associated with macrophages.  
Conclusion
Our study revealed that the interaction profile between lung microorganisms and the host genome changed after AECOPD. We speculate that the altered lung microbes of AECOPD may contribute to changing host gene transcription. This study may provide a clue to investigate the mechanism of COPD and potential biomarkers in clinical diagnosis and treatment.