Tag Archives: Singer lab

Separating cells is hard

I write this entry to accompany my short talk at Woodstock.bio meeting ( #physiologicalirrelevantconference ) .

A few years ago we published a paper in PNAS in which we showed that full-length mRNAs transfer between mammalian cells via a unique type of structure called membrane nanotubes, or tunneling nanotubes (TNTs). This work was started at Rob Singer’s lab, continued at the Gerst lab and in collaboration with Arjun Raj.

I wrote a “behind the scenes” post, detailing how that paper came to be, and some of the problems I had along the way.

I next published a method paper, which also included some new information – in particular that the transferred mRNA is encapsulated in an unknown protein shell. I wrote a “behind the paper” post at the Springer Nature blogs. There, I told about all the problems I had just because a simple change of the cell fixation conditions of my FISH protocol.

The problem is depicted on the right side of my Woodstock.bio slide:

Gal_Haimovich

Very briefly – because the regular FISH protocol leads to TNTs breakage and loss, I decided to increase TNTs stability by adding glutaraldehyde to the fixation buffer. This led to a four-fold increase in TNT preservation. But the transferred mRNA disappeared! It took me a very long time to figure out what’s going on there and partially solve this – at the expense of TNTs’ stability again.  I still have hopes to find a fixative that will preserve the TNTs without affecting the FISH quality.

The left side of the slide depicts our grad student’s greatest achievement – something we’ve been trying to get at over the past six (6!) years. The idea is very simple – co-culture human and mouse cells. After some time, separate then to pure human or mouse cell populations and send for RNA-seq. This should reveal the entire transferome – which human mRNAs are found in the mouse cells and vice versa. As a control, we have a mix of human & mouse cells which were cultured separately, mixed and immediately separated in parallel to the co-culture.

The issue is that we need very high purity. This is because we estimated the amount of transferred mRNA as 1% or less of the endogenous. So if we have 1% donor cell contamination, it will obscure the transferred mRNAs.

For about 2-3 years, I tried to separate the cells with flow cytometry, using various labeling strategies and conditions. But I never managed to get a clear signal of our positive control (MS2-labeled mouse beta-actin mRNA) in co-culture over mix. Then Sandipan Dasgupta joined our lab and instead of FACS sorting, he used affinity purification with magnetic beads to sort the cells. It seemed to be going fairly well. So much so that we also designed an in vivo experiment in mice. We then sent our samples to sequencing only to find out that the sequencing facility had made some mistakes, or there was another problem and all our samples were either contaminated with mouse RNA, or just mixed somehow. That facility closed (we were last in queue ) so there was no way to solve it. But, we also learnt that we probably would not have had enough coverage anyway.

So, Sandi repeated the (in vitro) experiment in order to collect new samples for RNA seq – but we noticed, based on more quality control experiments we did, that the separation was not good enough for us. Although the mouse cells were very pure (99.9%), the human cells always had a small level of mouse cells (98.5% purity of the human cells). Since our expected signal is about 1-2% of the mRNAs being transferred, we could barely see a signal in co-culture compared to mix (1.3-fold).

So, Sandi worked really hard, playing with the conditions until he solved it, and got consistent 99.9% purity of the human cells – just a few months ago. The qRT-PCR result in the slide shows 4-5 fold more human beta-actin mRNA in mouse cells in co-culture compared to mix (we have similar results for the mouse beta-actin mRNA in human cells). The samples were shipped for deep RNA seq (150 million reads per sample) and we are waiting for the results.

We also have more experiments going on – but these stories are for another time.

Maybe we should open a falafel stand” is an actual text from Jeff when we discussed one Saturday evening on Whatsapp about all the problems we encounter in our experiments.

 

 

MS2 mRNA imaging in yeast – problem solved

Previously, on the story of MS2 labeling of mRNA in yeast: Roy Parker published a short letter to the editor, indicating that the MS2 system might cause accumulation of 3′ fragments. We wrote a response, showing that it is not always the case for endogenously expressed mRNAs, but it is exaggerated when over-expressed (Part 1)*. Later, Karsten Weis’s group confirmed Parker’s initial observation but their report still had some questions unanswered, and no solution to the problem; I was unhappy (Part 2).  Now, Evelina Tutucci and Maria Vera together with Jeet Biswas (all from Rob Singer’s lab) seem to have resolved the issue and solved the problem, with the development of the MBS version 6Continue reading

Intercellular mRNA transfer through membrane nanotubes – behind the scenes.

