Integrated characterization of SARS-CoV-2 genome, microbiome, antibiotic resistance and host response from single throat swabs

Lu, Bo; Yan, Yi; Dong, Liting; Han, Lingling; Liu, Yawei; Yu, Junping; Chen, Jianjun; Yi, Danyang; Zhang, Meiling; Wang, Chao; Wang, Runkun; Wang, Dengpeng; Wei, Hongping; Liu, Di; Yi, Chengqi

doi:10.1101/2020.10.15.340794

Cited by 4 publications

(6 citation statements)

References 47 publications

(14 reference statements)

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“…Metagenomic analysis was popularly used to understand the diversity and pathogenesis of microbial populations in a group of subjects. However, metagenomics based on next‐generation sequencing (mNGS) was rarely applied to the clinical samples of SARS‐CoV‐2 5,16,17 . This technology could be used to uncover all microbiomes interacting in the same pathological niche, which might lead to ultimate pathophysiological conditions.…”

Section: Introductionmentioning

confidence: 99%

“…However, metagenomics based on next-generation sequencing (mNGS) was rarely applied to the clinical samples of SARS-CoV-2. 5,16,17 This technology could be used to uncover all microbiomes interacting in the same pathological niche, which might lead to ultimate pathophysiological conditions. The present study aims to perform metagenomic in-depth bioanalysis to characterize SARS-CoV-2 diabetic and nondiabetic patients compared with controls to identify the microbial interaction associated with the fatal consequences.…”

Section: Introductionmentioning

confidence: 99%

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Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID‐19 patients comorbidly affected by Type 2 diabetes

Al‐Emran¹,

Rahman²,

Hasan³

et al. 2022

Journal of Medical Virology

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The mortality of coronavirus disease 2019 (COVID‐19) disease is very high among the elderly or individuals having comorbidities such as obesity, cardiovascular diseases, lung infections, hypertension, and/or diabetes. Our study characterizes the metagenomic features in severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2)‐infected patients with or without type 2 diabetes, to identify the microbial interactions associated with its fatal consequences.This study compared the baseline nasopharyngeal microbiome of SARS‐CoV‐2‐infected diabetic and nondiabetic patients with controls adjusted for age and gender. The metagenomics based on next‐generation sequencing was performed using Ion GeneStudio S5 Series and the data were analyzed by the Vegan‐package in R. All three groups possessed significant bacterial diversity and dissimilarity indexes (p < 0.05). Spearman's correlation coefficient network analysis illustrated 183 significant positive correlations and 13 negative correlations of pathogenic bacteria (r = 0.6–1.0, p < 0.05), and 109 positive correlations between normal flora and probiotic bacteria (r > 0.6, p < 0.05). The SARS‐CoV‐2 diabetic group exhibited a significant increase in pathogens and secondary infection‐causing bacteria (p < 0.05) with a simultaneous decrease of normal flora (p < 0.05). The dysbiosis of the bacterial community might be linked with severe consequences of COVID‐19‐infected diabetic patients, although a few probiotic strains inhibited numerous pathogens in the same pathological niches. This study suggested that the promotion of normal flora and probiotics through dietary supplementation and excessive inflammation reduction by preventing secondary infections might lead to a better outcome for those comorbid patients.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID‐19 patients comorbidly affected by Type 2 diabetes

Al‐Emran¹,

Rahman²,

Hasan³

et al. 2022

Journal of Medical Virology

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“…Particularly, SARS‐CoV‐2 spike glycoprotein (S protein) plays an important role in initiating the host–pathogen interactions through the host cell surface angiotensin‐converting enzyme‐2 receptor (ACE2), enabling the entry of the virus into the host cell by membrane fusion 12 . Meanwhile, the spike homotrimers can protrude from the viral surface and act as a direct target for host immune responses, eliciting protective B‐cell and T‐cell mediated immune responses in the hosts during SARS‐CoV‐2 infection 13 . The consequence of viral S protein‐ACE2 interaction has a great impact on eliciting cell signaling cascades leading to diverse cellular responses 14 .…”

