Are They What They Eat? a Stable GIT Microbiome Characterized in P

Are they what they eat? A stable GIT microbiome characterized in P. resecata.

by Tarah Gustafson

A THESIS

submitted to

Oregon State University

Honors College

in partial fulfillment of the requirements for the degree of

Honors Baccalaureate of Science in Biochemistry and Molecular Biology (Honors Scholar)

Presented November 12, 2020 Commencement June 2021

AN ABSTRACT OF THE THESIS OF

Tarah Gustafson for the degree of Honors Baccalaureate of Science in Biochemistry and Molecular Biology presented on November 12, 2020. Title: Are they what they eat? A stable GIT microbiome characterized in P. resecata.

Abstract approved:______Ryan Mueller

Intertidal herbivores, such as isopods, help regulate and contribute to nutrient cycling and organic carbon flow through the trophic levels in estuaries and coastal ecosystems. Though much is known about the microbiomes of macrophyte leaves that serve as the primary food source for isopods, and (to a lesser extent) the microbiomes of herbivores themselves, little has been studied about the community assembly dynamics of herbivore microbial communities. In this study, the intertidal herbivore P. resecata (order: Isopoda) was fed three different common macrophyte diets (Z. marina, U. lactuca, and L. saccharina) and the 16S rRNA genes of the microbial communities from the leaves of each diet, isopod gastrointestinal (GIT) content, and fecal pellets were amplified and sequenced with Illumina MiSeq sequencing. These data were cleaned using a DADA2 pipeline in R studio and the community complexity, structure, and prevalent taxa were examined for changes between each compartment sampled and based on diet treatment. Fecal pellets and macrophyte leaf samples showed structural differences based on macrophyte type. An authentic, present, and stable GIT content microbiome was found; no changes were found between the GIT microbiome of P. resecata fed different macrophytes, providing support to the growing body of work indicating a GIT-associated microbiome is present in marine isopods.

Key Words: microbiome, intertidal isopod, beta diversity

Corresponding e-mail address: [email protected]

©Copyright by Tarah Gustafson November 12, 2020

Are they what they eat? A stable GIT microbiome characterized in P. resecata.

by Tarah Gustafson

A THESIS

submitted to

Oregon State University

Honors College

in partial fulfillment of the requirements for the degree of

Honors Baccalaureate of Science in Biochemistry and Molecular Biology (Honors Scholar)

Presented November 12, 2020 Commencement June 2021

Honors Baccalaureate of Science in Biochemistry and Molecular Biology project of Tarah Gustafson presented on November 12, 2020.

APPROVED:

______Ryan Mueller, Mentor, representing Microbiology

______Byron Crump, Committee Member, representing Earth, Ocean, and Atmospheric Sciences

______Lydia Baker, Committee Member, representing Microbiology

______Toni Doolen, Dean, Oregon State University Honors College

I understand that my project will become part of the permanent collection of Oregon State University, Honors College. My signature below authorizes release of my project to any reader upon request.

______Tarah Gustafson, Author

CONTRIBUTION OF AUTHORS

Dr. Ryan Mueller assisted with data analysis and writing. Dr. Gema Hernán, Michael Moses, Dr. Fiona Tomas Nash, Dr. Ryan Mueller performed and designed experiments. Sample collection, processing, and DNA extractions were completed by Dr. Gema Hernán. Additional collaboration was given by Alexis Morris, Christina Mauney, Jen Hayduk, Grant Schwinge, Dr. Winni Wang and MK English.

Introduction

Understanding the factors that control the digestion and feeding of herbivores can have important implications on overall ecosystem function. Herbivores that directly consume macrophytes within intertidal zones are vital to the regulation of nutrient and organic matter flow within their ecosystems as well as macroecological resource cycling within marine ecosystems (1). The top-down regulation of macrophytes and their epiphytes via herbivory impacts nutrient balancing in marine systems (1-3). Additionally, the detrital matter in herbivore feces settles into the sediment, disperses into the water column, and drifts into nearby ecosystems, which can impact the spread of nutrient resources from the primary producers into the surroundings (4-6). Consumption of herbivores by predators is a key step that acts to transfer the organic carbon fixed by macrophytes and epiphytes to higher trophic levels in these aquatic food webs (3,7).

Macrophytes (such as seagrasses and seaweeds), which are commonly found along ocean coastlines, fix a disproportionately high amount of carbon relative to the area they cover and thus act as an important carbon sink in marine systems (8-9). Unlike seagrasses, which are angiosperms and have only a few species, seaweeds consist of brown, red, and green algae that belong to diverse taxonomic groups (10-11). Along the coast of the Northeastern Pacific Ocean, one seagrass, Zostera marina, dominates many areas of coast and estuaries (12). In addition, there are many different types of seaweeds that grow in the littoral zone of these ecosystems and compete with seagrasses for light, nutrients, and space.

Microbes are ubiquitous across all components of these intertidal ecosystems, including the water column, the sediment, macrophytes, epiphytes, animals, and detrital matter (13-15) and can have important influences on ecosystem processes, such as nutrient cycling, and the health of the organisms with which they are associated (5,16-19). Despite the structural differences that result in distinct taxa and functions associated with each microenvironment, there are many common microbes shared across these niches, indicating dispersal of microbes between them (20).

Microbes that are found intimately associated with different host organisms (i.e., their microbiomes) can form specific relationships with the host in which one or both parties benefit (19). Specialized functional adaptations of hosts and microbes are often implicated as the drivers of symbiotic interactions between

9 hosts and specific microbiota of the microbiome (21). These interactions and the highly selective pressures found in host-associated niches often result in microbiomes that are specific, deterministic, and relatively stable over time (20). Examples of this co-adaptation between microbes and their hosts can be seen in many animal hosts including in aphids, whose microbiomes provide nutrient and digestive assistance and where similarities between microbiomes of different aphid populations relates more to phylogeny than to ecology (22). Despite knowledge of these general principles of community assembly of host-associated microbiomes, specifics such as the characterization of many of these microbial communities or specific beneficial aspects to host/microbe relationships is ongoing (16, 17, 20). Additionally, little is known regarding the effect of interactions between the microbiomes of different hosts when the hosts themselves interact.

