Introducing the Mangrove Microbiome Initiative: Identifying Microbial Research Priorities and Approaches To Better Understand, Protect, and Rehabilitate Mangrove Ecosystems

Mangrove ecosystems provide important ecological benefits and ecosystem services, including carbon storage and coastline stabilization, but they also suffer great anthropogenic pressures. Microorganisms associated with mangrove sediments and the rhizosphere play key roles in this ecosystem and make essential contributions to its productivity and carbon budget. Understanding this nexus and moving from descriptive studies of microbial taxonomy to hypothesis-driven field and lab studies will facilitate a mechanistic understanding of mangrove ecosystem interaction webs and open opportunities for microorganism-mediated approaches to mangrove protection and rehabilitation. Such an effort calls for a multidisciplinary and collaborative approach, involving chemists, ecologists, evolutionary biologists, microbiologists, oceanographers, plant scientists, conservation biologists, and stakeholders, and it requires standardized methods to support reproducible experiments. Here, we outline the Mangrove Microbiome Initiative, which is focused around three urgent priorities and three approaches for advancing mangrove microbiome research

16S rRNA gene amplicon-based metagenomic analysis of bacterial communities in the rhizospheres of selected mangrove species from Mida Creek and Gazi Bay, Kenya.

Prokaryotic communities play key roles in biogeochemical transformation and cycling of nutrients in the productive mangrove ecosystem. In this study, the vertical distribution of rhizosphere bacteria was evaluated by profiling the bacterial diversity and community structure in the rhizospheres of four mangrove species (Sonneratia alba, Rhizophora mucronata, Ceriops tagal and Avicennia marina) from Mida Creek and Gazi Bay, Kenya, using DNA-metabarcoding. Alpha diversity was not significantly different between sites, but, significantly higher in the rhizospheres of S. alba and R. mucronata in Gazi Bay than in Mida Creek. Chemical parameters of the mangrove sediments significantly correlated inversely with alpha diversity metrics. The bacterial community structure was significantly differentiated by geographical location, mangrove species and sampling depth, however, differences in mangrove species and sediment chemical parameters explained more the variation in bacterial community structure. Proteobacteria (mainly Deltaproteobacteria and Gammaproteobacteria) was the dominant phylum while the families Desulfobacteraceae, Pirellulaceae and Syntrophobacteraceae were dominant in both study sites and across all mangrove species. Constrained redundancy analysis indicated that calcium, potassium, magnesium, electrical conductivity, pH, nitrogen, sodium, carbon and salinity contributed significantly to the species-environment relationship. Predicted functional profiling using PICRUSt2 revealed that pathways for sulfur and carbon metabolism were significantly enriched in Gazi Bay than Mida Creek. Overall, the results indicate that bacterial community composition and their potential function are influenced by mangrove species and a fluctuating influx of nutrients in the mangrove ecosystems of Gazi Bay and Mida Creek

Diversity of <em>Termitomyces</em> Associated with Fungus-Farming Termites Assessed by Cultural and Culture-Independent Methods

<div><p>Background</p><p>Fungus-cultivating termites make use of an obligate mutualism with fungi from the genus <i>Termitomyces</i>, which are acquired through either vertical transmission via reproductive alates or horizontally transmitted during the formation of new mounds. <i>Termitomyces</i> taxonomy, and thus estimating diversity and host specificity of these fungi, is challenging because fruiting bodies are rarely found. Molecular techniques can be applied but need not necessarily yield the same outcome than morphological identification.</p> <p>Methodology</p><p>Culture-dependent and culture-independent methods were used to comprehensively assess host specificity and gut fungal diversity. Termites were identified using mitochondrial cytochrome oxidase II (COII) genes. Twenty-three <i>Termitomyces</i> cultures were isolated from fungal combs. Internal transcribed spacer (ITS) clone libraries were constructed from termite guts. Presence of <i>Termitomyces</i> was confirmed using specific and universal primers. <i>Termitomyces</i> species boundaries were estimated by cross-comparison of macromorphological and sequence features, and ITS clustering parameters accordingly optimized. The overall trends in coverage of <i>Termitomyces</i> diversity and host associations were estimated using Genbank data.</p> <p>Results and Conclusion</p><p>Results indicate a monoculture of <i>Termitomyces</i> in the guts as well as the isolation sources (fungal combs). However, cases of more than one <i>Termitomyces</i> strains per mound were observed since mounds can contain different termite colonies. The newly found cultures, as well as the clustering analysis of GenBank data indicate that there are on average between one and two host genera per <i>Termitomyces</i> species. Saturation does not appear to have been reached, neither for the total number of known <i>Termitomyces</i> species nor for the number of <i>Termitomyces</i> species per host taxon, nor for the number of known hosts per <i>Termitomyces</i> species. Considering the rarity of <i>Termitomyces</i> fruiting bodies, it is suggested to base the future taxonomy of the group mainly on well-characterized and publicly accessible cultures.</p> </div

