Capturing cellular re-localisation of RNA and protein in response to stress

Abstract 

The complexity of living organisms does not scale with the predicted number of protein coding genes. Many factors contribute to increasing complexity, including non-coding RNA mediated control mechanisms and post-transcriptional and post-translation processing. The location of protein synthesis also plays a key role in expanding protein functionality, with aberrant spatial translation being a driver in multiple diseases.

I will describe technology we have developed to capture the spatial relationship between RNA and protein on a cell-wide scale. I will discuss how we map the cellular spatial proteome (1) (2) based on physicochemical fractionation of cellular components (LOPIT), give examples of how we have applied these methods to interrogate many different biological scenarios (3) (4) and describe associated robust computational workflows (5) and how this method can be coupled with post translation modification analysis (6).

I will also describe a new method that allows the simultaneous mapping of the both the spatial proteome and spatial transcriptome on a cell-wide scale. Using the same set of samples, we can combine LOPIT with a novel approach, LoRNA (the Localisation of RNA) (7). We have applied this combined method to determine the orchestrated re-localisation of the spatial transcriptome and proteome downstream of the unfolded protein response (UPR). These data have revealed that ER-localised transcripts are more efficiently recruited to stress granules than cytosolic RNAs. Furthermore, the data show that eiF3D mediated translation is key to sustaining cytoskeletal function during cellular stress. These data also give insights into how post transcriptional modification of tRNA modifications through interaction with RNA binding proteins(8) may impact codon usage bias within the subset of the transcriptome recruited to stress granules upon UPR.

1. Mulvey et al (2017) doi: 10.1038/nprot.2017.026

2. Geladaki et al (2019) doi:10.1038/s41467-018-08191-w

3. Barylyuk et al (2020) doi:10.1016/j.chom.2020.09.011

4. Mulvey et al (2021) doi:10.1038/s41467-021-26000-9

5. Crook et al (2022) accepted and bioRxiv 2021.01.04.425239

6. Kafkia et al (2022) doi: 10.1126/sciadv.abq5206

7. Villanueva et al (2022) bioRxiv 2022.01.24.477541