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ABSTRACT Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospital COVID-19 patients, collected at the time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), redundancy analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Co-abundance network analysis determined that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Based on average abundance difference between the two guilds, the guild-level microbiome index (GMI) classified patients from different severity groups (average AUROC [area under the receiver operating curve] = 0.83). Moreover, age-adjusted partial Spearman’s correlation showed that GMIs at admission were correlated with 8 clinical parameters, which are predictors for COVID-19 prognosis, on day 7 in hospital. In addition, GMI at admission was associated with death/discharge outcome of the critical patients. We further validated that GMI was able to consistently classify patients with different COVID-19 symptom severities in different countries and differentiated COVID-19 patients from healthy subjects and pneumonia controls in four independent data sets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission. IMPORTANCE Previous reports on the associations between COVID-19 and gut microbiome have been constrained by taxonomic-level analysis and overlook the interaction between microbes. By applying a genome-resolved, reference-free, guild-based metagenomic analysis, we demonstrated that the relationship between gut microbiota and COVID-19 is genome-specific instead of taxon-specific or even species-specific. Moreover, the COVID-19-associated genomes were not independent but formed two competing guilds, with Guild 1 potentially beneficial and Guild 2 potentially more detrimental to the host based on comparative genomic analysis. The dominance of Guild 2 over Guild 1 at time of admission was associated with hospitalized COVID-19 patients at high risk for more severe outcomes. Moreover, the guild-level microbiome signature is not only correlated with the symptom severity of COVID-19 patients, but also differentiates COVID-19 patients from pneumonia controls and healthy subjects across different studies. Here, we showed the possibility of using genome-resolved and guild-level microbiome signatures to identify hospitalized COVID-19 patients with a high risk of more severe outcomes at the time of admission.

ABSTRACT The alteration of gut microbiota structure plays a pivotal role in the pathogenesis of abnormal glycometabolism. However, the microbiome features identified in patient groups stratified solely based on glucose levels remain controversial among different studies. In this study, we stratified 258 participants (discovery cohort) into three clusters according to an unsupervised method based on 16 clinical parameters involving the levels of blood glucose, insulin, and lipid. We found 67 cluster-specific microbiome features (i.e., amplicon sequence variants [ASVs]) based on 16S rRNA gene V3-V4 region sequencing. Specifically, ASVs belonging to Barnesville and Alistipes were enriched in cluster 1, in which participants had the lowest blood glucose levels, high insulin sensitivity, and a high-fecal short-chain fatty acid concentration. ASVs belonging to Prevotella copri and Ruminococcus gnavus were enriched in cluster 2, which was characterized by a moderate level of blood glucose, serious insulin resistance, and high levels of cholesterol and triglyceride. Cluster 3 was characterized by a high level of blood glucose and insulin deficiency, enriched with ASVs in P. copri and Bacteroides vulgatus. In addition, machine learning classifiers using the 67 cluster-specific ASVs were used to distinguish individuals in one cluster from those in the other two clusters both in discovery and testing cohorts (n = 83). Therefore, microbiome features identified based on the unsupervised stratification of patients with more inclusive clinical parameters may better reflect microbiota alterations associated with the progression of abnormal glycometabolism. IMPORTANCE The gut microbiota is altered in patients with type 2 diabetes (T2D) and prediabetes. The association of particular bacteria with T2D, however, varied among studies, which has made it challenging to develop precision medicine approaches for the prevention and alleviation of T2D. Blood glucose level is the only parameter in clustering patients when identifying the T2D-related bacteria in previous studies. This stratification ignores the fact that patients within the same blood glucose range differ in their insulin resistance and dyslipidemia, which also may be related to disordered gut microbiota. In addition to parameters of blood glucose levels, we also used additional parameters involving insulin and lipid levels to stratify participants into three clusters and further identified cluster-specific microbiome features. We further validated the association between these microbiome features and glycometabolism with an independent cohort. This study highlights the importance of stratification of patients with blood glucose, insulin, and lipid levels when identifying the microbiome features associated with the progression of abnormal glycometabolism.

The ketogenic diet with extremely high fat and very low carbohydrate levels is very popular in society today. Although it has beneficial effects on epilepsy and neurodegenerative diseases, how ketogenic diets impact host glucose and lipid metabolism and gut microbiota still needs further investigation.

