Tag Archives: single molecule

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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ASCB15 – part 2

I ended Part 1 after the morning session on pushing the boundaries of imaging.

After the amazing talks on imaging, I browsed the halls, visited some exhibitors, sampled a couple of exhibitor tech-talks. I later went to a mycrosymposium (#2: signaling in health & disease). This was mainly to see how this ePoster thing works, but also I promised Qunxiang Ong – with whom I discussed optogenetics the day before – to be at his presentation. He used a light-induced dimerization of signaling proteins to study the effect on neurite growth. The nice thing in his system was that the cells were plated in wells which were partly dark – so light-induction cannot take place in these regions. This allowed for analysis of neurite growth in lit vs “light-protected” regions of the same cell.

After this session, I attended my first “discussion table”. Continue reading

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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In the right place at the right time: visualizing and understanding mRNA localization

The title of this post is also the title of a review paper that I co-authored  with Adina Buxbaum, a recently graduated PhD student from Rob Singer’s lab. The review was published last week in Nature Reviews Molecular Cell biology.

In this paper we review some of the old and new methods to visualize mRNA. These include mostly FISH and MS2-like systems, which I’ve discussed extensively in this blog. There is also a short section (“box”) on quantitative analysis tools for mRNA localization imaging.

We then discuss the current knowledge on the mechanisms of mRNA localization and how it relates to the biology in two very distinct model systems – unicellular organisms (budding yeast) and the extremely polarized neuronal cell.  We also discuss examples in other organisms from bacteria through fly to frog and mammals.

I’m biased, of course, but I think this turned out to be a balanced, comprehensive, yet not too detailed review paper that will benefit both beginners which are unfamiliar with the RNA localization field, as well as experts which are used to a single method or a single model organism.
ResearchBlogging.orgBuxbaum, A., Haimovich, G., & Singer, R. (2014). In the right place at the right time: visualizing and understanding mRNA localization Nature Reviews Molecular Cell Biology DOI: 10.1038/nrm3918

Transcription caught on camera part 1: Halo transcription factors

Transcription factors (TFs) have a fundamental role is regulating gene expression. The basic model, based on numerous biochemical analyses, has determined where TFs bind (usually at specific sites at or near promoters), when they bind the DNA (at a resolution of minutes/hours) and what do they do there (induce/repress transcription. Duh!).  However, much is yet unknown. One aspect that is fairly unknown is the dynamics of how TFs search for their binding sites, bind them and later dissociate, particularly at the single molecule level. To explore this, the Transcription Imaging Consortium (TIC) at Janelia Research Center (JRC) (it used to be Janelia Farm, but the  “farm” part was removed from the name. oh well) applied sophisticated imaging techniques to measure the dynamics of two TFs, SOX2 and OCT4 in the nuclei of live embryonic stem (ES)cells. Their results were published in Cell almost a year ago.

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sequencing localized RNA in single cells by FISH

To celebrate the 2-year anniversary of this blog, lets talk about the new Science paper in which the authors claim to performs in situ single cell, single molecule  RNA sequencing. So what’s the big deal? Well, RNA sequencing (RNA-Seq) has become a very common method to study gene expression. In many cases, RNA-Seq uses cell extraction from an entire cell population -thus averaging the RNA content of each individual cells. In recent years, single-cell RNA-Seq is becoming more feasible (for example). In this case, cells are sorted via flow cytometry so that one can sort individual cells into designated wells in a multi-well plate. Thus, RNA from a single cell can be sequenced. Though this process is becoming both efficient and accurate, you loose information about the cellular localization of the RNA. FISH is a method that enables to determine the accurate localization of the target mRNA. However, FISH is limited to only a small number of mRNAs. Using color barcoding of the FISH probes can increase the complexity that is achieved (i.e. – one can simultaneously detect multiple types of RNAs) but these are still only a few compared to the entire transcriptome. This new paper in Science combines FISH with RNA sequencing to give Fluorescent in situ sequencing (FISSEQ). How did they do that? First, they generated cDNA by performing reverse-transcription in fixed cells with random primers. The cDNA was then circularized and then amplified. One of the nucleotides has a reactive group so that the cDNA is cross-linked to the surrounding macromolecules. Thus, the cDNA is localized to the same location as the RNA.  The primer has an adapter sequence that can be used as template for sequencing or for FISH. They show some 3D FISH images of cells and tissues using a probe for this adapter. Pretty pictures, but not much info there. From here on, it gets trickier. For the sequencing, they used the SOLiD method. One problem was to reduce the spot density so that it will be sufficiently low to distinguish single molecules. If I understand them correctly, they modified the SOLiD sequencing probes so that the sequencing primers have mismatches that reduce the efficiency. The second problem was to identify auto fluorescence and other fluorescent artifacts in their images. Rather than fine-tuning a specific detection threshold, they relied on the fact that they are monitoring sequences. That means that the fluorescence at each spot should account for a known sequence (i.e. the colors pattern should change based on the sequence), whereas auto fluorescence should remain stable. So, they actually used no threshold at all.

The sequencing reaction cycles and images of the first 15 cycles in primary fibroblasts. Source: Lee JH et. al. (2014) Science 343:1360.

The sequencing reaction cycles and images of the first 15 cycles in primary fibroblasts. Source: Lee JH et. al. (2014) Science 343:1360.

