Name: quantitative localization of a golgi protein by imaging its center of fluorescence mass
Uploaded: 2017-08-10T13:00:00
Description: Watch this Scientific Journal Video about Quantitative Localization of a Golgi Protein by Imaging Its Center of Fluorescence Mass at JoVE.com

We would like to thank D. Stephens (University of Bristol, Bristol, United Kingdom) for the TPST1-EGFP DNA plasmid, as well as Lakshmi Narasimhan Govindarajan for helping with the software optimization. This work was supported by grants from the National Medical Research Council (NMRC/CBRG/007/2012), Ministry of Education (AcRF Tier1 RG 18/11, RG 48/13 and RG132/15 and AcRF Tier2 MOE2015-T2-2-073) to L.L.

Note: Below is a step-by-step protocol of GLIM for determining the LQ of EGFP-tagged tyrosylprotein sulfotransferase 1 (TPST1), a Golgi resident enzyme, in HeLa cells.
1. Preparation of Fluorescence-labeled Golgi Mini-stacks
<ol>
	<li>Prepare glass coverslips
	<ol>
		<li>Aliquot 0.3 mL sterile Dulbecco Modified Eagle&#39;s Medium (DMEM) to a well of a 24-well plate in a tissue culture hood.</li>
		<li>Wipe a piece of &#934; 12 mm No.1.5 glass coverslip using soft tissue pape...

<ol>
	<li>Glick, B. S., Luini, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Models+for+Golgi+traffic:+a+critical+assessment.">Models for Golgi traffic: a critical assessment.</a> Cold Spring Harb Perspect Biol. 3 (11), 005215 (2011).</li><li>Klumperman, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Architecture+of+the+mammalian+Golgi.">Architecture of the mammalian Golgi.</a> Cold Spring Harb Perspect Biol. 3 (7), (2011).</li><li>Lu, L., Hong, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=From+endosomes+to+the+trans-Golgi+network.">From endosomes to the trans-Golgi network.</a> Semin Cell Dev Biol. , (2014).</li><li>De Matteis, M. A., Luini, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exiting+the+Golgi+complex.">Exiting the Golgi complex.</a> Nat Rev Mol Cell Biol. 9 (4), 273-284 (2008).</li><li>Lu, L., Ladinsky, M. S., Kirchhausen, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cisternal+organization+of+the+endoplasmic+reticulum+during+mitosis.">Cisternal organization of the endoplasmic reticulum during mitosis.</a> Mol Biol Cell. 20 (15), 3471-3480 (2009).</li><li>Schermelleh, L., Heintzmann, R., Leonhardt, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+guide+to+super-resolution+fluorescence+microscopy.">A guide to super-resolution fluorescence microscopy.</a> J Cell Biol. 190 (2), 165-175 (2010).</li><li>Tie, H. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+imaging+method+for+quantitative+Golgi+localization+reveals+differential+intra-Golgi+trafficking+of+secretory+cargoes.">A novel imaging method for quantitative Golgi localization reveals differential intra-Golgi trafficking of secretory cargoes.</a> Mol Biol Cell. 27 (5), 848-861 (2016).</li><li>Trucco, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Secretory+traffic+triggers+the+formation+of+tubular+continuities+across+Golgi+sub-compartments.">Secretory traffic triggers the formation of tubular continuities across Golgi sub-compartments.</a> Nat Cell Biol. 6 (11), 1071-1081 (2004).</li><li>Cole, N. B., Sciaky, N., Marotta, A., Song, J., Lippincott-Schwartz, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Golgi+dispersal+during+microtubule+disruption:+regeneration+of+Golgi+stacks+at+peripheral+endoplasmic+reticulum+exit+sites.">Golgi dispersal during microtubule disruption: regeneration of Golgi stacks at peripheral endoplasmic reticulum exit sites.</a> Mol Biol Cell. 7 (4), 631-650 (1996).</li><li>Rogalski, A. A., Bergmann, J. E., Singer, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+microtubule+assembly+status+on+the+intracellular+processing+and+surface+expression+of+an+integral+protein+of+the+plasma+membrane.">Effect of microtubule assembly status on the intracellular processing and surface expression of an integral protein of the plasma membrane.</a> J Cell Biol. 99 (3), 1101-1109 (1984).</li><li>Van De Moortele, S., Picart, R., Tixier-Vidal, A., Tougard, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nocodazole+and+taxol+affect+subcellular+compartments+but+not+secretory+activity+of+GH3B6+prolactin+cells.">Nocodazole and taxol affect subcellular compartments but not secretory activity of GH3B6 prolactin cells.</a> Eur J Cell Biol. 60 (2), 217-227 (1993).</li><li>Nakamura, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+a+cis-Golgi+matrix+protein,+GM130.">Characterization of a cis-Golgi matrix protein, GM130.