Chris M. van der Loos discusses how segmentation software can be used to discriminate cell type-specific Ki67 -positive poulations in organs and tissues

Accurate Quantitation of Ki67-positive Proliferating Hepatocytes in Rabbit Liver by a Multicolor Immunohistochemical (IHC) Approach Analyzed with Automated Tissue and Cell Segmentation Software by Chris M. van der Loos, Onno J. de Boer, Claire Mackaaij, Lisette T. Hoekstra, Thomas M. van Gulik, and Joanne Verheij.  J Histochem Cytochem January 2013 61: 11-18, first published on September 1, 2012 doi:10.1369/0022155412461154.

Detail of a rabbit liver tissue section immunohistochemistry (IHC) triple staining in the different stages of automated analysis.

Detail of a rabbit liver tissue section immunohistochemistry (IHC) triple staining in the different stages of automated analysis.

ABSTRACT: Determination of hepatocyte proliferation activity is hampered by the presence of Ki67-positive non-parenchymal cells. We validated a multicolor immunohistochemical (IHC) approach using multispectral tissue and cell segmentation software. Portal vein branches to the cranial liver lobes of 10 rabbits were embolized, leading to atrophy of the cranial lobes and hyperplasia of the caudal lobes. Slides from cranial and caudal lobes (n=20) were double-stained (CK8+18 and Ki67) and triple-stained (CK8+18, Ki67, and CD31). The Ki67 proliferation index was calculated using automated tissue and cell segmentation software and compared with manual counting by two independent observers. A substantial variation was seen in the number of Ki67-positive hepatocytes in the different specimens in both double and triple staining (range, 0–50). Correlation coefficients between manual counting and the digital analysis were 0.76 for observer 1 (p<0.001) and 0.78 for observer 2 (p<0.001) with double staining and R 2 = 0.91 for observer 1 and R 2 = 0.89 for observer 2, p<0.001 with triple staining. In conclusion, in rabbit, the hepatocellular proliferation index can be reliably determined using automated tissue and cell segmentation software in combination with IHC multiple staining. Our findings may be useful in clinical practice when Ki67 proliferation index yields prognostic significance.

How would you best summarize the content of your paper?

Both Ki67-positive hepatocytes and non-parenchymal Ki67-positive cells can be found in a rabbit liver regeneration model. Non-parenchymal cells, including leucocytes in the sinusoidal space, may compromise accurate evaluation of the percentage of Ki67-positive proliferating hepatocytes. To obtain a more precise measurement of the hepatocyte proliferation index, a triple IHC staining was performed which marked the relevant cell types: CD31 (endothelial cells for delineation of the sinusoidal space), cytokeratin 8/18 (hepatocytes), Ki67 (proliferating cells), and hematoxylin (all nuclei).  Machine-learning image segmentation software was used to identify and quantitate the co-expression of Ki67-positive nuclei and cytoplasmic cytokeratin 8/18 for evaluation of the hepatocellular proliferation index. Time-consuming manual counting of Ki67-positive hepatocytes and this fast new digital analysis showed a very high correlation coefficient.

How did you get interested in this project/field?

I am interested in multicolor IHC from the early 1980’ties. The visual observation of different colors, including co-localization by mixed-colors, had its obvious restrictions and drawbacks. The introduction of a commercially system for spectral imaging in 2004 was a huge step forward. This allowed unmixing of multicolor tissue samples based on the spectral characteristics of chromogens/dyes. The resulting component images are fit for standard imaging tools and when combining component images also for exclusively showing co-localization. The next step forward is the unique software we used in our paper that first performs spectral unmixing, next segments tissue elements either by hand or by machine-learning interface, and then segments down to cell level. The final result is a cell-by-cell observation that comes close to FACS, but now performed on an image of a tissue section.

How might your paper contribute to the relevant fields related to your paper?

In the paper we have already speculated on a pathology application where exact measurement of proliferating tumor cells in tissue sections is relevant. For example, the Ki67 proliferation index is required for grading purposes of different tumor types, such as neuro-endocrine tumors and neoplasms of the central nervous system. These are tumors in which a substantial number of tumor infiltrating lymphocytes can be found which hampers reliable determination of the proliferation index when only single-staining for Ki67 is used. This problem looks pretty similar with the situation we had in the rabbit liver, and can hopefully be solved in a similar way.

