Biology subjects

Vreugde, S.

Publications and source records attributed to Vreugde, S..

14 recordsLinked to original sources

bioRxiv2026

Genus-wide re-speciation of Corynebacterium and genomic characterisation of 87 sinus isolates resolves taxonomic conflicts and identifies four candidate novel species

Corynebacterium species are common members of the sinonasal microbiome and have shown conflicting associations with sinus health and chronic rhinosinusitis (CRS) in genus-level surveys. To better resolve the taxonomy and species-level functions of sinus corynebacteria, we generated complete long-read genome assemblies for 87 isolates, sourced from the middle meatus of 71 patients (51 with CRS, 20 healthy controls). We re-derived species boundaries de novo across the whole genus by average nucleotide identity (ANI), clustering 4,661 quality-filtered genomes retrieved from public databases and delineating higher-order species complexes. Our re-speciation assigned a species to 282 unlabelled corynebacteria, and corrected taxonomy for 266 NCBI accessions. We identified four novel candidate species from our isolate collection, and 39 public genomes fell within these species' boundaries. Whole-genome assignment reclassified 41 of our 87 isolates relative to mass-spectrometry (MALDI-TOF MS) identification, which only resolved to the species-complex level. Comparison of genome annotation characterised accessory functions that partitioned along species-complex lines, including glycogen and glycan utilisation, fatty-acid biosynthesis, cofactor (biotin and thiamine) auxotrophy, and iron-acquisition systems. Virulence and antimicrobial-resistance determinants were sparse, and the diphtheria toxin gene was universally absent. Acquired antimicrobial resistance was enriched on plasmids, whilst virulence genes were depleted from horizontally transferred compartments. Contrary to its frequent report in sinus microbiome studies, no C. tuberculostearicum genome publicly accessible via NCBI was found to be isolated from the sinonasal tract. Continued genome-level interrogation of Corynebacterium and contribution of sinus-commensals to reference databases will improve species-level understanding of the role of corynebacteria in the sinonasal microbiome.

microbiology↗

bioRxiv2026

Mutations in mfd cause Staphylococcus aureus mucoid hyper-biofilm phenotype in chronic rhinosinusitis

Chronic Rhinosinusitis (CRS) is a common chronic inflammation of the paranasal sinus mucosa. Staphylococcus aureus contributes to its severity through biofilm formation. In this study, we isolated eight sequential methicillin-resistant S. aureus (MRSA) isolates from a patient with severe CRS over a period of 672 days (T1-T8). The isolates were phenotypically and genomically characterised, and the extracellular biofilm proteome analysed. We identified an accumulation of mutations that included the acquisition of an IS21 family insertion sequence inactivating the icaR gene and nucleotide variants in various genes including the transcription repair coupling factor (mfd). The genomic changes were associated with a switch to a mucoid phenotype from T3 onwards (Day 178), with a significant increase in biofilm-forming capacity and the secretion of multiple enterotoxins. Targeted mutagenesis confirmed mfd is a regulator of strain mucoidy with enhanced biofilm and enterotoxin production. These findings support mfd as a target for novel anti-virulence therapies.

microbiology↗

bioRxiv2026

Baktfold: Sensitive protein functional annotation across the microbial tree of life using structural information

