Earthworm Microbiomes

The earthworm microbiome and its role in enabling host fitness and plasticity

  • PI: Dr Peter Kille (PK) School of Biosciences, Cardiff University
  • CoIs: Prof. Andrew Weightman – School of Biosciences, Cardiff University
    Prof. Dawn Field – Centre for Ecology and Hydrology, Wallingford
  • Advisory Team: Prof. A. John Morgan, A. Gray, R. White – Cardiff University
    Dr. David Spurgeon, NEBC and NBAF – Centre for Ecology and Hydrology,Wallingford
  • Student: Daniel Pass

Background

Earthworms are the single largest contributors to the soil invertebrate biomass in many ecosystems and have long been recognized for the benefits they bring to the environment. Important functions of earthworms include processes such as soil aeration, bioturbation and organic matter fragmentation that are vital for promoting soil structural development and nutrient cycling [1,2]. As soil organisms, earthworms are in intimate contact with changing soil chemistries and bio-available pollutants. It is essential to understand how these soil organisms adapt, in terms of both physiology and evolution, to these highly variable environments [3]. The earthworm plays host to a number of discrete bacterial communities acquired either horizontally from the surrounding soil, as with the gut fauna [4], or through vertical parental transmission, as observed for the nephridial symbiotes [5]. The earthworm gut microfauna exists within a discrete anaerobic environment and plays host to organisms containing unique suites of nitrogen fixing bacteria transforming the chemistry of the soil as it traverses the gut [4]. We will test the overarching hypothesis that “Earthworm microbiomes contribute directly to the host’s phenotypic plasticity” by use metagenomic analyses to determine the role played by these bacterial microbiomes in the ability of the earthworm to adapt to the extreme ranges of soil chemistry, both natural and anthroprogenic.

Objectives

The overall aim of the project will be to determine the mechanistic contribution played by the earthworm microbiome to the host ecology and plasticity by achieving the following objectives:

      1. To informatically profile the phylogenetic composition and transcriptional activity of the microbiomes (gut and nephridial) in genetically homogeneous populations of earthworms resident on soil of contrasting chemistry (heavy metals and pH).
      2. To derive the relationship between host genotype and microbiome phylogeny overlaid with function metagenomic analysis.
      3. To determine the fitness of earthworms hosting microbiomes transplanted from hosts resident on contrasting soil chemistry (heavy metals and pH).
      4. To describe and evaluate the changes in the earthworm microbiomes occurring when hosts are transplanted into soils with chemistries contrasting with their resident habitat.
      5. To determine whether mobile genetic elements (mobilome) within the earthworm microbiome facilitate viability within host resident to extreme soil environments.

Approach

We will exploit next-generation sequencing (NGS) to evaluate the structure and composition of the earthworm microbiome ultimately determining its contribution of host health and contribution to phenotypic plasticity.  Three specific approaches will be adopted to profile the microbiome, either non-targeted characterization of sequences derived from bacterial genome [6], transcriptome [7], or targeted amplification and sequencing of the 16S rRNA bacterial ‘bar code’ [8]. The relation between these various dimensions of genomic data will be integrated with the host genotype and soil geochemistry within a relational data structure allowing interrogative data mining to reveal discriminatory microbome profiles related to soil chemistry (Obj. i) or host genotype (Obj. ii).  One aspect of this analysis will require establishing an informatics pipeline for analyzing community-level NGS data allowing the generation of specific community diversity metrics, including species richness and diversity indices, and relate the sequences generated to relevant taxonomic catalogue from the Ribosomal  Database Project (RDP). The project will also benefit from the supervisory teams involvement with other, taxonomically more narrowly based metagenomic analysis pipelines such as VAMPS (GAST) [9], CAMERA [10], MG-RAST [11]. The project will also utilize QIIME, which a wraps commonly used algorithmic approaches used to analyses metagenomics to facilitates quantitative insights into microbial ecology [12], collaborating with the developing team. The project will also look to integrate its observations with the on-going terragenome project (http://www.terragenome.org) with a specific focus on determining whether there is a specific “transcriptional activation” of genes/pathways during earthworm gut transit. The group will link with Dr Shena Davidson who has characterized specific horizontally transmitted nephridial symbiotes [5] and optimized methodologies used for generating “sterile” earthworms and performing cocoon based re-inoculation (Obj. iii). Earthworm demographic models, developed by members of the advisory team [Spurgeon,] will be populated using earthworms with defined microbiome cultures on various soil types to determine the relationship between bacterial communities and host fitness (Obj. iv). Both informatics and experimental approaches will investigate the role played by mobile genetic elements in the adaptation of the earthworm symbiotic bacterial populations to soil chemistry and the consequential plasticity of the host (Obj. v)

