Red Mangrove Propagule Bacterial Communities Vary With Geographic, But Not Genetic Distance

doi:10.21203/rs.3.rs-1758172/v1

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Red Mangrove Propagule Bacterial Communities Vary With Geographic, But Not Genetic Distance

https://doi.org/10.21203/rs.3.rs-1758172/v1

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Bacterial communities associated with plant propagules remain understudied, despite the opportunities that propagules represent as dispersal vectors for bacteria to new sites. These communities may be the product of a combination of environmental influence and inheritance from parent to offspring. The relative role of these mechanisms could have significant implications for our understanding of plant-microbe interactions. We studied the correlates of microbiome community similarities across an invasion front of red mangroves (Rhizophora mangle L.) in Florida, where the species is expanding northward. We collected georeferenced propagule samples from 110 individuals of red mangroves across 11 populations in Florida and used 16S rRNA gene (iTag) sequencing to describe their bacterial communities. We found no core community of bacterial Amplicon Sequence Variants (ASVs) across the Florida range of red mangroves, though there were some ASVs shared among individuals within most populations. Populations differed significantly as measured by Bray-Curtis dissimilarity, but not Unifrac distance. We generated data from 6 microsatellite loci from 60 individuals across 9 of the 11 populations. Geographic distance was correlated with beta diversity, but genetic distance was not. We conclude that red mangrove propagule bacterial communities are likely influenced more by local environmental acquisition than by inheritance.

Rhizophora mangle

microsatellites

16S rRNA

mangrove

microbiome

propagule

Microbes are increasingly recognized for their intimate interactions with plants. Bacteria are ubiquitous on (epiphytes) and within (endophytes) plants where they may affect pathogen defense, nutrient acquisition, secondary metabolite production, and resistance to abiotic stressors [1]. Plant-associated communities are likely derived from a combination of environmental acquisition and inheritance from parent to offspring [2], and understanding the origin of these communities has important implications for our understanding of plants as holobionts ([3]). Considering multicellular organisms as holobionts (units composed of the multicellular organism and its associated microbiota) may be more productive than considering the multicellular organism alone in certain contexts, especially those where the microbiota is inherited from parent to offspring. If microbes are inherited across generations, they may provide additional raw material for natural, and thus influence the evolution of their hosts [4]. In many cases, it appears that offspring are inoculated with microbes from their parents, but that their microbiota changes as the individual develops and interacts with its environment [5]. Here, we examine variation in the propagule-associated bacterial communities of red mangroves (Rhizophora mangle L.; Rhizophoraceae) across geographic and genetic distance to determine the relative influence of host environment and maternal relatedness on bacterial community composition.

The strongest environmental influence on plant microbiomes may be the substrate on which a plant grows. Plants may selectively enrich microbes on and near their roots by releasing carbon-rich exudates in exchange for protection from soil-borne pathogens and increased access to soil nutrients [1]. Soils contain immense microbial diversity, and some soil-borne microbes may cross the root endodermis and move throughout the plant via vascular tissue [6]. Additionally, physical (e.g., particle size) and chemical (e.g., nutrient content) characteristics of the substrate can influence plant physiology, and thus the niche space exploited by microbes and the composition of plant-associated microbial communities [1]. Surprisingly, leaf bacterial communities appear to be affected more by soil-borne bacteria than airborne bacteria, possibly due to the relative difficulty in establishment in the complex environment of the leaf surface [7]. In mangroves, the soil environment also includes seawater that periodically inundates the soil and lower portions of the plants. Seawater bacterial communities contain high abundances of the phyla Proteobacteria and Bacteroidetes, while sediment communities host distinct, significantly more diverse communities with high abundances of Bacteroidetes but lower abundances of Proteobacteria [8].