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Akihiro Hosoya on Two Distinct Processes of Bone-like Tissue Formation by Dental Pulp Cells after Tooth Transplantation

Two Distinct Processes of Bone-like Tissue Formation by Dental Pulp Cells after Tooth Transplantation by Akihiro Hosoya, Akira Yukita, Kunihiko Yoshiba, Nagako Yoshiba, Masafumi Takahashi, and Hiroaki Nakamura.
J Histochem Cytochem November 2012 60: 861-873, first published on August 16, 2012 doi:10.1369/0022155412459741

J Histochem Cytochem  60(11) 861-73, Figure 7.ppt

Abstract:

Dental pulp is involved in the formation of bone-like tissue in response to external stimuli. However, the origin of osteoblast-like cells constructing this tissue and the mechanism of their induction remain unknown. We therefore evaluated pulp mineralization induced by transplantation of a green fluorescent protein (GFP)–labeled tooth into a GFP-negative hypodermis of host rats. Five days after the transplantation, the upper pulp cavity became necrotic; however, cell-rich hard tissue was observed adjacent to dentin at the root apex. At 10 days, woven bone-like tissue was formed apart from the dentin in the upper pulp. After 20 days, these hard tissues expanded and became histologically similar to bone. GFP immunoreactivity was detected in the hard tissue-forming cells within the root apex as well as in the upper pulp. Furthermore, immunohistochemical observation of α–smooth muscle actin, a marker for undifferentiated cells, showed a positive reaction in cells surrounding this bone-like tissue within the upper pulp but not in those within the root apex. Immunoreactivities of Smad4, Runx2, and Osterix were detected in the hard tissue-forming cells within both areas. These results collectively suggest that the dental pulp contains various types of osteoblast progenitors and that these cells might thus induce bone-like tissue in severely injured pulp.

How would you best summarize the content of your paper?

While dental pulp is involved in the formation of bone-like tissue following various external stimuli, the origin of osteoblast-like cells and the process of their differentiation are still unclear. In this study, to clarify the source of these osteoblast-like cells, we transplanted green fluorescent protein (GFP)-labeled rat molars into the hypodermis of normal host rats. At 5 days after the transplantation, the upper region of the pulp was necrotic; however, cell-rich hard tissue was found on the surface of the dentin at the root apex. At 10 days, woven bone-like tissue also formed apart from the dentin in the upper pulp. After 20 days, these hard tissues expanded within the pulp cavity and became histologically similar to bone. GFP immunoreactivity was confirmed in the osteoblast-like cells within the root apex as well as in the upper pulp. Furthermore, immunohistochemical observation of alpha-smooth muscle actin, a marker for undifferentiated cells, showed a positive reaction in cells surrounding this bone-like tissue within the upper pulp, but not in those within the root apex. Immunoreactivities of Smad4, Runx2, and Osterix were detected in the hard tissue-forming cells within both areas. These results suggest that bone-like tissues induced by tooth transplantation have originated from 2 different types of dental pulp cells, and thus a wide variety of dental pulp cells might participate in pulp regeneration.

How did you get interested in this project?

Previously, we reported that cell-rich hard tissues were induced in the pulp cavity of rat molars after tooth transplantation and replantation. These hard tissues were shown to be immunonegative for dentin sialoprotein, a protein highly specific to dentin, suggesting that their matrix property resembled that of bone. However, the cell origin of the bone-producing osteoblasts was still unknown. Two hypotheses regarding this origin can be proposed to explain their involvement in pulp regeneration. One is that undifferentiated cells in the dental pulp differentiate into osteoblasts. This possibility is supported by an earlier report indicating that multipotent stem cells exist within the dental pulp of human deciduous and permanent teeth. The second hypothesis is that mesenchymal cells migrate via vascular channels from outside of the pulp, and differentiate there into osteoblasts. Therefore, in this study, to differentiate between the above hypotheses, we evaluated bone-like tissue formation by using GFP-labeled rat molars.

Can this work be considered relevant as translational research?

Mineralization in the dental pulp is an important phenomenon as a reparative process to external stimuli. Many reports have described reparative dentin or dentin bridge formation after caries attack, cavity preparation, and direct pulp capping in dental practices. Also of interest, there is the fact that bone-like tissue is formed in developing tooth pulp after trauma and tooth replantation. In this study, we showed that the dental pulp contains various types of osteoblast progenitors and that these cells are able to induce mineralized bone-like tissue in severely injured pulp. These results support the importance of maintaining pulpal vitality and function, and suggest that dental pulp cells might be useful in a variety of tissue-engineering applications for use as hard tissue-forming cells.

