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Abstract BackgroundSpotting disease infects a variety of sea urchin species across many different marine locations. The disease is characterized by discrete lesions on the body surface composed of discolored necrotic tissue that cause the loss of all surface appendages within the lesioned area. A similar, but separate disease of sea urchins called bald sea urchin disease (BSUD) has overlapping symptoms with spotting disease, resulting in confusions in distinguishing the two diseases. Previous studies have focus on identifying the underlying causative agent of spotting disease, which has resulted in the identification of a wide array of pathogenic bacteria that vary based on location and sea urchin species. Our aim was to investigate the spotting disease infection by characterizing the microbiomes of the animal surface and various tissues. ResultsWe collected samples of the global body surface, the lesion surface, lesioned and non-lesioned body wall, and coelomic fluid, in addition to samples from healthy sea urchins. 16S rRNA gene was amplified and sequenced from the genomic DNA. Results show that the lesions are composed mainly of Cyclobacteriaceae, Cryomorphaceae, and a few other taxa, and that the microbial composition of lesions is the same for all infected sea urchins. Spotting disease also alters the microbial composition of the non-lesioned body wall and coelomic fluid of infected sea urchins. In our closed aquarium systems, sea urchins contracted spotting disease and BSUD separately and therefore direct comparisons could be made between the microbiomes from diseased and healthy sea urchins. ConclusionResults show that spotting disease and BSUD are separate diseases with distinct symptoms and distinct microbial compositions. Graphical abstract
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Bakdrive: identifying a minimum set of bacterial species driving interactions across multiple microbial communities
Abstract MotivationInteractions among microbes within microbial communities have been shown to play crucial roles in human health. In spite of recent progress, low-level knowledge of bacteria driving microbial interactions within microbiomes remains unknown, limiting our ability to fully decipher and control microbial communities. ResultsWe present a novel approach for identifying species driving interactions within microbiomes. Bakdrive infers ecological networks of given metagenomic sequencing samples and identifies minimum sets of driver species (MDS) using control theory. Bakdrive has three key innovations in this space: (i) it leverages inherent information from metagenomic sequencing samples to identify driver species, (ii) it explicitly takes host-specific variation into consideration, and (iii) it does not require a known ecological network. In extensive simulated data, we demonstrate identifying driver species identified from healthy donor samples and introducing them to the disease samples, we can restore the gut microbiome in recurrent Clostridioides difficile (rCDI) infection patients to a healthy state. We also applied Bakdrive to two real datasets, rCDI and Crohn's disease patients, uncovering driver species consistent with previous work. Bakdrive represents a novel approach for capturing microbial interactions. Availability and implementationBakdrive is open-source and available at: https://gitlab.com/treangenlab/bakdrive.
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- Award ID(s):
- 2126387
- PAR ID:
- 10427269
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Bioinformatics
- Volume:
- 39
- Issue:
- Supplement_1
- ISSN:
- 1367-4803
- Page Range / eLocation ID:
- p. i47-i56
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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