In plants, the typical pathway for inheritance is through seeds (the spermosphere) or fruits (the carposphere). Bacteria associated with the seeds of Chinese silver grass (Miscanthus sinensis) make significant contributions to the seedling microbiome, display adaptations to long-term survival within the seed, and respond rapidly to imbibition of water during germination by concentrating at the embryonic root tip [9]. A conserved assemblage of spermosphere bacteria has been identified across geographic and genetic distance in maize (Zea mays L.), and some of these bacteria may also inoculate the soil near the root system [10]. Seed endophytes in Elephant cactus (Pachycereus pringlei (S. Watson) Britton & Rose) contribute to the creation of suitable habitat by improving access to nutrients and promoting rock weathering[11, 12]. Spermosphere bacteria in green bristlegrass (Setaria viridis (L.) P. Beauv) increase germination rate, though after growing several generations of plants in sterile soil, seed endophyte diversity, seed germination, and plant growth rates all declined [2], suggesting that the interaction of seed endophytes and soil microbes is important for long-term plant health.

The carposphere is less well studied than the spermosphere, perhaps in part due to the increased complexity of fruits, or the immense variation in fruit anatomy and secondary chemistry. Studies to-date have largely focused on agricultural species. The microbiome of the carposphere is likely influenced by that of the anthosphere (the floral tissues). The bacterial microbiome of apple flowers (Malus domestica cultivar Gala (Suckow) Borkh.) undergoes successional changes during floral development, with different major clades rising and falling in abundance in predictable patterns over time [13]. Carposphere communities of grapes (Vitis vinifera L.) were distinct from those of the leaves and were influenced more strongly by local environmental differences than by host genotype [14]. Red mangroves produce viviparous propagules, which are single-seeded fruits that germinate prior to abscission from the parent plant [15] and have been shown to host bacterial communities distinct from their leaves, stems, and flowers that may vary across populations (Unpublished Data).

Mangroves are woody trees or shrubs found in the intertidal zones of the tropics and subtropics worldwide. There are approximately twenty evolutionary origins of mangrove habit [16], including three represented in the native flora of Florida. Red mangroves are distinguished from Florida’s other two native mangrove species by the former’s rhizophores (also known as prop roots) and elongated, viviparous propagules (Fig. 1). Red mangrove propagules include a prominent, waxy radicle (embryonic root) that ruptures the seed coat and fruit wall prior to germination. They have a longevity of at least one year in seawater and can establish rapidly after lodging in substrate following dispersal [15]. These adaptations, combined with a reduced frequency of hard winter freezes, are contributing to an ongoing poleward range expansion throughout its range [17]. This species also provides critical habitat to numerous organisms, including rare and endangered species including goliath grouper (Epinephelus itajara; [18]), smalltooth sawfish (Pristis pectinate; [19]), and lemon shark (Negaprion brevirostris; [20]).

Red mangroves have been the focus of several population genetics studies [21–23], through which several microsatellite loci have been developed. This species displays genetic variation throughout its Florida range, though previous work has not found significant evidence of population differentiation, suggesting that there is ongoing gene flow between populations [21, 22]. This is likely due in part to the long-distance dispersal capabilities of its propagules. The most north-western populations have lower genetic variation and higher population structure, probably due to founder effects [22].

We present data comparing the bacterial microbiome of one hundred propagule samples of Rhizophora mangle from eleven populations throughout much of its Florida range, as well as microsatellite data from six loci across nine populations to investigate the relative influence of host geography and genetic distance on propagule bacterial community composition. Specifically, we address the following sets of questions. (1) Two factors would tend to reinforce the distinctiveness of the bacteria within a population of R. mangle: inheritance of bacteria from parent to offspring when the offspring establishes at the same population as the parent, and introduction of bacteria from the local environment. Given this, are there any bacterial ASVs shared amongst propagules from the same population or across the different populations of R. mangle in Florida? Are different populations of R. mangle associated with significantly different bacterial communities? (2) However, long-distance dispersal could frequently lead to establishment of propagules at new populations. Are the microbiomes of propagules found on maternal plants that are geographically near to one another most similar, perhaps due to significant influence from the local species pool and/or frequent establishment of propagules locally? Or are the microbiomes of propagules more similar when the maternal plants are more genetically similar, even when the propagules are separated by great distance, perhaps due to a strong influence of inheritance on the composition of the microbiome?