The functional annotation of protein sequences has undergone tremendous progress over recent years, but still too-many protein sequences remain as so-called hypothetical proteins after applying state-of-the-art genome annotation software pipelines. Here, we introduce Baktfold, a new command line software tool for the ultra-sensitive but taxon-independent fast annotation of protein sequences across the microbial tree of life. Baktfold conducts sequential protein structure-based searches against four complementary structure databases. Protein sequences are transformed into Foldseek 3Di tokens via the ProstT5 protein language model and subsequently searched against structure databases via Foldseek. All results are exported in GFF3 and INSDC-compliant flat files as well as comprehensive JSON files facilitating automated downstream analysis 100% interoperable with the popular bacterial annotation tool Bakta. We compared Baktfolds performance in terms of wallclock runtime and functional annotation of hypothetical proteins from various sources including bacterial and archaeal isolates, plasmids, metagenomic-assembled genomes and micro-eukaryotes. When benchmarked on over three hundred thousand species representatives across the prokaryotic tree of life, Baktfolds median overall bacterial genome annotation rate is 87.8% compared to 72.9% with Bakta, while Baktfolds median bacterial annotation rate of remaining hypothetical proteins is 50.1% (n=290258). For archaea, Baktfolds overall median annotation rate is 71.5% compared to Prokkas 35.8%, with a median archaeal annotation rate of hypothetical proteins of 68.0% (n=14058), making Baktfold the most sensitive automated archaeal annotation method by far. Baktfold is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a MIT license at https://github.com/gbouras13/baktfold. Data SummaryO_LIBaktfold was developed in Python as a command line application for Linux and MacOS C_LIO_LIThe complete source code and documentation are available on GitHub under an MIT license: https://github.com/gbouras13/baktfold C_LIO_LIThe Baktfold database is hosted at Zenodo (https://zenodo.org/records/17347516) mirrored on HuggingFace (https://huggingface.co/datasets/gbouras13/baktfold-db) C_LIO_LIBaktfold is available via bioconda (https://anaconda.org/bioconda/baktfold) and PyPI (https://pypi.org/project/baktfold/) C_LIO_LIBaktfold can also be run without local installation using Google Colab at https://colab.research.google.com/github/gbouras13/baktfold/blob/main/run_baktfold. ipynb C_LIO_LIAll supplementary code, data and files required to reproduce the results of this manuscript are available at https://github.com/gbouras13/baktfold-analysis (code and small data) and https://zenodo.org/records/19333697 (large data) C_LI

bioinformatics↗

bioRxiv2025

Protein Structure Informed Bacteriophage Genome Annotation with Phold

Bacteriophage (phage) genome annotation is essential for understanding their functional potential and suitability for use as therapeutic agents. Here we introduce Phold, an annotation framework utilising protein structural information that combines the ProstT5 protein language model and structural alignment tool Foldseek. Phold assigns annotations using a database of over 1.36 million predicted phage protein structures with high quality functional labels. Benchmarking reveals that Phold outperforms existing sequence-based homology approaches in functional annotation sensitivity whilst maintaining speed, consistency and scalability. Applying Phold to diverse cultured and metagenomic phage genomes shows it consistently annotates over 50% of genes on an average phage and 40% on an average archaeal virus. Comparisons of phage protein structures to other protein structures across the tree of life reveals that phage proteins commonly have structural homology to proteins shared across the tree of life, particularly those that have nucleic acid metabolism and enzymatic functions. Phold is available as free and open-source software at https://github.com/gbouras13/phold.

bioinformatics↗

bioRxiv2025

LicD-Mediated Cell Wall Decoration Governs Phage Sensitivity in Enterococcus faecalis Clinical Isolates

Enterococcus faecalis has emerged as a prevalent antibiotic-resistant pathogen in clinical settings. Herein, we report the identification of three novel lytic phages targeting vancomycin-resistant E. faecalis. While the isolated phages all belonged to the Kochikohdavirus genus, there were distinctive differences in their tail fibre proteins, affecting their adsorption. The phages showed strong antibacterial activity with wide host range, infecting >90% of the tested E. faecalis clinical and hospital wastewater isolates (n=13) with variable efficiency. The variation in host range was genomically correlated to the presence of the LicD gene in phage sensitive bacteria, which is responsible for phosphorylcholine decoration of the bacterial cell wall. Furthermore, the isolated phages were predicted to harbour genes encoding for depolymerase enzymes, which was confirmed by in vitro testing showing a >80% reduction in biofilm biomass. Phages inhibited bacterial growth for [≥]12 hours, followed by the emergence of bacteriophage insensitive mutants (BIMs) that were 4-fold more sensitive to vancomycin compared to parent strains. In addition, the isolated BIMs showed less capability of evading THP-1 macrophage and produced weaker biofilms. These findings underpin the potential of the isolated phages in combating recalcitrant E. faecalis associated biofilm-mediated infections.

