Search

ObjectiveTo examine the nasal microbiota in relation to otitis status and nose health in Indigenous Australian children.MethodsChildren aged 2-7 years were recruited from two northern Australian (Queensland) communities. Clinical histories were obtained through parent interview and review of the medical record. Nasal cavity swabs were obtained, and the child’s ears, nose and throat were examined. DNA was extracted and analysed by 16S rRNA amplicon next generation sequencing of the V3/V4 region in combination with previously generated culture data.Results103 children were recruited (mean 4.7 years), 17 (16.8%) were ‘healthy’, i.e. normal examination and no history of otitis media (OM). Nasal microbiota differed significantly in relation to otitis status and nose health. Children with historical OM had higher relative abundance of Moraxella compared to healthy children, despite both having healthy ears at the time of swabbing. Children with healthy noses had higher relative abundance of S. aureus compared to those with rhinorrhoea. Dolosigranulum was correlated to Corynebacterium in healthy children. Haemophilus and Streptococcus correlated across phenotypes. Ornithobacterium was absent/low relative abundance in healthy children and clustered around otopathogens. It correlated with Helcococcus and Dichelobacter.ConclusionsDolosigranulum and Corynebacterium form a synergism that promotes URT/ear health in Indigenous Australian children. Ornithobacterium likely represents Candidatus Ornithobacterium hominis and in this population is correlated with a novel bacterium which appears to be related to poor upper respiratory tract/ear health.ImportanceRecurring and chronic infections of the ear (otitis media) are disproportionately prevalent in disadvantaged communities across the globe, and in particular, within Indigenous communities. Despite numerous intervention strategies, otitis media persists as a major health issue and is the leading cause of preventable hearing loss. In disadvantaged communities, this hearing loss is associated with negative educational and social development outcomes, and consequently, poorer employment prospects and increased contact with the justice system in adulthood. Thus, a better understanding of the microbial ecology is needed in order to identify new targets to treat, as well as prevent the infections. This study used a powerful combination of 16S rRNA sequencing and extended culturomics to show that Dolosigranulum pigrum, a bacterium previously identified as a candidate protective species, may require co-colonisation with Corynebacterium pseudodiptheriticum in order to prevent otitis media. Additionally, emerging and potentially novel pathogens and bacteria were identified.

Coastal salt marshes are some of the most productive ecosystems on Earth, providing numerous services such as soil carbon storage, flood protection and nutrient filtering, several of which are mediated by the sediment microbiome associated with marsh vegetation. Here, nutrient filtering (nitrate removal through denitrification) was examined by determining microbial community structure (16S rRNA gene iTag sequencing), diversity, denitrification rates and metabolic potential (assembled metagenomic sequences) in collocated patches ofSpartina alterniflora(Spartina) andJuncus roemerianus(Juncus) sediments. The iTag data showed that diversity and richness inSpartinaandJuncussediment microbial communities were highly similar. However, microbial community evenness differed significantly, with the most even communities observed inJuncussediments. Further, denitrification rates were significantly higher inJuncuscompared toSpartina, suggesting oscillations in microbial abundances and in particular the core microbiome identified herein, along with plant diversity influence marsh nitrogen (N) removal. Amplicon and assembled metagenome sequences pointed to a potentially important, yet unappreciated Planctomycetes role in N removal in the salt marsh. Thus, perturbations, such as sea-level rise, that can alter marsh vegetation distribution could impact microbial diversity and may ultimately influence the ecologically important ecosystem functions the marsh sediment microbiome provides.

Ancestral sequence reconstruction is a technique that is gaining widespread use in molecular evolution studies and protein engineering. Accurate reconstruction requires the ability to handle appropriately large numbers of sequences, as well as insertion and deletion (“indel”) events, but available approaches exhibit limitations. To address these limitations, we developed Graphical Representation of Ancestral Sequence Predictions (GRASP), which efficiently implements maximum likelihood methods to enable the inference of ancestors of families with more than 10,000 members. GRASP implements partial order graphs (POGs) to represent and infer insertion and deletion events across ancestors, enabling the identification of building blocks for protein engineering.To validate the capacity to engineer novel proteins from realistic data, we predicted ancestor sequences across three distinct enzyme families: glucose-methanol-choline (GMC) oxidoreductases, cytochromes P450, and dihydroxy/sugar acid dehydratases (DHAD). All tested ancestors demonstrated enzymatic activity. Our study demonstrates the ability of GRASP (1) to support large data sets over 10,000 sequences and (2) to employ insertions and deletions to identify building blocks for engineering biologically active ancestors, by exploring variation over evolutionary time.Author summaryMassive sequencing projects expose the extent of natural, genetic diversity. Here, we describe a method with capacity to perform ancestor sequence reconstruction from data sets in excess of 10,000 sequences, poised to recover ancestral diversity, including the evolutionary events that determine present-time biological function and structure.We introduce a novel strategy for suggesting “indel variants” that are distinct from, but can be explored alongside, substitution variants for creating ancestral libraries. We demonstrate how indels can be used as building blocks to form “hybrid ancestors”; based on this strategy, we synthesise ancestor variants, with varying enzymatic activities, for wide-ranging applications in the biotechnology sector.