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26 results for “holobiont”
Elucidating gene expression adaptation of phylogenetically divergent coral holobionts under heat stress
<p>As coral reefs struggle to survive under climate change, it is crucial to know whether they have the capacity to withstand changing conditions, particularly increasing seawater temperatures. Thermal tolerance requires the integrative response of the different components of the coral holobiont (coral host, algal photosymbiont, and associated microbiome). Here, using a controlled thermal stress experiment across three divergent Caribbean coral species, we attempt to dissect holobiont member metatranscriptome responses from coral taxa with different sensitivities to heat stress and use phylogenetic ANOVA to study the evolution of gene expression adaptation. We show that coral response to heat stress is a complex trait derived from multiple interactions among holobiont members. We identify host and photosymbiont genes that exhibit lineage-specific expression level adaptation and uncover potential roles for bacterial associates in supplementing the metabolic needs of the coral-photosymbiont duo during heat stress. Our results stress the importance of integrative and comparative approaches across a wide range of species to better understand coral survival under the predicted rise in sea surface temperatures.</p>
Elucidating gene expression adaptation of phylogenetically divergent coral holobionts under heat stress
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Data from: Entangled fates of holobiont genomes during invasion: nested bacterial and host diversities in Caulerpa taxifolia
Successful prevention and mitigation of biological invasions requires retracing the initial steps of introduction, as well as understanding key elements enhancing the adaptability of invasive species. We studied the genetic diversity of the green alga Caulerpa taxifolia and its associated bacterial communities in several areas around the world. The striking congruence of α and ß diversity of the algal genome and endophytic communities reveals a tight association, supporting the holobiont concept as best describing the unit of spreading and invasion. Both genomic compartments support the hypotheses of a unique accidental introduction in the Mediterranean and of multiple invasion events in Southern Australia. In addition to helping with tracing the origin of invasion, bacterial communities exhibit metabolic functions that can potentially enhance adaptability and competitiveness of the consortium they form with their host. We thus hypothesize that low genetic diversities of both host and symbiont communities may contribute to the recent regression in the Mediterranean, in contrast with the persistence of highly diverse assemblages in southern Australia. This study supports the importance of scaling up from the host to the holobiont for a comprehensive understanding of invasions.
Metatranscriptomic response of the wheat holobiont to decreasing soil water content
<p><strong>Background</strong></p> <p>This dataset contains processed high throughput metatranscriptomics (RNA) sequencing data related to the scientific article entitled <em>Metatranscriptomic response of the wheat holobiont to decreasing soil water content</em>. </p> <p>The files available in this archive are described below:</p> <p><strong>Contigs abundance:</strong><br> contigs/qc_mapping_stats.tsv<br> Contains read counts through various steps of the pipeline. </p> <p>contigs/merged_contigs_abundance.tsv<br> Number of reads that mapped to each contig for each sample. Rows = contig ID; column = sample ID.</p> <p>contigs/merged_contigs_abundance_cpm.tsv<br> Normalized (edgeR) number of reads (Count Per Million - CPM) that mapped to each contig for each sample. Rows = contig ID; column = sample ID.</p> <p><strong>Gene abundance:</strong><br> genes/merged_gene_abundance.tsv<br> Number of reads that mapped to each gene for each sample. Rows = gene ID; column = sample ID.</p> <p>genes/merged_gene_abundance_cpm.tsv<br> Normalized (edgeR) number of reads (Count Per Million - CPM) that mapped to each gene for each sample. Rows = gene ID; column = sample ID.</p> <p><strong>Beta diversity:</strong><br> Beta diversity tables computed (with microbiomeutils v0.9) on gene abundance and contig abundance and bacteria/archaea contigs abundance are available here:<br> betadiv/bray_curtis_contig_abundance/<br> betadiv/bray_curtis_gene_abundance/<br> betadiv/bray_curtis_contig_bacteriaArchaea/<br> Inside each of these directory is an index.html file allowing to visualize an Emperor interactive 3d vizualisation of beta diversity ordinations.