Complex communities of microbes – microbiota – are found everywhere: in soil, (fermented) foods, and both on and inside the human body. At NIZO, we have profound knowledge and experience in applying different techniques to determine microbial diversity. Furthermore, we can identify key microbial players or functions within the community related to human or animal health, food safety, crop development and fermentation.  

At NIZO, we have a unique combination of domain knowledge experts and proprietary tools for niche-specific sampling, nucleic acid isolation, purification, sequencing and analyses of microbial communities. Our unique bio-IT pipeline enables handling of data from single-strain genomes, 16S and shotgun metagenomics, and metatranscriptomics. It includes a multitude of univariate and multivariate statistical models and machine-learning algorithms for the identification of microbial biomarkers and microbes with functions related to health and disease.

We have in place several in silico and high-throughput in vitro micromodel systems of different ecological human niches and microbe–host cell interaction models. This enables us to discover microbiome modulators affecting metabolic activity, key community members, population structures and health-promoting metabolites. This integrative approach, from study design to interpretation of the data, ensures that solid conclusions can be drawn from the data generated from complex genomics projects. It also allows you to tackle spoilage issues in a product, identify new bio-stimulant organisms in soil or identify and validate intervention targets for gut or skin health.

For the interpretation of these complex data we use various analysis and visualization tools designed for the analysis of genomics data. These tools can also be applied to other large, complex datasets (big data). In addition, text-mining algorithms developed by our experts are used to complement the conclusions from microbiota and genomics studies with scientific literature or patent databases. Coupled with the knowledge of NIZO experts in the field of fermentation, gut health and immunity and food safety this results in solid conclusions on the relation of the microbiota to a food product or (human or animal) health.

Working together in consortia

  • Clospore
  • GenoBox: A GENOmic toolBOX for microbial genome analysis

Recent publications

  • Iron fortification adversely affects the gut microbiome, increases pathogen abundance and induces intestinal inflammation in Kenyan infants. Gut. 2015 May;
  • Zeeuwen PL, Boekhorst J, van den Bogaard EH, de Koning HD, van de Kerkhof PM, Saulnier DM, van Swam II, van Hijum SA, Kleerebezem M, Schalkwijk J, Timmerman HM. Microbiome dynamics of human epidermis following skin barrier disruption. Genome Biol. 2012 Nov 15;13(11):R101. doi: 10.1186/gb-2012-13-11-r101. PubMed PMID: 23153041; PubMed Central PMCID: PMC3580493.
  • Berendsen EM, Boekhorst J, Kuipers OP, Wells-Bennik MHJ. A mobile genetic element profoundly increases heat resistance of bacterial spores. ISME journal 2016, in press
  • Alkema W, Boekhorst J, Wels M, van Hijum SA. Microbial bioinformatics for food safety and production. Brief Bioinform. 2016 Mar;17(2):283-92. doi: 10.1093/bib/bbv034. Epub 2015 Jun 16. PubMed PMID: 26082168; PubMed Central PMCID: PMC4793891.
  • Ceapa C, Lambert J, van Limpt K, Wels M, Smokvina T, Knol J, Kleerebezem M. Correlation of Lactobacillus rhamnosus Genotypes and Carbohydrate Utilization Signatures Determined by Phenotype Profiling. Appl Environ Microbiol. 2015 Aug 15;81(16):5458-70. doi: 10.1128/AEM.00851-15. Epub 2015 Jun 5. PubMed PMID: 26048937; PubMed Central PMCID: PMC4510185.
  • Zoetendal EG, Raes J, van den Bogert B, Arumugam M, Booijink CC, Troost FJ, Bork P, Wels M, de Vos WM, Kleerebezem M. The human small intestinal microbiota is driven by rapid uptake and conversion of simple carbohydrates. ISME J. 2012 Jul;6(7):1415-26. doi: 10.1038/ismej.2011.212. Epub 2012 Jan 19. PubMed PMID: 22258098; PubMed Central PMCID: PMC3379644.

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