microbiology↗

bioRxiv2024

How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies

It is now possible to assemble near-perfect bacterial genomes using Oxford Nanopore Technologies (ONT) long reads, but short-read polishing is still required for perfection. However, the effect of short-read depth on polishing performance is not well understood. Here, we introduce Pypolca (with default and careful parameters) and Polypolish v0.6.0 (with a new careful parameter). We then show that: (1) all polishers other than Pypolca-careful, Polypolish-default and Polypolish-careful commonly introduce false-positive errors at low depth; (2) most of the benefit of short-read polishing occurs by 25x depth; (3) Polypolish-careful never introduces false-positive errors at any depth; and (4) Pypolca-careful is the single most effective polisher. Overall, we recommend the following polishing strategies: Polypolish-careful alone when depth is very low (<5x), Polypolish-careful and Pypolca-careful when depth is low (5-25x), and Polypolish-default and Pypolca-careful when depth is sufficient (>25x). Data SummaryPypolca is open-source and freely available on Bioconda, PyPI, and GitHub (github.com/gbouras13/pypolca). Polypolish is open-source and freely available on Bioconda and GitHub (github.com/rrwick/Polypolish). All code and data required to reproduce analyses and figures are available at github.com/gbouras13/depth_vs_polishing_analysis. All FASTQ sequencing reads are available at BioProject PRJNA1042815. A detailed list of accessions can be found in Table S1.

bioinformatics↗

bioRxiv2024

A comparison between full-length 16S rRNA Oxford Nanopore sequencing and Illumina V3-V4 16S rRNA sequencing in head and neck cancer tissues

IntroductionDescribing the microbial community within the tumour has been a key aspect in understanding the pathophysiology of the tumour microenvironment. In head and neck cancer (HNC), most studies on tissue samples have only performed 16S ribosomal RNA (rRNA) short-read sequencing (SRS) on V3-V5 region. SRS is mostly limited to genus level identification. In this study, we compared full-length 16S rRNA long-read sequencing (FL-ONT) from Oxford Nanopore Technology (ONT) to V3-V4 Illumina SRS (V3V4-Illumina). To date, this is the largest study using HNC tissues samples to perform FL-ONT of the 16S rRNA using ONT. MethodsSequencing of the full-length and the V3-V4 16S rRNA region was conducted on tumour samples from 26 HNC patients, using ONT and Illumina technologies respectively. Paired sample analysis was applied to compare differences in diversities and abundance of microbial communities. Further validation was also performed using culture-based methods in 16 bacterial isolates obtained from 4 patients using MALDI-TOF MS. ResultsWe observed similar alpha diversity indexes between FL-ONT and V3V4-Illumina technologies. However, beta-diversity was significantly different between techniques (PERMANOVA - R2 = 0.083, p < 0.0001). At higher taxonomic levels (Phylum to Family), all metrics were more similar among sequencing techniques, while lower taxonomy displayed more discrepancies. At higher taxonomic levels, correlation in microbial abundance from FL-ONT and V3V4-Illumina were higher, while this correlation decreased at lower levels. Finally, FL-ONT was able to identify more isolates at the species level that were identified using MALDI-TOF MS (81.3% v.s. 62.5%). ConclusionsFL-ONT was able to identify lower taxonomic levels at a better resolution as compared to V3V4-Illumina 16S rRNA sequencing. Depending on application purposes, both methods are suitable for identification of microbial communities, with FL-ONT being more superior at species level.

microbiology↗

bioRxiv2023

Hybracter: Enabling Scalable, Automated, Complete and Accurate Bacterial Genome Assemblies

