Menu

Close

Recognition of cellular RNAs by the S9.6 antibody creates pervasive artefacts when imaging RNA:DNA hybrids

John A. Smolka, Lionel A. Sanz, Stella R. Hartono, Frédéric Chédin

Preprint posted on January 13, 2020 https://www.biorxiv.org/content/10.1101/2020.01.11.902981v1

Detecting cellular R-loops with caution!

Selected by Ram

R-loops – RNA-DNA hybrids with displaced ssDNA – essentially form during transcription. Initially thought to be simple byproducts of transcription it is now widely considered that they play crucial roles in genome stability, DNA replication, recombination, transcription, chromatin structure, histone, DNA and RNA modifications. Most of the data related to R-loops comes from their impact on genome stability1,2So, how do investigators reliably detect them in the cells?

Currently, the major way to detect R-loops in cells (or tissues) is antibody-based. Using the S9.6 antibody that binds to RNA-DNA hybrids one could perform immunoblots, immunofluorescence and immunoprecipitate cellular R-loops. But here’s the rub: the antibody is not specific to RNA-DNA hybrids but also binds to other RNA moieties (like ssRNA, dsRNA) albeit with lower affinity3,4. Nevertheless, thanks to several biochemical tweaks and easily accessible genome sequencing technologies, the ways to sequence and map R-loops is ever increasing. However, S9.6 antibody falls short in imaging R-loops. This preprint from Dr Frederic Chedin’s lab (the first lab to map R-loops genome-wide using S9.6 antibody) tries to point out the pitfalls of using S9.6 antibody for imaging (and immunoprecipitation) and suggest few extra steps. In this preLight, I will try to point the most important highlights.

1.   Cytosolic S9.6 staining is not completely of mitochondrial origin.

Typically S9.6 mediated R-loop staining on fixed cells reveals three major patterns: cytosolic, nuclear, and nucleolar. The most prominent or bleb-like staining is attributed to nucleolar rDNA transcription; the more sparse, pan, or hotspots depicts RNA polymerase II transcription in non-nucleolar area of nuclei. Cytosolic staining was widely considered of R-loops arising due to mitochondrial transcription. However, in this preprint, the investigators demonstrate that cytoplasmic S9.6 signal coincides more with the total cellular marker (HSP27) rather than the mitochondrial marker (MitoTracker Deep Red FM). This suggests that S9.6 antibody also stains extra-mitochondrial nucleic acids in the cytoplasm.

2.   Use a combination of RNases to pretreat fixed cells.

Previous data suggest that S9.6 detects RNA moieties other than RNA-DNA hybrids3,4. So, the investigators used a combination of RNases like RNase T1, RNase III, and RNase H1 to digest single, double-stranded and hybrid RNA. It turns out that, RNase T1 had a significantly larger effect in decreasing both nuclear and cytoplasmic S9.6 staining rather than RNase III and RNase H1. Taking into consideration the specific nuances of these enzymes, the investigators conclude that the S9.6 signal in the cellular environment is largely by the detection of RNA but not RNA-DNA hybrids. On the contrary, S9.6 antibody was able to detect custom-designed Cy5-labelled RNA-DNA hybrids transfected into cells in an RNase H1 sensitive manner. This suggests that S9.6 antibody could detect RNA-DNA hybrids in cellular environments but lacks specificity.

Intriguingly their genome-wide data suggests otherwise. S9.6 antibody has been used to map R-loops genome-wide in different organisms by ‘immunoprecipitation followed by sequencing’ approach. The investigators used similar RNases to look for S9.6 specific signals. Pretreating the cell extracted nucleic acids with the RNases mentioned above, they found that S9.6 signal was sensitive to RNase H1 pretreatment rather than RNase T1 and RNase III, especially at bonafide R-loop loci. This suggests that S9.6 antibody have a ‘better specificity’ in biochemical pulldowns.

Finally, the investigators recommend others to (a) perform a combination of pretreatments using RNase T1, RNase III, and RNase H1 before immunoprecipitation and (b) use the DNA rather than RNA moiety of RNA-DNA hybrid for sequencing purposes to avoid any non-specific binding of S9.6 to RNA.

