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Environmental microbiomes

The metagenomics approach is rapidly transitioning into a mainstream tool in microbial ecology.

Metagenomics-Waiwera River

However, there is a need for approaches to reconstruct and analyse challenging mixtures of prokaryotic (bacterial and archaeal) community sequence data along with the genomes of other understudied organisms (viruses and microeukaryotes). The Environmental Microbiomes project looks to meet this need by providing clear methods and guidelines.

The Environmental Microbiomes project encompasses three work streams:

  1. Virome
  2. Microorganisms and microbial strain heterogeneity
  3. Microeukaryotes (tiny multicellular organisms).

The project will develop best practice guidelines for DNA and RNA virome analysis using metagenomic and metatranscriptomic data. This work capitalises on aquatic sequence data and virus genomes generated from the Environmental Metagenomics project. Additionally, two model systems will be used to explore environmental microbial strain heterogeneity to improve genome assemblies and assess ecological distributions and functions. Finally, a protocol will be developed to generate and analyse microeukaryote chromosomal and organelle genomes from metagenomic data.

The project aligns with key objectives for Genomics Aotearoa capability building and advanced genomics research, through the contribution of step-by-step workflows and hands-on-training, and research at the leading edge of microbial ecology.

Outcomes

  • Provide step-by-step guidelines in virome genome identification and annotation on github. 
  • Provide methods for recovering challenging prokaryotic genomes on github. 
  • Provision of step-by-step guidelines in eukaryote genome assembly, binning and analysis on github. 

Team

  • Kim Handley (University of Auckland) – lead researcher
  • Gavin Lear (University of Auckland)
  • Michael Hoggard (University of Auckland)
  • Jemma Geoghegan (University of Otago)
  • Murray Cox (Massey University)
  • Maui Hudson (    University of Waikato)
  • Hwee Sze Tee    (University of Auckland)
  • Chanenath Sriaporn (University of Auckland)
  • Jian Shen Boey (University of Auckland)
  • Carmen Astudillo-Garcia (University of Auckland)
  • Annie West (University of Auckland)
  • Esme Spoelstra (University of Auckland)
  • Sophie Palmer Dale (University of Auckland)
  • Millie Ram (University of Auckland)