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Services

A-LIFE offers advanced platforms for chemical and biological analysis, supporting exposomics, metabolomics, and effect-directed research.

Platform for targeted and non-target analysis (exposomics/metabolomics) 

Analysis of diverse organic contaminants in environmental, food, animal, and human samples using targeted analysis, or suspect and non-target screening workflows. These workflows employ conventional mass spectrometry (MS), high-resolution mass spectrometry (HRMS), as well as advanced ion mobility separation instruments, such as trapped ion mobility spectrometers (TIMS). Modelling and data analysis pipelines, are applied for exposure assessment, human biomonitoring, effect-directed analysis, and metabolomics/lipidomics purposes. 

The facilities include: 

  • Liquid Chromatography Systems: LC-MS/MS, UPLC-HR-qTOFMS, UPLC-HR-timsTOF. 
  • Gas Chromatography Systems: GC-Pyr-MS, GC-HR-qTOFMS. 
  • Mass Spectrometry Technologies: DART-MS. 
  • Ionization Techniques: Electron Ionization (EI), Electrospray Ionization (ESI), Heated-ESI (HESI), Atmospheric Pressure Chemical Ionization (APCI), Atmospheric Pressure Photoionization (APPI), Ion Booster, Direct Probe, Direct Analysis in Real Time (DART),  Soft Ionization by Chemical Reaction In Transfer (SICRIT), and Pyrolysis (Py). 

Services currently offered by the infrastructure: 

  1. Quantitative analysis of micro and nano-plastics using pyrolysis-gaschromatography coupled with mass spectrometry (Py-GC-MS). 
  2. Quantitative analysis of PFAS, plastic additives, parabens, chlorinated paraffins, or steroids using liquid chromatography coupled with mass spectrometry (LC-MSMS).  
  3. Semi-quantitative suspect and non-target screening of chemical contaminants using liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) 
  4. Quantitative targeted metabolomics and lipidomics using LC-HRMS 
  5. Semi-quantitative non-targeted metabolomics and lipidomics using LC-HRMS 
  6. Automated and tailormade workflows for HRMS data processing. Implementation of machine learning for feature prioritization. 

 If you are interested in our services, please contact: jacco.koekkoek@vu.nl 

Platform for high-throughput effect-directed analysis 

The high-throughput effect-directed analysis (HT-EDA) infrastructure at VU Amsterdam combines advanced fractionation, miniaturized bioassays, and state-of-the-art analytical platforms. The FractioMate®, developed by members our team, allows highly precise and reproducible transfer of LC-separated fractions into 96-, 384-, and 1536-well plates. This technology enables efficient coupling of chromatographic separation with high-throughput bioassays, creating a seamless workflow from complex mixtures to biological response data. Miniaturized assays such as reporter gene assays, protein-based assays, cell-based toxicity screens are implemented in support rapid and parallel testing of multiple toxicological endpoints. The biological activity profiles are directly linked to high-resolution mass spectrometry (HRMS) and ion mobility spectrometry (IMS), enabling the identification and prioritization of bioactive contaminants across environmental, food, animal, and human samples. 

Services currently offered by the infrastructure: 

  1. High-resolution fractionation of environmental or biological samples in 96, 384, or 1536 well-plates using liquid chromatography. Dried plates can be delivered worldwide. 
  2. Activity testing of the fractions using relevant bioassays in collaboration with the Environmental Human Toxicology group at the VU in Amsterdam. 
  • Molecular initiating events targeting thyroid hormone system disruption. 
  • Molecular initialing events and key events targeting androgenicity/estrogenicity. 
  • Tyrosine kinase inhibition. 
  • Microbial resistance. 
  • Developmental malformations / lethality in zebra fish embryos. 
  1. Identification of chemicals present in active fractions using high resolution mass spectrometry (HRMS). 
  • Option of including ion mobility separation for enhanced identification in complex matrices. 
  • Implementation of in silico prioritization strategies (QSAR models). 

If you are interested in our services, please contact: m.margalef.jornet@vu.nl

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