<br> ./3d_bray_curtis_plot/index.html</p> <p><strong>Functional annotations:</strong><br> Gene functional annotations procedures are inspired from the JGI annotation workflow and is described in PMID: 31600863.</p> <p>annotations/annotations.tsv<br> Functional annotations and taxonomic lineages (see below) are merged in a single tabular separated file. <br> Contains the results of <br> DIAMOND BLASTp of each gene amino acid sequence against KEGG genes database.<br> DIAMOND BLASTp of each gene amino acid sequence against NCBI nr database.<br> HMMSCAN of each gene amino acid sequence against PFAM-A database (in domtblout format).<br> HMMSCAN of each gene amino acid sequence against PFAM-A database (in tblout format).<br> RPS-BLAST of each gene amino acid sequence against COG database.</p> <p><br> <strong>Contigs-based taxonomy:</strong></p> <p>consensus/taxonomy.tsv<br> Contains the taxonomy assignment for each contig. Taxonomy assignment was performed with PMID : 31640809. <br> consensus/feature_table_<normalized>_L1 to _L7.txt<br> Contigs abundance tables of each contig for each sample. Taxonomy assignment was performed with PMID : 31640809. </p> <p>consensus/feature_table.tsv<br> Contains the raw reads abundance of each contig across all samples.</p> <p>consensus/feature_table_normalized.tsv<br> Contains the normalized (with edgeR) reads abundance of each bin across all samples.</p> <p> </p>
Disruption of fish gut microbiota composition and holobiont's metabolome during a simulated Microcystis aeruginosa (Cyanobacteria) bloom
<p>This archive contains the R code, QIIME2 script and datasets used to perform the analyses and figures in the manuscript.</p>
Seed imbibition and metabolism differentially contribute to initial assembly of the soybean holobiont
<p>Positive 16S rRNA controls linked to the NCBI Bioproject <a href="https://www.ncbi.nlm.nih.gov/sra/PRJNA915932">https://www.ncbi.nlm.nih.gov/sra/PRJNA915932</a></p>
Seed imbibition and metabolism differentially contribute to initial assembly of the soybean holobiont
<p>Negative 16S rRNA controls for data linked to the NCBI Bioproject <a href="https://www.ncbi.nlm.nih.gov/sra/PRJNA915932">https://www.ncbi.nlm.nih.gov/sra/PRJNA915932</a></p>
Data from: Entangled fates of holobiont genomes during invasion: nested bacterial and host diversities in Caulerpa taxifolia
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Holobiont traits shape climate change responses in cryptic coral lineages
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Thermal extremes likely trigger metabolic imbalance in coral holobionts
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Data from: Assessing the effects of iron enrichment across holobiont compartments reveals reduced microbial nitrogen fixation in the Red Sea coral Pocillopora verrucosa
The productivity of coral reefs in oligotrophic tropical waters is sustained by an efficient uptake and recycling of nutrients. In reef-building corals, the engineers of these ecosystems, this nutrient recycling is facilitated by a constant exchange of nutrients between the animal host and endosymbiotic photosynthetic dinoflagellates (zooxanthellae), bacteria, and other microbes. Due to the complex interactions in this so-called coral holobiont, it has proven difficult to understand the environmental limitations of productivity in corals. Among others, the micronutrient iron has been proposed to limit primary productivity due to its essential role in photosynthesis and bacterial processes. Here, we tested the effect of iron enrichment on the physiology of the coral Pocillopora verrucosa from the central Red Sea during a 12-day experiment. Contrary to previous reports, we did not see an increase in zooxanthellae population density or gross photosynthesis. Conversely, respiration rates were significantly increased, and microbial nitrogen fixation was significantly decreased. Taken together, our data suggest that iron is not a limiting factor of primary productivity in Red Sea corals. Rather, increased metabolic demands in response to iron enrichment, as evidenced by increased respiration rates, may reduce carbon (i.e., energy) availability in the coral holobiont, resulting in reduced microbial nitrogen fixation. This decrease in nitrogen supply in turn may exacerbate the limitation of other nutrients, creating a negative feedback loop. Thereby, our results highlight that the effects of iron enrichment appear to be strongly dependent on local environmental conditions and ultimately may depend on the availability of other nutrients.