Isopods, in general, have a variety of feeding strategies and can be omnivores and detritivores, as well as herbivores (1, 23). Pentidotia resecata is a generalist isopod herbivore found in many intertidal zones of the Northeastern Pacific Ocean (3, 24). Due to the difference between the low nitrogen food source and their relatively high tissue composition of nitrogen, herbivores often rely on microbial symbionts to increase their nitrogen intake (25). Generalist herbivores, despite consuming a wide variety of vegetative food sources, frequently have a fairly homogenous and simplistic microbiome, presumably due to specific functional interactions and symbioses (1).

Much of the current literature about isopod-microbe interactions is on the microbiome of the terrestrial isopods, due to their unique evolutionary history as the only terrestrial crustacean (26). This work has shown that their microbiome has dramatic impacts on many aspects of their behavior, physiology, and nutrition (19, 21, 26, 27). For example, several bacteria, such as Wolbachia, Rickettsia, Spiroplasma, and Cardinium affect sex ratios of the terrestrial isopods (19). Additionally, several taxa found in the gastrointestinal tract (GIT) of isopods, such as Candidatus Hepatoplasma crinochetorum, Candidatus Hepatincola porcellionum, and Rhabdochlamydia porcellionis, can help with nutrient absorption and degradation of complex molecules, such as lignins, phenolics, and cellulose (16, 17, 25–27). In terrestrial isopods, the origin of an organism’s microbiome is thought to be through ingestion (horizontal transfer) and not through vertical inheritance from the progenitor’s reproduction (28, 29). Much less is known of the microbiomes of aquatic isopods. In fact, there is debate on whether there is an authentic and specific GIT microbiome in marine isopods (16–18, 21, 27).

This paper explores this question and considers the possibility of horizontal transfer of the microbiome from macrophyte diets to the P. resecata GIT and investigates differences in microbiome structure leaf surfaces, GIT contents, and fecal pellets as a function of each different diet. We ask (i) if the P. resecata GIT microbiome exists as a constant community, (ii) if that community’s structure is stable regardless of diet, and (iii) if that structure is not stable, is the structure of the GIT microbiome closely related to the macrophyte microbiome ingested by the isopod? Finally, we compare these results to fecal microbiomes of each diet in order to better understand the microbial community changes occurring throughout the GIT.

Methods

Statement of Work and Originality

Experimental performance, sample collection, processing, DNA extraction, PCR, and sequencing were led and performed by Gema Hernán, a visiting researcher to the Mueller Lab. The methods pertaining to this work are included below for full context and taken from Hernán, et al. (in prep.). My role in the project was to specifically perform all post-sequencing processing and analysis steps for the data generated from these experiments. Original experimental method details are provided in the “Statistical Analysis of Microbiomes” section below. I took over this project after work on my initial thesis research project on the microbiomes of musical instruments was cut short due to COVID-19 restrictions.

Feeding Experiments and Sample Collection

Adult male P. resecata (synonymously identified as Idotea resecata or Idothea resecata) (30) were collected from Netarts Bay, Oregon. The isopods were kept in individual perforated cups within a seawater flow-through system. Quantities of Z. marina, U. lactuca, and L. saccharina that had been cleaned of epiphytes were collected weekly from Yaquina Bay, Oregon. After a starvation period of 24 hours, the isopods were fed a monospecies diet of one of the macrophytes for the next 31 days. Their growth, both in mass and length, was recorded (data not reported here). Throughout this period fecal pellets were collected when seen, as well as leftover macrophyte leaves, and labeled with the day (marked from day 0 being the starvation day) and later processed as described in the “16S Amplicon Sequencing” section. At

11 the end of 31 days, the isopods were anesthetized, sterilized, and contents of the GIT were collected to be further processed and analyzed following an established protocol (31).

DNA extraction, PCR and 16S Amplicon Sequencing

DNAs from macrophyte leaves collected prior to the beginning of feeding trials, fecal pellets collected during the experiment, and GIT contents of sacrificed isopods were extracted using phenol-chloroform based protocol (32). The V4 hypervariable region of the 16S rRNA gene was amplified from community DNA using barcoded PCR primers and following with the protocols of Wang et al. (33). PCR products were cleaned, quantified, and pooled at equimolar ratios and sequenced using the Illumina MiSeq instrument operated by personnel at Oregon State University’s Center for Genome Research and Biocomputing (CGRB).

Terminology

In this paper, there are several different groups of samples which will be referenced. All samples can be characterized by two different treatment groupings: “sample type” (consisting of the leaf, the GIT content, and the fecal samples) and “macrophyte type” (consisting of Z. marina, U. lactuca, and L. Saccharina). For example, if the Z. marina data were to be grouped, referring to all leaf, GIT content, and fecal samples where Z. marina involved, this would be considered a group by macrophyte type. Expanding that, if the data, grouped by macrophyte type and then further divided by sample type, three sets of comparisons would be reported (because the leaf, GIT content, and fecal sample types would be compared, in this scenario, within each macrophyte type). The term “leaf” is chosen to denote the samples of macrophyte that was available to be consumed by the isopods. “Diet” is used generally to denote when something is being eaten or fed (e.g., ‘some isopods were fed a diet of Z. marina’).

Statistical Analysis of Microbiomes

The Illumina MiSeq sequence data were de-replicated, denoised, forward and reverse reads were merged, non-biological chimeras and Eukaryotic sequences were removed using the ‘dada2’ package (34) of the R statistical software programming environment (35). This followed the Illumina DADA2 pipeline (34).

