Poster Presentation The 45th Lorne Conference on Protein Structure and Function 2020

Online databases complement wet lab approaches to understanding peptide GPCR function (#304)

Alice R Whitehead 1 2 , Daniel Scott 1 2 , Victoria Perreau 2 , Ross Bathgate 1 2
  1. The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
  2. The University of Melbourne, Parkville, VIC, Australia

G protein-coupled receptor (GPCR) function is impacted by a cell’s state, specifically by actions of other proteins being expressed . GPCRs are crucial mediators of cell signalling. Although they are expressed at low levels[1], just a few receptors can produce a massive signalling response. It is therefore important to understand the impact of co-expressed proteins on GPCR actions. We aim to utilise online RNA and protein databases to investigate proteins co-expressed with Relaxin Family Peptide Receptor 1 (RXFP1) and their impact on RXFP1 activity.

Searching the GEMMA[2] database for transcripts co-expressed with RXFP1 revealed C11Orf87, a gene yet to be extensively characterised. Searches for proteins homologous to C11Orf87 and using the Conserved Domain Database[3] identified it as a predicted membrane protein with a signal peptide, glycosylation site, and previously un-annotated Lipopolysaccharide assembly protein A domain. It is conserved from mammals back to zebrafish. Gene Ontology databases were used to investigate pathways which may link C11Orf87 and RXFP1. The discovery of C11Orf87 as a potentially important aspect of RXFP1’s cellular environment demonstrates the utility of online databases. As C11Orf87 isn’t noted in the literature, it would not have been otherwise identified.

Results of database searches prompted plans to experimentally validate the co-expression in RNAseq experiments, and investigate impacts of C11Orf87 on RXFP1 function in signalling assays. Existing RNAseq datasets in the Sequence Read Archives revealed that short-read RNAseq experiments of typical sequencing depth have very low coverage of RXFP1. This prompted inclusion of a targeted long-read sequencing approach in our experimental design, to complement short-read experiments.

These findings demonstrate the utility of online database searches as a complementary approach to wet lab experiments. Database searches provided novel, data-driven ideas to incorporate into our experiments studying RXFP1 expression and co-expressed proteins.

  1. Regard, J. B., Sato, I. T., & Coughlin, S. R. (2008). Anatomical profiling of G protein-coupled receptor expression. Cell, 135(3), 561-571.
  2. Zoubarev, A., Hamer, K. M., Keshav, K. D., McCarthy, E. L., Santos, J. R. C., Van Rossum, T., ... & Gillis, J. (2012). Gemma: a resource for the reuse, sharing and meta-analysis of expression profiling data. Bioinformatics, 28(17), 2272-2273.
  3. Marchler-Bauer, A., Bo, Y., Han, L., He, J., Lanczycki, C. J., Lu, S., ... & Gwadz, M. (2016). CDD/SPARCLE: functional classification of proteins via subfamily domain architectures. Nucleic acids research, 45(D1), D200-D203.