Atlas of Subcellular RNA Localization Revealed by APEX-seq
Preprint posted on 30 October 2018 https://www.biorxiv.org/content/early/2018/10/30/454470
Article now published in Cell at http://dx.doi.org/10.1016/j.cell.2019.05.027
Proximity RNA labeling by APEX-Seq Reveals the Organization of Translation Initiation Complexes and Repressive RNA Granules
Preprint posted on 25 October 2018 https://www.biorxiv.org/content/early/2018/10/25/454066
Article now published in Molecular Cell at http://dx.doi.org/10.1016/j.molcel.2019.07.030
APEX-Seq: A novel method to study RNA localisation reveals the spatial organisation of the transcriptome.
Selected by Christian Bates
Categories: biochemistry, bioinformatics, cell biology, molecular biology
Background
The central dogma of biology, DNA->RNA->Protein, is deceptively complex. Throughout the process of generating protein from DNA, a range of regulatory mechanisms coordinate the proteome. One important mechanism is the targeting of the intermediate RNA molecule, messenger RNA (mRNA), to particular sub-cellular locations. A classic example of mRNA localization is the shuttling of transcripts to membrane-delimited organelles, such as the endoplasmic reticulum (ER). However, mRNA can also be localized to membraneless sub-regions of the cell. Importantly, both of these processes are widespread; 7500+ human mRNAs are localized to the ER (Jan, et al., 2014) and as much as 70% of mRNA in the Drosophila melanogaster Oocyte appears to be localized (Lécuyer et al., 2007).
The popularity of mRNA localization is perhaps unsurprising, considering the energetic advantage that it affords. For instance, the localization of a single transcript that is able to generate several copies of a protein requires substantially less energy than transporting multiple proteins to the same location. Recent estimates indicate that a single mRNA is capable of generating an average of 1000 copies of a protein (Lawless et al., 2016). Therefore, RNA localization is an efficient mechanism of spatiotemporal mRNA regulation that helps to generate the particular sub-cellular niches of proteins that are required for functions ranging from differentiation, migration, signaling and cell survival during stress.
There are several systems for studying mRNA localization, although each has their pitfalls. For example, we can directly look at where an mRNA is in fixed cells, by in-situ hybridization (ISH) of probes that specifically bind to an mRNA of interest. This ISH methodology has recently been overhauled, and now it is possible to assess the locale of thousands of transcripts (Lubeck et al., 2014). Alternatively, mRNAs can be imaged in living cells, with tagging approaches such as the MS2 system. In this system, multiple stem-loops are cloned into the gene of interest, allowing mRNA visualization when a fluorescently tagged protein binds to them. However, both of these methods are limited in spatial resolution, prone to artifacts, provide little information regarding differential mRNA isoform localization and require specialized apparatus to perform in high-throughput.
It is also possible to assess the position of an mRNA using biochemical techniques. These typically enrich a particular sub-region of interest either by fractionation, or pulling down a key protein component of that region, and seeing what mRNA it is attached to. Coupling these methods to high-throughput sequencing has provided much information about the RNA composition of several sub-cellular regions. However, for some organelles, and highly dynamic regions of the cell, such as stress granules and processing bodies, implementing these biochemical approaches has proven to be particularly difficult (Khong et al., 2017).
These two preprints from the labs of Alice Ting and Nicholas Ingolia aim to develop a new biochemical protocol that allows researchers to easily study the position of thousands of RNA in the cell.
Key findings
Both articles employed the same novel method, termed APEX-seq. This name stems from the fact that they use a version of ascorbate peroxidase (APEX), named APEX2. This enzyme usually catalyzes the oxidation of phenol groups, generating short-lived radicals that can covalently react with nearby molecules. However, when presented with biotin-phenol, APEX2 will generate biotin radicals that ligate to nearby molecules, with a remarkably precise temporal (1 minute) and spatial (20nm radius) resolution. Biotin is incredibly useful because it can be easily and effectively purified using streptavidin, which binds to biotin with a high affinity (one of the strongest natural interactions ever studied).
Typically, APEX2 and other biotinylating enzymes are used to label proteins, not RNA, so both preprints begin by verifying that APEX2 is capable of biotinylating RNA directly. Fazal, et al. do this by incubating APEX2 expressing cells with biotin-phenol and hydrogen peroxide, whilst Padron, et al. tested the effect of purified APEX2 on RNA in vitro. Both studies found that APEX2 is capable of directly biotinylating RNA, and Fazal. et al. also showed that APEX2 appears to preferentially biotinylate G-rich regions of RNA.
