METASTAVA: Standardisation and validation of metagenomics methods for the detection of foodborne zoonoses, antimicrobial resistance and emerging threats

Start: 1 January 2018
Duration: 2 Years
Domain: Foodborne Zoonoses
Keywords: Next generation sequencing (NGS), metagenomics, method validation, diagnostics, quality assurance
Contact: Steven Van Borm (Sciensano)

The Project #METASTAVA

METASTAVA aims to evaluate the potential use of metagenomic analysis to the public health reference laboratory by targeted collection of reference data and reference materials, by generating focused validation data, and by proposing criteria and tools for a robust quality assurance (QA) of metagenomic workflows from sample selection to interpretation of result .

Metagenomic analysis is increasingly used to identify possible causes of unexplained disease outbreaks, to complement routine diagnostic evaluation, and to study the role of the microbiome and virome in health and disease. Currently, standardisation of metagenomics data generation and analysis tools is  being sufficiently covered by other ongoing initiatives (including COMPARE). However, translating these promising technological developments into diagnostic tools for veterinary and public health laboratories requires careful validation, which is the focus of this project.

In order to use Metagenomic analysis for robust diagnostics,  METASTAVA identified several important gaps in our knowledge of NGS and metagenomics that must be filled:

  1. Development of a set of reference data for the model pathogens, representing most common sample types
  2. Development of harmonized workflows for the generation and analysis of metagenomic data fitting to a defined diagnostic scope for the model pathogens
  3. Development of a validation protocol for metagenomic diagnostics (including quality assurance and robustness testing).

The METASTAVA project is addressing the identified gaps and using hepatitis E virus (HEV), norovirus (NoV), zoonotic pox viruses, antibiotic resistant bacteria and Shigatoxigenic Escherichia coli (STEC), as model pathogens in developing the methods and reference datasets.

In short, where ongoing initiatives invest in the standardization of metagenomics tool sets, METASTAVA wants to bring metagenomics to the diagnostic laboratory.


Chi-Wai Chan, M,. Roy, S., Bonifacio, J., Zhang, YY., Chhabra, P., Chan, JCM., Celma, C., Igoy, MA., Lau SL., Mohammad, KN., Vinjé, J., Vennema, H., Breuer, J., Koopmans, M., de Graaf, M. (2021). Detection of Norovirus Variant GII.4 Hong Kong in Asia and Europe, 2017-2019. Emerging Infectious Diseases. 27(1), pp 283- 293. DOI:

Sikkema, RS., Pas, SD., Nieuwenhuijse, DF., O’Toole, A., Verweij, JJ., van der Linden, A., Chestakova, I., Schapendonk, C., Pronk, M., Lexmond, P., Bestebroer, T., Overmars, RJ., van Nieuwkoop, S., van den Bijllaardt, W., Bentvelsen RG., van Rijen, MML., Buiting, AGM., van Oudheusden, AJG., Diederen, BM., Bergmans, AMC., van der Eijk, A., Molenkamp, R., Rambaut, A., Timen, A., Kluytmans, JAJW., Oude Munnink, BB., Kluytmans van den Bergh, MFQ., Koopmans, MPG. (2021). COVID-19 in health-care workers in three hospitals in the south of the Netherlands: a cross-sectional study. The Lancet: Infectious Disease. 20(11), p1273-1280. DOI:

Oude Munnink, BB., Nieuwenhuijse, DF., Stein, M., O’Toole, A., Haverkate, M., Mollers, M., Kamga, SK., Schapendonk, C., Pronk, M., Lexmond, P., van der Linden, A., Bestebroer, T., Chestakova, I., Overmars, RJ., van Nieuwkoop, S., Molenkamp, R., van der Eijk, AA,. Geurtsvan Kessel, C., Vennema, H., Meijer, A., Rambaut, A., van Dissel, J., Sikkema, RS., Timen, A., Koopmans, M. (2020). Rapid SARS-CoV-2 whole-genome sequencing and analysis for informed public health decision-making in the Netherlands. Nature Medicine. 26, p 1405–1410. DOI:

Van Borm, S., Fu, Q., Winand, R., Vanneste, K., Hakhverdyan, M., Höper, D., Vandenbussche, F. Evaluation of a commercial exogenous internal process control for diagnostic RNA virus metagenomics from different animal clinical samples. (2020). Journal of Virological Methods, 283. DOI: 

OpenAIRE Publications