The exploration of microbial communities by sequencing 16S rRNA genes has expanded with low-cost, high-throughput sequencing instruments. Illumina-based 16S rRNA gene sequencing has recently gained popularity over 454 pyrosequencing due to its lower costs, higher accuracy and greater throughput. Although recent reports suggest that Illumina and 454 pyrosequencing provide similar beta diversity measures, it remains to be demonstrated that pre-existing 454 pyrosequencing workflows can transfer directly from 454 to Illumina MiSeq sequencing by simply changing the sequencing adapters of the primers. In this study, we modified 454 pyrosequencing primers targeting the V4-V5 hyper-variable regions of the 16S rRNA gene to be compatible with Illumina sequencers. Microbial communities from cows, humans, leeches, mice, sewage, and termites and a mock community were analyzed by 454 and MiSeq sequencing of the V4-V5 region and MiSeq sequencing of the V4 region. Our analysis revealed that reference-based OTU clustering alone introduced biases compared to de novo clustering, preventing certain taxa from being observed in some samples. Based on this we devised and recommend an analysis pipeline that includes read merging, contaminant filtering, and reference-based clustering followed by de novo OTU clustering, which produces diversity measures consistent with de novo OTU clustering analysis. Low levels of dataset contamination with Illumina sequencing were discovered that could affect analyses that require highly sensitive approaches. While moving to Illumina-based sequencing platforms promises to provide deeper insights into the breadth and function of microbial diversity, our results show that care must be taken to ensure that sequencing and processing artifacts do not obscure true microbial diversity.

BackgroundAs the importance of beneficial bacteria is better recognized, understanding the dynamics of symbioses becomes increasingly crucial. In many gut symbioses, it is essential to understand whether changes in host diet play a role in the persistence of the bacterial gut community. In this study, termites were fed six dietary sources and the microbial community was monitored over a 49-day period using 16S rRNA gene sequencing. A deep backpropagation artificial neural network (ANN) was used to learn how the six different lignocellulose food sources affected the temporal composition of the hindgut microbiota of the termite as well as taxon-taxon and taxon-substrate interactions.ResultsShifts in the termite gut microbiota after diet change in each colony were observed using 16S rRNA gene sequencing and beta diversity analyses. The artificial neural network accurately predicted the relative abundances of taxa at random points in the temporal study and showed that low-abundant taxa maintain community driving correlations in the hindgut.ConclusionsThis combinatorial approach utilizing 16S rRNA gene sequencing and deep learning revealed that low-abundant bacteria that often do not belong to the core community are drivers of the termite hindgut bacterial community composition.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0469-5) contains supplementary material, which is available to authorized users.

The hindgut of the termite Reticulitermes flavipes harbors a complex symbiotic community consisting of protists, bacteria, and archaea. These symbionts aid in the digestion of lignocellulose from the termite’s wood meal. Termite hindguts were sampled and the V4 hyper-variable region of the 16S rRNA gene was sequenced and analyzed from individual termites. The core microbiota of worker termites consisted of 69 OTUs at the 97% identity level, grouped into 16 taxa, and together accounted for 67.05% of the sequences from the bacterial community. The core was dominated by Treponema, which contained 36 different OTUs and accounted for ∼32% of the sequences, which suggests Treponema sp. have an important impact on the overall physiology in the hindgut. Bray–Curtis beta diversity metrics showed that hindgut samples from termites of the same colony were more similar to each other than to samples from other colonies despite possessing a core that accounted for the majority of the sequences. The specific tasks and dietary differences of the termite castes could have an effect on the composition of the microbial community. The hindgut microbiota of termites from the alate castes differed from the worker caste with significantly lower abundances of Treponema and Endomicrobia, which dominated the hindgut microbiota in workers and soldiers. Protist abundances were also quantified in the same samples using qPCR of the 18S rRNA gene. Parabasalia abundances dropped significantly in the winged alates and the Oxymonadida abundances dropped in both alate castes. These data suggest that the changes in diet or overall host physiology affected the protist and bacterial populations in the hindgut. The in-depth bacterial characterization and protist quantification in this study sheds light on the potential community dynamics within the R. flavipes hindgut and identified a large and complex core microbiota in termites obtained from multiple colonies and castes.

Microbiomes impact a variety of processes including a host's ability to access nutrients and maintain health. While host species differences in microbiomes have been described across ecosystems, little is known about how microbiomes assemble, particularly in the ecological and social contexts in which they evolved. We examined gut microbiome composition in nine sympatric wild non-human primate (NHP) species. Despite sharing an environment and interspecific interactions, individuals harbored unique and persistent microbiomes influenced by host species, social group, and parentage, but surprisingly not by social relationships among members of a social group. We found a branching order of host-species networks constructed using the composition of their microbiomes as characters, which was incongruent with known NHP phylogenetic relationships, with chimpanzees (Pan troglodytes verus) sister to colobines, upon which they regularly prey. In contrast to phylogenetic clustering found in all monkey microbiomes, chimpanzee microbiomes were unique in that they exhibited patterns of phylogenetic overdispersion. This reflects unique ecological processes impacting microbiome composition in chimpanzees and future studies will elucidate the aspects of chimpanzee ecology, life history, and physiology that explain their unique microbiome community structure. Our study of contemporaneous microbiomes of all sympatric diurnal NHP in an ecosystem highlights the diverse dispersal routes shaping these complex communities.

Background Pseudomonas aeruginosa is a persistent and difficult-to-treat pathogen in many patients, especially those with Cystic Fibrosis (CF). Herein, we describe a longitudinal analysis of a series of multidrug resistant (MDR) P. aeruginosa isolates recovered in a 17-month period, from a young female CF patient who underwent double lung transplantation. Our goal was to understand the genetic basis of the observed resistance phenotypes, establish the genomic population diversity, and define the nature of sequence evolution over time. Methods Twenty-two sequential P. aeruginosa isolates were obtained within a 17-month period, before and after a double-lung transplant. At the end of the study period, antimicrobial susceptibility testing, whole genome sequencing (WGS), phylogenetic analyses and RNAseq were performed in order to understand the genetic basis of the observed resistance phenotypes, establish the genomic population diversity, and define the nature of sequence changes over time. Results The majority of isolates were resistant to almost all tested antibiotics. A phylogenetic reconstruction revealed 3 major clades representing a genotypically and phenotypically heterogeneous population. The pattern of mutation accumulation and variation of gene expression suggested that a group of closely related strains was present in the patient prior to transplantation and continued to change throughout the course of treatment. A trend toward accumulation of mutations over time was observed. Different mutations in the DNA mismatch repair gene mutL consistent with a hypermutator phenotype were observed in two clades. RNAseq performed on 12 representative isolates revealed substantial differences in the expression of genes associated with antibiotic resistance and virulence traits. Conclusions The overwhelming current practice in the clinical laboratories setting relies on obtaining a pure culture and reporting the antibiogram from a few isolated colonies to inform therapy decisions. Our analyses revealed significant underlying genomic heterogeneity and unpredictable evolutionary patterns that were independent of prior antibiotic treatment, highlighting the need for comprehensive sampling and population-level analysis when gathering microbiological data in the context of CF P. aeruginosa chronic infection. Our findings challenge the applicability of antimicrobial stewardship programs based on single-isolate resistance profiles for the selection of antibiotic regimens in chronic infections such as CF.