Category Archives: Image analysis

ASCB15 – part 3

(part 1, part 2)

I ended part 2 Monday night. It was an exciting day with many excellent talks, but the best talk (mine, of course!) was due the next day.

Tuesday started with the seminar on engineering cells and tissues. There was the mandatory CRISPR talk as the great new thing in bio-engineering these days. Jennifer Doudna talked about the discovery, then went on to discuss new experiments (using Halo-tag to track Cas9 in live cell nuclei to study movement & binding kinetics) and improved technologies (transfect cells with pre-assembled Cas9-gRNA for quick editing & less off-target cleavage).

Continue reading


Using Thresholds to Measure and Quantify Cells in Image J

Using Thresholds to Measure and Quantify Cells in Image J.

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

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.

Don’t eat this FISH-STIC

single molecule FISH (smFISH) is a great way to detect single RNA molecules in fixed cells. The “traditional” FISH uses fluorescently labeled oligonucleotides which directly hybridize with the target RNA sequence. The two most common approaches are the use of 1-5 50-mer oligos, that are labeled with 5 fluorophores, or the use of more than 20 20-mer oligos labeled at one or both ends.
A more recent approach is nicknamed “Christmas tree”, in which 2-3 rounds of hybridizations are done, with only the last round uses fluorescently labeled probed. I’ve expanded on that when I discussed RNAScope.  Other people have independently developed similar protocols (e.g. branched DNA FISH (bDNA), which was recently used to get smFISH transcriptomics in human cells).

Now, a new paper came out with a very similar method whish they call FISH-STIC (Fluorescence In Situ Hybridization with Sequential Tethered and Intertwined ODN Complexes).

However, their images do not compare to the quality shown by the RNAScope or bDNA papers. Maybe its just bad imaging and not the FISH itself, but their images look blurry and doesn’t seem to be up to modern FISH standards. I used 20-mer FISH and can get nicer images.

They also get a few high-intensity spots which the call “mRNA-independent” (since they can also see it outside the cell). To me it means that their protocol was just not optimized – either the washes, or the oligo sequences which should not make complexes like that.

They also seem to have higher background fluorescence compared to RNAScope.

Simultaneous detection of Actb and Actg mRNAs with FISH STIC probes. Source: Sinnamon & Czaplinski (2014) RNA 20:260-266.

Simultaneous detection of Actb and Actg mRNAs with FISH STIC probes. Source: Sinnamon & Czaplinski (2014) RNA 20:260-266.

On the other hand, their beta-actin FISH-STIC looks better than the RNAScope-FISH. beta-actin mRNA is found in 500-2000 copies per cell, so it is not easy to get smFISH. Still, 20-mer FISH that I do looks better than both.

20-mer FISH for beta-actin mRNA in immortalized MEFs. Source: myself.

20-mer FISH for beta-actin mRNA in immortalized MEFs. Source: myself.

Notice also in my image the transcription sites (TS) are clrearly visible, whereas I did not see any TS in their images, which is weird (unless they chose cells without TS on purpose. Don’t know why, since smFISH is a powerful tool to quantify transcription 1, 2).

They did not test FISH-STIC on a less prevalent mRNA, so I cannot comment on how it would look like compared to RNAScope or 20-mer FISH.

Anyway, the methods seem similar, but I think that the RNAScope demonstrates better results than the FISH-STIC. However, I haven’t tried this approach myself. I continue to do FISH with 20-mer probes and so far pleased with my results.

ResearchBlogging.orgSinnamon JR, & Czaplinski K (2014). RNA detection in situ with FISH-STICs. RNA (New York, N.Y.), 20, 260-266 PMID: 24345395
Battich N, Stoeger T, & Pelkmans L (2013). Image-based transcriptomics in thousands of single human cells at single-molecule resolution. Nature methods, 10 (11), 1127-33 PMID: 24097269

Open source microscope & software: openSPIM & Fiji

Just hears a great talk today by Pavel Tomancak from Max-Planck institute. He’s doing amazing work in systematic imaging of fly RNAome & proteome during development. Check out his website (click his name above).

He also talked about Fiji, which an open source software that is just like ImageJ, but with supporting community that develops new scripts & applications.

A most unusual “open source” development that he is very proud about is the openSPIM.

SPIM – Selective Plane Illumination Microscopy – is a microscopy method in which a laser beam sends a narrow light sheet to the specimen, and the objective is at 90 degree from the light sheet (there are SPIM developments with up to 4 objectives that can image from all 4 sides. See here). This type of microscopy is good for imaging thick live specimens (e.g. whole worm, fly or fish embryo etc..). Due to the thickness of the sample, wide field imaging will cause too much background.

So, there are good SPIM microscopes that you can buy from companies like Zeiss. but he developed the openSPIM, which is a build-it-yourself  SPIM microscope, that actually fits into a suitcase (he took it to South-Africa with him to show college & high-school kids). He claims that non-specialist can construct it in one hour. All the details (parts, assembly instructions (“IKEA/Lego style”) are found at the website. The cost, he estimates, is ~40,000$ (with the camera being about half the cost). He claims that the openSPIM is comparable, in quality of images, to commercial SPIM microscopes from 5 years ago.  Pretty good for standard imaging.

I like the idea.

Imaging gene expression – methods & protocols

A new book in the “Methods in molecular biology” series, recently published, contains 23 imaging protocols in three major research areas: gene expression & RNA dynamics, genome & chromatin dynamics, and nuclear process & structures.

book cover: Imaging Gene Expression

This is a fairly good overview of the field and can help both beginners and researchers looking for new ideas.

The book can be freely downloaded.

Here’s the contents of the book:

Continue reading