Sample Collection

Samples were collected and GPS coordinates were recorded from 110 individuals of R. mangle from 11 sites across Florida (Table 1, Fig. 2). Each site was visited once between October 1 and December 1, 2019. In a protocol like those commonly used in food microbiology [24] all samples were collected in 13 oz sterile Whirl-Pak sample bags (Nasco: Ft. Atkinson, WI) and stored on ice until they could be brought back to the lab and frozen at minus 20° Celsius. Aseptic techniques were used during sample collection and all utensils were sterilized with 95% ethanol between samples. Each sample consisted of ten fruits from a single individual, pooled in one sample bag. This approach generated data that did not distinguish between endo- and epiphytic microbes, but rather characterized the entire community. Sampled individuals were at least 5 meters away from one another. Leaf samples were also collected from each fruiting individual (i.e., the maternal plant) for microsatellite analysis.

Bacterial DNA Extraction

Sample collection and preparation followed previously published work [25]. Samples were prepared for DNA extraction by first adding 18 ml of phosphate buffer solution to each bag, then pulverizing the sample in a Nasco Stomacher 400 Circulator Lab Blender (Seward Laboratory Systems: Bohemia, NY) at 260 RPM for four minutes and thirty seconds. The liquid was then pipetted into a sterile centrifuge tube and spun at 4200 RPM for 12 minutes at 10° Celsius. All but 250 ml of the solution and the pellet was then pipetted off, and the remaining 250 ml was vortexed briefly to mix the pellet back into the liquid. This liquid then served as the input for the Zymobiomics DNA Microprep Kit (Genessee Scientific: Irvine, CA), which was used to extract the bacterial DNA according to the kit protocol.

16S Libraries and Sequencing

We used the forward/reverse bacterial primer pair S-D-Bact-0341-b-S-17/S-D-Bact-0785-a-A-21 [26]. 16S rRNA gene sequencing amplicon libraries were prepared using a two-step PCR as described in the Illumina 16S Library Preparation guide [27] with the following modifications: intermediate and final amplicons were examined by agarose gel electrophoresis, quantified by Qubit dsDNA HS Assay (Invitrogen: Carlsbad, CA), and pooled at equimolar concentrations. The library pool was analyzed using Agilent's TapeStation D1000 High Sensitivity Assay (Agilent: Santa Clara, CA) and quantified using KAPA qPCR for Illumina libraries. Libraries were sequenced on an Illumina MiSeq (San Diego, CA) using MiSeq Reagent Kit v3 (2x300 cycles). A rarefaction curve (Supplementary File One) was generated using QIIME2 v. 2019.7.0 [28] to visualize the relationship between sequencing effort and the number of ASVs identified per sample.

Microsatellites

Leaf samples taken from the fruiting individuals represent the maternal parent of each propagule sample. Leaves were ground using liquid nitrogen and a ceramic mortar and pestle. ~20 mg of ground tissue was used to extract plant DNA using a DNEasy Plant Mini kit (Qiagen, Valencia, CA, USA). Extractions were quantified using a Nanodrop 2000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and then concentrated to approximately 10ng/uL. Microsatellite data was generated using a triple multiplex panel approach with five loci per panel (Table 2). Multiplex procedure and PCR conditions were adapted from previous work in R. mangle [23] and can be found in Supplementary File Two. Fragment analysis was performed on an Applied Biosystems 3730 Genetic Analyzer with Capillary Electrophoresis (Waltham, MA, USA). Multiplex one failed to amplify during PCR, so subsequent analyses were based on Multiplexes two and three. Geneious Prime [29] was used to call peaks and identify alleles. Briefly, the steps involved were as follows. The trace document for each ladder was inspected, and ladder peaks were called manually as needed when Geneious failed to correctly identify them automatically. Loci were set by inputting basic information including expected size, repeat unit size, and the expected number of peaks for each locus. Alleles were binned using Geneious’ binning algorithm. In cases where Geneious left alleles unbinned, we followed their tutorial and manually adjusted bins in order to include all alleles present. We used GenAlEx [30, 31] to calculate the pairwise geographic and genetic distances between each sample, visualize genetic distances between samples using Principal Coordinates Analysis (PCoA), and calculate summary statistics for our microsatellite dataset. The PCoA was generated using a standardized covariance matrix of pairwise genetic distances between individuals. A sensitivity analysis was conducted by removing each of the 6 loci in turn and running the downstream analyses with each dataset of 5 loci.

