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Environmental metagenomics

Micro-organisms are a major component of the environment – determining their role therefore means understanding their impact on environmental health. A better understanding of New Zealand’s microbial ecosystem has major opportunities for our environmental, primary production and health research.

Water sampling

A powerful way of studying microorganisms is by direct sampling of their DNA from the environment. Metagenomics, the study of the genetic material recovered directly from environmental samples, allows sets of complete or partial genomes to be produced from complex DNA mixtures derived from the different microbial species inhabiting an environment.

While metagenomics is a rapidly growing research approach, there is limited capacity in New Zealand for utilising metagenomic technologies and applying them to environmental management. This project aims to fill a technology and capability gap, developing national capabilities in genomics to contribute to improved environmental monitoring approaches.

The researchers are producing high quality genomes of single organisms from microbial communities with different levels of species complexity using a range of up-to-date DNA sequencing technologies. The aim is to work towards developing monitoring tools that will be applicable in even very complex microbial ecosystems.

The project is already generating a high quality database of genomes from stream and estuarine environments and links with projects studying other aquatic systems. Genomes include those of simple viruses, prokaryotes (bacteria and archaea) and more complex microbial eukaryotes. This genetic data will be used to determine the stream’s metabolic potential (capacity to transform chemical species and pollutants such as nitrate) and implications for the health of the aquatic ecosystem.

This project brings together researchers from four Universities and the Cawthron Institute. Two postdocs, linked to our postdoc community through the bioinformatics infrastructure, and one research assistant are employed to build capability.


  • Guidelines for virome genome identification and annota
  • Guidelines for eukaryote metagenomics
  • Tools for recovering challenging prokaryotic genomes


    • Dr Kim Handley (University of Auckland) – lead researcher
    • Dr Gavin Lear (University of Auckland)
    • Dr Jemma Geogehan (University of Otago)
    • Professor Murray Cox (Massey University)
    • Maui Hudson (University of Waikato)
    • Dr Michael Hoggard (University of Auckland)
    • Hwee Sze Tee (University of Auckland)
    • Chanenath Sriaporn (University of Auckland)
    • Jian Shen Boey (University of Auckland)



    Genome streamlining, plasticity and metabolic versatility distinguish co-occurring toxic and non-toxic cyanobacterial strains of Microcoleus.
    2021 Tee HS, Wood SA, Bouma-Gregson K, Lear G, Handley KM.
    mBio. doi:10.1128/mBio.02235-21.
    Microbial river-to-sea continuum: gradients in benthic and planktonic diversity, osmoregulation and nutrient cycling
    2021 Tee HS, Waite DW, Lear G, Handley KM.
    Microbiome 9: 190
    Video abstract:
    Termite gas emissions select for hydrogenotrophic microbial communities in termite mounds
    2021 Chiri E, Nauer PA, Lappan R, Jirapanjawat T, Waite DW, Handley KM, Hugenholtz P, Cook PLM, Arndt SK, Greening C.
    PNAS 118: e2102625118.
    Genomic adaptations enabling Acidithiobacillus distribution across wide ranging hot spring temperatures and pHs
    Sriaporn C, Campbell KA, Van Kranendonk MJ, Handley KM. 
    Microbiome. 9,135, 2021
    Video abstract:

    Strategies for successful cyanobacterial proliferation in freshwater
    S Wood, HS Tee, KM Handley
    Nature Research Microbiology Community, May 2020

    Tools for successful proliferation: Diverse strategies of nutrient acquisition by a benthic cyanobacterium
    HS Tee, D Waite, L Payne, M Middleditch, S Wood, KM Handley
    The ISME Journal, 14, 2020,

    Determining microbial roles in ecosystem function: Redefining microbial food webs and transcending kingdom barriers
    KM Handley
    mSystems 4(3), e00153-19, 2019, doi:10.1128/mSystems.00153-19

    Bioinformatics resources on Genomics Aotearoa GitHub