They them showed a few applications of this method. One interesting feature was to show that the nucleus is enriched for non-coding and antisense RNAs compared to the cytoplasm that is enriched with mRNAs. Unfortunately, the nuclear/cytoplasm dichotomy was the only “localization” aspect in their paper. It would have been much more interesting to show mitochondrially-localized vs ER localized vs plasma membrane localized etc… Or, look at highly polarized cells like neurons and use FISSEQ to look at somatic vs dendritic or axonic RNAs. Another experiment they did was to look at the gene expression changes in response to a wound healing model. They found the expected increase in genes related to cell migration, and with some genes differentially expressed only in the migrating cells (at the “wound”) compared to contact inhibited cells that are close to them.  Again, It would have been even better if they could show the subcellular of these mRNAs – are they at focal adhesion sites or other unique sites in the migrating cells? Their results on the whole seem convincing, but I didn’t check all the little technical details.  One thing which is missing is a high resolution image showing the sequencing of just one RNA, compared to an auto fluorescence spot. All their images show one or many cells with multiple spots in different colors – but that is it. The authors say upfront that this is just a demonstration of their method, and that they expect it to improve in coming years, just like what happened with next-generation sequencing. We’ll see… ResearchBlogging.orgLee JH, Daugharthy ER, Scheiman J, Kalhor R, Yang JL, Ferrante TC, Terry R, Jeanty SS, Li C, Amamoto R, Peters DT, Turczyk BM, Marblestone AH, Inverso SA, Bernard A, Mali P, Rios X, Aach J, & Church GM (2014). Highly multiplexed subcellular RNA sequencing in situ. Science (New York, N.Y.), 343 (6177), 1360-3 PMID: 24578530   [post-pub note: this post was also published at the RNA-Seq blog, here].

Feb 2015 – the detailed protocol was published at Nature protocols.

Looking at single mRNAs in neurons hints at memory formation

It is postulated that learning and memory are modulated by synaptic plasticity – molecular changes  that result in changes in the synapse morphology and signaling capacity. Local protein translation is considered important for synaptic plasticity. Two works from our lab were published last month (back to back!) in Science. Both papers deal with how beta-actin mRNA localization and dynamics in neurons may account for local protein translation upon stimulation, and hence, may supply insight into memory formation.

The first paper by Adina Buxbaum shows that beta-actin mRNAs in dendrites are “unmasked” upon activation of the dendrites. Using single molecule FISH, She noticed that the average number of probes bound to the mRNAs in dendrites (but not in adjacent glia cells) was lower than expects, and this number increased upon stimulation. Not only that, there were more mRNAs in the stimulated dendrites. This indicated masking by a protein “coating” that prevented FISH probe binding in the unstimulated cells. A modified FISH protocol which included a protease digestion step prior to probe hybridization showed that indeed the mRNAs were masked by proteins.

single molecule FISH for beta-actin mRNA in dendrites shows that mRNAs in unstimulated neurons are masked. A) Unstimulated neuron. B) stimulated neuron showing increased number of spots. C) Unstimulated neuron, in which the fixed cells were digested with protease prior to FISH probe hybridization. Source: Buxbaum, Wu & Singer (2014). Science Vol. 343  pp. 419-422

single molecule FISH for beta-actin mRNA in dendrites shows that mRNAs in unstimulated neurons are masked. A) Unstimulated neuron. B) stimulated neuron showing increased number of spots. C) Unstimulated neuron, in which the fixed cells were digested with protease prior to FISH probe hybridization. Source: Buxbaum, Wu & Singer (2014). Science Vol. 343 pp. 419-422


She further showed that this masking relates to other mRNAs, as well as to ribosomes, and that this is due to a metabolic process resulting from stimulation. Thus, this unmasking process may be a way to “activate” localized mRNAs for translation.

Apart from being a very neat paper technically and biologically, I think it was exceptionally entertaining to begin her paper by quoting an 1894 work by Cajal, the father of neuroscience.

The second paper by Hye-Yoon Park follows the dynamics of single molecule endogenous beta-actin mRNAs in neurons by live imaging, using the MS2 system. She shows movement of mRNAs along dendrites, as well as some events of merging or splitting – suggesting that some mRNAs are packed together in larger granules – which may regulate local translation. She also looked at brain slices, visualizing beta actin transcription dynamics. This is an important achievement since it is much harder to look at mRNA dynamics in tissue slices than in single cells on plate, due to background fluorescence. Though some biological insight is derived here, this is more of a “new technology” report.

Live imaging of beta-actin mRNAs in dendrites (movie. Source: Park HY et al. (2014) Science Vol. 343 pp. 422-424)

These papers are just the beginning of a long-term story of how mRNA localization and local translation are regulated in neurons.  A lot of cool experiments are being done in our lab in this regard and I’ll report more as they are published.

ResearchBlogging.orgBuxbaum AR, Wu B, & Singer RH (2014). Single β-actin mRNA detection in neurons reveals a mechanism for regulating its translatability. Science (New York, N.Y.), 343 (6169), 419-22 PMID: 24458642
Park HY, Lim H, Yoon YJ, Follenzi A, Nwokafor C, Lopez-Jones M, Meng X, & Singer RH (2014). Visualization of dynamics of single endogenous mRNA labeled in live mouse. Science (New York, N.Y.), 343 (6169), 422-4 PMID: 24458643