Periodical cicadas (Hemiptera: Magicicada) have coevolved with obligate bacteriome-inhabiting microbial symbionts, yet little is known about gut microbial symbiont composition or differences in composition among allochronic Magicicada broods (year classes) which emerge parapatrically or allopatrically in the eastern United States. Here, 16S rRNA amplicon sequencing was performed to determine gut bacterial community profiles of three periodical broods, including II (Connecticut and Virginia, 2013), VI (North Carolina, 2017), and X (Maryland, 2021, and an early emerging nymph collected in Ohio, 2017). Results showed similarities among all nymphal gut microbiomes and between morphologically distinct 17-year Magicicada, namely Magicicada septendecim (Broods II and VI) and 17-year Magicicada cassini (Brood X) providing evidence of a core microbiome, distinct from the microbiome of burrow soil inhabited by the nymphs. Generally, phyla Bacteroidetes [Bacteroidota] (> 50% relative abundance), Actinobacteria [Actinomycetota], or Proteobacteria [Pseudomonadota] represented the core. Acidobacteria and genera Cupriavidus, Mesorhizobium, and Delftia were prevalent in nymphs but less frequent in adults. The primary obligate endosymbiont, Sulcia (Bacteroidetes), was dominant amongst core genera detected. Chryseobacterium were common in Broods VI and X. Chitinophaga, Arthrobacter, and Renibacterium were common in Brood X, and Pedobacter were common to nymphs of Broods II and VI. Further taxonomic assignment of unclassified Alphaproteobacteria sequencing reads allowed for detection of multiple copies of the Hodgkinia 16S rRNA gene, distinguishable as separate operational taxonomic units present simultaneously. As major emergences of the broods examined here occur at 17-year intervals, this study will provide a valuable comparative baseline in this era of a changing climate.

The bacteria that colonize humans and our built environments have the potential to influence our health. Microbial communities associated with seven families and their homes over 6 weeks were assessed, including three families that moved their home. Microbial communities differed substantially among homes, and the home microbiome was largely sourced from humans. The microbiota in each home were identifiable by family. Network analysis identified humans as the primary bacterial vector, and a Bayesian method significantly matched individuals to their dwellings. Draft genomes of potential human pathogens observed on a kitchen counter could be matched to the hands of occupants. After a house move, the microbial community in the new house rapidly converged on the microbial community of the occupants' former house, suggesting rapid colonization by the family's microbiota.

Vibrio species are both ubiquitous and abundant in marine coastal waters, estuaries, ocean sediment, and aquaculture settings worldwide. We report here the isolation, characterization, and genome sequence of a novel Vibrio species, Vibrio antiquarius, isolated from a mesophilic bacterial community associated with hydrothermal vents located along the East Pacific Rise, near the southwest coast of Mexico. Genomic and phenotypic analysis revealed V. antiquarius is closely related to pathogenic Vibrio species, namely Vibrio alginolyticus, Vibrio parahaemolyticus, Vibrio harveyi, and Vibrio vulnificus, but sufficiently divergent to warrant a separate species status. The V. antiquarius genome encodes genes and operons with ecological functions relevant to the environment conditions of the deep sea and also harbors factors known to be involved in human disease caused by freshwater, coastal, and brackish water vibrios. The presence of virulence factors in this deep-sea Vibrio species suggests a far more fundamental role of these factors for their bacterial host. Comparative genomics revealed a variety of genomic events that may have provided an important driving force in V. antiquarius evolution, facilitating response to environmental conditions of the deep sea.

Following publication of the original article [1], the authors would like to highlight the following two corrections.

Background

One of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole-genome shotgun sequencing data, comprehensive comparisons of these methods are limited.

Results

In this study, we use the largest-to-date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of 11 metagenomic classifiers. Tools were characterized on the basis of their ability to identify taxa at the genus, species, and strain levels, quantify relative abundances of taxa, and classify individual reads to the species level. Strikingly, the number of species identified by the 11 tools can differ by over three orders of magnitude on the same datasets. Various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species. Overall, pairing tools with different classification strategies (k-mer, alignment, marker) can combine their respective advantages.

Conclusions

This study provides positive and negative controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision, accuracy, and recall. We show that proper experimental design and analysis parameters can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.