Nasal Microbiome in COVID-19: A Potential Role of Corynebacterium in Anosmia

Nasal Microbiota Profiling as a Predictive Secondary Tool for COVID-19 Diagnosis: The Critical Role of Taxonomic Resolution

The SARS-CoV-2 pandemic has led to an urgent need for effective and rapid diagnostic tools. In the present study, we have evaluated the predictive diagnostic potential of nasal microbiota by analyzing microbial community structures at different taxonomic level resolutions-species, genus, family, order, class and phylum-using Random Forest modelling. A total of 179 nasal swabs from COVID-19-positive (n = 85) and COVID-19-negative (n = 94) individuals were sequenced using a full-length 16S rRNA sequencing (Oxford Nanopore) approach. During each iteration of the Random Forest model, the dataset was randomly split into a training set (70%) and a testing set (30%). Model performance improved with finer taxonomic resolution, achieving the highest accuracy at the Species level (AUROC = 0.821 ± 0.059) and a sensitivity of 55.6% at a specificity threshold of 90%. A progressive decline in AUROC and sensitivity was observed at broader taxonomic levels. Furthermore, Beta diversity analysis supported that microbial community structures are more distinct between COVID-19-positive and COVID-19-negative groups at finer taxonomic levels. These findings highlight the potential role of nasal microbiota profiling as a secondary diagnostic tool for COVID-19, particularly at species- and genus-level classification, and underscore the importance of high taxonomic resolution in microbiome-based diagnostics. However, limited by an uneven sample distribution and the lack of medical evaluations, further large-scale studies are needed before the nasal microbiota can be implemented in the clinical diagnostics of COVID-19.

The relationship between gut and nasopharyngeal microbiome composition can predict the severity of COVID-19

Coronavirus disease 2019 (COVID-19) is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that displays great variability in clinical phenotype. Many factors have been described to be correlated with its severity, and microbiota could play a key role in the infection, progression, and outcome of the disease. SARS-CoV-2 infection has been associated with nasopharyngeal and gut dysbiosis and higher abundance of opportunistic pathogens. To identify new prognostic markers for the disease, a multicentre prospective observational cohort study was carried out in COVID-19 patients divided into three cohorts based on symptomatology: mild (n = 24), moderate (n = 51), and severe/critical (n = 31). Faecal and nasopharyngeal samples were taken, and the microbiota was analysed. Linear discriminant analysis identified Mycoplasma salivarium, Prevotella dentalis, and Haemophilus parainfluenzae as biomarkers of severe COVID-19 in nasopharyngeal microbiota, while Prevotella bivia and Prevotella timonensis were defined in faecal microbiota. Additionally, a connection between faecal and nasopharyngeal microbiota was identified, with a significant ratio between P. timonensis (faeces) and P. dentalis and M. salivarium (nasopharyngeal) abundances found in critically ill patients. This ratio could serve as a novel prognostic tool for identifying severe COVID-19 cases.

Insights into the Naso-Oropharyngeal Bacterial Composition in Suspected SARS-CoV-2 Cases

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was the causative agent of the coronavirus disease 2019 (COVID-19) pandemic. While research on COVID-19 has mainly focused on its epidemiology, pathogenesis, and treatment, studies on the naso-oropharyngeal microbiota have emerged in the last few years as an overlooked area of research. Here, we analyzed the bacterial community composition of the naso-oropharynx in 50 suspected SARS-CoV-2 cases (43 detected, 7 not detected) from Veraguas province (Panama) distributed across five age categories. Statistical analysis revealed no significant differences (p < 0.05) in bacterial alpha and beta diversities between the groups categorized by SARS-CoV-2 test results, age, or patient status. The genera Corynebacterium, Staphylococcus, Prevotella, Streptococcus, and Tepidiphilus were the most abundant in both detected and not-detected SARS-CoV-2 group. The linear discriminant analysis effect size (LEfSe) for biomarker exploration indicated that Veillonella and Prevotella were enriched in detected and hospitalized patients with SARS-CoV-2 relative to non-detected patients, while Thermoanaerobacterium and Haemophilus were enriched in non-detected patients with SARS-CoV-2. The results also indicated that the genus Corynebacterium was found to decrease in patients with detected SARS-CoV-2 relative to those with non-detected SARS-CoV-2. Understanding the naso-oropharyngeal microbiota provides insights into the diversity, composition, and resilience of the microbial community in patients with SARS-CoV-2.

Enrichment of SARS-CoV-2 sequence from nasopharyngeal swabs whilst identifying the nasal microbiome

Simultaneously characterising the genomic information of coronaviruses and the underlying nasal microbiome from a single clinical sample would help characterise infection and disease. Metatranscriptomic approaches can be used to sequence SARS-CoV-2 (and other coronaviruses) and identify mRNAs associated with active transcription in the nasal microbiome. However, given the large sequence background, unenriched metatranscriptomic approaches often do not sequence SARS-CoV-2 to sufficient read and coverage depth to obtain a consensus genome, especially with moderate and low viral loads from clinical samples. In this study, various enrichment methods were assessed to detect SARS-CoV-2, identify lineages and define the nasal microbiome. The methods were underpinned by Oxford Nanopore long-read sequencing and variations of sequence independent single primer amplification (SISPA). The utility of the method(s) was also validated on samples from patients infected seasonal coronaviruses. The feasibility of profiling the nasal microbiome using these enrichment methods was explored. The findings shed light on the performance of different enrichment strategies and their applicability in characterising the composition of the nasal microbiome.

