ICBE Asia 2018: International Conference on Biomolecular Engineering

How do Computational Approaches Benefit Life Science Research? Case studies into immune, cancer and developmental cell dynamics

Author

Selvarajoo, K. - Presenter, BioTrans, A*STAR Singapore
Systems biology efforts are revealing complexities far beyond traditional reductionist approaches can anticipate. Single cells display stochastic or noisy gene/protein expressions and, sometimes, show emergent response when pooled into populations. Should modern day research move towards single cell research, as proposed by “single-cell biologists”, or continue to explore the dynamics of tissue-level response? Our research, over a decade, has focused on dynamic cellular behaviors to uncover novel network and global response properties both at single cells and populations. We investigated instructive cell signaling and high-throughput transcriptome-wide behaviors of immune, cancer, and embryonic development cells. Our data reveal that cultured populations display deterministic signaling that can be modeled using linear response rules. Adopting the rules, we have computationally predicted and verified experimentally novel signaling features and key targets for controlling proinflammatory responses and cancer survival. In addition, our transcriptome-wide statistical analyses of single cell embryonic developmental process, from oocyte to blastocysts cell stage differentiation, revealed global mechanisms for the onset of noisy transcription responsible for generating gene expression variability.

Selected References

  1. Selvarajoo K. A systems biology approach to overcome TRAIL resistance in cancer treatment. Prog Biophys Mol Biol. 2017, 128:142-154.
  2. Piras V, Selvarajoo K. The reduction of gene expression variability from single cells to populations follows simple statistical laws. Genomics. 2015, 105:137-44.
  3. Piras V, Tomita M, Selvarajoo K. Transcriptome-wide variability in single embryonic development cells. Sci Rep. 2014, 4:7137.
  4. Hayashi K, Piras V, Tabata S, Tomita M, Selvarajoo K. A systems biology approach to suppress TNF-induced proinflammatory gene expressions. Cell Commun Signal. 2013, 11:84.
  5. Tsuchiya M, Piras V, Choi S, Akira S, Tomita M, Giuliani A, Selvarajoo K. Emergent genome-wide control in wildtype and genetically mutated lipopolysaccarides-stimulated macrophages. PLoS One. 2009, 4:e4905.