My paper was recently published. I suggest that you read it before reading this post (it is an open access paper). In this paper we show that full-length mRNA molecules can be transferred between mammalian cells through membrane nanotube-like extensions that connect the cells.

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Imaging translation of single mRNAs in live cells

Translating the information encoded in mRNAs into proteins is one of the most basic processes in biology. The mechanism requires a machinery (i.e. ribosomes) and components (mRNA template, charged tRNAs, regulatory factors, energy) that are shared by all organisms on Earth. We’ve learned a great deal about translation over the last century. We know how it works, how it is being regulated at many levels and under varuious conditions. We know the structures of the components. We have drugs that can inhibit translation. With the emergance of next-gen sequencing, we can now perform ribosome profiling and determine exatly which mRNAs are being translated, how many ribosomes occupay each mRNA species and where these ribosomes “sit” on the mRNA, on average. New biochemical approaches like SILAC and PUNCH-P can quantifiy newly synthesized proteins & peptides. Yet, all of that information comes from population studies, typically whole cell populations. Rarely, whole transcriptome/ribosome analysis of a single cell is performed. Still, there is no dynamic information of translation, since cells are fixed and/or lysed. And there is no spatial information regarding where in the cell translation occurs (poor spatial information can be determined if cell fractionation is performed, which is never a perfect separation of organelles/regions and we are still not at the stage of single organelle sequencing).

Imaging translation in single cells is intended to provide both spatial and dynamic information on translation at the single cell and, hopefully, single mRNA molecule resolution. Recently, four papers were published (on the same day!) providing information on translation of single mRNAs. Here is a summary of these papers.

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Does bound MS2 coat protein inhibit mRNA decay?

Roy Parker recently sent a  “Letter to the Editor“, published in RNA journal, in which he suggested that the MS2 system might not be best suited for live imaging of mRNA in budding yeast. According to Parker, the MS2 system inhibits the function of Xrn1, the major cytoplasmic  5′ to 3′ RNA exonuclease in budding yeast, causing us to image mostly the remaining 3’UTR fragments. Thus, he claims, it is possible that interpertation of mRNA localization data using this system in yeast can be faulty. We wrote a response to his letter which just opened the debate even further.

But lets start with his Letter:

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Imaging with CRISPR/Cas9

The hottest buzz-word in biology today is CRISPR: an adaptive immune system in bacteria and archea. At its basis is a nuclease, named Cas9, which is targeted to DNA by a short single-guide RNA (sgRNA). This turned out to be a very useful system for genome engineering in any organism due to its specificity (provided by the sgRNA) and its simplicity (all you need is to express the Cas9 and sgRNA in the cell). However, this system can also be used for other purposes. One such use is modulation of gene expression, for example by targeting a nuclease dead Cas9 (dCas9) fused to a transcription activator or repressor to promoter regions. Another such use is for imaging.

Here, I’ll described how Cas9 can be used to visualize specific DNA loci or specific RNA transcripts in fixed and live cells.

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Visualizing translation: insert TRICK pun here

Unlike transcription, it is much harder to image translation at the single molecule level. The reasons are numerous. For starters, transcription sites (TS) are fairly immobile, whereas mRNAs, ribosomes and proteins move freely in the cytoplasm, often very fast. Then there are only a few TS per nucleus, but multiple mRNAs are translating in the cytoplasm. Next, there’s the issue of signal to noise – at the transcription site, the cell often produces multiple RNAs, thus any tagging on the RNA is amplified at the transcription site.  Last, it is fairly easy to detect the transcription product – RNA – at a single-molecule resolution due to multiple tagging on a single molecule (either by FISH or MS2-like systems). However, it is much more difficult to detect a single protein, be it by fluorescent protein tagging, or other ways (e.g. FabLEMs).

The rate of translation is ~5 amino acids  per second, less than 4 minutes to a protein 1000 amino-acids long. This is faster than the folding and maturation rate of most of even the fastest-folding fluorescent proteins. This means that by the time the protein fluoresce, it already left the ribosome. However, attempts were made in the past with some success.

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