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Killingsworth et al. Reveal the Distribution of Somatostatin in Somatostatinoma by Correlated Epifluorescence, Super-resolution and Immunoelectron Microscopy

Murray C. Killingsworth discusses his article “Quantum Dot Immunocytochemical Localization of Somatostatin in Somatostatinoma by Widefield Epifluorescence, Super-resolution Light, and Immunoelectron Microscopy” from the November 2012 JHC. We have included the abstract for reference. The full article may be found on the the JHC website: http://jhc.sagepub.com/

Abstract:
Quantum dot nanocrystal probes (QDs) have been used for detection of somatostatin hormone in secretory granules of somatostatinoma tumor cells by immunofluorescence light microscopy, super-resolution light microscopy, and immunoelectron microscopy. Immunostaining for all modalities was done using sections taken from an epoxy resin-embedded tissue specimen and a similar labeling protocol. This approach allowed assessment of labeling at light microscopy level before examination at super-resolution and electron microscopy level and was a significant aid in interpretation. Etching of ultrathin sections with saturated sodium metaperiodate was a critical step presumably able to retrieve some tissue antigenicity masked by processing in epoxy resin. Immunofluorescence microscopy of QD-immunolabeled sections showed somatostatin hormone localization in cytoplasmic granules. Some variable staining of tumor gland-like structures appeared related to granule maturity and dispersal of granule contents within the tumor cell cytoplasm. Super-resolution light microscopy demonstrated localization of somatostatin within individual secretory granules to be heterogeneous, and this staining pattern was confirmed by immunoelectron microscopy.

1. How would you best summarize the content of your paper?
I hope this work demonstrates the potential use of nanoparticles as probes to localize target structures in the cell cytoplasm. We were able to apply quantum dot nanocrystals as immunocytochemical probes for somatatostatin hormone in human tumor cells. We then used three different microscopy modalities to view them with increasing resolution.

2. How did you get interested in this project/field?
I have been interested in immunocytochemistry since attending a cryoultramicrotomy course with Professor H. Sitte in Seefeld, Austria in 1983 and I became interested in quantum dots after learning of their properties from the physicist Professor David Cockayne at a microscopy meeting in the 1990s.

3. How will other scientists be able to apply your work to advance the field and what is the future of this field of research?
Our work should be easily reproducible but the challenge lies in using the approach to label other antigens. We used a polyclonal antibody probe but have had some difficulty in getting monoclonal antibody probes to work. I feel that advances in antigen retrieval processing will gradually expand the range of antigens for which this approach is useful.

4. What is the next step in your research?
Quantum dot nanocrystals are very small at 3 – 6 nm so the next step in our research is to try to visualize the probes more efficiently by transmission electron microscopy. Perhaps compositional mapping will be the answer?

5. Of scientists living and dead, who would you most likely want to collaborate with?
Professor K. T. Tokuyasu a great scientist and innovator in the field of immunocytochemistry.

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Velia M Fowler Discusses her work on Tropomodulin1 and her article in JHC titled “Tropomodulin 1 Constrains Fiber Cell Geometry during Elongation and Maturation in the Lens Cortex”

Velia M. Fowler was kind enough to give us some in-depth answers to our questions about her research for the article  “Tropomodulin1 is required for membrane skeleton organization and hexagonal geometry of fiber cells in the mouse lens,” which she co-authored with Roberta B. Nowak in J Histochem Cytochem June 2012 60: 414-427, doi:10.1369/0022155412440881.

Tell us about your work?
I want to begin with some background. This study is about the hexagonal packing geometry of cells in the eye lens. We got interested in this problem because we were studying the actin cytoskeleton, and how it links to the plasma membrane. We made a knockout mouse, to delete one of the actin binding proteins of this membrane- associated actin cytoskeleton (tropomodulin) and found that there was a disruption in the hexagonal packing geometry of the fiber cells of the eye lens. Our first observation1. was published in the Journal of Cell Biology, where we reported the disordered packing of the lens fiber cells, and by doing some biochemistry, we also characterized the disruptions in the actin cytoskeleton in the mutant lenses.

Getting back to the hexagonal geometry of lens cells. The lens cells are very long and thin and stretch from the front to the back of the eye lens. If you cut the lens at the equator so that you can see how the cells are packed geometrically together, you see that they are packed in this beautiful hexagonal packing pattern. This is the most perfect hexagonal packing geometry of any tissue that we know of; certainly the most perfect in a vertebrate, although in invertebrates, the Drosophila eye is exquisitely regular as well.

Since we had discovered this defect in the hexagonal packing, I got interested in that problem and started doing lots of reading about it — the field that studies this mostly is the developmental biology field of epithelial morphogenesis, for example, in flies.  In certain stages of embryonic development, there are movements of epithelial sheets during dorsal closure or germ band elongation, where the cells change their shape and their packing geometry and rearrange. There is a huge amount of work in this area showing that cell adhesion and mechanical forces influence the packing geometry.