Improvements in the accuracy and availability of long-read sequencing mean that complete bacterial genomes are now routinely reconstructed using hybrid (i.e. short- and long-reads) assembly approaches. Complete genomes allow a deeper understanding of bacterial evolution and genomic variation beyond single nucleotide variants (SNVs). They are also crucial for identifying plasmids, which often carry medically significant antimicrobial resistance (AMR) genes. However, small plasmids are often missed or misassembled by long-read assembly algorithms. Here, we present Hybracter which allows for the fast, automatic, and scalable recovery of near-perfect complete bacterial genomes using a long-read first assembly approach. Hybracter can be run either as a hybrid assembler or as a long-read only assembler. We compared Hybracter to existing automated hybrid and long-read only assembly tools using a diverse panel of samples of varying levels of long-read accuracy with manually curated ground truth reference genomes. We demonstrate that Hybracter as a hybrid assembler is more accurate and faster than the existing gold standard automated hybrid assembler Unicycler. We also show that Hybracter with long-reads only is the most accurate long-read only assembler and is comparable to hybrid methods in accurately recovering small plasmids. Data SummaryO_LIHybracter is developed using Python and Snakemake as a command-line software tool for Linux and MacOS systems. C_LIO_LIHybracter is freely available under an MIT License on GitHub (https://github.com/gbouras13/hybracter) and the documentation is available at Read the Docs (https://hybracter.readthedocs.io/en/latest/). C_LIO_LIHybracter is available to install via PyPI (https://pypi.org/project/hybracter/) and Bioconda (https://anaconda.org/bioconda/hybracter). A Docker/Singularity container is also available at https://quay.io/repository/gbouras13/hybracter. C_LIO_LIAll code used to benchmark Hybracter, including the reference genomes, is publicly available on GitHub (https://github.com/gbouras13/hybracter_benchmarking) with released DOI (https://zenodo.org/doi/10.5281/zenodo.10910108) available at Zenodo. C_LIO_LIThe subsampled FASTQ files used for benchmarking are publicly available at Zenodo with DOI (https://doi.org/10.5281/zenodo.10906937). C_LIO_LIAll super accuracy simplex ATCC FASTQ reads sequenced as a part of this study can be found under BioProject PRJNA1042815. C_LIO_LIAll Hall et al. fast accuracy simplex and super accuracy duplex ATCC FASTQ read files (prior to subsampling) can be found in the SRA under BioProject PRJNA1087001. C_LIO_LIAll raw Lermaniaux et al. FASTQ read files and genomes (prior to subsampling) can be found in the SRA under BioProject PRJNA1020811. C_LIO_LIAll Staphylococcus aureus JKD6159 FASTQ read files and genomes can be found under BioProject PRJNA50759. C_LIO_LIAll Mycobacterium tuberculosis H37R2 FASTQ read files and genomes can be found under BioProject PRJNA836783. C_LIO_LIThe complete list of BioSample accession numbers for each benchmarked sample can be found in Supplementary Table 1. C_LIO_LIThe benchmarking assembly output files are publicly available on Zenodo with DOI (https://doi.org/10.5281/zenodo.10906937). C_LIO_LIAll Pypolca benchmarking outputs and code are publicly available on Zenodo with DOI (https://zenodo.org/doi/10.5281/zenodo.10072192). C_LI Impact StatementComplete bacterial genome assembly using hybrid sequencing is a routine and vital part of bacterial genomics, especially for identification of mobile genetic elements and plasmids. As sequencing becomes cheaper, easier to access and more accurate, automated assembly methods are crucial. With Hybracter, we present a new long-read first automated assembly tool that is faster and more accurate than the widely-used Unicycler. Hybracter can be used both as a hybrid assembler and with long-reads only. Additionally, it solves the problems of long-read assemblers struggling with small plasmids, with plasmid recovery from long-reads only performing on par with hybrid methods. Hybracter can natively exploit the parallelisation of high-performance computing (HPC) clusters and cloud-based environments, enabling users to assemble hundreds or thousands of genomes with one line of code. Hybracter is available freely as source code on GitHub, via Bioconda or PyPi.

bioinformatics↗

bioRxiv2023

Bacteriophage in combination with ciprofloxacin against Pseudomonas aeruginosa infections in diabetic foot ulcer patients