Merging required at least 12 bp overlap between forward and reverse sequences, and any sequence that did not meet this criteria was removed. Taxonomy was assigned to the resulting amplicon sequence variants (ASVs) generated by the DADA2 pipeline by comparison against the Silva reference database. Lastly, poorly sequenced samples with fewer than 1000 reads after quality filtering and pre-processing were removed. ASV sequence count and taxonomy tables, a sample metadata table, and a fasta file from all final sequence data were generated and exported from R. Samples were not rarefied as the range in sequencing depth across all libraries was within an order of magnitude.

A filtered alignment of representative ASV sequences against the pre-computed SILVA Ref NR 132 alignment was created using the 'align.seqs' and 'filter.seqs' commands of the mothur software package (v 1.40.5) (36). FastTreeMP (v 2.1.7) (37) calculated a phylogenetic tree from the filtered alignment applying a generalized time-reversible model of evolution. The resulting tree was midpoint rooted using ‘reroot.pl’ (38).

The analysis of the ASV sequence count data for all sequenced samples was completed with the phyloseq package in R (39). The Shannon index was calculated using the phyloseq “plot_richness” function to find the alpha diversity of the sample groups, from which two-way ANOVA tests were performed to identify if the data statistically varied between treatment groups (significance level p≤.05). A post-hoc test further examined pairwise comparisons of the specific categories of samples for differences in alpha diversity. The ‘ggboxplot’ function of the ‘ggplot2’ R package (40) was used to visualize box plots of these data.

Beta diversity analyses was performed with the phyloseq package (‘ordinate’ function). Weighted and unweighted UniFrac distances were calculated from the phylogenetic tree of all sequences and ASV count tables and then plots from Principal Coordinate Analyses (PCoA) were simultaneously produced. Two- way PERMANOVA tests (‘adonis2’) identified if the independent variables of experimental treatments were associated with significant structural differences (significance level p≤.05) between the microbial communities.

On the basis of significant between-treatment PERMANOVA test results, the package ‘ALDEx2’ (41) was employed to test for significant differences in the relative abundances of populations between different treatment groups. Heatmaps of significant taxa contributing to the distinct structural

13 characteristics of different macrophytes and sample type groups were created. This analysis was used to compare all sequenced communities on the basis of different sample types, as well as to just comparisons between leaf samples from different macrophyte species.

Results

The overall quality of the 16S amplicon sequence data can be initially assessed by examining the retention rates of the reads during the cleaning process and the number of reads per sample after all processing steps were completed (Table 1). At the end of the quality control and dada2 sequence processing pipeline, 60.8% of the original reads remained. The average number of reads in a sample was found to be 9973. 76% of all sequenced libraries (71 of 94) contained sufficient high-quality prokaryotic reads (n ≥ 1000) after all quality control and initial sequence processing steps. Removal of eukaryotic reads (i.e., chloroplast and mitochondria) from libraries resulted in the largest reduction in reads from samples, accounting for ~25% of all originally sequenced reads.

The alpha diversity analysis shows a stark difference in the number of ASVs when comparing between sample types. Shannon diversity indices, which account for both evenness and richness, were significantly lower in gut content samples compared to the leaf and fecal samples (Table 2 & Figure 1). An overall difference in Shannon diversity was not found between samples based on macrophyte type alone (Table 2). Using post hoc statistical analysis, a difference was found between all three sample types (leaf-content: p=<.001, feces-content: p=<.001, feces-leaf: p=.00309). Post hoc analysis of sample pairings based on macrophyte type showed U. lactuca microbial communities to have significant differences in alpha- diversity compared to both L. saccharina (p=.038) and Z. marina (p=.004). Alpha-diversity of communities found on L. saccharina and Z. marina were not significantly different (p=.738).

The most prevalent taxa of the sample types, macrophyte types, and macrophyte leaves were identified and the abundances within the samples were examined (Supplementary Figure 1). When grouped by macrophyte type, Z. marina samples were most populated by Saccharospirillaceae, Alteromonadaceae, and Flavobacteriaceae; U. lactuca samples showed most abundance in Saccharospirillaceae, Colwelliaceae, and Vibrionaceae; and the most prevalent families within the L. saccharina communities were Pirellulaceae, Hyphomonadaceae, and Flavobacteriaceae (Supplementary Figure 1a). Further

14 investigations by consideration of just the leaf samples showed the most abundant three families, Saprospiraceae, Flavobacteriaceae, and Rhodobacteraceae, were the same for the Z. marina and U. lactuca leaf samples (Supplementary Figure 1b). There was much more variation in the most prevalent families when considering communities grouped by sample type. All three sample types had a unique set of most common families: leaf samples were most abundant in Flavobacteriaceae, Saprospiraceae, and Rhodobacteraceae, GIT content samples were dominated by Vibrionaceae, Cardiobacteriaceae, and Sulfurospirillaceae, and Colwelliaceae, Saccharospirillaceae, and Alteromonadaceae were most abundant in fecal samples.

In order to explore the differences in community structure between samples, beta diversity comparisons between sample pairs were made with the UNIFRAC metric and the resulting distance matrix relationships were visualized with Principal Coordinates Analysis (PCoA) plots (Figure 2, b-d). The PERMANOVA test produced results consistent with what was observed from the PCoA plots (Table 3). Sample type significantly impacted the structure of the microbial community (p=.001). For example, in Figure 2a, individual points representing each sequenced microbial community appear to be clustered by sample type and each cluster is separate from the other sample types. When divided out into plots showing only one macrophyte type per plot, again this grouping by sample type is apparent (Supplementary Figure 2). For microbial communities obtained from experiments with both U. lactuca and Z. Marina as the herbivore’s sole dietary source, differences based on sample type (i.e., Leaf vs. GIT content vs. Feces) were significant (p=.001). Poor sequencing of the L. saccharina GIT and fecal samples yielded no data on their microbial communities, and therefore precluded analyses on these samples.