Data and code for: Photoacclimation dynamics in coral holobionts responding to thermal and irradiance changes correlate with photon pressure per symbiont
<p>Code and data used in the publication "Photoacclimation dynamics in coral holobionts responding to thermal and irradiance changes correlate with photon pressure per symbiont". For queries about this dataset please email robert.mason1@uq.net.au</p>
Lichen holobionts show compositional structure along elevation
<p>Holobionts are dynamic ecosystems that may respond to abiotic drivers with compositional changes. Uncovering elevational diversity patterns within these microecosystems can further our understanding of community-environment interactions. Here we assess how the major components of lichen holobionts – fungal hosts, green algal symbionts, and the bacterial community – collectively respond to an elevational gradient.</p> <p>We analyze populations of two lichen symbioses, Umbilicaria pustulata and U. hispanica, along an elevational gradient spanning 2100 altitudinal meters and covering three major biomes. Our study shows (i) discontinuous genomic variation in fungal hosts with one abrupt genomic differentiation within each of the two host species, (ii) altitudinally structured bacterial communities with pronounced turnover within and between hosts, and (iii) altitude-specific presence of algal symbionts. Alpha diversity of bacterial communities decreased with increasing elevation. A marked turnover in holobiont diversity occurred across two altitudinal belts: at 11-13°C average annual temperature (here: 800-1200m a.s.l.), and at 7-9°C average annual temperature (here: 1500-1800m a.s.l.). The two observed zones mark a clustering of distribution limits and community shifts. The three ensuing altitudinal classes, i.e. the most frequent combinations of species in holobionts, approximately correspond to the Mediterranean, cool-temperate, and alpine climate zones. We conclude that multitrophic microecosystems, such as lichen holobionts, respond with concerted compositional changes to climatic factors that also structure communities of macroorganisms, e.g. vascular plants.</p>
Thermal adaptation in a holobiont accompanied by phenotypic changes in an endosymbiont
<p>How and if organisms can adapt to changing temperatures has drastic consequences for the natural world. Thermal adaptation involves finding a match between temperatures permitting growth and the expected temperature distribution of the environment. However, if and how this match is achieved, and how tightly linked species change together, are poorly understood. <i>Paramecium bursaria</i> is a ciliate that has a tight physiological interaction with endosymbiotic green algae (zoochlorellae). We subjected a wild population of <i>P. bursaria </i>to a cold and warm climate (20℃ and 32℃) for ~300 generations. We then measured the thermal performance curve (TPC) for intrinsic rate of growth (<i>r</i><sub>max</sub> ) for these evolved lines across temperatures. We also evaluated number and size of the zoochlorellae populations within paramecia cells. TPCs for warm-adapted populations were shallower and broader than TPCs of cold-adapted populations, indicating that the warm populations adapted by moving along a thermal generalist/specialist trade off rather than right-shifting the TPC. Zoochlorellae populations within cold-adapted paramecia<i> </i>had fewer and larger zoochlorellae than hot-adapted paramecia, indicating phenotypic shifts in the endosymbiont accompany thermal adaptation in the host. Our results provide new and novel insight into how species involved in complex interactions will be affected by continuing increasing global temperatures. </p>
Lichen holobionts show compositional structure along elevation
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Thermal adaptation in a holobiont accompanied by phenotypic changes in an endosymbiont
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Data from: Assessing the effects of iron enrichment across holobiont compartments reveals reduced microbial nitrogen fixation in the Red Sea coral Pocillopora verrucosa