BackgroundIn diabetic foot ulcer (DFU) patients, Pseudomonas aeruginosa (P. aeruginosa) infections are linked to poor wound healing. The ineffectiveness of antibiotics against these infections promotes the emergence of multidrug-resistant (MDR) strains. Bacteriophage (phage) therapy has recently gained popularity as an alternative to antibiotics. MethodologyBacterial and viral swabs and tissue were obtained from DFU infections (DFI). Bacteria were cultured followed by MALDI-TOF MS for identification. 16S rRNA long-read sequencing was used to identify the microbiota. Bacteriophages were isolated and underwent transmission electron microscopy, genomic sequencing, and stability testing. The antimicrobial activity of phages alone and in combination with ciprofloxacin against P. aeruginosa planktonic cells and biofilm grown in vitro and in ex vivo tissue was tested by measuring the optical density (OD), crystal violet assays and live/dead staining with visualisation using confocal scanning laser microscopy respectively. ResultsA total of 34 DFI patients were recruited from which microbiota were analysed for 25 patients. P. aeruginosa was the most prevalent pathogen cultured and was one of the top 6 most prevalent and abundant species in the microbiota analysis. Phage APTC-PA18 was isolated from DFIs, belonged to the myoviridae family and was strictly lytic. PA18 was stable between 4 and 70 degrees Celsius and between pH 3 and 11. Seven of eight P. aeruginosa clinical isolates were sensitive to APTC-PA18, and when APTC-PA18 was combined with ciprofloxacin against planktonic and biofilm of P. aeruginosa, synergistic effects were observed in vitro and in DFI tissue samples. ConclusionPhage APTC-PA18, when combined with ciprofloxacin, has the ability to kill P. aeruginosa clinical isolates both in vitro and ex vivo and is a promising treatment option for P. aeruginosa infections in DFUs.

microbiology↗

bioRxiv2023

Prophage acquisition by Staphylococcus aureus contributes to the expansion of Staphylococcal immune evasion

Staphylococcus aureus colonizes 30% of the human population, but only a few clones cause severe infections. S. aureus virulence varies and partly depends on the presence of prophages, viral DNA embedded in the S. aureus core genome, such as hlb-converting prophage ({phi}Sa3int). Human-adapted S. aureus often harbours a {phi}Sa3int group of prophages preferentially integrated into their {beta}-hemolysin (hlb) gene that encodes human immune evasion cluster (IEC) genes. Exotoxins and immune modulatory molecules encoded by this prophage can inhibit human innate immunity increasing S. aureus pathogenicity. This study aims to investigate the genomic and phenotypic plasticity of S. aureus and changes in its extracellular proteome after the acquisition of {phi}Sa3int prophage. To achieve this, we used S. aureus strains isolated from the sinus cavities of a patient with severe chronic rhinosinusitis (CRS) at two different time points (S. aureus SA222 and S. aureus SA333) and hybrid sequenced the strains using short-read Illumina and long-read Oxford nanopore technology. In silico analysis showed the presence of a {phi}Sa3int prophage in the later isolate but not in the earlier isolate while most of the core genes remained identical. Using mitomycin C, we induced the {phi}Sa3int prophage, and transduced it into the Sa3int-prophage-free SA222 isolate to obtain a laboratory generated double lysogen. We confirmed the successful lysogenisation with culture methods (spot assay, blood agar) and also by sequencing. We compared growth kinetics, biofilm biomass and metabolic activity between parent and the lysogen by establishing growth curves, crystal violet and resazurin assays. Exoproteins were identified and quantified using mass spectrophotometry. Integration of {phi}Sa3int prophage in SA222 down-regulated the beta-hemolysin expression of the lysogen. In silico analysis of the S. aureus genome confirmed the insertion of a [~]43.8 kb {phi}Sa3int prophage into hlb gene. Insertion of prophage DNA did not alter the growth kinetics, biofilm formation, adhesion to primary human nasal epithelial cells and the metabolic activity in a biofilm. However, the acquisition of {phi}Sa3int prophage significantly changed the expression of various secreted proteins, both bacterial and prophage-encoded. Altogether, thirty-eight exoproteins were significantly differentially regulated in the laboratory created lysogen, compared to its recipient strain SA222. Among these proteins, there was significant upregulation of 21 exoproteins (55.3 %) including staphylokinase (sak), SCIN (scn), and intercellular adhesion protein B (icaB) and downregulation of 17 exoproteins (44.7 %), including {beta}-hemolysin (hlb/sph) and outer membrane porin (phoE). Most of the upregulated proteins were involved in immunomodulation that help S. aureus escape human innate immunity and help cause chronic infection. These findings may contribute to the development of novel approaches to render S. aureus susceptible to the immune response by blocking prophage-associated defence mechanisms. HighlightsO_LIA {phi}Sa3int prophage preferentially integrates into the {beta}-haemolysin gene (hlb) gene thereby disrupting the beta-hemolysin function. C_LIO_LIA [~]43.8 kb {phi}Sa3int prophage acquisition by S. aureus has no impact on its growth kinetics, biofilm formation and adhesion to primary human nasal epithelial cells (HNECs). C_LIO_LIThe presence of a {phi}Sa3int group prophage likely enhances Staphylococcus aureus human immune evasion capability as the prophage encodes a complete set of immune evasion cluster (IEC) genes. C_LIO_LITargeted identification of virulence factors in addition to species and strain identification may lead to better-personalized therapy as not all S. aureus carry the same virulence genes. C_LI