Data Analysis

Raw 16S data in the form of forward and reverse demultiplexed FASTQ files were obtained from the Illumina MiSeq platform. These files were then analyzed using QIIME2 v. 2019.7.0 [28]. The DADA2 plugin [32] was used to join forward and reverse reads, and for quality control involving an assessment of the frequency of occurrence of non-plastid, high-quality, non-chimeric reads. The Silva v. 138 [33] database was used to assign taxonomy to each Amplicon Sequence Variant (ASV). The core-features plugin in QIIME2 was used to identify “core” ASVs within populations and across all populations. These core community members were considered at thresholds ranging from 25–100% of samples of a given grouping (i.e., all sampled individuals of a population or all sampled individuals).

The R package Wrench [34]was used to normalize and log-transform the data. The package GUnifrac [35] was used to calculate Generalized Unifrac distances among samples. The package vegan [36] was used to calculate Bray-Curtis distances between samples and to perform pairwise PERMANOVA tests comparing Generalized Unifrac distances and Bray-Curtis distances across populations. Bray-Curtis measures community dissimilarity by comparing counts of community members (bacterial ASVs) among samples [37] while Unifrac distances measure the shared genetic distance of community members among samples [35]. The package vegan was also used to conduct Mantel tests and partial Mantel tests (permutations = 999) using our reduced dataset to compare Generalized Unifrac distances and Bray-Curtis distances with genetic and geographic distances.

One hundred of 110 propagule samples were successfully extracted, amplified, sequenced, and passed quality control (Table 1). Following DADA2 and the filtering out of all plastid, archaeal, and mitochondrial sequences there were 177,732 reads associated with 2,868 ASVs. The most common phylum represented in these samples was Proteobacteria (Relative Abundance (RA) = 60.4%), with substantial proportions of Actinobacteria (RA = 14.2%), and Bacteroidetes (RA = 11.8%) as well. The two most abundant classes were within Proteobacteria: Alphaproteobacteria (Total RA = 48.6%) and Gammaproteobacteria (Total RA = 9.9%).

The rarefaction curve (Supplementary File One) demonstrated that increasing sampling effort beyond 400 to 2,000 reads per sample was unnecessary, suggesting that this approach provided a sufficiently accurate description of these bacterial communities.

Core Communities and Differences Between Populations

No ASVs were shared between 25% or more of all samples, suggesting there is no core community of ASVs associated with red mangrove propagules along our sampling of the Florida coast. However, at the taxonomic level of phylum, most of our samples contained Proteobacteria (94% of samples), Actinobacteria (76%), and Bacteroidetes (51%). We found variation in the number of ASVs shared across individuals within each site (Table 3). One ASV from the Rhodobacteraceae was found in 77.5% of samples from Biscayne Bay, and this was the highest percentage of samples to contain the same ASV within any population. Two ASVs were found in 70% of samples from St. George Island, and 10 ASVs were found in 47.5% of samples from that population. This population had more shared ASVs in half its samples than any other population. (See Supplementary File Three for identities of Core ASVs within each location).

A pairwise PERMANOVA of Bray-Curtis distances found 48 of 55 population comparisons to be significantly different (Table 4). Biscayne Bay, the only population from the Atlantic coast, was significantly different from every other population. A pairwise PERMANOVA of generalized Unifrac distances did not find any significant differences between populations (Supplementary File Four).

Microsatellite Loci

We obtained data from ten microsatellite loci, but this full dataset had a significant amount of missing data (41.5%). To reduce bias associated with missing data, we used a reduced dataset of 6 loci (missing data = 7.3%). See Supplementary File Five for a comparison of the two datasets. Previous work in other organisms have used a similar number of loci to compare microbiome composition and host genotype (e.g., Griffiths et al., 2019; Parker et al., 2020). This reduced dataset had 60 individuals across 9 populations. The sensitivity analysis did not find differences in significance between the systematically reduced datasets of 5 loci when compared to each other or the 6-locus dataset. We visualized genetic distances between samples using Principal Coordinates Analysis (PCoA) (Figure 3), calculated the pairwise fixation index (FST) between all populations (Table 5), and calculated summary statistics across microsatellite loci (Table 6) and across populations (Table 7). The first axis of our PCoA explained 17.07% of the variation, the second axis explained 9.30%, and the third axis explained 8.60%.