Next, both teams wanted to know whether APEX2 could be used to biotinylate RNA in a spatially precise manner. In particular, whether APEX2 could differentially biotinylate pools of RNA from different sub-cytoplasmic regions. To test this, both labs tested whether APEX could specifically biotinylate mRNA that is trafficked to the cytoplasmic face of the ER membrane. Testing this is very important as a previous APEX based approach, APEX2-RIP, failed to perform adequately in this experiment, despite working well for membrane-enclosed organelles (Kaewsapsak et al., 2017).
Both Padron, et al. and Fazal, et al. tested the biotinylated RNA from the ER membrane localized APEX vs cytosolic APEX with deep sequencing and found that the mRNAs enriched at the ER membrane encoded membrane-associated, and secretory proteins, respectively, as would be expected. These findings represent a considerable enhancement compared to previous attempts with APEX-RIP, and suggest that APEX-seq could be used to assess RNA localization with a high spatial resolution.
After demonstrating that this approach can be used to study the RNA content of regions that were previously inaccessible, both groups used the power of this method to uncover several novel aspects of molecular biology, including the sequential recruitment of specific mRNAs and proteins to stress granules, and the RNA component of 9 different sub-cellular regions.
Why I chose these articles
The ability to study where RNA is, or moves to, following a treatment is important. For example, the contribution of a gene to a particular disease, or biological process might be inferred by whether levels of the mRNA change throughout these processes. However, it is possible that some mRNAs do not change in abundance, but in locality. Yet to date, there has not been any robust method of assessing cellular RNA localisation in a high-throughput manner. These preprints describe a novel way of studying the position of RNA within the cell, by targeting a biotinylating protein to a particular region and seeing what RNAs are biotinylated, it allows us to build a picture of the RNAs close to, or within that region.
I also like how the two preprints inadvertently show the power and usefulness of this approach, as beyond the initial validation experiments, both groups implement APEX-seq in very different ways to address the biological question that they are interested in.
Questions for the authors
- Do you think that this method could also be used to infer where on an RNA, a particular APEX-tagged protein may bind based on the fact that nearby nucleotides would be more likely to be biotinylated?
- Could a split-APEX be used to further increase the signal to noise ratio by reducing potential background?
Bibliography
Jan, C. H., Williams, C. C. and Weissman, J. S. (2014) ‘Principles of ER cotranslational translocation revealed by proximity-specific ribosome profiling. TL – 346’, Science (New York, N.Y.), 346 VN-, p. 1257521.
Kaewsapsak, P., Shechner, D. M., Mallard, W., Rinn, J. L. and Ting, A. Y. (2017) ‘Live-cell mapping of organelle-associated RNAs via proximity biotinylation combined with protein-RNA crosslinking’, eLife, 6.
Khong, A., Matheny, T., Jain, S., Mitchell, S. F., Wheeler, J. R. and Parker, R. (2017) ‘The Stress Granule Transcriptome Reveals Principles of mRNA Accumulation in Stress Granules’, Molecular Cell. Elsevier, 68, p. 808–820.e5.
Lawless, C., Holman, S. W., Brownridge, P., Lanthaler, K., Harman, V. M., Watkins, R., Hammond, D. E., Miller, R. L., Sims, P. F. G., Grant, C. M., Eyers, C. E., Beynon, R. J. and Hubbard, S. J. (2016) ‘Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring’, Molecular & Cellular Proteomics. American Society for Biochemistry and Molecular Biology, 15, pp. 1309–1322.
Lécuyer, E., Yoshida, H., Parthasarathy, N., Alm, C., Babak, T., Cerovina, T., Hughes, T. R., Tomancak, P. and Krause, H. M. (2007) ‘Global Analysis of mRNA Localization Reveals a Prominent Role in Organizing Cellular Architecture and Function’, Cell, 131, pp. 174–187.
Lubeck, E., Coskun, A. F., Zhiyentayev, T., Ahmad, M. and Cai, L. (2014) ‘Single-cell in situ RNA profiling by sequential hybridization’, Nature Methods. Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved., 11, p. 360.
Posted on: 14 January 2019
doi: https://doi.org/10.1242/prelights.7202
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