AUTHOR=Li Sijia , Yang Siyuan , Zhou Yuzheng , Disoma Cyrollah , Dong Zijun , Du Ashuai , Zhang Yongxing , Chen Yong , Huang Weiliang , Chen Junru , Song Deqiang , Chen Zongpeng , Liu Pinjia , Li Shiqin , Zheng Rong , Liu Sixu , Razzaq Aroona , Chen Xuan , Tao Siyi , Yu Chengping , Feng Tianxu , Liao Wenyan , Peng Yousong , Jiang Taijiao , Huang Jufang , Wu Wei , Hu Liqiang , Wang Linghang , Li Shanni , Xia Zanxian 

TITLE=Microbiome Profiling Using Shotgun Metagenomic Sequencing Identified Unique Microorganisms in COVID-19 Patients With Altered Gut Microbiota

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2021.712081

DOI=10.3389/fmicb.2021.712081

ISSN=1664-302X

ABSTRACT=COVID-19 is mainly associated to respiratory distress syndrome, but a subset of patients often present gastrointestinal (GI) symptoms. Imbalances of gut microbiota have been previously linked to respiratory virus infection. To understand how the gut-lung axis affects the progression of COVID-19 can provide a novel framework for therapies and management. In this study, we examined the gut microbiota of patients with COVID-19 (n=47) and compared it to healthy controls (n=19). Using shotgun metagenomic sequencing, we have identified four microorganisms unique in COVID-19 patients, namely Streptococcus thermophilus, Bacteroides oleiciplenus, Fusobacterium ulcerans and Prevotella bivia. The abundances of Bacteroides stercoris, B. vulgatus, B. massiliensis, Bifidobacterium longum, Streptococus thermophilus, Lachnospiraceae bacterium 5163FAA, Prevotella bivia, Erysipelotrichaceae bacterium 6145 and Erysipelotrichaceae bacterium 2244A were enriched in COVID-19 patients, whereas the abundances of Clostridium nexile, Streptococus salivarius, Coprococcus catus, Eubacterium hallii, Enterobacter aerogenes and Adlercreutzia equolifaciens were decreased (p<0.05). The relative abundance of butyrate-producing Roseburia inulinivorans is evidently depleted in COVID-19 patients, while the relative abundances of Paraprevotella sp. and the probiotic Streptococcus thermophilus were increased. We further identified 30 KEGG orthology (KO) modules overrepresented, with 7 increasing and 23 decreasing modules. Notably, 15 optimal microbial markers were identified using the random forest model to have strong diagnostic potential in distinguishing COVID-19. Based on Spearman's correlation, 8 species were associated with 8 clinical indices. Moreover, the increased abundance of Bacteroidetes and decreased abundance of Firmicutes were also found across clinical types of COVID-19. Our findings suggest that the alterations of gut microbiota in patients with COVID-19 influence disease severity. Our COVID-19 classifier, which was cross-regionally verified, provides a proof-of-concept that a set of microbial species markers can distinguish the presence of COVID-19.