New CRIPSR-based RNA imaging tool

About a year and a half ago I wrote here about new uses of CRISPR/Cas9 as an imaging tool. In particular, I was excited about the possibility to use enzyme-dead Cas9 (dCas9) as an RNA binding protein for live imaging of mRNA. Unfortunately, in my hands this did not work (the dCas9 has exited the nucleus with non-targeting guide RNA at the same rate as with the specific guide RNA).

Last week, a new CRISPR tool was published in Nature, from Feng Zhang’s lab. Briefly, Zhang’s team found in the past a new type of Cas protein which was named C2c2 and later Cas13. Unlike Cas9, which typically binds and cuts DNA, Cas13 specifically binds and cuts RNA. In this paper, they isolated a Cas13a variant from Leptotrichia Wadei (LwaCas13a),  and used it as a programmable tool to knock-down expression. As a tool for knowckdown it is pretty awesome – it is comparable to shRNA in terms of knock-down (~40-90%), but it has three big advantages:

1. Unlike shRNA, LwaCas13a can also target nuclear RNA.

2. It can be used easily for multiplexed knock-down of sereval RNAs.

3. Amazingly, it seems that it has NO OFF-TARGET effect. They used RNA-seq to look at the change in expression level of all RNAs in the cells. Whereas shRNA showed hundreds of off-target knocked-down RNAs, LwaCas13a was very specific and only the targeted mRNA was knocked-down.

They then mutated LwaCas13a to create a dead variant (dLwaCas13a) and asked if it can be used for pull-down assays and for live imaging.

Just like the RNA-dCas9, the pull down efficiency of beta-actin mRNA wasn’t great (2-3 fold over non-targeting guide RNA). However, for Luciferase mRNA, this ratio was better (8-11 fold enrichment). So, this has good potential. Too bad they did not compare it to puul down using MS2-labeling and see if the same proteins are pulled down with the mRNA.

And now I come to my problem with this paper – the imaging.

Just like the RNA-Cas9 paper, they imaged beta-actin mRNA with a single guide RNA and single GFP fused to dLwaCas13a. dLwaCas13a was nuclear localized, but exited the nucleus when specific guide RNA was used. However, they claim only a 3-3.7 fold enrichment of cytoplasmic/nuclear ratio compared to non-targeting guide RNA. They acknowledge that there is neclaer escape due to nuclear off-target binding or other reasons. They added a negative feedback system to improve SNR. Still, the best they got was 3.7-fold. So, if you look at a specific cell – how can you tell if you are looking on RNA-bound or not? you can’t.

They also compared their labeling to FISH staining. Their FISH looks much better than in the RNA-Cas9 paper, really single spots. But to say that it co-localizes? There is more-or less uniform cytoplasmic green staining. Of course it will “co-localize” with the cytoplasmic beta-actin mRNA FISH spots. At the very least they should have done a control with FISH against another highly expressed mRNA (e.g. GAPDH), or perform beta-actin FISH of cells expressing a guide RNA against a differnt mRNA, and not just compare to the non-targeting control.

Last point – stress granules again? I guess it’s just an easy assay to do, that also gets the RNA in a concentrated blob: good if you don’t have single molecule resolution. But nobody really knows what SGs are and only now starting to figure out how and why they form.

They claim that when they induce stress granules (SG) formation, the GFP-dLwaCas13a co-localizes with the SG marker. However, their images are not very good. You see something in Fig 4 (only 2 cells in the control!) but Extended Fig 10 is terrible. Low resolution, small images – can anyone tell from this figure if there is or isnt co-localization, and get some qualitative, if not quantitative sense?

They do provide quantitative data, but although it could be statistically significant, it does not look striking. Really marginal differnece compared to the non-targeting guide RNA (or non-stressed cells).

Is this a good tool for RNA imaging? I don’t think so. Not until you can get single-molecule resolution.



Quantum dots for Immunofluorescence — Rapha-z-lab

An important post on quantum dots:

Guest post by Dave Mason In modern cell biology and light microscopy, immunofluorescence is a workhorse experiment. The same way antibodies can recognise foreign pathogens in an animal, so the specificity of antibodies can be used to label specific targets within the cell. When antibodies are bound to a fluorophore of your choice, and in […]

via Quantum dots for Immunofluorescence — Rapha-z-lab

Poking holes into membranes to label proteins for live imaging

There are two major way to label inner proteins, structures or organnelles for live cell imaging. The most common method is fusing the studied protein to a fluorescent protein. A second approach is the addition of labeling agents from outside the cells. However, many labels cannot penetrate through the cell membrane. This is true to some, but not all dyes, but more importantly, to larger agents, such as antibodies or DNA/RNA oligos. To allow these agents to enter cells, researchers can use microinjection, electroporation, bead-loading, or transfection (e.g. of short oligos).