Supervisory and Advisory Team

Primary supervision at each institution will be provided by Peter Kille (PK – Cardiff University) and Dawn Field (DF – CEH) with Prof. Andrew Weightman providing secondary supervisory support (AW – Cardiff). PK has graduated 23 PhD students, the majority of which have been co-supervised, 4 of which with DS at CEH as a partner and 2 with Professor Gray (AG) in Computer Science, a track record that attests to his experience and ability to balance the demands of providing an appropriate training environment for a studentship in a interdisciplinary and multi-institutional project. Dr Dawn Field, of Centre for Ecology and Hydrogy (Wallingford), who is Director of the bioinformics node of the NERC Biomolecular Analysis Facility (NBAF) as well as managing a vibrant molecular evolution and bioinformatics research group that undertakes metagenomics research.  The informatics outputs of this project will ensure NBAF is embedded with the cutting-edge of metagenomics and biodiversity research. AJW is a molecular microbiologist and has successfully supervised 24 PhD students; he has directed bioinformatic projects leading to the development of tools for the analysis of 16S rRNA (e.g. Pintail programme now used by the RDP) and metagenomic gene sequences. An extended advisory team will include Professor Alex Gray and Dr Richard White (School of Computer Science, Cardiff University), Professor A. John Morgan (Cardiff School of Biosciences), the NERC Bioinformtics Analysis Facility/NERC Environmental Bioinformatic Centre (CEH Wallingford) and Drs David Spurgeon (DS) (CEH Wallingford). This extended advisory team each bring complementary skills ranging from database interoperability to earthworm ecology and population modeling.

Training Environment

The student will have access to the computation and support facilities at both Cardiff University and CEH including the supercompting facility based at Advanced Research Computing @ Cardiff (ACCRA). Day-to-day supervision will be provided by PK, AW and DF and the student will be expect to comply with the official graduate training program of the School of Biosciences which will aid his personnel development, monitor his progress and ensure the quality of his research output and supervision.  Bi-annual advisory group meetings and will provide a forum at which the student can benefit from the wealth of experience and interest of the extended advisory group. The studentship will be associated with the Division of Organisms and the Environment (OnE) working within the Genomes Diversity and Adaptation area lead by Dr Peter Kille.

[1] Darwin, C. (1883) The formation of vegetable mould through the action of earthworms, London, John Murray.

[2] Heemsbergen, D. A., et al. (2004) Science, 306, 1019-20.

[3] Edwards, C. A. (Ed.) (2004) Earthworm Ecology, Baton Rouge, CRC Press

[4] Drake, H.L., and Horn, M.A. (2007) As the worm turns: The earthworm gut as a transient habitat for soil microbial biomes. Annual Review of Microbiology 61: 169-189.

[5] Davidson, S.K., and Stahl, D.A. (2006) Transmission of nephridial bacteria of the earthworm Eisenia fetida. Applied and Environmental Microbiology 72: 769-775.

[6] Shaw, A. K., Halpern, A. L., Beeson, K., Tran, B., Venter, J. C., Martiny, J. B. (2008) It’s all relative: ranking the diversity of aquatic bacterial communities. Environ Microbiol. 2008 Sep 10; 10(9): 2200-10.

[7] Gilbert, J.A., Field, D., Huang, Y., Edwards, R., Li, W., Gilna, P. and Joint, I. (2008) Detection of Large Numbers of Novel Sequences in the Metatranscriptomes of Complex Marine Microbial Communities. PLoS ONE 3(8): e3042

[8] Dethlefsen, L., Huse, S.,  Sogin, M.L. and Relman, D.A. (2008) The Pervasive Effects of an Antibiotic on the Human Gut Microbiota, as Revealed by Deep 16S rRNA Sequencing. PLoS Biol 6(11): e280.

[9] Huse, S.M., L. Dethlefsen, J.A. Huber, D. Mark Welch, D.A. Relman, M.L. Sogin (2008).  Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing. PLoS Genetics.4(11): e1000255

[10] Seshadri, R., Kravitz, S.A., Smarr, L., Gilna, P. and Frazier, M. (2007) CAMERA: A Community Resource for Metagenomics. PLoS Biol 5(3): e75.

[11] Meyer, F., Paarmann, D., D’Souza, M., Olson, R., Glass, E.M., Kubal, M., Paczian, T., Rodriguez, A., Stevens, R., Wilke, A., Wilkening, J. and Edwards, R.A. (2008) The Metagenomics RAST server – A public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9:386.

[12] Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R. (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010 May;7(5):335-6.