The oral microbiota is a reservoir for antimicrobial resistance: resistome and phenotypic resistance characteristics of oral biofilm in health, caries, and periodontitis

BACKGROUND

Antimicrobial resistance (AMR) is an ever-growing threat to modern medicine and, according to the latest reports, it causes nearly twice as many deaths globally as AIDS or malaria. Elucidating reservoirs and dissemination routes of antimicrobial resistance genes (ARGs) are essential in fighting AMR. Human commensals represent an important reservoir, which is underexplored for the oral microbiota. Here, we set out to investigate the resistome and phenotypic resistance of oral biofilm microbiota from 179 orally healthy (H), caries active (C), and periodontally diseased (P) individuals (TRN: DRKS00013119, Registration date: 22.10.2022). The samples were analysed using shotgun metagenomic sequencing combined, for the first time, with culture technique. A selection of 997 isolates was tested for resistance to relevant antibiotics.

RESULTS

The shotgun metagenomics sequencing resulted in 2,069,295,923 reads classified into 4856 species-level OTUs. PERMANOVA analysis of beta-diversity revealed significant differences between the groups regarding their microbiota composition and their ARG profile. The samples were clustered into three ecotypes based on their microbial composition. The bacterial composition of H and C samples greatly overlapped and was based on ecotypes 1 and 2 whereas ecotype 3 was only detected in periodontitis. We found 64 ARGs conveying resistance to 36 antibiotics, particularly to tetracycline, macrolide-lincosamide-streptogramin, and beta-lactam antibiotics, and a correspondingly high prevalence of phenotypic resistance. Based on the microbiota composition, these ARGs cluster in different resistotypes, and a higher prevalence is found in healthy and caries active than in periodontally diseased individuals. There was a significant association between the resistotypes and the ecotypes. Although numerous associations were found between specific antibiotic resistance and bacterial taxa, only a few taxa showed matching associations with both genotypic and phenotypic analyses.

CONCLUSIONS

Our findings show the importance of the oral microbiota from different niches within the oral cavity as a reservoir for antibiotic resistance. Additionally, the present study showed the need for using more than one method to reveal antibiotic resistance within the total oral biofilm, as a clear mismatch between the shotgun metagenomics method and the phenotypic resistance characterization was shown.

Genetic diversity of honeybee colonies predicts gut bacterial diversity of individual colony members

The gut microbiota of social bees is relatively simple and dominated by a set of core taxa found consistently in individuals around the world. Yet, variation remains and can affect host health. We characterized individual- and regional-scale variation in honeybee (Apis mellifera) gut microbiota from 64 colonies in North-West England by sequencing the V4 region of the 16S rRNA gene and asked whether microbiota were influenced by host genotype and landscape composition. We also characterized the genotypes of individual bees and the land cover surrounding each colony. The literature-defined core taxa dominated across the region despite the varied environments. However, there was variation in the relative abundance of core taxa, and colony membership explained much of this variation. Individuals from more genetically diverse colonies had more diverse microbiotas, but individual genetic diversity did not influence gut microbial diversity. There were weak trends for colonies in more similar landscapes to have more similar microbiota, and for bees from more urban landscapes to have less diverse microbiota. To our knowledge, this is the first report for any species that the gut bacterial communities of individuals are influenced by the genotypes of others in the population.

Changes in Microbiome Dominance Are Associated With Declining Lung Function and Fluctuating Inflammation in People With Cystic Fibrosis

Airway inflammation and microbiome dysbiosis are hallmarks of cystic fibrosis (CF) lung disease. However, longitudinal studies are needed to decipher which factors contribute to the long-term evolution of these key features of CF. We therefore evaluated the relationship between fluctuation in microbiome and inflammatory parameters in a longitudinal study including a short- (1-year) and a long-term (3+ years) period. We collected 118 sputum samples from 26 CF adult patients and analyzed them by 16S rRNA gene sequencing. We measured the levels of inflammatory cytokines, neutrophil elastase, and anti-proteinases; lung function (FEV1% predicted); and BMI. The longitudinal evolution was analyzed based on (i) the rates of changes; (ii) the intra-patient stability of the variables; and (iii) the dependency of the rates of changes on the baseline values. We observed that the diversity of the microbiome was highly variable over a 1-year period, while the inflammatory markers showed a slower evolution, with significant changes only observed in the 3+ year cohort. Further, the degree of fluctuation of the biomass and the dominance of the microbiome were associated with changes in inflammatory markers, especially IL-1β and IL-8. This longitudinal study demonstrates for the first time that the long-term establishment and periodical variation of the abundance of a dominant pathogen is associated with a more severe increase in inflammation. This result indicates that a single time point or 1-year study might fail to reveal the correlation between microbial evolution and clinical degradation in cystic fibrosis.

Fungal microbiomes are determined by host phylogeny and exhibit widespread associations with the bacterial microbiome

Interactions between hosts and their resident microbial communities are a fundamental component of fitness for both agents. Though recent research has highlighted the importance of interactions between animals and their bacterial communities, comparative evidence for fungi is lacking, especially in natural populations. Using data from 49 species, we present novel evidence of strong covariation between fungal and bacterial communities across the host phylogeny, indicative of recruitment by hosts for specific suites of microbes. Using co-occurrence networks, we demonstrate marked variation across host taxonomy in patterns of covariation between bacterial and fungal abundances. Host phylogeny drives differences in the overall richness of bacterial and fungal communities, but the effect of diet on richness was only evident in the mammalian gut microbiome. Sample type, tissue storage and DNA extraction method also affected bacterial and fungal community composition, and future studies would benefit from standardized approaches to sample processing. Collectively these data indicate fungal microbiomes may play a key role in host fitness and suggest an urgent need to study multiple agents of the animal microbiome to accurately determine the strength and ecological significance of host-microbe interactions.

The genetic architecture of resistance to virus infection in Drosophila

Variation in susceptibility to infection has a substantial genetic component in natural populations, and it has been argued that selection by pathogens may result in it having a simpler genetic architecture than many other quantitative traits. This is important as models of host-pathogen co-evolution typically assume resistance is controlled by a small number of genes. Using the Drosophila melanogaster multiparent advanced intercross, we investigated the genetic architecture of resistance to two naturally occurring viruses, the sigma virus and DCV (Drosophila C virus). We found extensive genetic variation in resistance to both viruses. For DCV resistance, this variation is largely caused by two major-effect loci. Sigma virus resistance involves more genes - we mapped five loci, and together these explained less than half the genetic variance. Nonetheless, several of these had a large effect on resistance. Models of co-evolution typically assume strong epistatic interactions between polymorphisms controlling resistance, but we were only able to detect one locus that altered the effect of the main effect loci we had mapped. Most of the loci we mapped were probably at an intermediate frequency in natural populations. Overall, our results are consistent with major-effect genes commonly affecting susceptibility to infectious diseases, with DCV resistance being a near-Mendelian trait.