I think, that’s the bigger picture area that our work is related to, the broader area of cell biology. Also, these movements of epithelia sheets happen in vertebrates during gastrulation, it’s not just something that happens in invertebrate embryos. In our study that’s published in JHC, we wanted to see what the extent of the hexagonal packing disruption really was, we wanted to quantify it. Basically, we had observed these disordered cells in the lens sections but we didn’t know whether all the cells were disordered, what percent of the cells were disordered, and just how disordered were they.

Now the field of epithelial morphogenesis that I mentioned earlier has developed computational image analysis software in order to actually count the number of nearest neighbors each cell has in order to define their nearest neighbors. We had a summer student come to the lab, he was an external Masters student from Strasbourg, France, and his project for the summer was to apply this software that was developed for a completely different problem to our images of the lens. That was one of the things that we worked on and we found that the disordered packing of the cells was only in patches and not in all the cells. That was a major finding that the disorder was in patches and the other major finding was that these patches arise as the cells mature and get older. So, now I need to tell you that the lens cells form on the outside of the lens and then the cells elongate and are laid down like layers of an onion, and they are laid down in this perfect register with this hexagonal packing pattern. We looked in these sections at the youngest cells, which are on the outside and then a little further in older, older, and older cells and we could see that these patches of disorder were very infrequent in the outer layers of cells and they became more abundant as the cells moved inward and matured, and also the patches became larger.

The summer student from France, Martin Dressler, although not an author on the paper, made a very important contribution to the study in working out the computational analyses. He was thinking along the lines of mechanical forces and how they affect hexagonal packing. Now here is where we get into a whole other area that is another basis for the study and contains the conceptual underpinnings of our ideas.

There are physicists that study hexagonal packing in nature and it turns out that soap bubbles, the lowest energy form of packing is hexagonal, a hexagonal geometry, which is true for many objects. If you have a lot of spheres and you put them together, they are going to fit together best in a hexagonal packing geometry. This area of physics talks a lot about minimizing forces, minimizing energies of interactions and so taking from that field, we’re thinking about forces and the people studying the fly epithelial sheets are also thinking about these forces.

From these ideas, we conceptualized that the changes in the packing from no disordered patches and very small patches to bigger patches as being due to the mechanical stresses on the cells in the lens as the lens is growing and getting bigger.   The idea is that there would be more physical forces pushing on them due to the size of the lens as they get packed into the center, as well pulling forces on the lens from the extracellular fibers which attach to the outside of the lens capsule and hold the lens in the eye.  There are also osmotic pressure forces in the lens, due to water fluid flowpumps and channels, which can create mechanical forces.  Thus, maybe in a normal lenses, a wild-type lens, the cells have a cytoskeleton that can exert tension against these forces and keep them balanced and keep the cells packed properly in a symmetric hexagonal pattern, but in the knock out lens where the cytoskeleton is disrupted, the cells cannot resist the forces, leading to asymmetric distributions of forces, and this leads to disordered cell slippage and disordered packing. That’s kind of a long way to describe the main points of the study!

My lab (http://www.scripps.edu/fowler/) is basically a cell and developmental biology lab, and we’re also interested in physiology, but we like and are drawn to the study of order in biological systems with a precise geometric organization. We’ve trying to understand how molecules and cells that are normally not like this become constrained to assume these beautiful arrangements. So the lens is one of the systems that we study. We also study muscle which has a precisely organized arrangement of sarcomeres and myofibrils that’s very important for contraction, just as a side point. But in all the systems I study, we are interested in how molecules can impose order on chaos, basically. And it’s interesting, at least in this field of hexagonal packing, the physicists think that it uses basic principles of minimizing energy, in order to achieve ordered geometric packing.

How will this paper contribute to relevant fields?
Most people that will be interested in this paper will be people studying the lens. Probably not people studying the fly morphogenesis because we drew from them rather than they drawing from us.  In the lens field, outside of the concepts that I discussed above, one of the main advances of this paper is applying quantitative methods to measure the disorder and irregularity in these lens cells. Other people studying lens fiber cell organization have sometimes gotten a mouse knockout where they’ve seen the disordered packing but nobody has quantified anything. We have developed some relatively simple methods to quantify the percent of disorder in the lens, which actually is already being used by some other lens researchers. First that’s really nice to see, but then hopefully, when more people apply these approaches to their mouse lens mutants we will be able to understand, looking at a bigger picture, what controls the regular geometry of lens cell packing.