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Data for: Relative abundance of nitrogen cycling microbes in coral holobionts reflects environmental nitrate availability
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Data for "Heat stress reduces the contribution of diazotrophs to coral holobiont nitrogen cycling"
<p>Raw data associated with publication 'Heat stress reduces the importance of diazotrophs for coral holobiont nitrogen cycling'. </p> <p>"Rädecker_etal_16S.csv" contains sequence abundance data of annotated 16S rRNA ASVs for all five coral colonies during control or heat stress conditions at day 10 of the experiment. </p> <p>"Rädecker_etal_nifH.csv" contains sequence abundance data of annotated nifH rRNA ASVs for all five coral colonies during control or heat stress conditions at day 10 of the experiment. </p> <p>"Rädecker_etal_N2Fix.csv" contains bulk (acetylene reduction) as well as net (15N2 assimilation) measurements of microbial nitrogen fixation for all five coral colonies during control or heat stress conditions at day 10 of the experiment. </p> <p>"Rädecker_etal_NanoSIMS.csvv" contains raw mass count data of coral host and algal symbiont ROIs (15 images per treatment) for one coral colony during control or heat stress conditions at day 10 of the experiment. </p>
Data from: Direct contribution of invertebrate holobionts to methane release from coastal sediments
<p>In this study, we incubated 103 animals specimens equivalent to 19 macrofaunal species to quantify holobiont-associated methane (CH<sub>4</sub>) fluxes and metabolic processes [oxygen (O<sub>2</sub>) - respiration and ammonium (NH<sub>4</sub><sup>+</sup>) - excretion rates]. The specific goals were to quantify holobionts CH<sub>4</sub> production/uptake and to establish correlations between CH<sub>4</sub> fluxes and environmental factors (e.g., salinity).</p> <p>Invertebrates were collected in 4 coastal systems and incubated in 22 mL glass microcosms filled with 0.22 µm twice-filtered <em>in situ</em> water. Individual and Mass-standardized CH<sub>4</sub> Production Rates (IPR and MPR, respectively), O<sub>2</sub> Respiration Rates (IRR and MRR) and NH<sub>4</sub><sup>+ </sup>Excretion Rates (IER and MER) were measured in 103 animals’ incubations.</p> <p>1. IRR were calculated from linear regression analysis of the solute (O<sub>2</sub>) versus time equation: </p> <p> <span class="math-tex">\(IRR=(Reg.Slope × V)/N\)</span></p> <p><em> where IRR (µmol O<sub>2</sub> ind.<sup>−1</sup> day<sup>−1</sup>) is the respiration of the chemical species O<sub>2</sub>; Reg.Slope is the slope of the regression (µmol O<sub>2</sub> L<sup>−1</sup> day<sup>−1</sup>); V (L) is the water volume in the glass microcosm; N is the number of incubated animals per microcosm.</em></p> <p>2. IER and IPR were calculated from the difference in concentrations (NH<sub>4</sub><sup>+</sup> and CH<sub>4</sub>) in the water using the equation:</p> <p> <span class="math-tex">\(IER and IPR = ((C_f-C_i )×V)/(N×t)\)</span></p> <p><em> where IER and IPR (µmol ind.<sup>−1</sup> day<sup>−1</sup> and nmol ind.<sup>−1</sup> day<sup>−1</sup>) are the excretion or production of the chemical species (NH<sub>4</sub><sup>+</sup> or CH<sub>4</sub>); C<sub>f</sub> and C<sub>i</sub> (µmol or nmol L<sup>−1</sup>) are the final and initial concentrations of the chemical species; V (L) is the water volume in the glass microcosm; N is the number of incubated animals per microcosm; and t (days) is the incubation time. Positive values represent productions while negative values represent uptake.</em></p> <p>Same equations were used to calculated mass-standardized rates, but instead of <em>N</em> the total animal biomass (g<sub>dw</sub>) was used. Animals’ biomass was determined as dry weight (DW) or as dry weight shell free (DWSF) for bivalves, after the desiccation at 70°C until constant mass. Water temperature and salinity were measured in situ with a multiple probe (556 MPS, YSI). Rates are reported as average ± standard error.</p>
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