Tobi Elmar W

How the cell integrates environmental signals into its regulatory fabric fascinates me as an engineer. I wish to understand how the environment leaves a lasting imprint on cellular metabolism. To this end I have extensively studied so-called epigenetic modifications of DNA. Epigenetic modifications are persistent, but in essence reversible, modulators of the activity of genes encoded in DNA. My fascination stems from studying metabolic engineering of micro-organisms as an undergraduate. Still as a graduate I was given the opportunity to shift to human epigenetic studies, back then an entirely new field of study. As a graduate student I was instrumental in building up basic knowledge on DNA methylation, one of the major epigenetic marks on DNA, in human populations. I used this knowledge to study individuals exposed to the Dutch Famine in the womb. I was first to show that a transient environmental exposure may indeed leave a lasting imprint on the DNA in humans (PNAS, 2008). The resulting paper is frequently used in (under)graduate courses and was even included in the Dutch Biology A-levels exam. At the end of my PhD I traded candidate gene studies for epigenome-wide approaches. I visited the lab of Dr. Meissner (Harvard University) to perform Reduced Representation Bisulphite sequencing, allowing the genome-wide assessment of DNA methylation and a more comprehensive view on the epigenetic setting of entire metabolic pathways (Nature Communications, 2014). As a post-doc I then shifted to array based methods and contributed to the statistics and bio-bioinformatic pipelines to analyze genome-wide epigenetic data in human cohorts. In 2016 I received a starting grant (VENI) from the Dutch government’s science foundation NWO to branch out to study the most pressing prenatal exposure in human populations: gestational diabetes. Gestational diabetes primes a child to develop diabetes and obesitas in later life, thereby contributing to the obesity and diabetics pandemic. For this pressing societal problem I aim to use the genomics approaches and advanced statistical methodologies I learned over the years. I hope to learn when and how gestational diabetes leaves a lasting mark on the metabolism of a child on a cellular level.