Now why do we care whether fiber cells are disordered? There is a general hypothesis in the lens field that the ordered packing of the cells is essential for the clarity of the lens. So the idea is that if you have disorganized cells with altered spaces between them and irregularity, then you are going to get more light scattering and that could be leading you to having a cataract. It could underlie some of the human cataracts. But, if we can’t quantify the percent of disorder, we’re never going to be able to figure out how much disorder can the lens tolerate before it starts to scatter light and result in opacities that lead to cataracts. I think in the long view, that by applying these quantitative methods, we’re going to be able to quantitatively correlate cellular organization to the degree of light scattering to understand how the cellular organization contributes to lens transparency. Looking forward, that is one of the main applications of what we have done.

Are you going to continue working in this particular field?
One unsolved questions is that the mouse knockout we have been studying, was created to delete the actin binding protein tropomodulin that we’ve been studying for years, but this deletion turned out to be on a background of a mutation in an intermediate filament protein. So there’s always been the question of to what extent does the absence of the special lens-specific intermediate filament protein contribute to the defects in the actin cytoskeleton due to the absence of the tropomodulin?  A study we are working on now and have nearly completed compares the four different genotypes:  wild type lenses, lens missing only the tropomodulin that have a disruption of the actin cytoskeleton, then lenses missing only the intermediate filament protein, and lenses missing both the tropomodulin and the intermediate filament protein. Thus, we are comparing two single knockouts and a double knockout with the wild-type lenses.  This study uses the same methods that we developed here in the JHC study to quantify the amount of disorder, and also uses some additional approaches to quantify the degree of transparency. Basically, we’re trying to get a better handle on what’s causing what.

Then additionally, we have added on another set of assays to look at lens resilience. The lens transmits light so you can see and you can focus on objects and in order to focus, it has to change shape, as opposed to a microscope lens. A microscope lens does not change shape, it’s a fixed shape and it moves up and down in order to focus on near or distant objects. But in the human eye, we don’t move our lens back and forth, our lens actually changes shape to focus on a close object or a faraway object. This change in length and shape requires a certain degree of flexibility and resilience in the lens.  Now the mouse lens doesn’t actually change it’s shape but it likely does have resiliency properties that are similar to primate’s lenses. So we looked at the mechanics of the lens from our single and double knockouts, and basically we ended up finding that the transparency, the disorder and the mechanics are determined synergistically by the two cytoskeletons, and that none of these biological properties are really independent of the other ones. So the work just got really complicated.

Did that make sense to you as a scientist that they would be synergistic or did that surprise you?

As a scientist it makes sense, since there are a lot of proteins that have been discovered in the last ten years that link between actin filaments and intermediate filaments.  Although the tropomodulin protein we are investigating is different in that it is a small protein and the other linkers are very large, it could still be linking actin filaments to intermediate filaments. As a scientist, this totally makes sense and what you are really talking about is structural cross-talk between two different cytoskeletal systems, similar to signaling. That all makes sense to me but I was really hoping there wouldn’t be because it is very expensive to maintain all these lines of mice and now I find that I have to study a lot more mice than I thought I would study. and where I thought I could actually narrow my focus, instead I have to broaden my focus. So it is more expensive and a bigger field of literature, reagents etc. However, it is very interesting!

This goes back to fields of research tending to be very narrow because we want to simplify things and because we have this principle of reductionism, scientific reductionism, where we would like to find the root cause and we would like it to be one gene or one protein or one interaction and then we can study that in great detail. In reality however, for any cell or tissue in your body, there are many interacting systems both in signaling pathways with cross-talk, and in structural systems where things are connected to one another in order to accomplish the purpose of the tissue.  In general, you are seeing all fields moving past reductionism to try and understand what are the connections between systems and what is the meaning of it. So again, while we don’t study the signaling pathways where cross-talk is well-established, we study the structural linkages and I think my work is moving in that direction.

I would like to end by noting that future studies in the lens and other tissues will involve looking at the cross talk and interactions between structural networks that achieve different functions in the tissues. For example, a contracting muscle uses  actin and myosin filaments in sarcomeres to generate forces, but the contracting sarcomeres are attached to the edge of the cell with intermediate filaments–  otherwise the muscle can’t actually move anything and you’re not going to go anywhere.  Similarly, in the lens, you need to link the systems in order to accomplish the goals of fiber cell organization, for transparency and for mechanical resiliency.

If you think of other areas such as genomics, a good comparison for readers is the field of bioinformatics. Bioinformatics is a huge growing area of systems biology; these are ways to look at connections between gene expression, and between different mutations. That’s another type of investigation, but again it’s focusing on the systems and the connections and we’re trying to do a similar thing on a structural level.