microbiology↗

bioRxiv2023

Staphylococcus aureus biofilm secreted factors cause mucosal damage, mast cell infiltration and goblet cell hyperplasia in a rat rhinosinusitis model

Chronic Rhinosinusitis (CRS) is an inflammatory condition of the paranasal sinus mucosa. Despite being a common health issue, the exact cause of CRS is yet to be understood. However, research suggests that Staphylococcus aureus, particularly in the biofilm form, drives the disease. This study aimed to investigate the impact of long-term exposure to secreted factors of Staphylococcus aureus biofilm (SABSF), harvested from clinical isolates of non-CRS carriers and CRS patients, on the nasal mucosa in a rat model. Wistar rats were randomised (n=5/group) to receive daily intranasal instillations of 40 L (200 g/L) SABSF for 28 days or vehicle control with S. aureus isolated from the sinuses of a non-CRS carrier, a type 2 endotype CRS with nasal polyps (CRSwNP) patient, and a non-type 2 endotype CRS without nasal polyps (CRSsNP) patient. The sinonasal samples of the rats were then analysed through histopathology and transcriptome profiling. The results showed that all three intervention groups displayed significant lymphocytic infiltration (p[≤]0.05). However, only the SABSF collected from the CRSwNP patient caused significant mucosal damage, mast cell infiltration, and goblet cell hyperplasia compared to the control. The transcriptomics results indicated that SABSF significantly enriched multiple inflammatory pathways and showed distinct transcriptional expression differences between the control group and the SABSF collected from CRS patients (p[≤]0.05). Additionally, the SABSF challenges induced the expression of IgA and IgG but not IgE. In conclusion, this in vivo study indicates that long-term exposure to SABSF leads to an inflammatory response in the nasal mucosa with increased severity for S. aureus isolated from a CRSwNP patient. The findings of this study shed light on the role of S. aureus in the development of CRS and could inform future research and treatment efforts.

immunology↗

bioRxiv2023

The Intra-Host Evolutionary Landscape And Pathoadaptation Of Persistent Staphylococcus aureus In Chronic Rhinosinusitis