In future, it might be interesting to compare with other less know R-loop detecting antibodies5 or use RNA-DNA hybrid binding proteins/domains to robustly catch cellular R-loops6,7. Indeed antibody-free methods to map R-loops genome-wide are gaining popularity8,9. Alternatively, one could also develop existing proximity ligation assays, electron microscopy, atomic force microscopy, and super-resolution microscopy to better image R-loops. But live-cell imaging of R-loops at single-molecule resolution can debunk many R-loop mysteries.

Acknowledgements: I thank Dr Frederic Chedin for promptly reaching back to me with responses.

References:

1.       Cell. 2019 Oct 17;179(3):604-618. doi: 10.1016/j.cell.2019.08.055.

2.       Mol Cell. 2019 Feb 7;73(3):398-411. doi:10.1016/j.molcel.2019.01.024.

3.       J. Mol. Recognit. 2013;26:376–381. doi:10.1002/jmr.2284.

4.       J Mol Biol. 2018 Feb 2;430(3):272-284. doi:10.1016/j.jmb.2017.12.016.

5.       Hybridoma .1994 Dec;13(6):499-507. doi:10.1089/hyb.1994.13.499.

6.       Nucleic Acids Res. 2014 Aug;42(14):9047-62. doi:10.1093/nar/gku601.

7.       Nature. 2014 Jul 17;511(7509):362-5. doi:10.1038/nature13374.

8.       Nat Protoc. 2019 May;14(5):1661-1685. doi:10.1038/s41596-019-0154-6.

9.       Curr Protoc Mol Biol. 2020 Mar;130(1):e113. doi:10.1002/cpmb.113.

Tags: imaging, rloops, s9.6 antibody

Posted on: 27th May 2020 , updated on: 31st May 2020

doi: https://doi.org/10.1242/prelights.21214

Read preprint (No Ratings Yet)




  • Author's response

    Dr Frederic Chedin (FC) shared

    Questions to the authors:

    a) It is clear from this work that cytosolic S9.6 signal is mostly non-mitochondrial, what do the authors speculate the signal would be?

    FC: Since that signal is not RNase H sensitive despite evidence that RNase H is active under these conditions, we know it is not RNA-DNA hybrid-derived. Because that signal is predominantly RNase T1 sensitive, evidence suggests that it is RNA-derived. This fits with the known affinity of S9.6 for dsRNA and with the fact that RNA material is overwhelmingly more abundant than RNA-DNA hybrids in cells.

    b) Did the authors consider to compare S9.6 signal with other less know RNA-DNA hybrid antibodies (like D5H6 clone)?

    FC: No – this would be interesting in future studies.

    c) The authors mention that there is not much difference in S9.6 staining between formaldehyde fixation and methanol-based fixation when pretreated with respective RNases. However, the stand-alone S9.6 staining pattern looks different between different fixatives (Fig 2 and S3 of the preprint). Moreover, some investigators showed that S9.6 staining is ‘better’ in methanol-based fixation1. It would be interesting to hear the authors perspective on this.

    FC: We have often seen that methanol fixation results in a brighter S9.6 IF signal (note: this does not mean “better”) but the overall pattern itself is not significantly changed. It is still predominantly cytoplasmic and nucleolar with faint nuclear signals.

    d) RNase pretreatment data from this study suggests that S9.6 antibody might not be a good choice to image cellular R-loops: although it is not clear why the antibody works better for immunoprecipitation. What do the authors speculate on this?

    FC: Our genomic DNA extraction step largely removes RNA from the sample so the IP doesn’t suffer from the same problems (as shown here by the fact that RNase T1 and RNase III don’t have any effect). In addition, when the downstream readout queries DNA (i.e. qPCR or DNA-based sequencing), RNA contamination is less of an issue. Note that this is not bulletproof: if the downstream readout builds off RNA (as in RNA-based sequencings such as in DRIPc-seq or RDIP-seq), there is a chance for any contaminating RNA to lead to problems.

    e) It is encouraging to read that the authors tried to address some previous caveats in R-loop sequencing techniques from the host lab (like DRIPc-seq)2. However, it would be great to hear updated suggestions from the authors. For eg., using sonication instead of using restriction enzyme cocktail to fragment nucleic acids before immunoprecipitating R-loops.