Tropomodulin1 is required for membrane skeleton organization and hexagonal geometry of fiber cells in the mouse lens by Roberta B. Nowak, Rebecca K. Zoltoski, Jerome R. Kuszak, and Velia M. Fowler
J Cell Biol 2009 186:915-928. Published September 14, 2009, doi:10.1083/jcb.200905065

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Quantum Dots in Cell Biology

We’re back from a end of summer break. This week we have Margarida Barroso discussing her review of Quantum Dots in Cell Biology. Her review was first published in JHC in March of 2011.

My paper is a review of Quantum Dots in cell biology. First of all, I tried to give an idea of what Quantum Dots are and then how do they fit in applications that are important for cell biologists. So I wasn’t interested so much in their physical characteristics but more in how they apply to certain important applications.  And the two main applications that I talked about are tracking, the ability of tracking of organelles or particles throughout the cell and FRET, Fluorescence resonance energy transfer meaning the ability to detect when two proteins interact with each other. Quantum Dots have characteristics that make them very useful for these applications and I tried to give an idea of the pros and cons of their use in these applications.

How I became interested in this research was sort of serendipitous. I’m interested in imaging, the ability to follow or label certain compartments in the cells and the proteins in the cells and follow their activities and functions, localization and distributions in the cell, and so one of issues in that is the ability to label proteins at a very high efficiency, a very high brightness. To do this we need to have fluorophores or dyes that label the proteins at a very high brightness. So that is an issue in imaging and when Quantum Dots came in, one of their advantages is that they are very bright. Their quantum field is very high and they are very bright. Well that caught my curiosity and by pure chance, one of the first companies that was producing them was right next to me in my neighborhood here in Albany New York. We started talking and I got some samples and that’s how I started working with Quantum Dots.

I had hoped with this paper to raise some questions and get people interested in using different fluorophores, well in this case quantum dots and understand that nothing in imaging comes with only positives or only negatives. Quantum Dots have lots of advantages in imaging but there are negatives as well which need to be taken into consideration. The other things that is interesting in imaging is normally, at some point, those negatives in imaging can be used by very clever people as advantages. You actually need to have a good knowledge and deep knowledge of the advantages and the disadvantages of the characteristics of what you are using so that you can take full and complete advantage of them in your applications.
Some things that initially may look very negative may in the end be very positive. For example, for Quantum Dots, Quantum Dots blink, they go through stages of darkness while they are being imaged and that in principle is a negative because we can lose track of what we are imaging as suddenly the Quantum Dot goes dark.  However, researchers have used this characteristic to apply high resolution imaging to increase the visualize the distribution of quantum dot labeled proteins in nanometer scale.  Therefore, this seemingly negative characteristic becomes an advantage to develop even more interesting techniques for imaging.

Image

(A) Generation of transferrin (Tfn)–quantum dot (QD) bioconjugates. (B) Two molecules of Tfn (iron bound; asterisks) bind each transferrin receptor (TFR) dimer at the plasma membrane. In this particular example, one QD–Tfn and one unlabeled Tfn bind a TFR dimer. (C) TFR–Tfn complexes are internalized via clathrin-coated pits (CCP) and delivered to endosomes by clathrin-coated vesicles. Upon endosome acidification, iron is released from Tfn, and then the TFR–Tfn complexes are recycled back to the plasma membrane (PM) via recycling endosomes. (D) Endocytic uptake of Tfn–QD580 leads to a tubulo-vesicular staining throughout the cell. Confocal images were collected via a vertical z-scan with a 1-µm interval. Copyright by The Histochemical Society.

How this will advance in the future depends on developments in chemistry. With regards to Quantum Dots, what is at issue is their size. Quantum Dots can be up to ten nanometers, larger, that can be a little too big in terms of cells and protein interaction.  So making them smaller is important, and in some cases, we would like Quantum Dots that do not blink, removing that characteristic would also be a positive. Additionally, making them brighter so it would be easier to label proteins.

Now there is an important thing to consider when comparing Quantum Dots and dyes, that is small organic dyes. Multiple small organic dyes labelone protein so that one protein will have two or three dyes labeling it. With Quantum Dots, it is the opposite. Because of their size, you may have multiple proteins bound to one Quantum Dot. It would be nice to have the ability to quantitate that, to have a way to get one Quantum Dot per protein or if you want a specific number of proteins per Quantum Dot, etc. Right now, it’s not straightforward to do that. However, again a negative for some applications can be a positive for others, and one can use this characteristic of QDs to study the cross-linking of membrane bound receptors.