Microbiome Profiling in Bladder Cancer Patients Using the First-morning Urine Sample

Background

Several studies support the interplay between the urinary microbiome (ie, urobiome) and bladder cancer (BCa). Specific urinary bacteria may be responsible for chronic inflammation, which in turn promotes carcinogenesis. Different signatures of urobiome in BCa patients were identified depending on tumor type, geographical area, age, and sex.

Objective

We explored the urobiome in BCa patients undergoing transurethral resection of bladder tumor (TURBT), to identify possible predictive biomarkers of cancer.

Design setting and participants

The urobiome analysis was conducted in 48 patients (13 females) undergoing TURBT, of whom 30 with BCa (five females) and 18 with benign bladder tumor, analyzing bacterial 16S rRNA by next-generation sequencing in first-morning (FM) urine samples. Forty-three cancer-free individuals and 17 prostate cancer patients were used as controls.

Outcome measurements and statistical analysis

First, we identified the better urine collection procedure to perform the urobiome analysis, comparing bacterial composition between catheterized (CAT) and FM urine samples in TURBT patients. Successively, we observed a specific urobiome in BCa patients rather than controls. A combined pipeline including the DESeq2 and linear discriminant analysis effect size tests was used to identify differential urinary taxa, strictly associated with BCa patients.

Results and limitations

The bacterial composition of CAT and FM urine samples was comparable, so the latter was used for the following analyses. An increased abundance of Porphyromonas and Porphyromonas somerae was found in BCa patients compared with controls. This signature seems to be more related (p <0.05) to male BCa patients over 50 yr old. Owing to the low biomass of urinary microbiota, several samples were excluded from the study, reducing the number of BCa patients considered.

Conclusions

FM urine samples represent a manageable specimen for a urobiome analysis; P. somerae is a specific biomarker of BCa risk.

Patient summary

Our study showed an increased abundance of Porphyromonas and Porphyromonas somerae in male bladder cancer (BCa) patients, supporting the use of a first-morning urine sample, a less invasive and low-cost collection method, for the urobiome analysis of patients at risk of BCa.

Detrimental effects of COVID-19 in the brain and therapeutic options for long COVID: The role of Epstein-Barr virus and the gut-brain axis

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in a serious public health burden worldwide. In addition to respiratory, heart, and gastrointestinal symptoms, patients infected with SARS-CoV-2 experience a number of persistent neurological and psychiatric symptoms, known as long COVID or "brain fog". Studies of autopsy samples from patients who died from COVID-19 detected SARS-CoV-2 in the brain. Furthermore, increasing evidence shows that Epstein-Barr virus (EBV) reactivation after SARS-CoV-2 infection might play a role in long COVID symptoms. Moreover, alterations in the microbiome after SARS-CoV-2 infection might contribute to acute and long COVID symptoms. In this article, the author reviews the detrimental effects of COVID-19 on the brain, and the biological mechanisms (e.g., EBV reactivation, and changes in the gut, nasal, oral, or lung microbiomes) underlying long COVID. In addition, the author discusses potential therapeutic approaches based on the gut-brain axis, including plant-based diet, probiotics and prebiotics, fecal microbiota transplantation, and vagus nerve stimulation, and sigma-1 receptor agonist fluvoxamine.

Analysis of the nasopharyngeal microbiome and respiratory pathogens in COVID-19 patients from Saudi Arabia

BACKGROUND

Infection with SARS-CoV-2 may perturb normal microbiota, leading to secondary infections that can complicate the viral disease. The aim of this study was to probe the alteration of nasopharyngeal (NP) microbiota in the context of SARS-CoV-2 infection and obesity and to identify other respiratory pathogens among COVID-19 cases that may affect patients' health.

METHODS

A total of 107 NP swabs, including 22 from control subjects and 85 from COVID-19 patients, were processed for 6S amplicon sequencing. The respiratory pathogens causing secondary infections were identified by RT-PCR assay, using a kit that contained specific primers and probes combinations to amplify 33 known respiratory pathogens.

RESULTS

No significant (p > 0.05) difference was observed in the alpha and beta diversity analysis, but specific taxa differed significantly between the control and COVID-19 patient groups. Genera of Sphingomonas, Kurthia, Microbacterium, Methylobacterium, Brevibacillus, Bacillus, Acinetobacter, Lactococcus, and Haemophilus was significantly abundant (p < 0.05) in COVID-19 patients compared with a healthy control group. Staphylococcus was found in relatively high abundance (35.7 %) in the COVID-19 patient groups, mainly those treated with antibiotics. A relatively high percentage of Streptococcus was detected in COVID-19 patient groups with obesity or other comorbidities. Respiratory pathogens, including Staphylococcus aureus, Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, and Salmonella species, along with Pneumocystis jirovecii fungal species were detected by RT-PCR mainly in the COVID-19 patients. Klebsiella pneumoniae was commonly found in most of the samples from the control and COVID-19 patients. Four COVID-19 patients had viral coinfections with human adenovirus, human rhinovirus, enterovirus, and human parainfluenza virus 1.

CONCLUSIONS

Overall, no substantial difference was observed in the predominant NP bacterial community, but specific taxa were significantly changed between the healthy control and COVID-19 patients. Comparatively, an increased number of respiratory pathogens were identified in COVID-19 patients, and NP colonization by K. pneumoniae was probably occurring in the local population.