Gut mycobiota alterations in patients with COVID-19 and H1N1 infections and their associations with clinical features.

The relationship between gut microbes and COVID-19 or H1N1 infections is not fully understood. Here, we compared the gut mycobiota of 67 COVID-19 patients, 35 H1N1-infected patients and 48 healthy controls (HCs) using internal transcribed spacer (ITS) 3-ITS4 sequencing and analysed their associations with clinical features and the bacterial microbiota. Compared to HCs, the fungal burden was higher. Fungal mycobiota dysbiosis in both COVID-19 and H1N1-infected patients was mainly characterized by the depletion of fungi such as Aspergillus and Penicillium, but several fungi, including Candida glabrata, were enriched in H1N1-infected patients. The gut mycobiota profiles in COVID-19 patients with mild and severe symptoms were similar. Hospitalization had no apparent additional effects. In COVID-19 patients, Mucoromycota was positively correlated with Fusicatenibacter, Aspergillus niger was positively correlated with diarrhoea, and Penicillium citrinum was negatively correlated with C-reactive protein (CRP). In H1N1-infected patients, Aspergillus penicilloides was positively correlated with Lachnospiraceae members, Aspergillus was positively correlated with CRP, and Mucoromycota was negatively correlated with procalcitonin. Therefore, gut mycobiota dysbiosis occurs in both COVID-19 patients and H1N1-infected patients and does not improve until the patients are discharged and no longer require medical attention.

The serum metabolome of COVID-19 patients is distinctive and predictive.

BACKGROUND: Metabolism is critical for sustaining life, immunity and infection, but its role in COVID-19 is not fully understood. METHODS: Seventy-nine COVID-19 patients, 78 healthy controls (HCs) and 30 COVID-19-like patients were recruited in a prospective cohort study. Samples were collected from COVID-19 patients with mild or severe symptoms on admission, patients who progressed from mild to severe symptoms, and patients who were followed from hospital admission to discharge. The metabolome was assayed using gas chromatography-mass spectrometry. RESULTS: Serum butyric acid, 2-hydroxybutyric acid, l-glutamic acid, l-phenylalanine, l-serine, l-lactic acid, and cholesterol were enriched in COVID-19 and COVID-19-like patients versus HCs. Notably, d-fructose and succinic acid were enriched, and citric acid and 2-palmitoyl-glycerol were depleted in COVID-19 patients compared to COVID-19-like patients and HCs, and these four metabolites were not differentially distributed in non-COVID-19 groups. COVID-19 patients had enriched 4-deoxythreonic acid and depleted 1,5-anhydroglucitol compared to HCs and enriched oxalic acid and depleted phosphoric acid compared to COVID-19-like patients. A combination of d-fructose, citric acid and 2-palmitoyl-glycerol distinguished COVID-19 patients from HCs and COVID-19-like patients, with an area under the curve (AUC) > 0.92 after validation. The combination of 2-hydroxy-3-methylbutyric acid, 3-hydroxybutyric acid, cholesterol, succinic acid, L-ornithine, oleic acid and palmitelaidic acid predicted patients who progressed from mild to severe COVID-19, with an AUC of 0.969. After discharge, nearly one-third of metabolites were recovered in COVID-19 patients. CONCLUSIONS: The serum metabolome of COVID-19 patients is distinctive and has important value in investigating pathogenesis, determining a diagnosis, predicting severe cases, and improving treatment.

Alterations of the Gut Microbiota in Patients With Coronavirus Disease 2019 or H1N1 Influenza.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emerging serious global health problem. Gastrointestinal symptoms are common in COVID-19 patients, and severe acute respiratory syndrome coronavirus 2 RNA has been detected in stool specimens. However, the relationship between the gut microbiome and disease remains to be established. METHODS: We conducted a cross-sectional study of 30 patients with COVID-19, 24 patients with influenza A(H1N1), and 30 matched healthy controls (HCs) to identify differences in the gut microbiota by 16S ribosomal RNA gene V3-V4 region sequencing. RESULTS: Compared with HCs, COVID-19 patients had significantly reduced bacterial diversity; a significantly higher relative abundance of opportunistic pathogens, such as Streptococcus, Rothia, Veillonella, and Actinomyces; and a lower relative abundance of beneficial symbionts. Five biomarkers showed high accuracy for distinguishing COVID-19 patients from HCs with an area under the curve (AUC) up to 0.89. Patients with H1N1 displayed lower diversity and different overall microbial composition compared with COVID-19 patients. Seven biomarkers were selected to distinguish the 2 cohorts (AUC = 0.94). CONCLUSIONS: The gut microbial signature of patients with COVID-19 was different from that of H1N1 patients and HCs. Our study suggests the potential value of the gut microbiota as a diagnostic biomarker and therapeutic target for COVID-19, but further validation is needed.

The faecal metabolome in COVID-19 patients is altered and associated with clinical features and gut microbes.