The other thing is to improve the coats of the Quantum Dots and reduce the non specific binding which is an issue. So there are some technological advances, mostly chemistry that would make Quantum dots more useful for cell biologists. At the same time, cell biologists have to understand how Quantum Dots work and use them to their advantage. In terms of that, for the future if we could for example use them for tracking a certain protein and at the same time following with FRET the interaction of that protein with another protein, then we would be doing two techniques at the same time. Not only tracking a protein along a certain process within the cell but also tracking it as it interacts with another protein within the cell. That was the idea from the start with this paper that this would be something very interesting in the future if we could use these type of probes to be able to not only bring two approaches in cell biology together; one to track a protein and the other one to track their interaction with another protein. Right now we cannot easily do that in the same experiment. In the future, I can see us doing that at the same time, simultaneously.

In terms of this paper being considered translational research, not so much. This paper is written on a very basic cell biology approach but one should not forget that a lot of the proteins that are tracked by imaging approaches in cells are receptors, member bound receptors and also FRET, allows us to determine whether those receptors dimerize or oligomerize . So these are techniques that provide information about the function and activity of receptors which are involved in very important processes such as cancer and neurotransmission and other things like that so at some point it will be translatable but not directly.

I worked at the University of Virginia so I must answer the question about whether Thomas Jefferson would understand my work. And I would say yes, if we talk in terms of the ability to track something and the idea of interactions between things, everyone understands that. We do that routinely in our lives, we follow people around, we follow cars around or we see people interacting, talking to one another in the cafeteria. Well that’s what we are trying to do with our technology for imaging proteins, we are trying to see where does this protein go and what does it talk to. We do this routinely in social interactions and we hardly even notice but for proteins it’s very hard to do it, you have to understand we are in the dark once we look at the cell and the mixture of proteins in the cell, it’s like you are in a dark room, we don’t see anything. We must label things, we have to turn on some lights so that we can actually see something and follow it. But again, if we just label one thing, we are just seeing a light moving around in a dark room, it’s kind of meaningless. We need to provide some reference and that’s what we are doing. Seeing where something (protein) is going and what it is talking to and interacting with and anyone can understand that.

Quantum Dots in Cell Biology by Margarida M. Barroso
J Histochem Cytochem March 2011 59: 237-251, doi:10.1369/0022155411398487

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Mun-Yong Lee discusses his article “Sustained Expression of Osteopontin Is Closely Associated with Calcium Deposits in the Rat Hippocampus After Transient Forebrain Ischemia”

This week we have a post from Dr. Mun-Yong lee that includes a description of his article. We have also included an image from the paper.

Ultrastructural localization of osteopontin (OPN) by the immunogold-silver method in the CA1 region at 4 weeks following ischemia. (A, B) Silver grains indicative of OPN accumulated along the surface of electron-dense calcified deposits, which were irregular in shape and size and were located extracellularly surrounded by a large amount of cellular debris. Note that these deposits showed increased electron density at the periphery and sometimes contained degenerated mitochondria (arrowheads in B). (C, D) OPN-labeled deposits were observed within the soma (arrowheads in C) and dendrites (arrowheads in D) of degenerating neurons containing several lipid inclusions (arrows in C, D). nu, nucleus. (Inset in D) Higher magnification view of the boxed area in D. Note that silver grains were evenly localized within the intracellular deposit. (E, F) Some astrocytes contained lipid inclusions (arrow in E) and multiple OPN-labeled deposits, some of which were closely associated with glial filaments (f in F). (Inset in E) Higher magnification view of the boxed area in E. Note that silver grains were rather diffusely localized in the intracellular deposit. Scale bars A, C-E = 4µm; B and F = 1µm; D and E Insets = 0.5µm

Please give us a brief description of the major findings of your paper?

1) The OPN protein accumulated profusely along the surface of diverse types of calcium deposits, ranging from small intracellular deposits to large extracellular conglomerates.
2) The labeled calcium deposits appeared to be gradually phagocytized by microglia/brain macrophages and some astrocytes over 8–12 weeks after ischemia.

What qualities do you look for in a prospective postdoctoral fellow to work in your lab?

It is when one works as a Postdoctoral fellow that he or she can most passionately and purely focus on their research. So I expect to see integrity and passion from them. A Postdoctoral fellow should have an active, rather than passive, attitude that initiates a driving force in the lab. It is also essential for them to have an uncompromising suspicion, even if it were about a firmly established conclusion. A skeptical view leads to a stronger confirmation. At the basis, however, I expect a kind heart and willingness to listen to fellow workers and graduate students. After all, a reliable worker with whom I can share my passion is what I ask for.

