You might imagine the cells in your body as quite static. In reality, they are hives of activity and contain cocktails of different molecules. Just like us, these different molecules in our cells all have a job. Just like us, those jobs span a wide range of roles and take place in designated spaces – instead of offices or labs, for example, they take place in specialised compartments of the cell called organelles. And just like us, these molecules must be in the right place at the right time, might need to visit different locations throughout their ‘working day’ and often team up with co-workers to perform their role. Ultimately, all of this needs to come together in order for the cell to maintain all its vital functions to stay alive.

RNAs and proteins are two groups of molecules that are key players helping everything to run smoothly and frequently work together. By identifying where different RNAs and proteins are within the cell at a given time, it can help researchers to work out what their jobs are and how they may interact.

Having this global ‘Google Map’ of RNAs and proteins together within a cell would give researchers a paradigm-shifting tool to support a range of different studies. However, currently technology and techniques don’t support this level of resolution as to what is happening cell wide. Most of the current techniques only allow you to look at RNAs or at proteins or are restricted to looking at one cell compartment at a time missing the wider context of a whole cell.

However, new collaborative research between the Lilley lab at the University of Cambridge’s Department of Biochemistry and the Willis group in the Unit, published today in the journal Nature Methods, outlines the creation of a new method to study the cell wide localisation of RNA and proteins simultaneously.

This new framework combines two methods: Localisation of RNA (LoRNA) and Localisation of Proteins by Isotype Tagging (dLOPIT). Together, they map RNA and proteins to organelles or other regions within the entire cell at the same time, giving a distribution map of each molecule type under a certain condition. If we know where a given protein or RNA molecule should be under normal conditions, but under certain stressful or disease conditions, it is missing or in the wrong location that can potentially help scientists to find ways to treat conditions and restore things to normal. This is an unprecedented level of information that this new technique can provide.

As an example, in this study, the researchers looked at what might change under a certain condition called the unfolded protein response (UPR). This is a way in which a cell responds to the ‘stress’ of having too many misfolded proteins at a specific organelle called the endoplasmic reticulum. The UPR helps the cell to return levels of misfolding to ‘normal’ by reducing the number of proteins to be folded or removing some proteins, for example. When the UPR doesn’t work correctly, it has been linked to neurodegenerative disease, cancer progression or diabetes.

By combining LoRNA and dLOPIT, they were able to measure the reorganisation of the cell’s RNAs and proteins when the UPR was activated. They found that certain subsets of RNAs were more efficiently relocated to other compartments of the cell, whereas others aren’t affected and what proteins may be involved in maintaining a RNA’s location.

Together, this is the most detailed and comprehensive overview to date of RNA and protein localisation in the cell and their movements. This technique provides biologically relevant information at a paradigm-shifting resolution that will lead to new research avenues for scientists and an unprecedented level of understanding exactly what the hive of activity in our cells looks like.

‘System-wide analysis of RNA and protein subcellular localisation dynamics’ was published on 30th November 2023 in Nature Methods. Read the full publication here.

We would like to thank our Proteomics Facility for their support with this study.