</a> J Cell Biol. 131, 1715-1726 (1995).</li><li>Roth, J., Berger, E. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immunocytochemical+localization+of+galactosyltransferase+in+HeLa+cells:+codistribution+with+thiamine+pyrophosphatase+in+trans-Golgi+cisternae.">Immunocytochemical localization of galactosyltransferase in HeLa cells: codistribution with thiamine pyrophosphatase in trans-Golgi cisternae.</a> J Cell Biol. 93 (1), 223-229 (1982).</li><li>Baeuerle, P. A., Huttner, W. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tyrosine+sulfation+is+a+trans-Golgi-specific+protein+modification.">Tyrosine sulfation is a trans-Golgi-specific protein modification.</a> J Cell Biol. 105 (6), 2655-2664 (1987).</li><li>Honda, A., Al-Awar, O. S., Hay, J. C., Donaldson, J. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeting+of+Arf-1+to+the+early+Golgi+by+membrin,+an+ER-Golgi+SNARE.">Targeting of Arf-1 to the early Golgi by membrin, an ER-Golgi SNARE.</a> J Cell Biol. 168 (7), 1039-1051 (2005).</li><li>Lavieu, G., Zheng, H., Rothman, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stapled+Golgi+cisternae+remain+in+place+as+cargo+passes+through+the+stack.">Stapled Golgi cisternae remain in place as cargo passes through the stack.</a> Elife. 2, 00558 (2013).</li><li>Zhao, X., Lasell, T. K., Melancon, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Localization+of+large+ADP-ribosylation+factor-guanine+nucleotide+exchange+factors+to+different+Golgi+compartments:+evidence+for+distinct+functions+in+protein+traffic.">Localization of large ADP-ribosylation factor-guanine nucleotide exchange factors to different Golgi compartments: evidence for distinct functions in protein traffic.</a> Mol Biol Cell. 13 (1), 119-133 (2002).</li><li>Dejgaard, S. Y., Murshid, A., Dee, K. M., Presley, J. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Confocal+microscopy-based+linescan+methodologies+for+intra-Golgi+localization+of+proteins.">Confocal microscopy-based linescan methodologies for intra-Golgi localization of proteins.</a> J Histochem Cytochem. 55 (7), 709-719 (2007).</li><li>Fourriere, L., Divoux, S., Roceri, M., Perez, F., Boncompain, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microtubule-independent+secretion+requires+functional+maturation+of+Golgi+elements.">Microtubule-independent secretion requires functional maturation of Golgi elements.</a> J Cell Sci. 129 (17), 3238-3250 (2016).</li><li>Volchuk, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Countercurrent+distribution+of+two+distinct+SNARE+complexes+mediating+transport+within+the+Golgi+stack.">Countercurrent distribution of two distinct SNARE complexes mediating transport within the Golgi stack.</a> Mol Biol Cell. 15 (4), 1506-1518 (2004).</li><li>Popoff, V., Adolf, F., Brugger, B., Wieland, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=COPI+budding+within+the+Golgi+stack.">COPI budding within the Golgi stack.</a> Cold Spring Harb Perspect Biol. 3 (11), 005231 (2011).</li></ol>

Previously, the localization of a Golgi protein under the light microscopy was mainly quantified by the degree of correlation or overlapping of the image of the protein with the image of a Golgi marker of known localization15,16,17. The resulting correlation or overlapping coefficient reflects how close the testing protein is to the Golgi marker spatially. There are at least three caveats for this approach. First, the correlatio...

The Golgi complex plays essential roles in secretory/endocytic trafficking of proteins and lipids (hereafter cargos) in mammalian cells1,2,3. At the Golgi, cargos are not only sorted to various sub-cellular compartments but also modified by diverse types of glycosylation. The mammalian Golgi complex comprises numerous laterally connected Golgi stacks, which typically consists of 4 - 11 tightly adjacent and flat membrane sacs called cisternae. The serially stacked Golgi cisternae are further categorized, from one end to the other, as cis, medial and trans-cisternae. At the trans-side of a Golgi stack, the trans-most membrane sac develops into a tubular and reticulum membrane network called the trans-Golgi network (TGN)4. In the secretory pathway, cargos derived from the endoplasmic reticulum (ER) enter a Golgi stack at its cis-side and then sequentially pass through medial and trans-cisternae. Cargos eventually exit the Golgi at the trans-Golgi or TGN destining to the plasma membrane, endosomes or secretory granules.
