Dataset Information

Modeling of the Coral Microbiome: the Influence of Temperature and Microbial Network.

ABSTRACT: Host-associated microbial communities are shaped by extrinsic and intrinsic factors to the holobiont organism. Environmental factors and microbe-microbe interactions act simultaneously on the microbial community structure, making the microbiome dynamics challenging to predict. The coral microbiome is essential to the health of coral reefs and sensitive to environmental changes. Here, we develop a dynamic model to determine the microbial community structure associated with the surface mucus layer (SML) of corals using temperature as an extrinsic factor and microbial network as an intrinsic factor. The model was validated by comparing the predicted relative abundances of microbial taxa to the relative abundances of microbial taxa from the sample data. The SML microbiome from Pseudodiploria strigosa was collected across reef zones in Bermuda, where inner and outer reefs are exposed to distinct thermal profiles. A shotgun metagenomics approach was used to describe the taxonomic composition and the microbial network of the coral SML microbiome. By simulating the annual temperature fluctuations at each reef zone, the model output is statistically identical to the observed data. The model was further applied to six scenarios that combined different profiles of temperature and microbial network to investigate the influence of each of these two factors on the model accuracy. The SML microbiome was best predicted by model scenarios with the temperature profile that was closest to the local thermal environment, regardless of the microbial network profile. Our model shows that the SML microbiome of P. strigosa in Bermuda is primarily structured by seasonal fluctuations in temperature at a reef scale, while the microbial network is a secondary driver.IMPORTANCE Coral microbiome dysbiosis (i.e., shifts in the microbial community structure or complete loss of microbial symbionts) caused by environmental changes is a key player in the decline of coral health worldwide. Multiple factors in the water column and the surrounding biological community influence the dynamics of the coral microbiome. However, by including only temperature as an external factor, our model proved to be successful in describing the microbial community associated with the surface mucus layer (SML) of the coral P. strigosa The dynamic model developed and validated in this study is a potential tool to predict the coral microbiome under different temperature conditions.

SUBMITTER: Lima LFO

PROVIDER: S-EPMC7064765 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Modeling of the Coral Microbiome: the Influence of Temperature and Microbial Network.

Lima Laís F O LFO Weissman Maya M Reed Micheal M Papudeshi Bhavya B Alker Amanda T AT Morris Megan M MM Edwards Robert A RA de Putron Samantha J SJ Vaidya Naveen K NK Dinsdale Elizabeth A EA

mBio 20200303 2

Host-associated microbial communities are shaped by extrinsic and intrinsic factors to the holobiont organism. Environmental factors and microbe-microbe interactions act simultaneously on the microbial community structure, making the microbiome dynamics challenging to predict. The coral microbiome is essential to the health of coral reefs and sensitive to environmental changes. Here, we develop a dynamic model to determine the microbial community structure associated with the surface mucus layer ...[more]

PMID: 32127450

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Project description:Studies of the coral microbiome predominantly characterize the microbial community of the host species as a collective, rather than that of the individual. This ecological perspective on the coral microbiome has led to the conclusion that the coral holobiont is the most diverse microbial biosphere studied thus far. However, investigating the microbiome of the individual, rather than that of the species, highlights common and conserved community attributes which can provide insights into the significance of microbial associations to the host. Here, we show there are consistent characteristics between individuals in the proposed three components of the coral microbiome (i.e., "environmentally responsive community," "resident or individual microbiome," and "core microbiome"). We found that the resident microbiome of a photoendosymbiotic coral harbored <3% (?605 phylotypes) of the 16S rRNA phylotypes associated with all investigated individuals of that species ("species-specific microbiome") (?21,654 phylotypes; individuals from Pachyseris speciosa [n = 123], Mycedium elephantotus [n = 95], and Acropora aculeus [n = 91] from 10 reef locations). The remaining bacterial phylotypes (>96%) (environmentally responsive community) of the species-specific microbiome were in fact not found in association with the majority of individuals of the species. Only 0.1% (?21 phylotypes) of the species-specific microbiome of each species was shared among all individuals of the species (core microbiome), equating to ?3.4% of the resident microbiome. We found taxonomic redundancy and consistent patterns of composition, structure, and taxonomic breadth across individual microbiomes from the three coral species. Our results demonstrate that the coral microbiome is structured at the individual level.IMPORTANCE We propose that the coral holobiont should be conceptualized as a diverse transient microbial community that is responsive to the surrounding environment and encompasses a simple, redundant, resident microbiome and a small conserved core microbiome. Most importantly, we show that the coral microbiome is comparable to the microbiomes of other organisms studied thus far. Accurately characterizing the coral-microbe interactions provides an important baseline from which the functional roles and the functional niches within which microbes reside can be deciphered.

