All Publications

  • Molecular mechanism of GPCR-mediated arrestin activation NATURE Latorraca, N. R., Wang, J. K., Bauer, B., Townshend, R. L., Hollingsworth, S. A., Olivieri, J. E., Xu, H., Sommer, M. E., Dror, R. O. 2018; 557 (7705): 452-+


    Despite intense interest in discovering drugs that cause G-protein-coupled receptors (GPCRs) to selectively stimulate or block arrestin signalling, the structural mechanism of receptor-mediated arrestin activation remains unclear1,2. Here we reveal this mechanism through extensive atomic-level simulations of arrestin. We find that the receptor's transmembrane core and cytoplasmic tail-which bind distinct surfaces on arrestin-can each independently stimulate arrestin activation. We confirm this unanticipated role of the receptor core, and the allosteric coupling between these distant surfaces of arrestin, using site-directed fluorescence spectroscopy. The effect of the receptor core on arrestin conformation is mediated primarily by interactions of the intracellular loops of the receptor with the arrestin body, rather than the marked finger-loop rearrangement that is observed upon receptor binding. In the absence of a receptor, arrestin frequently adopts active conformations when its own C-terminal tail is disengaged, which may explain why certain arrestins remain active long after receptor dissociation. Our results, which suggest that diverse receptor binding modes can activate arrestin, provide a structural foundation for the design of functionally selective ('biased') GPCR-targeted ligands with desired effects on arrestin signalling.

    View details for DOI 10.1038/s41586-018-0077-3

    View details for Web of Science ID 000432242000065

    View details for PubMedID 29720655

  • From cacti to carnivores: Improved phylotranscriptomic sampling and hierarchical homology inference provide further insight into the evolution of Caryophyllales AMERICAN JOURNAL OF BOTANY Walker, J. F., Yang, Y., Feng, T., Timoneda, A., Mikenas, J., Hutchison, V., Edwards, C., Wang, N., Ahluwalia, S., Olivieri, J., Walker-Hale, N., Majure, L. C., Puente, R., Kadereit, G., Lauterbach, M., Eggli, U., Flores-Olvera, H., Ochoterena, H., Brockington, S. F., Moore, M. J., Smith, S. A. 2018; 105 (3): 446–62


    The Caryophyllales contain ~12,500 species and are known for their cosmopolitan distribution, convergence of trait evolution, and extreme adaptations. Some relationships within the Caryophyllales, like those of many large plant clades, remain unclear, and phylogenetic studies often recover alternative hypotheses. We explore the utility of broad and dense transcriptome sampling across the order for resolving evolutionary relationships in Caryophyllales.We generated 84 transcriptomes and combined these with 224 publicly available transcriptomes to perform a phylogenomic analysis of Caryophyllales. To overcome the computational challenge of ortholog detection in such a large data set, we developed an approach for clustering gene families that allowed us to analyze >300 transcriptomes and genomes. We then inferred the species relationships using multiple methods and performed gene-tree conflict analyses.Our phylogenetic analyses resolved many clades with strong support, but also showed significant gene-tree discordance. This discordance is not only a common feature of phylogenomic studies, but also represents an opportunity to understand processes that have structured phylogenies. We also found taxon sampling influences species-tree inference, highlighting the importance of more focused studies with additional taxon sampling.Transcriptomes are useful both for species-tree inference and for uncovering evolutionary complexity within lineages. Through analyses of gene-tree conflict and multiple methods of species-tree inference, we demonstrate that phylogenomic data can provide unparalleled insight into the evolutionary history of Caryophyllales. We also discuss a method for overcoming computational challenges associated with homolog clustering in large data sets.

    View details for PubMedID 29738076

  • Game-of-Life Mosaics Bosch, R., Olivieri, J. : 325–28
  • Drawing DNA Sequences Networks Olivieri, J. Electronic Thesis or Dissertation. 2016 1–21
  • Designing Game of Life mosaics with integer programming Journal of Mathematics and the Arts Bosch, R., Olivieri, J. 2014; 8 (3-4): 120-132