When considering communities from each sample type separately, macrophyte type also was significantly correlated with microbial community structure. While this relationship is weaker than the differences based on sample type (Table 2, Figure 2a), individual PCoA plots of communities grouped by macrophyte type within a sample type reveal significant distinctions between communities found on leaves (p=.0002) and in feces (p=.006). Conversely, microbial communities of the herbivore GIT showed no significant difference. in structure based on which macrophyte was fed to the isopod (p=.386)(Figure 2, b-d).

Further investigation of the drivers of diversity differences between feces and leaves of the various macrophyte types and of the low diversity found exclusively in the GIT content samples revealed

15 significant relative abundance changes of specific taxa. Taxa with significant relative abundance differences between different sample types and between the different macrophytes are shown in the heatmap and hierarchical clustering plot of Figure 3. Four ASVs were found to be enriched in leaf samples relative to GIT contents and feces (Cluster I and II, Figure 3a), whereas ten ASVs showed the highest relative abundance in the fecal sample types (Cluster V, Figure 3a). Cluster III contains 11 ASVs generally found in both leaf and feces samples, with asv0018 and asv0029 being found more commonly in the leaves than feces, and with the remaining ASVs of cluster V being relatively more abundant in feces than leaves. Cluster IV of Figure 3a only contained two ASVs, which were the only ASVs that were relatively most abundant in the GIT content samples.

Given that significant differences were observed between the macrophyte microbial communities, differences in the relative abundances of specific ASVs based on each macrophyte type were also analyzed (Figure 3b). Cluster I consisted of eight ASVs all showing the highest relative abundances on Z. marina leaves (Figure 3b). Cluster III contained seven ASVs that were relatively most abundant on U. lactuca samples. asv0047 was the only ASV found to have significantly higher relative abundances on L. saccharina surfaces, although this taxon was also commonly found on U. lactuca. On the basis of the relative abundances of these ASVs, two samples were identified that may have been mislabeled after sample collection (“G58_marina_diet_d0” and “G92_laminaria_diet_d0”), as they show patterns that run contrary to their assigned macrophyte leaf type, and instead closely match the ASV relative abundance patterns of U. lactuca samples.

Discussion

This research examined variation in the taxonomic structure of microbiomes associated with marine macrophytes and isopods commonly found along the Oregon coast and tested the impact of different macrophytes and their microbiomes on herbivorous isopods and their respective microbiomes. Specifically, differences between microbial communities found on the surfaces of Z. marina (seagrass), U. lactuca (green algae), and L. saccharina (brown algae) were investigated. Additionally, feeding trial experiments were conducted using a common herbivorous isopod, P. resecata, and each macrophyte as the sole food source. These experiments were designed to test whether or not the taxonomic structure of the herbivore gastrointestinal tract (GIT) microbiome is altered by different macrophyte diets, and, if so,

16 whether the changes in microbial communities had structural or taxonomic similarities to the macrophyte microbiome consumed. This work also tested whether P. resecata maintains a distinct and specific gut microbiome that is separate from ingested bacteria, as previous investigations into this question for terrestrial and marine isopods have been mixed (17, 18, 33).

In this study, leaf microbiome samples were taken after being placed into the water with the isopod sample organisms. Due to macrophytes having distinct microbiomes in comparison to the seawater column microbes (8), we can be fairly confident that being placed in this new water did not impact the macrophyte microbiome. We found macrophyte microbiomes to be distinct from each other, despite residing in the same container for a week before sampling, which also supports the independence of the leaf microbiomes and the water column microbes, and the conclusion that the macrophyte microbiomes ingested varied by diet.

Notably, even with the aforementioned distinct macrophyte surface microbiomes, we found a stable and present microbial community in the GIT of P. resecata that did not change as a function of different diets. Most work on isopod microbiomes has focused on terrestrial isopods and the microbes found within the GIT. More specifically, this work focuses on the hepatopancreas, which is a midgut gland located between the foregut region and three hindgut regions (anterior chamber, papillate region, and rectum) (23, 42, 43). Although all regions of the terrestrial isopod GIT have been found to contain dense microbial biofilms, the hepatopancreas has been hypothesized to specifically house symbiotic bacterial populations in the isopod (42). Several studies have indicated that acquisition of these populations come horizontally from the environment, instead of vertically from sexual reproduction (28, 29). Although less research has been done on the microbes found in the foregut and hindgut regions, other crustaceans have been found to have the same microbial communities through their fore and hind gut with a unique hepatopancreas microbial community (44). Our work did not discriminate between these different GIT compartments. Thus, further work will be needed to investigate whether the specific microbes found here are localized to different compartments or found throughout the GIT.

Beyond whether GIT microbiomes change across the GIT of marine isopods, there is skepticism as to whether or not the marine isopods, like their terrestrial counterparts, even contain specific microbial symbionts within their GIT at all. Indeed, several studies have not found microbial communities within

17 marine isopods (17, 18, 27, 45, 46). Explanations for these results have varied, from suggesting the presence of either endogenous or exogenous antibiotics (46) to proposing that the environment within the isopod does not vary enough from the outside environment to create niches that would encourage colonization (45). In opposition to these results, there is also precedence for the detection of specific microbes in the GIT of marine isopods (19, 21), although a specific GIT microbiome has never been reported in P. resecata to the best of our knowledge.

Our work supports the findings of Mattila et al. (21) and Wenzel et al. (19) by showing that P. resecata do have a specific and authentic GIT microbiome, which is largely distinct from the microbes found on their diet. The taxa that are found most heavily in the GIT contents are also present in the feces, albeit at lower relative abundances, indicating that a community from the GIT may inoculate the material that is eventually expelled as fecal pellets. Importantly, these taxa were not represented in the leaf, further supporting this conclusion. The stability of the GIT microbiome may relate to the reliance of the isopod to make up the nitrogen deficit in its diet and the proposed role of the microbiome in providing some of this nitrogen (25). Future experiments testing whether the GIT-specific microbes found here have the capacity to provide fixed forms of nitrogen to the host using metagenomics or similar methods will be useful in defining potential host-microbiome interactions.

When investigating the taxa that were specific to the GIT content samples, only two prominent taxa were enriched in these samples, Vibrio and Cardiobacteriaceae. This small number of sequenced GIT content samples passing our filtering threshold prevented these samples from being further divided into macrophyte groups, which would help confirm the results found in the beta diversity analysis. Despite this limitation, there is precedence in the literature supporting the selection for these specific taxa in the GIT samples. Further, the pattern displayed (of ASVs being present in mainly the GIT, but also the feces) does not suggest contamination of extraneous DNA during the PCR amplification step, since we would expect samples other than the GIT content samples to be contaminated as well.

Vibrio has been found in many marine systems, and are commonly associated with different crustaceans (29, 47). In fact, many species within the Vibrionaceae are known to be associated with the guts of marine organisms leading this group to be dubbed the “enterics of the sea”, although this is likely an over- simplification (48). Further, intertidal isopod gastrointestinal tracts have also had previously reported

18 populations of Vibrios (19). Unfortunately, the limits of our ASV taxonomic assignments preclude direct comparison of the sequences of the Vibrio ASV we found to be enriched in the GIT content samples with those of other studies. Thus, further investigation confirming the specific taxonomic assignments of the Vibrios found in the GIT of P. resecata will be valuable in understanding any potential functional relationships these bacteria may have with their isopod hosts.

The other taxon significantly enriched in the GIT content samples was assigned to the Cardiobacteriaceae. Oddly, populations of this family are typically considered human respiratory pathogens. However, one study has documented that sequences of this taxon are present in marine environments and are even found specifically associated with lesions on crustaceans exhibiting signs of diet-induced shell disease (49).

Overall the finding of a specific P. resecata GIT microbiome that is different from the external environment and does not vary based on the differing diets fits within the general expectations that the herbivore gut is a selective environment on the basis of their feeding behaviors and nutritional needs. If the environment inside the isopod was similar to the external environment we would have seen differences in the microbial populations between diets within the GIT and would not have seen differences between the leaf and the content samples of the same macrophyte type. This is the opposite of the results found. We also can support the conclusion that the environment within the isopod is extremely selective because, despite the rich diversity found on the leaf, the GIT microbiome is homogenous and has considerably lower diversity.

An important caveat of our work is the lack of significant differences between the GIT contents samples from different diets may have resulted from the low power of the statistical models applied to a limited number of GIT samples. In this experiment DNA extractions from GIT content samples proved particularly difficult, often leading to poor DNA quality and/or no amplification of 16S genes. Samples from L. saccharina treatment group were particularly challenging to extract high quality DNA from. This is notable, as the GIT contents from isopods fed this diet were significantly different in overall appearance (texture, color, consistency) from those of isopods fed U. lactuca or Z. Marina (G. Hernán, personal communication). Additionally, the isopods from the L. saccharina treatment group were the only ones to demonstrate significant differences in morphometric traits by the end of the experiment (data not shown). These results indicate that there is likely a significant interaction between the L. saccharina diet, GIT

19 content, and P. resecata physiology that should be explored with additional experiments, and further refinement of DNA extraction methods from isopod GIT contents will be essential for the success of these experiments. Terrestrial isopods have been shown to have a heavier reliance on the sugar content in the diet than other compounds or nutrients, which may partially explain why the diet consisting of L. saccharina, or sugar kelp, led to the only morphological differences seen (50).

Interestingly, the selective nature of the internal environment may extend to the leaf microbes that are not specifically interacting with the host. This conclusion is supported by the finding of a redifferentiation of the microbes in the feces by macrophyte type. This is indicative of heavy selective pressures throughout the GIT that change the leaf-associated microbiome structure as a result of gut passage, whereby the relative abundances of taxa present on leaves change significantly once the digested material exits the system in the form of fecal pellets. Our results indicate the inoculation of the feces come from the ingested macrophyte leaves in addition to the contribution from the resident GIT microbes. The difference in population structures between the various macrophyte type feces could have been caused by a combination of factors, including the different inoculating populations, different selection factors, and the potential for additional colonization from the leaf or water column communities post excretion.

While we were not able to rule out this last factor as a possibility, it seems unlikely. Firstly, since the macrophyte leaf independently maintains a biome unique from the water column biome, the transferral of the microbes into the water from the leaf may be limited. With regard to the water column more generally, microbial growth on isopod fecal pellets does result in the release of microbes from the fecal pellet surface into the surrounding water, increasing the density of the microbes in the water column directly adjacent to these pellets, which may result in the feces being more likely to impact the water column than the macrophytes (5). Finally, since all of the isopods were in the same water (placed in individual perforated cups) any post excretion colonization from the water column would have most likely muted the observed differences between fecal pellets from the different macrophyte diets. More immediate collection after excretion would better clarify where the inoculation of the feces occurred, though.

The bacteria found in association with the different macrophyte leaves mostly agreed with previous characterizations of macrophyte microbiomes. Many of the taxa that the macrophyte-associated ASVs are commonly found in marine systems (51–53), and some, such as Ulvibacter (54–56) and Granulosicoccus

(57) are known associates with the macrophytes they were differentially enriched on (U. lactuca and Z. marina, respectively). Some taxa seemed to have biases towards a certain macrophyte, with several ASVs of the same taxonomic group being enriched in samples of the same macrophyte type. An example of this was seen with ASVs of Colwellia on the Z. Marina leaves. Conversely, multiple taxa were also found to have different ASVs enriched in samples of different macrophytes. These results are in apparent conflict with each other, but may be representative of divergent strain specialization for the more widely distributed taxa, whereas for taxa like Colwellia multiple ASVs of these groups may all specialize on the same macrophyte.