Correlations Between Beta Diversity and Geographic and Genetic Distances

Geographic and genetic distance between maternal plants were positively correlated (r= 0.3977, p= 0.001). Using a Mantel test, we found a weak positive correlation between Bray-Curtis and geographic distance between samples (r=0.07903, p=0.033), but no significant correlation between Bray-Curtis and maternal genetic distance (r= 0.008878, p=0.429). Unifrac distance was not significantly correlated with geographic distance (r=-0.04915, p=0.908) or genetic distance (r=-0.006976, p=0.502). Furthermore, partial mantel tests did not find a significant correlation between either beta diversity metric and genetic distance after controlling for geographic distance (Bray-Curtis: Mantel Statistic=-0.01718, Significance= 0.622; Unifrac: Mantel Statistic=0.01298, Significance=0.379). Genetic distances between individuals and populations were visualized using PCoA (Figure 3). Pairwise F_st between populations was correlated with geographic distance (Figure 4), demonstrating that a significant proportion of the variation is due to isolation by distance.

Most Populations Are Significantly Different When Comparing Bray-Curtis, But Not Unifrac Distances.

We did not find evidence for any core community of ASVs shared broadly across the Florida Gulf Coast range of R. mangle, though most samples had at least one ASV from each of the phyla Proteobacteria, Actinobacteria, and Bacteroidetes. These phyla may also be very abundant in seawater and coastal sediments [8, 38], suggesting that the propagule communities could be significantly influenced by these environmental sources. We found variation in the number of core ASVs shared between individuals within each population (Table 3). These results are consistent with patterns found across leaves, stems, flowers, and propagules from three populations of red mangroves in the Florida Panhandle in terms of the dearth of shared ASVs (Unpublished Data). Interestingly, work on the microbiome of Rhizophora stylosa found no bacteria associated with the leaf or stem tissue [39].

Most work exploring core communities within plants has focused on terrestrial species, where core communities sometimes occur across broad ranges. Bacterial communities associated with ponderosa pine (Pinus ponderosa P. Lawson & C. Lawson) were found to display lower intraspecies variability than interspecies variability when compared to those of a congener and two other tree species, even where samples of Pinus ponderosa originated on different continents [40]. Furthermore, four bacterial species were found in seeds from 14 cultivars of maize (Zea mays L.) as well as its wild ancestor teosinte (Zea diploperennis H.H.Iltis et al.); several additional bacterial species were found in most of the cultivars sampled [10].

The lack of a core propagule bacterial community in R. mangle could be related to their viviparous nature. Morphologically, anatomically, and physiologically the propagules are similar to seedlings rather than seeds. As germinated seedlings, propagules interact with their dispersal environment in ways that seeds do not, suggesting the potential for environmental influence in ways not experienced by bacterial communities of seeds.

Carposphere bacterial community composition varied across mangrove populations. That we found Bray-Curtis to differ significantly between most pairwise comparisons of populations while no comparisons based on Unifrac distances were significantly different suggests that although the identities and relative abundances of ASVs associated with each population were different, the higher-level taxonomic diversity is relatively similar. This can be restated as bacterial communities differ in the precise ASVs found within them, but those ASVs are closely related to one another. These communities could contain similar taxonomic groups due to the similarity in the morphology, anatomy, and physiology of red mangrove propagules which are themselves a product of host evolution, even if the bacteria themselves are not faithfully inherited across generations.

The seeds of terrestrial plants, and perhaps endophytic communities in general, tend to be dominated by Proteobacteria, Firmicutes, Bacterioidetes, and Actinobacteria [41]. Our results generally align with this pattern, though we found few ASVs from the phylum Firmicutes (RA = 2.1%). While there is ample evidence in the literature of inheritance of microbes in plants [9, 10], we think it is unlikely that the patterns we describe here are the result of inheritance, for reasons explored below.

