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This article was submitted to Aquatic Microbiology, a section of the journal Frontiers in Microbiology
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In recent years, there has been an increase in the rate and severity of diseases affecting habitat-forming marine organisms, such as corals, sponges, and macroalgae.
Anthropogenic environmental stressors (e.g., pollution and climate change) are increasing the rate and severity of marine diseases worldwide (
Several macroalgae (seaweeds) suffer from microbial diseases, but there is a general lack of understanding for the mechanistic processes and ecological factors that determine disease (
Time-series experiment under controlled conditions can provide valuable insight into processes of disease development and specific environmental and biological factors that drive it. For example, for the sponge
Two criteria were set to be met for an aquarium model to be suitable to study the effect of environmental stressors on the occurrence of bleaching and its associated microbial community shifts: (1) the algae should remain healthy under control conditions for the duration of the experiment and (2) an environmentally relevant stressor should cause bleaching symptoms in a reproducible and predictable manner. To address these two points, three separate temperature-stress experiments were conducted in an aquarium-laboratory at the Sydney Institute of Marine Science (SIMS).
For these experiments,
For each temperature-stress experiment, individual thalli of
At time 0 and thereafter every 7 days, each individual was carefully taken out of the container and placed on a light-colored surface to carefully inspect for the appearance of any signs of bleaching. In addition, the algae were photographed and the effective quantum yield of photosynthetic energy conversion (Δ
An experiment was carried to assess the possible impact of aquarium-maintenance on the microbial community associated with
For TRFLP analysis, the 16S rRNA gene was amplified by PCR in a final volume of 40 μl containing 12 μl sterile, de-ionized water, 20 μl EconoTaq Plus Green 2X Master Mix (Lucigen), 2 μl of each of the primers 27F-FAM and 1492R for a final concentration of 2 ng/μl each and 4 μl of DNA template (20 pg/μl). The PCR cycling conditions consisted of: 3 min at 94°C; 30 cycles of 30 s at 94°C, 30 s at 55°C, and 1 min at 72°C, and a final 10 min at 72°C. PCR products were purified using a DNA Clean and Concentrator Kit (Zymo Research) following the manufacturer’s protocol and the DNA was eluted in 30 μl of sterile, de-ionized water. Purified PCR products were digested in 20 μl reactions containing 17 μl purified PCR product, 2 μl 10X restriction buffer and 1 μl
Three DNA samples from each of the three groups (aquarium t1, field t0, and field t1) were randomly picked for sequencing of the 16S rRNA gene. The V4 region of the 16S rRNA gene was amplified following standard protocols of the Earth Microbiome Project
Sequence processing was carried out using the Mothur software v.1.34 (
The most abundant sequence for each OTU was used as reference for taxonomic classification. Sequences were classified using the ‘classify.otu’ command in Mothur with default parameters based on three different bacterial 16S rRNA taxonomic outlines, including Silva (release 119), RDP (PDS version 10) and Greengenes (release of August 2013). For the OTUs selected from the statistical analysis, a consensus of the three classifications was manually built by choosing the deepest taxonomic assignment (reporting from the three classifications, only the highest confidence value observed). When different classifications were obtained, alternative taxa are reported.
To test for statistically significant differences in the richness (Chao1) and diversity (InvSimpson) between sample groups, Analysis of Variance (ANOVA) was calculated using a one-factor design with three levels: aquarium t1, field t0, and field t1 (overall test in
TRFLP-based PERMANOVA test results for microbial community structure (i.e., abundances) and composition (i.e., presence/absence) of
Structure | Composition | |||||
---|---|---|---|---|---|---|
Test | pseudo- |
unique perms | pseudo- |
unique perms | ||
overall test | 3.86 | 0.00005∗ | 85168 | 3.64 | 0.0001∗ | 9815 |
field t0 – field t1 | 1.11 | 0.2126 | 126 | 1.07 | 0.2802 | 126 |
field t0 – aquarium t1 | 2.23 | 0.0048∗ | 210 | 2.28 | 0.0054∗ | 210 |
field t1 – aquarium t1 | 2.16 | 0.0022∗ | 462 | 2.09 | 0.0021∗ | 462 |
Hypothesis tests of different measurements for the microbial communities of
Chao | InvSimpson | Structure | Composition | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Test | pseudo- |
Unique perms | pseudo- |
Unique perms | ||||||
overall test | 12.31 | 0.0075∗ | 0.04 | 0.965 | 4.03 | 0.0035∗ | 280 | 3.57 | 0.0029∗ | 280 |
field t0 – field t1 | 5.56 | 0.0779 | – | – | 1.46 | 0.1236 | MC | 1.42 | 0.135 | MC |
field t0 – aquarium t1 | 42.08 | 0.0029∗ | – | – | 2.34 | 0.0172∗ | MC | 2.18 | 0.0209∗ | MC |
field t1 – aquarium t1 | 4.57 | 0.0993 | – | – | 2.08 | 0.0281∗ | MC | 1.94 | 0.0358∗ | MC |
Operational taxonomic units that contributed most to the difference between sample types were identified by adjusting the OTU matrix to a multivariate generalized linear model using the Mvabund R package (
After 1 week of maintenance in the aquarium, we could detect algal thalli that show signs of bleaching (
In all three trials the proportion of bleached (including damaged-by-bleaching; for definition see “Materials and Methods”) individuals in the HT treatment increased with time, but never increased above a 40% frequency (
This experiment showed that the aquarium conditions alone can produce bleaching in
The transfer of marine organisms from their natural environment to an aquarium can have an impact on their associated microbial communities (
From the sequencing of the 16S rRNA gene we obtained between 25,297 (F1-3) and 66,948 (F0-3) quality-filtered sequences, which clustered into OTUs (at 97% sequence identity) ranging between 566 (A1-3) and 1,068 (F0-3) per sample (see
We then asked if the differences between field- and aquarium-held thalli were due to the colonization and proliferation of non-native bacteria (e.g., contaminants from the aquarium environment) or due to a general shift of the natural microbial community of
Most of differential OTUs were assigned to the phyla Actinobacteria, Bacteroidetes, Planctomycetes, Proteobacteria and Verrucomicrobia (
Infection assays using
Increases of temperature to 25°C, which is the peak level observed in the field (
In the aquarium set-up used here, we also observed that up to half of the
One of the factors that could influence the performance of
As previously proposed for corals (
Firstly, changes in the microbial community could cause bacterial infection and this would lead to bleaching, as observed here. The thalli, which were used to test the effect of the aquarium conditions on the microbiota associated with
Secondly, microbial changes could represent an adaptive response of the holobiont to the aquarium environment as has been suggested for corals (
EZ-V and TT designed and conceived the research. EZ-V and AJR-S performed the experiments. EZ-V and AJR-S analysed the data. EZ-V and TT wrote the manuscript with input from AJR-S.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
This work was supported by the Australian Research Council. We thank Vipra Kumar and Josh Aldridge for their help in setting up the aquarium experiments. We also thank Alexandra H. Campbell for her advise in the experimental design and Ezequiel Marzinelli for the collection of the samples. We thank Suhelen Egan for comments on the manuscript and CONACYT (National Council for Science and Technology of Mexico) for providing a Ph.D. scholarship to EZ-V.
The Supplementary Material for this article can be found online at: