The freshwater cnidarian Hydra coexists with a rich diversity of host-associated microbes. These microbes colonize external epithelial surfaces (Fraune et al. (2015) Deines and Bosch (2016)), inhabit intercellular spaces (Rathje et al. (2020)), and in some species can even occur inside cells as endosymbionts (Fraune and Bosch (2007)). The Hydra microbiota has diverse effects on the host. Animals with their microbiota experimentally removed have reduced movement and contractility (Murillo-Rincon et al. (2017)) and impaired ability to reproduce asexually (Rahat and Dimentman (1982)). Interactions between microbial components influence pattern formation (Taubenheim et al. (2020)), and can induce tumor development (Rathje et al. (2020)), but the presence of core microbial elements also protects the host against fungal infections (Fraune et al. (2015)).

Hydra polyps actively shape the composition of their associated bacterial community through the secretion of antimicrobial peptides (Fraune et al. (2010), S. Franzenburg et al. (2013), Augustin et al. (2017)). As a result, laboratory maintained Hydra species differ in the bacterial community (S. Franzenburg et al. (2013)), and show long-term association with the host, partly reflecting differences observed in their natural habitats (Fraune and Bosch (2007)). Furthermore, components of the microbiota are at least partly transmitted vertically to embryos through a process controlled by maternal antimicrobial peptides (Fraune et al. (2010), Franzenburg et al. (2013)), providing an opportunity for coevolution between host physiology and microbial diversity. However, factors driving variation in the microbial composition and diversity of natural Hydra populations remained so far unexplained.

In a current study we aimed to understand the factors that shape bacterial diversity in natural Hydra populations. To this end, we collected Hydra polyps belonging to three different co-existing species (H. oligactis, H. vulgaris and H. circumcincta) from 21 Central European locations. We asked whether bacterial diversity in Hydra is affected by 1) sampling population ID, 2) water body type 3) nutrient load of sampling population, 4) host species, and 5) host reproductive state. In line with previous studies (e.g. Fraune and Bosch (2007)) we predicted that the three Hydra species will be associated with distinct microbial communities and were interested in finding out how consistent these species differences are across a range of distinct populations. Furthermore, we hypothesized that the type of habitat could influence the microbial diversity from which host-associated microbial communities are assembled and therefore recorded, for each location, whether it was standing or flowing water and categorized them in terms of nutrient load: meso-eutrophic, eutrophic or hyper-eutrophic. Finally, we hypothesized that life history stage of the host (specifically, whether it was reproducing sexually or asexually) can affect the diversity of microbial taxa associated with the host because of the altered physiology associated with sexual reproduction. In at least one of the three species (H. oligactis), sexual reproduction is associated with marked reductions in somatic maintenance functions, including loss of regeneration ability, stem cell depletion and disappearance of nematocytes (stinging cells) important for food capture (Sebestyén, Barta, and Tökölyi (2018)), and these physiological changes could also affect the ability to regulate host-associated microbes.

We found that the sampling site (population) has the strongest effect on α-and β-diversity, followed by the type of the water body, while the host factors (species and reproduction mode) had a much weaker, but consistent effect on the bacterial diversities. The results showed that environmental factors were most strongly associated with changes in the microbial community while the bacterial communities still specifically reflect the host species.

The aim of this small project is the evaluation of the metabolic capabilities of wild type Hydra bacteria using picrust2 (Douglas et al. (2020)) and comparing the results to the bacterial diversity.

In this repository you will find a data/ directory which contains following files:

• A fasta file for the 16S sequences for each ESV of the study
• A table with taxonomic annotations for the different 16S sequences
• A matrix containing the raw read counts for each sample (columns) and ESV (rows)
• An annotation file for each sample (what species, sampling site etc.)

1. Use the data to predict enzymatic activity of each ESV using picrust2
   1. Predict KEGG, NOG and EC numbers for each ESV
   2. Keep intermediate files for reproducibility
   3. Determine the number of ESVs where no prediction could be made per sample. Think of a good way to plot these numbers, once weighted and unweighted by ESV abundance
2. Predict pathway abundances per sample using picrust2
3. Analyse α- and β-diversity measures (Shannon and Bray-Curtis) for the Pathway abundances
   1. Create boxplots showing differences in Shannon diversity for Species, Sampling Site (PopID), Nutritional level of the water body and water body type.
   2. Calculate PC-Analysis on the β-diversity measures, plot the first 3 principal components in scatter plots against each other. Create versions of the plot where the color of the dots indicate Species, Sampling Site (PopID), Nutritional level of the water body and water body type.
4. Keep track and comment on all analysis steps for reproducibility

Help can be found by contacting us on the slack channel.

Here some hints for performing the analysis:

picrust2 is used for metabolic function prediction from 16S data. For the original publication see here: Langille et al. (2013) and Douglas et al. (2020)

For data analysis we usually refer to R. Specifically here are some packages to have a look at

• data.table for data manipulation
• ggplot2 for plotting
• vegan for basic ecological analysis
• phyloseq for advanced ecological analysis - specialized to 16S sequencing data

Augustin, René, Katja Schröder, Andrea P. Murillo Rincón, Sebastian Fraune, Friederike Anton-Erxleben, Eva-Maria Herbst, Jörg Wittlieb, et al. 2017. “A Secreted Antibacterial Neuropeptide Shapes the Microbiome of Hydra.” Nature Communications 8 (1): 698. https://doi.org/10.1038/s41467-017-00625-1.

Deines, Peter, and Thomas C. G. Bosch. 2016. “Transitioning from Microbiome Composition to Microbial Community Interactions: The Potential of the Metaorganism Hydra as an Experimental Model.” Frontiers in Microbiology 7 (October). https://doi.org/10.3389/fmicb.2016.01610.

Douglas, Gavin M., Vincent J. Maffei, Jesse R. Zaneveld, Svetlana N. Yurgel, James R. Brown, Christopher M. Taylor, Curtis Huttenhower, and Morgan G. I. Langille. 2020. “PICRUSt2 for Prediction of Metagenome Functions.” Nature Biotechnology 38 (6): 685–88. https://doi.org/10.1038/s41587-020-0548-6.

Franzenburg, Sören, Sebastian Fraune, Philipp M Altrock, Sven Künzel, John F Baines, Arne Traulsen, and Thomas CG Bosch. 2013. “Bacterial Colonization of Hydra Hatchlings Follows a Robust Temporal Pattern.” The ISME Journal 7 (4): 781–90. https://doi.org/10.1038/ismej.2012.156.

Franzenburg, S., J. Walter, S. Kunzel, J. Wang, J. F. Baines, T. C. G. Bosch, and S. Fraune. 2013. “Distinct Antimicrobial Peptide Expression Determines Host Species-Specific Bacterial Associations.” Proceedings of the National Academy of Sciences 110 (39): E3730–E3738. https://doi.org/10.1073/pnas.1304960110.

Fraune, S., R. Augustin, F. Anton-Erxleben, J. Wittlieb, C. Gelhaus, V. B. Klimovich, M. P. Samoilovich, and T. C. G. Bosch. 2010. “In an Early Branching Metazoan, Bacterial Colonization of the Embryo Is Controlled by Maternal Antimicrobial Peptides.” Proceedings of the National Academy of Sciences 107 (42): 18067–72. https://doi.org/10.1073/pnas.1008573107.

Fraune, S., and T. C. G. Bosch. 2007. “Long-Term Maintenance of Species-Specific Bacterial Microbiota in the Basal Metazoan Hydra.” Proceedings of the National Academy of Sciences 104 (32): 13146–51. https://doi.org/10.1073/pnas.0703375104.

Fraune, Sebastian, Friederike Anton-Erxleben, René Augustin, Sören Franzenburg, Mirjam Knop, Katja Schröder, Doris Willoweit-Ohl, and Thomas CG Bosch. 2015. “BacteriaBacteria Interactions Within the Microbiota of the Ancestral Metazoan Hydra Contribute to Fungal Resistance.” The ISME Journal 9 (7): 1543–56. https://doi.org/10.1038/ismej.2014.239.

Langille, Morgan G I, Jesse Zaneveld, J Gregory Caporaso, Daniel McDonald, Dan Knights, Joshua A Reyes, Jose C Clemente, et al. 2013. “Predictive Functional Profiling of Microbial Communities Using 16S rRNA Marker Gene Sequences.” Nature Biotechnology 31 (9): 814–21. https://doi.org/10.1038/nbt.2676.

Murillo-Rincon, Andrea P., Alexander Klimovich, Eileen Pemöller, Jan Taubenheim, Benedikt Mortzfeld, René Augustin, and Thomas C. G. Bosch. 2017. “Spontaneous Body Contractions Are Modulated by the Microbiome of Hydra.” Scientific Reports 7 (1): 15937. https://doi.org/10.1038/s41598-017-16191-x.

Rahat, M., and Ch. Dimentman. 1982. “Cultivation of Bacteria-Free Hydra Viridis : Missing Budding Factor in Nonsymbiotic Hydra.” Science 216 (4541): 67–68. https://doi.org/10.1126/science.7063873.

Rathje, Kai, Benedikt Mortzfeld, Marc P. Hoeppner, Jan Taubenheim, Thomas C. G. Bosch, and Alexander Klimovich. 2020. “Dynamic Interactions Within the Host-Associated Microbiota Cause Tumor Formation in the Basal Metazoan Hydra.” Edited by Fanxiu Zhu. PLOS Pathogens 16 (3): e1008375. https://doi.org/10.1371/journal.ppat.1008375.

Sebestyén, Flóra, Zoltán Barta, and Jácint Tökölyi. 2018. “Reproductive Mode, Stem Cells and Regeneration in a Freshwater Cnidarian with Postreproductive Senescence.” Edited by David Reznick. Functional Ecology 32 (11): 2497–2508. https://doi.org/10.1111/1365-2435.13189.

Taubenheim, Jan, Doris Willoweit-Ohl, Mirjam Knop, Sören Franzenburg, Jinru He, Thomas C. G. Bosch, and Sebastian Fraune. 2020. “Bacteria- and Temperature-Regulated Peptides Modulate β-Catenin Signaling in Hydra.” Proceedings of the National Academy of Sciences 117 (35): 21459–68. https://doi.org/10.1073/pnas.2010945117.