The molecular and cellular mechanisms of how cargos transit a Golgi stack and how the Golgi maintains its cisternal organization remain mysterious and are currently still under a heated debate1. One of difficulties in this field is that Golgi cisternae can only be resolved under the electron microscopy (EM) since the resolution of an optical microscope (~ 200 nm) is insufficient to resolve individual Golgi cisternae (&#60; 100 nm in both cisternal thickness and distance). Therefore, the sub-Golgi localization of resident proteins and transiting cargos are conventionally determined by the immuno-gold EM. However, the immuno-gold EM is very technically demanding and it is beyond the capability of most cell biology labs. Although the resolution of the EM can be sub-nanometer, the resolution afforded by the immuno-gold EM is greatly hampered by the size of the antibody complex (primary plus the secondary antibody) and the gold particle, and it can be worse than 20 nm. Furthermore, EM images are obtained from 2D thin-sections instead of a 3D global view of the Golgi, which can result in erroneous conclusions depending on the relative position and orientation of the 2D section5. For example, studying an EM single-section is unable to reliably differentiate a vesicle from the orthogonal view of a tubule since both can display identical round membrane profiles. The recent advent of super-resolution microscopy techniques, such as 3D-structured illumination microscopy (3D-SIM), stimulated emission depletion (STED), photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), makes it possible to resolve sub-Golgi structures under light microscopes6. However, there are at least four drawbacks that can significantly limit their uses in the cell biological study of the Golgi. 1) Current super-resolution techniques require expensive and special hardware configuration which is beyond most cell biology labs. 2) Special fluorescence labeling protocols are needed for some super-resolution techniques. 3) Although, under the best condition, these techniques claim 20-110 nm in spatial resolution, the practical resolution obtained in real samples can be much worse. 4) In comparison to conventional microscopy, these super-resolution techniques still have difficulties in conducting multicolor, 3D or live cell imaging, either singly or in combination. Probably most importantly, both immuno-gold EM and the super-resolution microscopy techniques yield qualitative instead of quantitative localization data.
Attempting to partially solve problems mentioned above, we have recently developed a conventional light microscopy based method, which is named Golgi protein localization by imaging centers of mass (GLIM), to systematically and quantitatively localize a Golgi protein at a resolution equivalent to that of the immuno-gold EM7. In this method, the Golgi in cultured mammalian cells is dispersed as Golgi mini-stacks by the treatment of nocodazole, a microtubule depolymerizing drug. Extensive studies have demonstrated that nocodazole-induced Golgi mini-stacks (hereafter Golgi mini-stacks) closely resemble native Golgi stacks in both organization and cellular functions8,9,10,11. The localization quotient (LQ) of a test protein can be acquired through GLIM and it denotes the quantitative sub-Golgi localization. The numerical values of LQs can be compared and a LQ database of more than 25 Golgi markers has been available.
In GLIM, Golgi mini-stacks are triple-labeled by endogenous or exogenously expressed GM130, GalT-mCherry and the test protein (x). GM130 and GalT-mCherry, cis- and trans-Golgi markers respectively12,13, provide reference points. The triple fluorescence, red (R), green (G) and far-red (B), are artificially displayed as red, green and blue, respectively. Center of fluorescence mass (hereafter center) is adopted to achieve sub-pixel resolution. The Golgi axis is defined as the vector from the center of GM130 to that of GalT-mCherry. The Golgi mini-stack is modeled as a cylindrical structure with infinite rotational symmetry around the Golgi axis. Therefore, a Golgi mini-stack can be further modeled as an one-dimensional structure along the Golgi axis. The LQ of the test protein x is defined as dx/d1, in which dx is the distance from the center of x to that of GM130, while d1 is the distance from the center of GalT-mCherry to that of GM130. If the center of x is off-axis, its projection axial distance is used for the calculation. The variables, including Golgi axis, axial angle, dx, d1, angle &#945; and angle &#946;, for GLIM are schematically illustrated in Figure 1. LQ is independent of the Golgi axial angle though Golgi mini-stacks orient randomly in a cell.
