Here, we reviewed the results of studies on the α-diversity of the human gut, respiratory, oral, and skin microbiota associated with SARS-CoV-2. We assembled the largest dataset available to date in order to assess the relationship between SARS-CoV-2 infection and the α-diversity of the human microbiota. Our meta-analysis revealed a significant down-regulation of the microbiota α-diversity in the gut and respiratory systems among individuals with SARS-CoV-2 infection, which is consistent with numerous current findings [
8‐
12,
16,
29‐
34]. It should be noted that although state-of-the-art and widely used microbiological analysis software such as QIIME2 and the DADA2 algorithm were employed to mitigate heterogeneity in the processing and analysis of raw sequences from different studies, notable heterogeneity still existed among the included studies. For gut and respiratory studies, we observed that study type was one of the sources of heterogeneity. Cross-sectional and case–control studies typically involved samples collected at a single time point, while longitudinal studies consisted of samples collected at multiple time points. In gut studies, other sources of heterogeneity included antibiotics, country, and sequencing platform. In respiratory studies, sources of heterogeneity also encompassed sequencing regions. Previous studies have demonstrated that regional factors [
35], antibiotic [
36], gender [
37], age [
38], and diet [
39] can influence the composition of the human microbiota. Due to limited access to open information included in this study, we were unable to analyze the sources of heterogeneity from additional perspectives. In summary, our study clarified that the α-diversity of gut and respiratory microbiota is downregulated after SARS-CoV-2 infection, providing readers with an understanding of the microbial characteristics of different human body sites after SARS-CoV-2 infection.
ML based on the human microbiota has been applied to predict various diseases and identify biomarkers. For example, it has been used to predict Vibrio cholerae infection [
40], ulcerative colitis [
41], and more. Similarly, the gut microbiota has shown promise in distinguishing the severity of COVID-19 [
18] and effectively predicting protein markers for severe cases [
42]. However, it remains to be explored whether the microbiota altered by SARS-CoV-2 infection can predict disease prognosis, including survival and death. In our study, we found that in the early stages of SARS-CoV-2 infection, alterations in the nasopharyngeal and oropharyngeal microbiota had the potential to predict patient survival and death. We observed that the predictive performance differed between the nasopharynx and oropharynx, as well as among different ML models. This suggests that when utilizing human microbiota to predict disease prognosis, we should consider the results from different body parts and ML models comprehensively. In the models we constructed, the AUC of the optimal model was only 0.847. This might be due to the small sample size and changes in microbiota characteristics following treatment for SARS-CoV-2 infection. Nonetheless, our study demonstrated the potential of ML based on human microbiota in predicting the prognosis of SARS-CoV-2-infected individuals, which may help in providing targeted treatment for severely SARS-CoV-2-infected individuals.
A study found that Dialister invisus ASV represents a unique case of overlap between the oral and gut microbiota in healthy individuals. Normally, the oral and gut microbiota differ under physiological conditions, and the presence of overlapping microbiota may indicate a certain pathological state [
43]. In our study, we discovered genera such as
Prevotella and
Streptococcus that overlapped in the gut, respiratory tract, and oral cavity. Several studies have also demonstrated a significant up-regulation of
Prevotella [
44‐
47],
Streptococcus [
9,
44‐
46] and
Veillonella [
9,
44‐
46] following SARS-CoV-2 infection.
Prevotella, a strictly anaerobic gram-negative bacillus, is known to be a major genus found in human skin, oral cavity, vagina, and gut [
48]. It is frequently associated with respiratory tract infections, such as inhalation pneumonia [
49] and pulmonary empyema [
50]. Additionally, studies [
51] have shown an increased abundance of
Prevotella in the presence of viral infections associated with Human Immunodeficiency Virus, Papillomavirus, Herpesviridae, and respiratory viruses. Our study confirmed dysregulation of
Prevotella in the human skin, oral cavity, gut, and respiratory tract after SARS-CoV-2 infection. Furthermore,
Prevotella was found to be related to the severity and recovery of SARS-CoV-2 infection. Other studies have reported a correlation between long-lasting COVID-19 symptoms and elevated expression of oral
Prevotella [
52], which may be due to the ability of
Prevotella to produce proteins that promote SARS-CoV-2 infection [
53]. The precise mechanism by which
Prevotella affects COVID-19 is not yet clear. However, previous research [
54] has revealed that certain
Prevotella strains can produce virulence factors that increase inflammatory response by activating Toll-like receptor 2 and inducing Th17-polarizing cytokines in antigen-presenting cells (such as IL-23 and IL-1), or stimulating epithelial cells to produce IL-8, IL-6, and CCL20. In summary, when individuals become ill due to the invasion of foreign pathogens, the normal human microbiota may be translocated and transformed into pathogenic bacteria, exacerbating the disease. The key bacteria
Prevotella and
Streptococcus proposed by us provide clues for future animal and in vitro experiments on SARS-CoV-2 infection intervention.
Our study has the following limitations: Firstly, due to the continuous updating of databases, our research may not reflect the latest research status. Secondly, the limited number of studies included in our analysis leads to certain limitations in generalizing our findings. Thirdly, there is a lack of animal and in vitro experimental validation for the key microbial communities we identified.