Biography

Molecules are everywhere. The diverse structures and functions of small and specialized molecules have always fascinated me. Specialized molecules play key roles in nature as inter-species and even inter-kingdom messengers or as chemical weapons to deter or eliminate­ competing organisms nearby. Furthermore, these specialized molecules are also important components of food often determining crop growth and fitness and their nutritional value. I recognise three paths to better understand complex specialized metabolite mixtures: i) increased metabolite annotation power, ii) chemically-informed comparative metabolomics, and iii) linked metabolomics profiles to function and genotype/genomic information.

My research vision is to close the gap between what we can see in metabolomics and what we can actually learn from it. This will enable biochemical interpretation of spectral data obtained from complex metabolite mixtures through structural and functional annotations. This will depend on finding out: i) which structural information is encoded in metabolomics data; ii) how novel chemistry can be recognised in spectral data, and iii) how to effectively identify relevant metabolite groups in metabolomics profiles of complex metabolite mixtures?

My research agenda is to develop algorithms and models to improve structural annotation of metabolite features and to obtain direct biochemical knowledge from metabolomics profiles. In my group, I will develop computational metabolomics approaches inspired by two other fields - that of natural language processing (NLP) and genomics. For example, I have demonstrated the use of topic modeling NLP algorithms to discover substructures from metabolomics profiles, and I am currently pioneering the use of word embedding NLP approaches to aid in metabolomics analyses. For example, linking the outcome of genomics and metabolomics data mining tools will accelerate the natural products discovery field by making connections between biosynthetic gene clusters and spectra of the molecular structures they encode for. I will use the plant root microbiome and human food metabolome as prime applications since they represent complex metabolite mixtures full of yet unknown metabolic matter that once elucidated will boost our insights in molecular mechanisms underpinning the regulation of growth, development, and health.

Short Bio:

In collaboration with Dr Simon Rogers (Computing Science, University of Glasgow, UK), Justin published a PNAS paper where topic modelling – often used in text-mining – is used for unsupervised substructure exploration in metabolomics data sets using a newly developed software tool MS2LDA. Justin has been working on metabolomics projects thereby exploiting the information-rich fragmentation data that modern mass spectrometers generate and alleviate the bottleneck of metabolite annotation and identification in untargeted metabolomics approaches. He then moved (back) to the WUR to take up a shared Postdoc position between WUR and the group of Prof. Pieter Dorrestein at the UCSD, USA, where he focused on how to combine workflows developed for genome and metabolome mining to aid in functional annotations of genes and structural annotations of metabolites. Afterwards, he took on his current position as Assistant Professor in Computational Metabolomics at WUR Bioinformatics.

Justin has been an active member of the Metabolomics Society. He was part of the founding Early-Careers Members Network (EMN) committee and chaired the committee in the lead-up to Metabolomics2016 in Dublin. Furthermore, Justin was elected into the Board of Directors during 2016 - 2020. He is still part of the Strategy Task Group and the Metabolite Identification Task Group – something which is close to his heart.

Links:
iOMEGA project: https://github.com/iomega
MS2LDA tool: http://www.ms2lda.org
matchms package: https://github.com/matchms/matchms
LinkedIn profile: http://www.linkedin.com/pub/justin-van-der-hooft/35/a93/9aa
Google Citations: https://scholar.google.nl/citations?user=zv9seLwAAAAJ&hl=en
MAGMa tool: https://www.emetabolomics.org/
WUR-Bioinformatics: http://www.wur.nl/en/Expertise-Services/Chair-groups/Plant-Sciences/Bioinformatics.htm
Pieter Dorrestein group at UCSD: http://dorresteinlab.ucsd.edu/Dorrestein_Lab/Research.html
Glasgow Polyomics: http://www.polyomics.gla.ac.uk/