Section: Introductionmentioning

confidence: 99%

“…12 Meanwhile, the spike homotrimers can protrude from the viral surface and act as a direct target for host immune responses, eliciting protective Bcell and T-cell mediated immune responses in the hosts during SARS-CoV-2 infection. 13 The consequence of viral S protein-ACE2 interaction has a great impact on eliciting cell signaling cascades leading to diverse cellular responses. 14 Several studies have demonstrated that SARS-CoV-2 S protein alone is enough to elicit cell signaling events, which signifying a unique biological mechanism of SARS-CoV-2 spike protein.…”

mentioning

confidence: 99%

Comprehensive role of SARS‐CoV‐2 spike glycoprotein in regulating host signaling pathway

Banerjee¹,

Wang

et al. 2022

Journal of Medical Virology

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Since the outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, global public health and the economy have suffered unprecedented damage. Based on the increasing related literature, the characteristics and pathogenic mechanisms of the virus, and epidemiological and clinical features of the disease are being rapidly discovered. The spike glycoprotein (S protein), as a key antigen of SARS-CoV-2 for developing vaccines, antibodies, and drug targets, has been shown to play an important role in viral entry, tissue tropism, and pathogenesis. In this review, we summarize the molecular mechanisms of interaction between S protein and host factors, especially receptor-mediated viral modulation of host signaling pathways, and highlight the progression of potential therapeutic targets, prophylactic and therapeutic agents for prevention and treatment of SARS-CoV-2 infection.

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“…Metagenomic analysis is popularly used to understand the diversity and pathogenesis of microbial populations in a group of subjects. However, metagenomics based on next-generation sequencing (mNGS) is rarely applied to the clinical samples of SARS-CoV-2 4, 11, 12 . This technology can be used to uncover all microbiome interacting in the same pathological niche which leads to ultimate pathophysiological conditions.…”

Section: Introductionmentioning

confidence: 99%

Metagenomic diagnosis and pathogenic network profile of SARS-CoV-2 in patients co-morbidly affected by type 2 diabetes

Al‐Emran¹,

Rahman

Hasan³

et al. 2021

Preprint

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Background: The mortality of COVID-19 disease is very high among males or elderly or individuals having comorbidities with obesity, cardiovascular diseases, lung infections, hypertension, and/or diabetes. Our study characterizes the metagenomic feature of SARS-CoV-2 infected patients with or without type 2 diabetes to identify the microbial interactions associated with its fatal consequences. Method: This study compared the baseline nasopharyngeal microbiome of SARS-CoV-2 infected diabetic and non-diabetic patients with controls adjusted with age and gender. The mNGS were performed using Ion GeneStudio S5 Series and the data were analyzed by the Vegan-package in R. Results: All three groups possessed significant bacterial diversity and dissimilarity indexes (p<0.05). Spearmans correlation coefficient network analysis illustrated 183 significant positive correlations and 13 negative correlations of pathogenic bacteria (r=0.6-1.0, p<0.05), and 109 positive correlations among normal-flora and probiotic bacteria (r>0.6, p<0.05). The SARS-CoV-2 diabetic group exhibited a significant increase of pathogens (p<0.05) and opportunistic pathogens (p<0.05) with a simultaneous decrease of normal-flora (p<0.05). The molecular docking analysis of Salivaricin, KLD4 (alpha), and enterocin produced by several enriched probiotic strains presented strong binding affinity with Shiga toxin, outer membrane proteins (ompA, omp33) or hemolysin. Conclusion: The dysbiosis of the bacterial community might be linked with severe consequences of COVID-19 infected diabetic patients, although few probiotic strains inhibited numerous pathogens in the same pathological niches. This study suggested that the promotion of normal-flora and probiotics through dietary changes and reduction of excessive pro-inflammatory states by preventing pathogenic environment might lead to a better outcome for those co-morbid patients.

show abstract

Integrated characterization of SARS-CoV-2 genome, microbiome, antibiotic resistance and host response from single throat swabs

Cited by 4 publications

References 47 publications

Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID‐19 patients comorbidly affected by Type 2 diabetes

Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID‐19 patients comorbidly affected by Type 2 diabetes

Comprehensive role of SARS‐CoV‐2 spike glycoprotein in regulating host signaling pathway

Metagenomic diagnosis and pathogenic network profile of SARS-CoV-2 in patients co-morbidly affected by type 2 diabetes

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