    FC: We constantly strive to improve our protocols. Every approach has strengths and weaknesses and researchers will have to carefully consider which version of DRIP best fits their needs. The original DRIP-seq approach with restriction enzymes is very robust but offers lower resolution and lacks strand-specificity. It should be the preferred method for anyone new to R-loop mapping. DRIPc-seq has an unparalleled resolution, signal/noise ratios, and strand-specificity but since it relies on RNA-sequencing it is vulnerable to RNA contamination (as we showed in our S. pombe work). sDRIP-seq is a good compromise in that it allows strand-specificity and builds off DNA sequencing. However, sonication leads to a loss of signal and the signal/noise ratio is not as strong. Importantly these three approaches produce highly concordant datasets that were validated by non-denaturing bisulfite approaches3. Thus, we know that the S9.6 R-loops maps we produced are highly reliable.

    References:

    1. Nature. 2014 Dec 18;516(7531):436-9. doi:10.1038/nature13787.
    2. Mol Cell. 2016 Jul 7;63(1):167-78. doi: 10.1016/j.molcel.2016.05.032.
    3. J Mol Biol. 2020 Mar 27;432(7):2271-2288. doi:10.1016/j.jmb.2020.02.014.

    Have your say

    Your email address will not be published. Required fields are marked *

    This site uses Akismet to reduce spam. Learn how your comment data is processed.

    Sign up to customise the site to your preferences and to receive alerts

    Register here

    Also in the cell biology category:

    Planar Cell Polarity – PCP

    This preList contains preprints about the latest findings on Planar Cell Polarity (PCP) in various model organisms at the molecular, cellular and tissue levels.

     



    List by Ana Dorrego-Rivas

    BioMalPar XVI: Biology and Pathology of the Malaria Parasite

    [under construction] Preprints presented at the (fully virtual) EMBL BioMalPar XVI, 17-18 May 2020 #emblmalaria

     



    List by Gautam Dey, Samantha Seah

    1

    Cell Polarity

    Recent research from the field of cell polarity is summarized in this list of preprints. It comprises of studies focusing on various forms of cell polarity ranging from epithelial polarity, planar cell polarity to front-to-rear polarity.

     



    List by Yamini Ravichandran

    TAGC 2020

    Preprints recently presented at the virtual Allied Genetics Conference, April 22-26, 2020. #TAGC20

     



    List by Maiko Kitaoka, Madhuja Samaddar, Miguel V. Almeida, Sejal Davla, Jennifer Ann Black, Gautam Dey

    3D Gastruloids

    A curated list of preprints related to Gastruloids (in vitro models of early development obtained by 3D aggregation of embryonic cells)

     



    List by Paul Gerald L. Sanchez and Stefano Vianello

    ECFG15 – Fungal biology

    Preprints presented at 15th European Conference on Fungal Genetics 17-20 February 2020 Rome

     



    List by Hiral Shah

    ASCB EMBO Annual Meeting 2019

    A collection of preprints presented at the 2019 ASCB EMBO Meeting in Washington, DC (December 7-11)

     



    List by Madhuja Samaddar, Ramona Jühlen, Amanda Haage, Laura McCormick, Maiko Kitaoka

    EMBL Seeing is Believing – Imaging the Molecular Processes of Life

    Preprints discussed at the 2019 edition of Seeing is Believing, at EMBL Heidelberg from the 9th-12th October 2019

     



    List by Gautam Dey

    Autophagy

    Preprints on autophagy and lysosomal degradation and its role in neurodegeneration and disease. Includes molecular mechanisms, upstream signalling and regulation as well as studies on pharmaceutical interventions to upregulate the process.

     



    List by Sandra Malmgren Hill

    Lung Disease and Regeneration

    This preprint list compiles highlights from the field of lung biology.

     



    List by Rob Hynds

    Cellular metabolism

    A curated list of preprints related to cellular metabolism at Biorxiv by Pablo Ranea Robles from the Prelights community. Special interest on lipid metabolism, peroxisomes and mitochondria.

     



    List by Pablo Ranea Robles

    BSCB/BSDB Annual Meeting 2019

    Preprints presented at the BSCB/BSDB Annual Meeting 2019

     



    List by Gautam Dey

    Biophysical Society Annual Meeting 2019

    Few of the preprints that were discussed in the recent BPS annual meeting at Baltimore, USA

     



    List by Joseph Jose Thottacherry

    ASCB/EMBO Annual Meeting 2018

    This list relates to preprints that were discussed at the recent ASCB conference.

     



    List by Gautam Dey, Amanda Haage
    Close