Chronic rhinosinusitis (CRS) is a common chronic sinonasal mucosal inflammation associated with Staphylococcus aureus biofilm and relapsing infections. This study aimed to determine rates of S. aureus persistence and pathoadaptation in CRS patients by investigating the genomic relatedness and antibiotic resistance/tolerance in longitudinally collected S. aureus clinical isolates. A total of 68 S. aureus isolates were sourced from 34 CRS patients at least six months apart. Isolates were grown into 48-hour biofilms and tested for tolerance to antibiotics. A hybrid sequencing strategy was used to obtain high-quality reference-grade assemblies of all isolates. Single nucleotide variants (SNV) divergence in the core genome and sequence type clustering were used to analyse the relatedness of the isolate pairs. Single nucleotide and structural genome variations, plasmid similarity, and plasmid copy numbers between pairs were examined. Our analysis revealed that 41% (14/34 pairs) of S. aureus isolates were persisters, while 59% (20/34 pairs) were non-persisters. Persister isolates showed episode-specific mutational changes over time with a bias towards events in genes involved in adhesion to the host and mobile genetic elements such as plasmids, prophages, and insertion sequences. A significant increase in the copy number of conserved plasmids of persister strains (p<0.05) was seen, indicating a role of the "mobilome" in promoting persistence. This was accompanied by a significant increase in biofilm tolerance against all tested antibiotics (p<0.001), which was linked to a significant increase in biofilm biomass (p<0.05) over time, indicating a biofilm central pathoadaptive process in persisters. In conclusion, our study provides important insights into the mutational changes underlying S. aureus persistence in CRS patients highlighting pathoadaptive mechanisms in S. aureus persisters culminating in increased biofilm biomass linked to an increase in plasmid copy number over time.

microbiology↗

bioRxiv2019

Microbiotyping the sinonasal microbiome

This study offers a novel description of the sinonasal microbiome, through an unsupervised machine learning approach combining dimensionality reduction and clustering. We apply our method to the International Sinonasal Microbiome Study (ISMS) dataset of 410 sinus swab samples. We propose three main sinonasal microbiotypes or states: the first is Corynebacterium-dominated, the second is Staphylococcus-dominated, and the third dominated by the other core genera of the sinonasal microbiome (Streptococcus, Haemophilus, Moraxella, and Pseudomonas). The prevalence of the three microbiotypes studied did not differ between healthy and diseased sinuses, but differences in their distribution were evident based on geography. We also describe a potential reciprocal relationship between Corynebacterium species and Staphylococcus aureus, suggesting that a certain microbial equilibrium between various players is reached in the sinuses. We validate our approach by applying it to a separate 16S rRNA gene sequence dataset of 97 sinus swabs from a different patient cohort. Sinonasal microbiotyping may prove useful in reducing the complexity of describing sinonasal microbiota. It may drive future studies aimed at modeling microbial interactions in the sinuses and in doing so may facilitate the development of a tailored patient-specific approach to the treatment of sinus disease in the future.

microbiology↗

bioRxiv2019

The international sinonasal microbiome study (ISMS): a multi centre, international characterization of sinonasal bacterial ecology

The sinonasal microbiome remains poorly defined, with our current knowledge based on a few cohort studies whose findings are inconsistent. Furthermore, the variability of the sinus microbiome across geographical divides remains unexplored. We characterise the sinonasal microbiome and its geographical variations in both health and disease using 16S rRNA gene sequencing of 410 individuals from across the world. Although the sinus microbial ecology is highly variable between individuals, we identify a core microbiome comprised of Corynebacterium, Staphylococcus, Streptococcus, Haemophilus, and Moraxella species in both healthy and chronic rhinosinusitis (CRS) cohorts. Corynebacterium (mean relative abundance = 44.02%) and Staphylococcus (mean relative abundance = 27.34%) appear particularly dominant in the majority of patients sampled. There was a significant variation in microbial diversity between countries (p = 0.001). Amongst patients suffering from CRS with nasal polyps, a significant depletion of Corynebacterium (40.29% vs 50.43%; p = 0.02) and over-representation of Streptococcus (7.21% vs 2.73%; p = 0.032) was identified. The delineation of the sinonasal microbiome and standardised methodology described within our study will enable further characterisation and translational application of the sinus microbiota.

microbiology↗