Project description:Despite their relatively high thermal optima (Topt ), tropical taxa may be particularly vulnerable to a rising baseline and increased temperature variation because they live in relatively stable temperatures closer to their Topt . We examined how microbial eukaryotes with differing thermal histories responded to temperature fluctuations of different amplitudes (0 control, ±2, ±4°C) around mean temperatures below or above their Topt . Cosmopolitan dinoflagellates were selected based on their distinct thermal traits and included two species of the same genus (tropical and temperate Coolia spp.), and two strains of the same species maintained at different temperatures for >500 generations (tropical Amphidinium massartii control temperature and high temperature, CT and HT, respectively). There was a universal decline in population growth rate under temperature fluctuations, but strains with narrower thermal niche breadth (temperate Coolia and HT) showed ~10% greater reduction in growth. At suboptimal mean temperatures, cells in the cool phase of the fluctuation stopped dividing, fixed less carbon (C) and had enlarged cell volumes that scaled positively with elemental C, N, and P and C:Chlorophyll-a. However, at a supra-optimal mean temperature, fixed C was directed away from cell division and novel trait combinations developed, leading to greater phenotypic diversity. At the molecular level, heat-shock proteins, and chaperones, in addition to transcripts involving genome rearrangements, were upregulated in CT and HT during the warm phase of the supra-optimal fluctuation (30 ± 4°C), a stress response indicating protection. In contrast, the tropical Coolia species upregulated major energy pathways in the warm phase of its supra-optimal fluctuation (25 ± 4°C), indicating a broadscale shift in metabolism. Our results demonstrate divergent effects between taxa and that temporal variability in environmental conditions interacts with changes in the thermal mean to mediate microbial responses to global change, with implications for biogeochemical cycling.

Project description:Insects share an intimate relationship with their gut microflora and this symbiotic association has developed into an essential evolutionary outcome intended for their survival through extreme environmental conditions. While it has been clearly established that insects, with very few exceptions, associate with several microbes during their life cycle, information regarding several aspects of these associations is yet to be fully unraveled. Acquisition of bacteria by insects marks the onset of microbial symbiosis, which is followed by the adaptation of these bacterial species to the gut environment for prolonged sustenance and successful transmission across generations. Although several insect-microbiome associations have been reported and each with their distinctive features, diversifications and specializations, it is still unclear as to what led to these diversifications. Recent studies have indicated the involvement of various evolutionary processes operating within an insect body that govern the transition of a free-living microbe to an obligate or facultative symbiont and eventually leading to the establishment and diversification of these symbiotic relationships. Data from various studies, summarized in this review, indicate that the symbiotic partners, i.e., the bacteria and the insect undergo several genetic, biochemical and physiological changes that have profound influence on their life cycle and biology. An interesting outcome of the insect-microbe interaction is the compliance of the microbial partner to its eventual genome reduction. Endosymbionts possess a smaller genome as compared to their free-living forms, and thus raising the question what is leading to reductive evolution in the microbial partner. This review attempts to highlight the fate of microbes within an insect body and its implications for both the bacteria and its insect host. While discussion on each specific association would be too voluminous and outside the scope of this review, we present an overview of some recent studies that contribute to a better understanding of the evolutionary trajectory and dynamics of the insect-microbe association and speculate that, in the future, a better understanding of the nature of this interaction could pave the path to a sustainable and environmentally safe way for controlling economically important pests of crop plants.

Project description:BackgroundRecent studies have provided insights into the persistence and succession of microbes aboard the International Space Station (ISS), notably the dominance of Klebsiella pneumoniae. However, the interactions between the various microbes aboard the ISS and how they shape the microbiome remain to be clearly understood. In this study, we apply a computational approach to predict possible metabolic interactions in the ISS microbiome and shed further light on its organization.ResultsThrough a combination of a systems-based graph-theoretical approach, and a constraint-based community metabolic modeling approach, we demonstrated several key interactions in the ISS microbiome. These complementary approaches provided insights into the metabolic interactions and dependencies present amongst various microbes in a community, highlighting key interactions and keystone species. Our results showed that the presence of K. pneumoniae is beneficial to many other microorganisms it coexists with, notably those from the Pantoea genus. Species belonging to the Enterobacteriaceae family were often found to be the most beneficial for the survival of other microorganisms in the ISS microbiome. However, K. pneumoniae was found to exhibit parasitic and amensalistic interactions with Aspergillus and Penicillium species, respectively. To prove this metabolic prediction, K. pneumoniae and Aspergillus fumigatus were co-cultured under normal and simulated microgravity, where K. pneumoniae cells showed parasitic characteristics to the fungus. The electron micrography revealed that the presence of K. pneumoniae compromised the morphology of fungal conidia and degenerated its biofilm-forming structures.ConclusionOur study underscores the importance of K. pneumoniae in the ISS, and its potential positive and negative interactions with other microbes, including potential pathogens. This integrated modeling approach, combined with experiments, demonstrates the potential for understanding the organization of other such microbiomes, unravelling key organisms and their interdependencies. Video Abstract.

Dataset Information

Modeling of the Coral Microbiome: the Influence of Temperature and Microbial Network.

Publications

Modeling of the Coral Microbiome: the Influence of Temperature and Microbial Network.

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