Midpoint-rooted maximum-parsimony phylogeny of selected <i>Termitomyces</i> cultures (one per host) inferred from combined ITS, macromorphological and physiological characters.

<p>The host/mound index (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056464#pone-0056464-t001" target="_blank">table 1</a>) is the bold part of the labels of the leaves. Numbers above branches, separated by vertical bars, are maximum-parsimony branch lengths (DELTRAN optimization) estimated from the ITS (left), macromorphological (middle left), enzymatic test and carbon-degradation assay (middle right), and all characters (right). They are not shown for zero-length branches. Numbers below branches, separated by vertical bars, are partitioned and total Bremer support values, depicted in the same order. Single numbers printed in bold below branches are maximum-parsimony bootstrap support values from 1000 replicates. Stars indicate those branches on which macromorphology and/or physiology yielded more support and/or more changes than ITS. Vertical bars on the right side indicate the accordingly estimated species boundaries.</p

Temporal development of coverage of <i>Termitomyces</i> diversity by GenBank ITS sequences based on optimal clustering parameters (thick lines) as well as a selection of suboptimal ones (thin lines) to assess parameter sensitivity of the overall trends.

<p>As in Fig. 2, the clustering parameter <i>F</i> is indicated by color: light gray, <i>F</i> = 0.0; dark grey, <i>F</i> = 0.5; black, <i>F</i> = 1.0. The suboptimal threshold values were varied between 1% and 5% in steps of 1% and are either arranged in decreasing or increasing order, depending on the context; see the text for further details. Deposition years were extracted from the GenBank accessions; the incomplete year 2012 was coded as 2011.5. A, cumulative number of clusters; B, average number of sequences per cluster; C, average number of distinct host genera per cluster indicated in the GenBank accessions; D, average number of distinct host species per cluster indicated in the GenBank accessions; E, average number of clusters per host genus; F, average number of clusters per host species. In C and D, values below 1 may occur because host affiliations need not be indicated in GenBank entries.</p

Clustering-optimization plot for the selected ITS data, using the species boundaries estimated via Fig. 1 as reference partition.

<p>Shown are the partition-agreement metrics (MRI) in dependency of the ITS sequence dissimilarity thresholds for three values of the <i>F</i> clustering parameter: light gray, <i>F</i> = 0.0; dark grey, <i>F</i> = 0.5; black, <i>F</i> = 1.0.</p

Termite specimens, COII Genbank accession numbers, taxonomical affiliations in OPTSIL clustering, and collection data.

<p>Termite specimens, COII Genbank accession numbers, taxonomical affiliations in OPTSIL clustering, and collection data.</p

Introducing the Mangrove Microbiome Initiative: Identifying Microbial Research Priorities and Approaches To Better Understand, Protect, and Rehabilitate Mangrove Ecosystems.

Mangrove ecosystems provide important ecological benefits and ecosystem services, including carbon storage and coastline stabilization, but they also suffer great anthropogenic pressures. Microorganisms associated with mangrove sediments and the rhizosphere play key roles in this ecosystem and make essential contributions to its productivity and carbon budget. Understanding this nexus and moving from descriptive studies of microbial taxonomy to hypothesis-driven field and lab studies will facilitate a mechanistic understanding of mangrove ecosystem interaction webs and open opportunities for microorganism-mediated approaches to mangrove protection and rehabilitation. Such an effort calls for a multidisciplinary and collaborative approach, involving chemists, ecologists, evolutionary biologists, microbiologists, oceanographers, plant scientists, conservation biologists, and stakeholders, and it requires standardized methods to support reproducible experiments. Here, we outline the Mangrove Microbiome Initiative, which is focused around three urgent priorities and three approaches for advancing mangrove microbiome research