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  • Drivers and patterns of microbial community assembly in a Lyme disease vector. Ecology and evolution Couper, L. I., Kwan, J. Y., Ma, J., Swei, A. 2019; 9 (13): 7768–79

    Abstract

    Vector-borne diseases constitute a major global health burden and are increasing in geographic range and prevalence. Mounting evidence has demonstrated that the vector microbiome can impact pathogen dynamics, making the microbiome a focal point in vector-borne disease ecology. However, efforts to generalize preliminary findings across studies and systems and translate these findings into disease control strategies are hindered by a lack of fundamental understanding of the processes shaping the vector microbiome and the interactions therein. Here, we use 16S rRNA sequencing and apply a community ecology framework to analyze microbiome community assembly and interactions in Ixodes pacificus, the Lyme disease vector in the western United States. We find that vertical transmission routes drive population-level patterns in I. pacificus microbial diversity and composition, but that microbial function and overall abundance do not vary over time or between clutches. Further, we find that the I. pacificus microbiome is not strongly structured based on competition but assembles nonrandomly, potentially due to vector-specific filtering processes which largely eliminate all but the dominant endosymbiont, Rickettsia. At the scale of the individual I. pacificus, we find support for a highly limited internal microbial community, and hypothesize that the tick endosymbiont may be the most important component of the vector microbiome in influencing pathogen dynamics.

    View details for DOI 10.1002/ece3.5361

    View details for PubMedID 31346439

    View details for PubMedCentralID PMC6635933

  • Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing JOVE-JOURNAL OF VISUALIZED EXPERIMENTS Couper, L., Swei, A. 2018

    Abstract

    In recent decades, vector-borne diseases have re-emerged and expanded at alarming rates, causing considerable morbidity and mortality worldwide. Effective and widely available vaccines are lacking for a majority of these diseases, necessitating the development of novel disease mitigation strategies. To this end, a promising avenue of disease control involves targeting the vector microbiome, the community of microbes inhabiting the vector. The vector microbiome plays a pivotal role in pathogen dynamics, and manipulations of the microbiome have led to reduced vector abundance or pathogen transmission for a handful of vector-borne diseases. However, translating these findings into disease control applications requires a thorough understanding of vector microbial ecology, historically limited by insufficient technology in this field. The advent of next-generation sequencing approaches has enabled rapid, highly parallel sequencing of diverse microbial communities. Targeting the highly-conserved 16S rRNA gene has facilitated characterizations of microbes present within vectors under varying ecological and experimental conditions. This technique involves amplification of the 16S rRNA gene, sample barcoding via PCR, loading samples onto a flow cell for sequencing, and bioinformatics approaches to match sequence data with phylogenetic information. Species or genus-level identification for a high number of replicates can typically be achieved through this approach, thus circumventing challenges of low detection, resolution, and output from traditional culturing, microscopy, or histological staining techniques. Therefore, this method is well-suited for characterizing vector microbes under diverse conditions but cannot currently provide information on microbial function, location within the vector, or response to antibiotic treatment. Overall, 16S next-generation sequencing is a powerful technique for better understanding the identity and role of vector microbes in disease dynamics.

    View details for DOI 10.3791/58239

    View details for Web of Science ID 000444913100137

    View details for PubMedID 30199026

    View details for PubMedCentralID PMC6231894