Search

The oral microbiome, studied by sampling the saliva or by oral rinse, has been long thought to have diagnostic capacity for head and neck cancers (HNC). However, previous reports on the HNC oral microbiome provide inconsistent results. The aim of this study is to consolidate these datasets and determine the oral microbial composition between HNC patients to healthy and premalignant individuals. We analyzed 16 published head and neck cancer (HNC) short-read 16S rRNA sequencing datasets, specifically targeting the V3V4, V4 and V4V5 regions. These datasets included saliva and oral rinse samples from donors with HNC, as well as from healthy and premalignant donors. Differences in diversities and microbial abundance were determined. HNC saliva displayed lower alpha diversity than healthy donors. In contrast, the opposite trend was observed for oral rinse samples. Beta diversity scores were largely similar across different patient types. Similar oral phyla were detected for all samples, but proportions were largely dependent on sample type (i.e., saliva or oral rinse) and primer set utilized for 16S rRNA sequencing. Neisseria, Leptotrichia and Megasphaera were elevated in healthy saliva, while Mycoplasma was elevated in HNC saliva. Oral rinse and saliva displayed similar enrichment for Fusobacterium, while Veillonella, Alloprevotella, and Campylobacter showed conflicting results. The sparse partial least squares discriminant analysis model performed effectively in discriminating HNC from healthy or premalignant patients using V3V4 saliva (AUC = 0.888) and V3V4 oral rinse (AUC = 0.928), while poor discriminative capacity was observed for V4 saliva (AUC = 0.688). In conclusion, our meta-analysis highlighted the limitations of 16S rRNA sequencing, particularly due to variations across study batches, primer sets (i.e., V3V4, V4), and sample types. Hence, caution should be exercised when interpreting 16S rRNA sequencing results across studies, especially when different primer sets and sample types are used. [ABSTRACT FROM AUTHOR]

Introduction: In chronic rhinosinusitis (CRS), the congestion and blockage of the nose can cause anaerobic conditions within the sinus cavities which may promote the expression of virulence and antibiotic resistance genes in invading pathogens. Pseudomonas aeruginosa is a facultative anaerobic bacteria and causes severe recalcitrant CRS. In this study, we aimed to evaluate the antimicrobial resistance of P. aeruginosa isolates of CRS patients in planktonic and biofilm form grown in aerobic and anaerobic conditions. Methods: P. aeruginosa clinical isolates of CRS patients (n = 25) were grown in planktonic and biofilm form in aerobic and anaerobic conditions. Minimum inhibitory concentrations (MIC) of planktonic forms and minimum biofilm eradication concentrations (MBEC) were determined. Additionally, metabolic activity by fluorescein diacetate assay, biofilm biomass by crystal violet assay and eDNA concentration were assessed in both conditions. Results: P. aeruginosa planktonic cells grown in anaerobic condition exhibited increased gentamicin resistance (p < .01), whereas P. aeruginosa biofilms grown in anaerobic condition displayed significantly increased MBEC values for gentamicin (p < .0001) and levofloxacin (p < .001). The metabolic activity of anaerobic biofilms was significantly higher compared with aerobic biofilms (p < .0001). However, the biofilm biomass of isolates grown in aerobic conditions was higher than anaerobic conditions (p < .5). Conclusion: P. aeruginosa isolates from CRS patients grown in anaerobic conditions showed significantly increased resistance to antibiotics with an increased metabolic activity but decreased biofilm biomass. [ABSTRACT FROM AUTHOR]

Chronic rhinosinusitis (CRS) represents chronic inflammation of the sinus mucosa characterised by dysfunction of the sinuses' natural defence mechanisms and induction of different inflammatory pathways ranging from a Th1 to a Th2 predominant polarisation. Recalcitrant CRS is associated with Staphylococcus aureus dominant mucosal biofilms; however, S. aureus colonisation of the sinonasal mucosa has also been observed in healthy individuals challenging the significance of S. aureus in CRS pathogenesis. We aimed to investigate the relationship between CRS key inflammatory markers, S. aureus biofilm properties/virulence genes and the severity of the disease. Tissue samples were collected during endoscopic sinus surgery from the ethmoid sinuses of CRS patients with (CRSwNP) and without (CRSsNP) nasal polyps and controls (n = 59). CD3+ T‐cell subset frequencies and key inflammatory markers of CD4+ helper T cells were determined using FACS analysis. Sinonasal S. aureus clinical isolates were isolated (n = 26), sequenced and grown into biofilm in vitro, followed by determining their properties, including metabolic activity, biomass, colony‐forming units and exoprotein production. Disease severity was assessed using Lund–Mackay radiologic scores, Lund–Kennedy endoscopic scores and SNOT22 quality of life scores. Our results showed that S. aureus biofilm properties and CRS severity scores correlated positively with total CD4+ T‐cell frequencies but looking into CD4+ T‐cell subsets showed an inverse correlation with Th1 and Th17 cell frequencies. CD4+ T‐cell frequencies were higher in patients harbouring lukF.PV‐positive S. aureus while its regulatory and Th17 cell subset frequencies were lower in patients carrying sea− and sarT/U‐positive S. aureus. Recalcitrant CRS is characterised by increased S. aureus biofilm properties in relation to increased total CD4+ helper T‐cell frequencies and reduced frequencies of its Th1, Th17 and regulatory T‐cell subsets. These findings offer insights into the pathophysiology of CRS and could lead to the development of more targeted therapies. [ABSTRACT FROM AUTHOR]

Summary In recent years, there has been an increasing interest in bacteriophages, which has led to growing numbers of bacteriophage genomic sequences becoming available. Consequently, there is a need for a rapid and consistent genomic annotation tool dedicated for bacteriophages. Existing tools either are not designed specifically for bacteriophages or are web- and email-based and require significant manual curation, which makes their integration into bioinformatic pipelines challenging. Pharokka was created to provide a tool that annotates bacteriophage genomes easily, rapidly and consistently with standards compliant outputs. Moreover, Pharokka requires only two lines of code to install and use and takes under 5 min to run for an average 50-kb bacteriophage genome. Availability and implementation Pharokka is implemented in Python and is available as a bioconda package using 'conda install -c bioconda pharokka'. The source code is available on GitHub (https://github.com/gbouras13/pharokka). Pharokka has been tested on Linux-64 and MacOSX machines and on Windows using a Linux Virtual Machine. [ABSTRACT FROM AUTHOR]