Conclusion

We can conclude from the results that there was no impact on the GIT microbes from the macrophyte diet they consumed. Additionally, the observed differentiation of the fecal microbiomes from the leaf surface microbiomes based on macrophyte type indicates a continuity of microbes in the diet that pass through the herbivore gut, whereby transient microbial communities are altered by the selective environment of the gut. The selective nature of the GIT environment is also reflected by the low alpha diversity found in the GIT content compared to the fecal and leaf samples. That is, the low diversity of these communities indicates that this environment has a highly homogeneous niche structure compared to the environment outside of the isopod.

These findings may have important implications on the relationship between diet, isopod physiology, and the potential function of the GIT microbiome. For instance, the nitrogen contents of macrophytes in an herbivore’s diet are known to be insufficient for the needs of the herbivore itself, and it has been proposed that a symbiotic microbiome is important in supplementing the nitrogen demands of the host (16, 25). Under this scenario, the existence of a stable microbiome may provide a useful and reliable source of nitrogen to the host in exchange for a stable environment and nutrition sources for the microbes, although further investigation will be needed to confirm these interactions. The importance of this proposed mechanism may be particularly relevant in comparisons of diet and physiology between isopods with a GIT microbiome and those that lack an authentic GIT microbiome. The stable GIT microbiome should be understood as an integral player in the nutrient cycling through marine ecosystems, due to its importance to the herbivore.

Acknowledgements

I would like to thank Hatfield Marine Science center for the use of their facilities in this project as well as the CGRB for sequencing. Additionally, I would like to recognize Dr. Gema Hernán; all of the data in this paper was a result of her previous work collecting and processing the samples, and therefore none of this analysis would have been possible without her. Finally, I are grateful for HMSC’s Mamie Markham Research Award and Fundacion la Ciaxa for funding, which was awarded to Michael Moses and Gema Hernán, respectively, to support experiments and travel related to this project. I would also like to acknowledge Jen Hayduk and Grant Swinge for help in collecting isopods and Alexis Morris and Christina Mauney for support in maintaining experiments.

Tables and Figures

Table 1: Sequence Quality Filtering and Processing Results Average reads Percent Reads Total reads per sample Remaining De-replicated Reads 1,165,093 12,395 100% Denoised Forward Reads 1,131,537 12,038 97% Denoised Reverse Reads 1,118,624 11,900 96% Merged Reads 1,002,624 10,667 86% Chimera Sequence Removal 1,000,771 10,647 86% Eukaryotic Sequence Removal 714,852 7,605 61% Removal of Poorly Sequenced Samples* 708,082 9,973 61%

*Poorly sequenced samples are those with < 1000 reads after all quality filtering and initial processing steps were completed.

Table 2: Two-way ANOVA of Shannon diversity indices.

Df Sum Sq Mean Sq F value Pr(>F)

Sample type 2 89.71 44.86 147.36 0 Macrophyte type 2 1.15 0.58 1.89 0.1648 Residuals 37 11.26 0.3

Table 3: Two-way PERMANOVA of microbiome community structure data

Df Sum Of Sqs R2 F Pr(>F) Sample type 2 0.02 0.51 22.61 0.001 Macrophyte type 2 0 0.05 2.29 0.02 Sample type : Macrophyte 2 0 0.04 1.9 0.07 Residual 35 0.01 0.4 Total 41 0.03 1

Alpha Diversity 5

4 Diet 3 L. saccharina 2 Z. marina U. lactuca

Shannon Index 1

0 GIT Content Leaf Feces Sample Type

Figure 1: Average Shannon diversity indices of communities from different samples. Samples in each boxplot are grouped by sample type (“GIT content”, “Leaf”, and “Feces”) and further broken down by colored boxes representing different macrophyte types fed to isopods (“Diet”). The average number of ASVs per sample varied greatly: leaf samples averaged 147, content 7 ASVs, feces 150 ASVs, Z. marina 113 ASVs, L. saccharina 95 ASVs, and U. lactuca 105 ASVs.

Herbivore Microbiome MacrophyteHerbivore Microbiome Leaf Microbiome 0.02 Macrophyte Type Macrophyte Type L. saccharina SampleL. saccharina Type 0.02 0.01Z.0.02 marina dietZ. marina

U. lactuca U. lactuca

Macrophyte Type 0.00 0.00 Sample0.00 Type Samplelaminaria Type

[14.3%] Axis.2 Axis.2 [14.3%] Axis.2 Axis.2 [22.2%] Axis.2 GIT Content marinaGIT Content

Leaf ulvaLeaf −0.01 Feces Feces −0.02 −0.02

a. −0.02 0.00 0.02 c. −0.01−0.02 0.00 0.00 0.01 0.02 Axis.1 [45.8%] Axis.1Axis.1 [27.7%][45.8%]

HerbivoreHerbivore GIT GIT Contents Contents Microbiome Microbiome Herbivore Fecal Microbiome 0.010

0.100.10

0.005 Sample Type feces 0.050.05 MacrophyteMacrophyte Type Type marina0.000marina Macrophyte Type ulvaulva 0.000.00 marina Axis.2 [37.3%] Axis.2 Axis.2 [37.3%] Axis.2 Axis.2 [18.7%] Axis.2 −0.005 ulva

− 0.05−0.05 −0.010 0.000.00 0.050.05 −0.01 0.00 0.01 b. Axis.1Axis.1 [47.6%] [47.6%] d. Axis.1 [71.3%]

Figure 2. Structural differences in microbial communities. Beta diversity plots showing similarities and differences of the microbial community structure based on sample type. The different colored dots represent different macrophytes. (a) The plot “Herbivore Microbiome” illustrates the structural differences both based on sample type (color) and macrophyte type (shape). (b) “Herbivore GIT Content Microbiome” displays the GIT content samples with color distinctions based on macrophyte type. (c) “Herbivore Fecal

Microbiome” illustrates the characteristics of the microbial communities in the fecal samples with respect to the macrophyte diet isopods were fed. (d) “Macrophyte Leaf Microbiome” shows the relationship of the microbiomes on three different leaf types. Patterns were largely replicated with unweighted UNIFRAC values (see supplementary figure 3).

