firstname.lastname@example.orgGrowth, Development and Metabolism Programme
An impaired maternal nutrition and/or other external factors can cause sub-optimal fetal development and affected babies face an increased risk of developing cardiovascular disease, type 2 diabetes mellitus (T2DM) and adiposity later in life. The pathophysiologies of T2DM and other metabolic disorders are associated with abnormalities in endocrine signaling. Differences in various transcriptional networks are expected between Intra Uterine Growth Restriction (IUGR)/ low birth weight and normal birth weight babies in terms of major growth and development associated transcription factor signalling. It has been hypothesized that the molecular mechanism underlying the phenomenon of developmental plasticity may in part be related to epigenetic modulation of expression of key developmental genes. Using clinical specimens of umbilical cord tissues, my focus is to identify these trancriptional networks and the underlying epigenetic control mechanisms by employing a combination of powerful biological and systems biology tools, including genetic and cell-based techniques such as Chromatin Immuno Precipitation (ChIP), as well as next generation sequencing techniques etc. The findings from our work may have direct applications towards the development of therapeutic targets for a wide range of metabolic diseases. Additionally, our molecular profiling studies may lead to the identification of biomarkers that potentially reflect antenatal development and which may be predictive of future, postnatal onset of metabolic disease phenotypes.
Joseph R., Orlov Y.L., Huss M., Ukil L., Sun W., Pan Y.F., Kong S.L., Lim M., Thomsen J.S., Ruan Y., Clarke N.D., Prabhakar S., Cheung E., Liu E.T. (2010). Genomic factors determining binding site selection by estrogen receptor α. Molecular Systems Biology, 6: 456
Fullwood et al. (2009). An oestrogen-receptor-α-bound human chromatin interactome. Nature, 462: 58-64
Orlov Y. L., Mikael E. H., Joseph R., Vega B. et al. (2009). Genome wide statistical analysis of multiple transcription factor binding sites obtained by ChIP-seq technologies. CompBio’09, May 18-20, 2009, Ischia, Italy.