ABSTRACT Cyclophosphamide (CTX) is widely used in cancer chemotherapy, but it often induces mucositis, in which the disruption of the gut microbiota might play a pivotal role. Whether the manipulation of the gut microbiota can be used as a strategy to improve CTX-induced mucositis remains to be studied. Here we observed the effects of a 4-week calorie restriction (CR) on CTX-induced mucositis. Compared with ad libitum-fed mice, CR mice showed significantly less mucositis in response to CTX, including lower intestinal permeability, less bacterial translocation, higher number of epithelial stem cells, and less epithelium damage. CTX induced significant shifts of the gut microbiota of the gut microbiota in ad libitum-fed control mice. In contrast, CR mice showed no significant change in their gut microbiota in responding to CTX treatment. CR significantly enriched the gut microbiota in Lactobacillus and Lachnospiraceae which are known to mitigate inflammation and improve gut barrier function. These findings suggest that CR remodeled gut microbiota is more robust and may contribute to attenuate the side effects of cyclophosphamide, which supports the concept that cancer chemotherapy would benefit from strategies targeting the gut microbiota. IMPORTANCE Improving the gut microbiota via calorie restriction is beneficial for human health. Our findings showed differential responses between calorie-restricted mice and ad libitum-fed mice. Compared with the ad libitum-fed mice, the calorie-restricted mice were less susceptible to cyclophosphamide side effects otherwise observed on the gut integrity and its microbiota. These results show the potential benefits of manipulating the gut microbiota with CR prior to cancer chemotherapy.

ABSTRACT Accumulating evidence implicates gut microbiota as promising targets for the treatment of type 2 diabetes mellitus (T2DM). With a randomized clinical trial, we tested the hypothesis that alteration of gut microbiota may be involved in the alleviation of T2DM with hyperlipidemia by metformin and a specifically designed herbal formula (AMC). Four hundred fifty patients with T2DM and hyperlipidemia were randomly assigned to either the metformin- or AMC-treated group. After 12 weeks of treatment, 100 patients were randomly selected from each group and assessed for clinical improvement. The effects of the two drugs on the intestinal microbiota were evaluated by analyzing the V3 and V4 regions of the 16S rRNA gene by Illumina sequencing and multivariate statistical methods. Both metformin and AMC significantly alleviated hyperglycemia and hyperlipidemia and shifted gut microbiota structure in diabetic patients. They significantly increased a coabundant group represented by Blautia spp., which significantly correlated with the improvements in glucose and lipid homeostasis. However, AMC showed better efficacies in improving homeostasis model assessment of insulin resistance (HOMA-IR) and plasma triglyceride and also exerted a larger effect on gut microbiota. Furthermore, only AMC increased the coabundant group represented by Faecalibacterium spp., which was previously reported to be associated with the alleviation of T2DM in a randomized clinical trial. Metformin and the Chinese herbal formula may ameliorate type 2 diabetes with hyperlipidemia via enriching beneficial bacteria, such as Blautia and Faecalibacterium spp. IMPORTANCE Metabolic diseases such as T2DM and obesity have become a worldwide public health threat. Accumulating evidence indicates that gut microbiota can causatively arouse metabolic diseases, and thus the gut microbiota serves as a promising target for disease control. In this study, we evaluated the role of gut microbiota during improvements in hyperglycemia and hyperlipidemia by two drugs: metformin and a specifically designed Chinese herbal formula (AMC) for diabetic patients with hyperlipidemia. Both drugs significantly ameliorated blood glucose and lipid levels and shifted the gut microbiota. Blautia spp. were identified as being associated with improvements in glucose and lipid homeostasis for both drugs. AMC exerted larger effects on the gut microbiota together with better efficacies in improving HOMA-IR and plasma triglyceride levels, which were associated with the enrichment of Faecalibacterium spp. In brief, these data suggest that gut microbiota might be involved in the alleviation of diabetes with hyperlipidemia by metformin and the AMC herbal formula.

ABSTRACT The genomic basis of the response to dietary intervention of human gut beneficial bacteria remains elusive, which hinders precise manipulation of the microbiota for human health. After receiving a dietary intervention enriched with nondigestible carbohydrates for 105 days, a genetically obese child with Prader-Willi syndrome lost 18.4% of his body weight and showed significant improvement in his bioclinical parameters. We obtained five isolates (C1, C15, C55, C62, and C95) of one of the most abundantly promoted beneficial species, Bifidobacterium pseudocatenulatum, from a postintervention fecal sample. Intriguingly, these five B. pseudocatenulatum strains showed differential responses during the dietary intervention. Two strains were largely unaffected, while the other three were promoted to different extents by the changes in dietary carbohydrate resources. The differential responses of these strains were consistent with their functional clustering based on the COGs (Clusters of Orthologous Groups), including those involved with the ABC-type sugar transport systems, suggesting that the strain-specific genomic variations may have contributed to the niche adaption. Particularly, B. pseudocatenulatum C15, which had the most diverse types and highest gene copy numbers of carbohydrate-active enzymes targeting plant polysaccharides, had the highest abundance after the dietary intervention. These studies show the importance of understanding genomic diversity of specific members of the gut microbiota if precise nutrition approaches are to be realized. IMPORTANCE The manipulation of the gut microbiota via dietary approaches is a promising option for improving human health. Our findings showed differential responses of multiple B. pseudocatenulatum strains isolated from the same habitat to the dietary intervention, as well as strain-specific correlations with bioclinical parameters of the host. The comparative genomics revealed a genome-level microdiversity of related functional genes, which may have contributed to these differences. These results highlight the necessity of understanding strain-level differences if precise manipulation of gut microbiota through dietary approaches is to be realized.