Sample Type GIT content leaf feces

Figure 3: Heatmaps of relative abundance values for ASVs with significant abundance differences between treatment groups. ASVs are listed along the X-axis in columns and individual samples are listed along the Y-axis in rows. Heatmap color intensity represents a log10-transformation of sequence counts for a given ASV in a given sample. ASVs with similar abundance profiles across samples (i.e., individual columns) are grouped by hierarchical clustering (top), and clusters of ASVs with the same relative abundance patterns are noted. (a) ASVs with significant relative abundance differences between communities from different sample types (Leaf, GIT content, and Feces) are shown. The hierarchical

Macrophyte Type U. lactuca Z. marina L. saccharina

clustering cladogram was divided into five main clades on the basis of cladogram depth and individual clusters are labeled I-V at the top of the display. (b) ASVs with significant relative abundance differences between surfaces of different macrophytes prior to their use as a food source in herbivore feeding experiments. The hierarchical clustering cladogram was divided into three main clades on the basis of cladogram depth and individual clusters are labeled I-III at the top of the display.

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Supplementary Information

Supplemental Methods (from G. Hernán, T. Gustafson, F. Tomas Nash, R. S. Mueller, in prep.)

Sample Collection

Similar sized male isopods of the species Pentidotea resecata were collected from Netarts Bay (OR) and transported to the Hatfield Marine Science Center into a seawater container with an oxygenizer and plant material from the site in order to reduce stress. Zostera marina, Laminaria saccharina, and Ulva lactuca were collected weekly from Yaquina bay (OR) and transported to the Hatfield Marine Science Center into a seawater container. In the Hatfield Marine Science Center algae and seagrasses were kept in tanks with seawater flow-through system.

Feeding Experiment and Fitness Assessment

All feeding experiments were performed in an outdoor seawater flow-through system (i.e., ambient seawater conditions) and under natural light conditions. Isopods were maintained in perforated plastic cups (13 cm diameter x 6 cm height) with lids and fed for 31 days with a monospecific diet of L.

33 saccharina, U. lactuca or Z. marina clean of epiphytes. During this period we assessed the herbivore growth rate (i.e., length and weight), feeding rate (i.e., g. of tissue consumed per day) and survival. Fecal pellets, plant and algae tissue and the gut of the isopods were collected to characterize GIT microbiome community structure.

At the beginning of the diet experiment all isopods were weighed and measured from the head to the end of the body in the middle of the telson. Five isopods were weighed, measured and dissected at the beginning of the experiment and after 1, 2, 4, 8, 17, 19, 23 and 31 days. Weight and length change was calculated as final measurement minus initial measurement. Together with the dissected tissue we also collected fecal pellets and leftover algae or seagrass tissue from the container where the isopod was being kept.

The feeding rate experiments consisted of 10-12 replicates and were performed during 24-48h after 3, 9, 15 and 22 days, and each time with different isopods. We also performed a 3-choice feeding experiment with isopods that were previously acclimated during 24h at starvation. The experiments consisted of 22 replicates and ended when approximately 50% of initial material was consumed. Consumption was calculated as leaf biomass eaten of each tissue relative to the total amount of leaf biomass eaten in the assay. To measure any potential changes in leaf tissue not related to grazing, control 3 cups, the same type as the experimental ones but without herbivores, were used to correct for autogenic changes in biomass prior to the statistical analyses.

Dissection of Tissues

For dissection anesthetized isopods were introduced in subsequent baths for 30 seconds and vigorously shaken in order to sterilize the isopod following a protocol form (1). The baths were performed in 50 mL tubes containing in the following order absolute ethanol, undiluted commercial bleach (6% sodium hypochlorite) and sterilized 1X phosphate buffered saline (PBS; diluted from 10X PBS pH 7.4).

DNA Extraction and Sequencing of Microbiome Samples

Microbial community from fecal pellets, leftover algae and seagrass tissue and microbial communities from the GIT were extracted following established protocol by (2). PCR amplification and DNA sequencing was performed following established protocols (2). 16S rRNA genes were PCR-amplified using barcoded PCR primers targeting the V4 region of 16S rRNA genes. PCR products were combined in equimolar quantities and sequenced. 16S gene amplicons were sequenced with the Illumina MiSeq sequencing platform (Oregon State University Center for Genome Research and Biocomputing core facility).

Supplemental Methods References

1. Ceja-Navarro JA, Brodie EL, Vega FE. 2012. A technique to dissect the alimentary canal of the coffee berry borer (Hypothenemus hampei ), with isolation of internal microorganisms. J Entomol Acarol Res 44:e21–e21.

2. Metagenome Sequencing of a Coastal Marine Microbial Community from Monterey Bay, California | Microbiology Resource Announcements.

Prevalent Families found within each Macrophyte Type Families with fewer than 200 reads Vibrionaceae 100% Sulfurospirillaceae Sphingomonadaceae 90% Saprospiraceae 80% Saccharospirillaceae Rhodobacteraceae 70% Pseudomonadaceae 60% Pseudoalteromonadaceae Pirellulaceae 50% Oleiphilaceae NA 40% Methylophilaceae 30% Marinomonadaceae Hyphomonadaceae 20% Flavobacteriaceae 10% Entomoplasmatales_Incertae_Sedis Relative abundance of Taxanomic Families Colwelliaceae 0% Cardiobacteriaceae Z. marina L. saccharina U. lactuca Alteromonadaceae a. All Samples grouped by Macrophyte Type Prevalent Families within Macrophyte Leaf Samples Familes with fewer than 100 reads 100% Tenderiaceae 90% Sphingomonadaceae Ectothiorhodospiraceae 80% Cellvibrionaceae Saprospiraceae 70% Psychromonadaceae 60% Thiohalorhabdaceae Hyphomonadaceae 50% Methylophilaceae Rubritaleaceae 40% Flavobacteriaceae 30% NA Pirellulaceae 20% Rhodobacteraceae Pseudoalteromonadaceae