In a paper just published in eLife, a new technique is described to form temporary holed in the cell membrane. These holes allow delivery of any labeling agent into cells. Continue reading

MS2 mRNA imaging in yeast: more evidence for artefacts

Previously, on the story of MS2 in yeast: Last year, Roy Parker published a short article, in which he claimed that using the MS2 system in yeast causes the accumulation of 3′ RNA fragments, probably due to inhibition of mRNA degradation by the 5′ to 3′ exoribonuclease Xrn1. He argued that these findings put in question all the work on mRNA localization in yeast using the MS2 system. About a year later, we wrote a response to that article. We argued that, yes, such fragments exist, but 1. most of it stems from over-expression of the labeled mRNA. Parker agreed with that. 2. That these fragments accumulate in P-bodies, and are distinguishable from single mRNAs and we can discard cells which show these structures. 3. We argued that this might not be the case for every mRNA and should be tested on a case by case basis.  4. We and Parker agreed that the best way to determine if such fragments exist is by performing single-molecule FISH (smFISH) with double labeling – a set of probes for the length of the mRNA and a set of probes for the MS2 stem-loops. Now, a new paper from Karsten Weis’ lab shows more evidence, by doing smFISH, for the existence of these fragments.

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The Bio-protocol experience

A few months ago, I joined Bio-protocol as an associate editor. The first  protocol I edited is now published, so I thought I’ll write about this experience.


Bio-protocol is an open access, peer-reviewed e-journal which specializes, you guessed it, in publishing life-science protocols. Submission is almost exclusively by formal invitation and it is free of charge (i.e. no submission or publishing fees).

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Roger Tsien – the scientist that colored our research

Roger Tsien died a few days ago, at the relatively young age of 64. He was a UCSD scientist, a Nobel laureate and he was one of the first to see the significance and usefulness of GFP.

I’ve never met him. But, I guess, this blogs owes him its existence.

I don’t want to discuss his body of work, his achievements, or awards he won (e.g. the Nobel award). Many wrote nice things about him, such as here, here or here and all over the internet, with nice pictures of fluorescent proteins used in research.

I thought it will be nice to look back at his first GFP paper.


His goal in this paper was to investigate the formation of the fluorophore of GFP. Specifically, he asked:

“What is the mechanism of fluorophore formation? How does fluorescence relate to protein structure? Can its fluorescence properties be tailored and improved-in particular, to provide a second distinguishable color for comparison of independent proteins and gene expression events?”

Already here he looked to utilize GFP – to improve it, to change it, so it can be useful for fluorescent studies in biology.

He used random mutagenesis of the GFP cDNA to screen for mutants with altered brightness and emission. A simple yet powerful method, still used today, to find new FPs with exciting and useful properties.

Here is an ex/em spectral analysis of some of the mutants:


One mutant, I167T, proved to be almost twice as bright as the WT GFP protein.

But the most exciting was the finding of a blue FP (Y66H):

blue mutant

To sum up in his words:

“The availability of several forms of GFP with such different excitation and emission maxima [the most distinguishable pair being mutant P4 (Y66H) vs. mutant Pll (I167T)] should facilitate two-color assessment of differential gene expression, developmental fate, or protein trafficking. It may also be possible to use these GFP variants analogously to fluorescein and rhodamine to tag interacting proteins or subunits whose association could then be monitored dynamically in intact cells by fluorescence resonance energy transfer (19, 20). Such fluorescence labeling via gene fusion would be site-specific and would eliminate the present need to purify and label proteins in vitro and microinject them into cells.”

He saw the future, and it was bright green.

ResearchBlogging.orgHeim, R., Prasher, D., & Tsien, R. (1994). Wavelength mutations and posttranslational autoxidation of green fluorescent protein. Proceedings of the National Academy of Sciences, 91 (26), 12501-12504 DOI: 10.1073/pnas.91.26.12501

Design guidlines for tandem fluorescent timers

Almost 4 years ago, I wrote a post on tandem fluorescent timers (tFTs). The idea is to have two different fluorescent proteins fused together to the protein of interest. In the paper from 4 years ago, it was superfolder GFP (sfGFP) and mCherry. sfGFP matures very fast (within minutes) and mCherry  matures more slowly (t1/2 ~40min). The ratio beween green to red fluorescent signal indicates the percentage of new vs old proteins, thus acts as a “timer”.  This latests paper on tFTs from the same group of Michael Knop’s lab, found that analyzing tFTs might be more complicated due to some possible problems of this system.

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