An official website of the United States government
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
more »
« less
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.
more »
« less
- 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
More Like this
-
-
Abstract BackgroundThe aerial surface of plants, known as the phyllosphere, hosts a complex and dynamic microbiome that plays essential roles in plant health and environmental processes. While research has focused on root-associated microbiomes, the phyllosphere remains comparatively understudied, especially in forest ecosystems. Despite the global ecological dominance and importance of conifers, no previous study has applied shotgun metagenomics to their phyllosphere microbiomes. ResultsThis study uses metagenomic sequencing to explore the microbial phyllosphere communities of subalpine Western conifer needle surfaces from 67 trees at six sites spanning the Rocky Mountains, including 31 limber pine, 18 Douglas fir, and 18 Engelmann spruce. Sites span ~ 1,075 km and nearly 10° latitude, from Glacier National Park to Rocky Mountain Biological Laboratory, capturing broad environmental variation. Metagenomes were generated for each of the 67 samples, for which we produced individual assemblies, along with three large coassemblies specific to each conifer host. From these datasets, we reconstructed 447 metagenome-assembled genomes (MAGs), 417 of which are non-redundant at the species level. Beyond increasing the total number of extracted MAGs from 153 to 294, the three coassemblies yielded three large MAGs, representing partial sequences of host genomes. Phylogenomics of all microbial MAGs revealed communities predominantly composed of bacteria (n = 327) and fungi (n = 117). We show that both microbial community composition and metabolic potential differ significantly across host tree species and geographic sites, with site exerting a stronger influence than host. ConclusionsThis dataset offers new insights into the microbial communities inhabiting the conifer needle surface, laying the foundation for future research on needle microbiomes across temporal and spatial scales. Variation in functional capabilities, such as volatile organic compound (VOC) degradation and polysaccharide metabolism, closely tracks shifts in taxonomic composition, indicating that host-specific chemistry, local environmental factors, and regional microbial source pools jointly shape ecological roles. Moreover, the observed patterns of mobile genetic elements and horizontal gene transfer suggest that gene exchange predominantly occurs within microbial lineages, with occasional broader transfers dispersing key functional genes (e.g., those involved in polysaccharide metabolism), which may facilitate microbiome adaptation.more » « less
-
Submerged plants can thrive entirely underwater, playing a crucial role in maintaining water quality, supporting aquatic organisms, and enhancing sediment stability. However, they face multiple challenges, including reduced light availability, fluctuating water conditions, and limited nutrient access. Despite these stresses, submerged plants demonstrate remarkable resilience through physiological and biochemical adaptations. Additionally, their interactions with microbial communities are increasingly recognized as pivotal in mitigating these environmental stresses. Understanding the diversity of these microbial communities is crucial for comprehending the complex interactions between submerged plants and their environments. This research aims to identify and screen microbes from submerged plant samples capable of producing 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase and to explore microbial diversity through metagenomic analysis. Microbes were isolated and screened for ACC deaminase production, and metagenomic techniques, including co-occurrence network analysis, were used to examine microbial diversity and interactions within the communities. ACC deaminase-producing microbes can significantly enhance plant metabolism under stress conditions. The identification of the culturable bacteria revealed that most of these microbes belong to the genera Pseudomonas, Bacillus, and Acinetobacter. A total of 177 microbial strains were cultured, with molecular identification revealing 79 reductant, 86 non-reductant, and 12 uncultured strains. Among 162 samples screened for ACC deaminase activity, 50 tested positive. To further understand microbial dynamics, samples were collected from both natural sources and artificial pond reservoirs to assess the impact of the location on flood-associated microbiomes in submerged plants. Metagenomic analysis was conducted on both the epiphytic and endophytic samples. By exploring the overall composition and dynamics of microbial communities associated with submerged plants, this research seeks to deepen our understanding of plant–microbe interactions in aquatic environments. The microbial screening helped to identify the diverse microbes associated with ACC deaminase activity in submerged plants and amplicon sequencing analysis paved the way towards identifying the impact of the location in shaping the microbiome and the diversity associated with endophytic and epiphytic microbes. Co-occurrence network analysis further highlighted the intricate interactions within these microbial communities. Notably, ACC deaminase activity was observed in plant-associated microbes across different locations, with distinct variations between epiphytic and endophytic populations as identified through co-occurrence network analysis.more » « less
-
With emerging infectious disease outbreaks in human, domestic and wild animal populations on the rise, improvements in pathogen characterization and surveillance are paramount for the protection of human and animal health, as well as the conservation of ecologically and economically important wildlife. Genomics offers a range of suitable tools to meet these goals, with metagenomic sequencing facilitating the characterization of whole microbial communities associated with emerging and endemic disease outbreaks. Here, we use metagenomic sequencing in a case-control study to identify microbes in lung tissue associated with newly observed pneumonia-related fatalities in 34 white-tailed deer (Odocoileus virginianus) in Wisconsin, USA. We identified 20 bacterial species that occurred in more than a single individual. Of these, onlyClostridium novyiwas found to substantially differ (in number of detections) between case and control sample groups; however, this difference was not statistically significant. We also detected several bacterial species associated with pneumonia and/or other diseases in ruminants (Mycoplasma ovipneumoniae,Trueperella pyogenes,Pasteurella multocida,Anaplasma phagocytophilum,Fusobacterium necrophorum); however, these species did not substantially differ between case and control sample groups. On average, we detected a larger number of bacterial species in case samples than controls, supporting the potential role of polymicrobial infections in this system. Importantly, we did not detect DNA of viruses or fungi, suggesting that they are not significantly associated with pneumonia in this system. Together, these results highlight the utility of metagenomic sequencing for identifying disease-associated microbes. This preliminary list of microbes will help inform future research on pneumonia-associated fatalities of white-tailed deer.more » « less
-
Campbell, Barbara J. (Ed.)ABSTRACT Host-associated microbiomes can be critical for the health and proper development of animals and plants. The answers to many fundamental questions regarding the modes of acquisition and microevolution of microbiome communities remain to be established. Deciphering strain-level dynamics is essential to fully understand how microbial communities evolve, but the forces shaping the strain-level dynamics of microbial communities remain largely unexplored, mostly because of methodological issues and cost. Here, we used targeted strain-level deep sequencing to uncover the strain dynamics within a host-associated microbial community using the honey bee gut microbiome as a model system. Our results revealed that amplicon sequencing of conserved protein-coding gene regions using species-specific primers is a cost-effective and accurate method for exploring strain-level diversity. In fact, using this method we were able to confirm strain-level results that have been obtained from whole-genome shotgun sequencing of the honey bee gut microbiome but with a much higher resolution. Importantly, our deep sequencing approach allowed us to explore the impact of low-frequency strains (i.e., cryptic strains) on microbiome dynamics. Results show that cryptic strain diversity is not responsible for the observed variations in microbiome composition across bees. Altogether, the findings revealed new fundamental insights regarding strain dynamics of host-associated microbiomes. IMPORTANCE The factors driving fine-scale composition and dynamics of gut microbial communities are poorly understood. In this study, we used metagenomic amplicon deep sequencing to decipher the strain dynamics of two key members of the honey bee gut microbiome. Using this high-throughput and cost-effective approach, we were able to confirm results from previous large-scale whole-genome shotgun (WGS) metagenomic sequencing studies while also gaining additional insights into the community dynamics of two core members of the honey bee gut microbiome. Moreover, we were able to show that cryptic strains are not responsible for the observed variations in microbiome composition across bees.more » « less