Host Geography, But Not Maternal Genotype, Is Correlated With Beta Diversity

We found Bray-Curtis dissimilarity, but not Generalized Unifrac distance, to be correlated with geographic distance between samples. Samples located close together tended to be more similar in terms of the identities and relative abundances of their ASVs, but not in terms of the genetic similarity of the bacterial communities. Together, these results suggest that geography might affect propagule-associated bacterial diversity at fine taxonomic scales, but broader taxonomic groupings remain relatively unaffected across geographic distance. This is broadly consistent with our understanding of plant-associated microbial communities [10, 40] and with the results of our pairwise PERMANOVA (Table 4).

Additionally, neither beta diversity metric was correlated with maternal genetic distance, suggesting that maternal genotype did not have a significant influence on bacterial community composition. These results are somewhat inconsistent with the literature. Bacterial endophytes of corn seeds were shown to be influenced by host genotype, and a core community of bacteria was identified across cultivars and even in the wild ancestor, Zea mays [10]. The bacterial and fungal leaf communities of grapes were shown to be influenced more heavily by geographic region (and the associated differences in environmental conditions) than by maternal genotype [14], suggesting that microbial communities found across different plant systems may differ in the relative influence of environment, geography, and genotype. Our sampling methods captured bacteria from the propagule surface and within the plant tissue. Bacterial communities associated with plant surfaces may be more readily influenced by differences in environmental conditions such as UV radiation, humidity, exposure to seawater, and ambient temperature than those found within plant tissues [42], and therefore may vary more strongly over geographic distances.

Genetic and geographic distance among mangroves were correlated, suggesting that more closely located individuals tended to be more closely related. We found evidence for population differentiation, with geographic distance accounting for nearly 67% of genetic variation (Figure 4). This is broadly consistent with previous work which found significant genetic variation between populations using 8 and 7 microsatellite loci, respectively [21, 22]. However, additional analysis with larger RADseq datasets found lower F_ST between populations [43].

This work provides, to our knowledge, the first investigation of the influence of geography and maternal genotype on the bacterial communities of red mangrove propagules. We did not find a Florida-wide core community of species-level bacterial ASVs associated with red mangrove propagules, though the phyla Proteobacteria, Actinobacteria, and Bacteroidetes were found in most samples. Different populations of mangroves were associated with different ASVs but were not significantly different in the relatedness of their communities. We found variation in red mangrove propagule bacterial communities across geographic distance, but not across maternal genetic distance. This variation suggests that differences in host environment or local bacterial species pools influence bacterial community composition more than maternal genotype does. Taken together, we propose that red mangrove propagule bacterial communities are not inherited with fidelity across generations. Experiments mimicking dispersal could provide valuable insight into whether propagule communities change during the seawater dispersal of red mangroves.

Funding

This work was supported by small research grants from the Florida Native Plant Society Magnolia Chapter and Florida State University.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Brendan Scherer. The first draft of the manuscript was written by Brendan Scherer and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Data Availability

The datasets generated during and/or analyzed during the current study will be available in the NCBI SRA Database repository under submission numbers PRJNA844062 and PRJNA842720 upon acceptance of publication. [https://www.ncbi.nlm.nih.gov/sra/PRJNA844062, https://www.ncbi.nlm.nih.gov/sra/PRJNA842720]

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Table 1-7 are available in the Supplemental Files section.

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Editorial decision: Major Revisions Needed
19 Jul, 2022
Reviewers agreed at journal
20 Jun, 2022
Reviewers invited by journal
17 Jun, 2022
Editor assigned by journal
15 Jun, 2022
First submitted to journal
14 Jun, 2022

You are reading this latest preprint version

Red Mangrove Propagule Bacterial Communities Vary With Geographic, But Not Genetic Distance

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Abstract

Figures

Introduction

Methods

Sample Collection

Bacterial DNA Extraction

16S Libraries and Sequencing

Microsatellites

Data Analysis

Results

Discussion

Conclusion

Declarations

References

Tables

Supplementary Files

Status:

Version 1