Although SARS-CoV-2 can invade the intestine, though its effect on digestion and absorption is not fully understood. In the present study, 56 COVID-19 patients and 47 age- and sex-matched healthy subjects were divided into a discovery cohort and a validation cohort. Blood, faeces and clinical information were collected from the patients in the hospital and at discharge. The faecal metabolome was analysed using gas chromatography-mass spectrometry, and Spearman's correlation analyses of clinical features, the serum metabolome, and the faecal micro- and mycobiota were conducted. The results showed that, the faeces of COVID-19 patients were enriched with important nutrients that should be metabolized or absorbed, such as sucrose and 2-palmitoyl-glycerol; diet-related components that cannot be synthesized by humans, such as 1,5-anhydroglucitol and D-pinitol; and harmful metabolites, such as oxalate, were also detected. In contrast, purine metabolites such as deoxyinosine and hypoxanthine, low-water-soluble long-chain fatty alcohols/acids such as behenic acid, compounds rarely occurring in nature such as D-allose and D-arabinose, and microbe-related compounds such as 2,4-di-tert-butylphenol were depleted in the faeces of COVID-19 patients. Moreover, these metabolites significantly correlated with altered serum metabolites such as oxalate and gut microbesincluding Ruminococcaceae, Actinomyces, Sphingomonas and Aspergillus. Although levels of several faecal metabolites, such as sucrose, 1,5-anhydroglucitol and D-pinitol, of discharged patients were not different from those of healthy controls (HCs), those of oxalate and 2-palmitoyl-glycerol did differ. Therefore, alterations in the faecal metabolome of COVID-19 patients may reflect malnutrition and intestinal inflammation and warrant greater attention. The results of present study provide new insights into the pathogenesis and treatment of COVID-19.

Comparative Genomic Analyses Reveal a Specific Mutation Pattern Between Human Coronavirus SARS-CoV-2 and Bat-CoV RaTG13.

BACKGROUND: The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, rapidly grew into a global pandemic. How SARS-CoV-2 evolved remains unclear. METHODS: We performed a comprehensive analysis using the available genomes of SARS-CoV-2 and its closely related coronaviruses. RESULTS: The ratio of nucleotide substitutions to amino acid substitutions of the spike gene (9.07) between SARS-CoV-2 WIV04 and Bat-CoV RaTG13 was markedly higher than that between other coronaviruses (range, 1.29-4.81); the ratio of non-synonymous to synonymous substitution rates (dN/dS) between SARS-CoV-2 WIV04 and Bat-CoV RaTG13 was the lowest among all the performed comparisons, suggesting evolution under stringent selective pressure. Notably, the relative proportion of the T:C transition was markedly higher between SARS-CoV-2 WIV04 and Bat-CoV RaTG13 than between other compared coronaviruses. Codon usage is similar across these coronaviruses and is unlikely to explain the increased number of synonymous mutations. Moreover, some sites of the spike protein might be subjected to positive selection. CONCLUSIONS: Our results showed an increased proportion of synonymous substitutions and the T:C transition between SARS-CoV-2 and RaTG13. Further investigation of the mutation pattern mechanism would contribute to understanding viral pathogenicity and its adaptation to hosts.

Clinical Characteristics and Factors Associated With Long-Term Viral Excretion in Patients With Severe Acute Respiratory Syndrome Coronavirus 2 Infection: a Single-Center 28-Day Study.

BACKGROUND: Despite the ongoing spread of coronavirus disease 2019 (COVID-19), knowledge about factors affecting prolonged viral excretion is limited. METHODS: In this study, we retrospectively collected data from 99 hospitalized patients with coronavirus disease 2019 (COVID-19) between 19 January and 17 February 2020 in Zhejiang Province, China. We classified them into 2 groups based on whether the virus test results eventually became negative. Cox proportional hazards regression was used to evaluate factors associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shedding. RESULTS: Among 99 patients, 61 patients had SARS-CoV-2 clearance (virus-negative group), but 38 patients had sustained positive results (virus-positive group). The median duration of SARS-CoV-2 excretion was 15 (interquartile range, 12-19) days among the virus-negative patients. The shedding time was significantly increased if the fecal SARS-CoV-2 RNA test result was positive. Male sex (hazard ratio [HR], 0.58 [95% confidence interval {CI}, .35-.98]), immunoglobulin use (HR, 0.42 [95% CI, .24-.76]), APACHE II score (HR, 0.89 [95% CI, .84-.96]), and lymphocyte count (HR, 1.81 [95% CI, 1.05-3.1]) were independent factors associated with a prolonged duration of SARS-CoV-2 shedding. Antiviral therapy and corticosteroid treatment were not independent factors. CONCLUSIONS: SARS-CoV-2 RNA clearance time was associated with sex, disease severity, and lymphocyte function. The current antiviral protocol and low-to-moderate dosage of corticosteroid had little effect on the duration of viral excretion.