Relative Abundance of Taxanomic Families 10% Saccharospirillaceae 0% Colwelliaceae Z. marina L. saccharina U. lactuca Alteromonadaceae b. Leaf Samples shown by Macophyte type

Prevalent Families found across Sample Types 100% Families with fewer than than 500 reads Vibrionaceae 90% Sulfurospirillaceae Saprospiraceae 80% Saccharospirillaceae Rubritaleaceae 70% Rhodobacteraceae 60% Psychromonadaceae Pseudoalteromonadaceae 50% Pirellulaceae Oleiphilaceae 40% Nitrincolaceae NA 30% Marinomonadaceae Relative abundance of Families 20% Flavobacteriaceae Cryomorphaceae 10% Colwelliaceae Cardiobacteriaceae 0% Alteromonadaceae c. Leaf Content Feces

Supplementary Figure 1. Most abundant families present in macrophyte types, macrophyte leaves and sample types. These graphs show the percent each taxonomic family makes of the average sample. Families that were not prevalent enough to be viewed without difficulty if distinguished on the graph were all summed into a group labeled “Families with fewer than [n] reads”. The number of reads (n) used to filter for the purposes of these graphs varied due to legibility and was selected to keep the number of families near 20 for each graph. All legends are listed in the order displayed (from top to bottom) in each bar of the chart. (a.) The top graph displays all the samples divided by macrophyte type and shows families with more than 200 reads. (b.) The graph names “Prevalent Families within Macrophyte Leaf Samples” shows only the leaf samples broken down by macrophyte type. Since there were only leaf samples for l. saccharina, the middle bar is the same for the first two graphs of this figure (a. & b.). All families labeled in this graph contained more than 100 reads. (c.) The last graph in this figure again represents all the samples but here divided by sample type. All families labeled in this graph had at least 500 reads.

Z. marina Diet Isopod Microbiome Herbivore Microbiome U. lactuca Diet Microbiome Z. marina Diet Isopod Microbiome

Macrophyte Type 0.04 0.010.01 Macrophyte Type L. saccharina MacrophyteMacrophyte Type Type ulva 0.02 Z. marina marinamarina U. lactuca 0.02 0.000.00 Sample Type SampleSample Types Types content 0.00 Sample Type contentcontent Axis.2 [11.5%] Axis.2 Axis.2 [11.5%] Axis.2 Axis.2 [16.3%] Axis.2 0.00 −0.01diet

Axis.2 [14.3%] Axis.2 −0.01 GIT Content dietdiet feces Leaf Feces −0.02 −0.02 −0.03 −0.02 −0.01 0.00 0.01 0.02 −−0.030.03 −−0.020.02 −−0.010.01 0.000.00 0.010.01 0.020.02 −0.02 0.00 0.02 a. b. Axis.1Axis.1 [56.5%] [56.5%] Axis.1 [45.8%] Axis.1 [48.3%]

Supplementary Figure 2. Structural differences in microbial communities between sample types. These beta diversity plots demonstrate the structural similarities and differences in the microbial communities between different sample types. (a) This plot demonstrates the community differences between all samples of the U. lactuca macrophyte type, showing the groups based on sample types (leaf, GIT content, and feces). (b) All samples of the Z. marina macrophyte type with structural relationships between sample types (leaf, GIT content, and feces) are visually represented here.

Herbivore Microbiome Herbivore Microbiome Macrophyte Leaf Microbiome Macrophyte Type Macrophyte Type 0.2 L. saccharina SampleL. saccharina Type

0.02Z. marina Z.diet marina 0.0 0.1 U. lactuca U. lactuca 0.0 Macrophyte Type 0.00 Sample Type −0.2 Sample Type laminaria

[14.3%] Axis.2 −0.1 GIT Content Axis.2 [9.4%] Axis.2 Axis.2 [11.4%] Axis.2 GIT Content marina Leaf Leaf ulva Feces −0.4 −0.02−0.2 Feces

a. −0.4 −0.2 0.0 0.2 c. −0.02−0.2 0.000.0 0.20.02 Axis.1 [38.6%] Axis.1Axis.1 [45.8%] [21%]

HerbivoreHerbivore GIT Contents GIT Contents Microbiome Microbiome Herbivore Fecal Microbiome

0.10 0.2 Sample_Type Sample Type 0.2 content feces 0.1 0.05 Macrophyte Type

marina 0.0 Macrophyte0.0 Type Macrophyte Type ulva marina marina Axis.2 [28.1%] Axis.2 0.00 [15.3%] Axis.2 Axis.2 [37.3%] Axis.2 −0.1ulva ulva −0.2

−0.4 −0.2 0.0 0.2 −0.4 −0.2 0.0 0.2 0.4 − 0.05 Axis.1 [30.8%] Axis.1 [67.8%] b. 0.00 0.05 d. Axis.1 [47.6%]

Supplementary Figure 3: Unweighted UNIFRAC beta diversity plots show very similar structural differences seen by weighted plots (see Figure 2). As demonstrated by the legend, color represents macrophyt e type and shape represents sample type. Differences in community structure are represented by distance on the graph and similarities by close proximity. (a) Community structure differences between all types of samples and macrophytes are seen in the “Herbivore Microbiome” plot. (b) The two macrophyte type community structures within the GIT content samples are compared in the “Herbivore GIT Contents Microbiome” plot. (c) The microbial structures of the three macrophyte leaf sample types

39 are showing in “Macrophyte Leaf Microbiome”. (d) In the “Herbivore Fecal Microbiome” plot, the fecal microbial communities are show divided by the two macrophyte types.