| Literature DB >> 35358660 |
Rosa Giugliano1, Assunta Sellitto2, Carlo Ferravante2, Teresa Rocco3, Ylenia D'Agostino3, Elena Alexandrova2, Jessica Lamberti2, Domenico Palumbo2, Massimiliano Galdiero1, Emilia Vaccaro4, Pasquale Pagliano3, Alessandro Weisz5, Giorgio Giurato6, Gianluigi Franci7, Francesca Rizzo8.
Abstract
Since its first appearance, the SARS-CoV-2 has spread rapidly in the human population, reaching the pandemic scale with >280 million confirmed infections and more than 5 million deaths to date (https://covid19.who.int/). These data justify the urgent need to enhance our understanding of SARS-CoV-2 effects in the respiratory system, including those linked to co-infections. The principal aim of our study is to investigate existing correlations in the nasopharynx between the bacterial community, potential pathogens, and SARS-CoV-2 infection. The main aim of this study was to provide evidence pointing to possible relationships between components of the bacterial community and SARS-CoV-2 in the nasopharynx. Meta-transcriptomic profiling of the nasopharyngeal microbial community was carried out in 89 SARS-Cov-2 positive subjects from the Campania Region in Italy. To this end, RNA extracted from nasopharyngeal swabs collected at different times during the initial phases of the pandemic was analyzed by Next-Generation Sequencing (NGS). Results show a consistently high presence of members of the Proteobacteria (41.85%), Firmicutes (28.54%), and Actinobacteria (16.10%) phyla, and an inverted correlation between the host microbiome, co-infectious bacteria, and super-potential pathogens such as Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, and Neisseria gonorrhoeae. In depth characterization of microbiota composition in the nasopharynx can provide clues to understand its potential contribution to the clinical phenotype of Covid-19, clarifying the interaction between SARS-Cov-2 and the bacterial flora of the host, and highlighting its dysbiosis and the presence of pathogens that could affect the patient's disease progression and outcome.Entities:
Keywords: COVID-19; Meta-transcriptomics; Nasal swabs; Nasopharyngeal microbiome; SARS-CoV-2
Mesh:
Year: 2022 PMID: 35358660 PMCID: PMC8958261 DOI: 10.1016/j.micpath.2022.105506
Source DB: PubMed Journal: Microb Pathog ISSN: 0882-4010 Impact factor: 3.738
Patient cohort description.
| March-Apr-May 2020 (n = 27) | Sept-Oct-Nov 2020 (n = 43) | Jan–Feb 2021 (n = 19) | |
|---|---|---|---|
| 0–20 | 3 (11%) | 3 (7%) | 5 (26%) |
| 21–40 | 4 (15%) | 8 (19%) | 1 (5%) |
| 41–60 | 4 (15%) | 15 (35%) | – |
| 61–80 | 10 (37%) | 13 (30%) | 6 (32%) |
| >80 | 3 (11%) | 4 (9%) | 7 (37%) |
| Unknown | 3 (11%) | – | |
| Male (%) | 16 (59%) | 27 (63%) | 5 (26%) |
| Female (%) | 8 (30%) | 16 (37%) | 14 (74%) |
| Unknown | 3 (11%) | – | – |
| Asymptomatic | 11 (41%) | 15 (35%) | – |
| Mild | 7 (26%) | 6 (14%) | – |
| Moderate | 2 (7%) | – | 4 (21%) |
| Severe | 5 (2 dead) (19%) | 4 (1 dead) (9%) | 1 (5%) |
| Unknown | 27%) | 18 (42%) | 14 (74%) |
Fig. 1Bacterial microbiota composition in the nasopharynx of COVID-19 patients. Relative percentage of abundance for the main phyla identified in SARS-CoV-2 positive (panel A) and negative (panel B) patients and in SARS-CoV-2 patients across three periods of sampling (panel C).
Fig. 2Comparison between bacterial genus identified in SARS-CoV-2 positive patients and control group (A) and taxonomy profiling, expressed as a percentage of the total, in three different periods of sampling (B).
Fig. 3Percentage of relative abundance for bacterial genera identified in nasopharyngeal swabs from patients with High or Low SARS-CoV-2 RNA amount.
Relative abundance of super-pathogen bacteria in nasopharyngeal samples from COVID-19 patients.
| Bacterial Species | OMS priority | Patients in which the pathogen has been identified | n° patients in which the pathogen represents >10% of total reads | n° patients in which the pathogen represents >5% of total reads | n° patients in which the pathogen represents >2% of total reads |
|---|---|---|---|---|---|
| High | 98% | 21 | 30 | 34 | |
| Critical | 80% | 0 | 2 | 12 | |
| High | 79% | 0 | 0 | 5 | |
| Medium | 52% | 0 | 0 | 1 | |
| Critical | 19% | 0 | 0 | 1 | |
| Critical | 16% | 0 | 0 | 1 |
Fig. 4Heatmap showing median centered expression values of 55 bacterial species across 89 samples from SARS-CoV-2 positive patients. Unsupervised hierarchical clustering, generated with Multi-Experiment Viewer (MeV 4.5.1) using default parameters revealed clear segregation of samples in two major clusters, characterized by a different abundance of commensal, opportunistic pathogens, and super-pathogen bacteria.