Can this work be considered relevant as translational research?

Our data suggest that OPN initially physically inhibits crystal growth, and simultaneously provides a recognition site and/or concentration gradient for macrophages, thereby leading to acidification and dissolution of calcium. These results can provide the basic mechanisms of pathogenesis, cellular mechanism of neural repair during acute and repair phases after stroke and raise therapeutic possibilities of OPN which can be involved in phagocytosis of ischemic debris, and in the regulation of ectopic calcification in the ischemic brain.

Sustained Expression of Osteopontin Is Closely Associated with Calcium Deposits in the Rat Hippocampus After Transient Forebrain Ischemia By  Jang-Mi Park, Yoo-Jin Shin, Hong Lim Kim, Jeong Min Cho, and Mun-Yong Lee. J Histochem Cytochem July 2012 60: 550-559, first published on April 11, 2012 doi:10.1369/0022155412441707

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Peter Nagy on trastuzumab resistance in the treatment of ErbB2-overexpressing breast cancer

Before leaving on vacation, Peter Nagy emailed us answers to our questions about his work that was published in the August issue of JHC. We have also included an image from the paper that Dr. Nagy feels best exemplifies the work.

1. How would you best summarize the content of your paper?
Although the anti-ErbB2 antibody, trastuzumab, significantly improves the treatability of ErbB2-overexpressing breast cancer, some tumors don’t respond to it from the beginning, while others acquire resistance during treatment. Several mechanisms have been proposed to explain resistance. Previously we have found in cultured cells and experimental animals that overproduction of hyaluronan leads to masking of the trastuzumab binding epitope on ErbB2 and diminished binding of the antibody. However, confirmation of these findings was missing for human subjects. This is what we have done in the current paper. We have analyzed frozen tissue sections of ErbB2-overexpressing breast cancer removed during surgery. The binding of fluorescent trastuzumab was measured by confocal microscopy and it was normalized to the expression level of ErbB2 which was also evaluated by fluorescent staining. We correlated normalized trastuzumab binding to the pericellular density of hyaluronan also measured fluorescently. The key to the successful completion of the project was to perform quantitative image analysis restricted to the plasma membrane. The most important finding was that the normalized binding of trastuzumab was negatively correlated with the pericellular density of hyaluronan, and hyaluronidase digestion of the tissue sections with high hyaluronan expression significantly improved trastuzumab binding. These results strongly suggest that hyaluronan overproduction inhibits trastuzumab binding in breast cancer patients and may give rise to resistance.

2. How might your paper contribute to the relevant fields related to your paper?
Finding factors predicting trastuzumab resistance is important from the clinical point of view. Hyaluronan can be fluorescently stained, and therefore could be analyzed in clinical samples. Many effects have already been attributed to hyaluronan regarding oncogenesis. Our findings add epitope masking to this list.

3. How will other scientists be able to apply your work to advance the field and what is the future of this field of research?
Not only scientists, but also practicing pathologists can benefit from our findings. Although to the best of my knowledge the quantitative analysis of hyaluronan levels and its location (pericellular or not) hasn’t been validated for clinical work, this would be an important thing. I think quantitative analysis, in general, is an important concept which hasn’t gained wide recognition either in the field of translational research or clinical routine. While the importance of an increasing number of signaling pathways is revealed in carcinogenesis we still describe oncogene expression on a “present-absent” scale. Designing effective treatments tailored to the expression profile of a patient will require a more quantitative approach.

Representative images showing the anticorrelation between hyaluronan density and trastuzumab binding. Tissue samples were labeled with trastuzumab, OP15, and hyaluronic acid binding complex (HABC). MAb OP15 binds to an intracellular epitope on ErbB2, whereas HABC labels hyaluronan. Pixels corresponding to the membrane were identified as described in Materials and Methods. The background-corrected fluorescence intensities in the trastuzumab and OP15 images were divided by each other on a pixel-by-pixel basis, yielding the trastuzumab/ErbB2 image. The scale bar, valid for every image, is 20 µm.

Binding of Trastuzumab to ErbB2 Is Inhibited by a High Pericellular Density of Hyaluronan By Tímea Váradi, Tamás Mersich, Päivi Auvinen, Raija Tammi, Markku Tammi, Ferenc Salamon, István Besznyák, Jr., Ferenc Jakab, Zsolt Baranyai, János Szöllősi, and Peter Nagy
J Histochem Cytochem August 2012 60: 567-575, first published on May 4, 2012 doi:10.1369/0022155412448070

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