Golgi mini-stacks appear inhomogeneous in images. We developed three criteria to select analyzable Golgi mini-stacks for GLIM. 1) The signal-to-noise ratio criterion, in which the ratio of the total intensity of a Golgi mini-stack to the standard deviation (SD) of the background is &#8805; 30 in each channel. This criterion is to ensure the positioning accuracy of the center of mass, which depends on the signal-to-noise ratios of Golgi mini-stacks. 2) The axial angle or distance criterion, which requires d1&#8805; 70 nm. d1 decreases with the increase of the Golgi axial angle. When the axial angle is approaching 90&#176; or vertical, the mini-stack becomes non-resolvable as d1 is approaching 0. d1&#8805; 70 nm can effectively exclude near vertical Golgi mini-stacks. 3) The co-linearity criterion, in which either |tan &#945;| or |tan &#946;| is &#8804; 0.3. This criterion ensures that the three centers of a mini-stack are sufficiently co-linear for our one-dimensional model of the Golgi mini-stack. All light microscopes suffer from chromatic aberration which can seriously distort the relative positions of red, green and far-red fluorescence centers. Chromatic aberration of microscope systems is experimentally calibrated by imaging 110 nm beads, which are triple-labeled by red, green and far-red fluorescence. For each bead image, the center of red is defined as the true position of the bead and chromatic-shifts of green and far-red centers are fitted by first-order polynomial functions. Centers of Golgi mini-stacks are subjected to the polynomial functions to correct the chromatic-shifts in green and far-red channels.
Through GLIM we can achieve a resolution of ~ 30 nm along the Golgi axis under standard conditions. Importantly, it provides a systematical method to quantitatively map any Golgi protein. GLIM can be performed by conventional microscopes, such as wide-field or confocal microscopes, using common fluorescence labeling protocols. The imaging and data processing can take as short as an hour. Through GLIM, we have directly demonstrated the progressive transition of the secretory cargo from the cis- to trans-side of the Golgi7.

<table>
	<tbody>
		<tr>
			<td class="xl67">fluorescence beads. Commercial name: TetraSpeck beads</td>
			<td class="xl67">Invitrogen</td>
			<td class="xl75">T7279</td>
			<td class="xl67">As multi-color beads to calibrate chromatic-shift of the microscope.</td>
		</tr>
		<tr>
			<td class="xl67">Glass coverslip &#934; 12 mm (No. 1.5)</td>
			<td class="xl67">Menzel</td>
			<td class="xl75">CB00120RAC</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">Glass coverslip &#934; 25 mm (No. 1.5)</td>
			<td class="xl67">Menzel</td>
			<td class="xl75"></td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">DMEM</td>
			<td class="xl67">Capricon</td>
			<td class="xl75">DMEM-HPA-P50</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">Trypsin-EDTA</td>
			<td class="xl67"></td>
			<td class="xl75"></td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">FBS</td>
			<td class="xl67">GE Hyclone</td>
			<td class="xl75">SV30160.03</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">Nocodazole</td>
			<td class="xl67">Merck</td>
			<td class="xl75">487928</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">transfection reagent. Commercial name: Lipofectamine 2000</td>
			<td class="xl67">Invitrogen</td>
			<td class="xl75">11668-019</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">transfection medium. Commercial name: OptiMEM</td>
			<td class="xl67">Invitrogen</td>
			<td class="xl75">31985070</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">TPST1-EGFP</td>
			<td class="xl67">Addgene</td>
			<td class="xl75">66617</td>
			<td class="xl67">A gift from D. Stephens (University of Bristol, Bristol, United Kingdom)</td>
		</tr>
		<tr>
			<td class="xl67">GalT-mCherry</td>
			<td class="xl67"></td>
			<td class="xl75"></td>
			<td class="xl67">Made in our lab.</td>
		</tr>
		<tr>
			<td class="xl67">paraformaldehyde</td>
			<td class="xl67">Merck</td>
			<td class="xl75">1.04005.1000</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">saponin</td>
			<td class="xl67">Sigma-Aldrich</td>
			<td class="xl75">47036</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">poly(vinyl alcohol) (Mw ~31,000). Commercial name: Mowiol-488</td>
			<td class="xl67">CALBIOCHEM</td>
			<td class="xl75">475904</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">BSA</td>
			<td class="xl67">Sigma-Aldrich</td>
			<td class="xl75">A9647</td>
			<td class="xl67"></td>
		</tr>
		<tr>
			<td class="xl67">Mouse anti-GM130</td>
			<td class="xl67">BD Biosciences</td>
			<td class="xl75">610823</td>
			<td class="xl67">Primary antibody for human GM130</td>
		</tr>
		<tr>
			<td class="xl67">far-red fluorescence conjugated goat anti-mouse IgG. Commercial name: Alexa Fluor 647 conjugated goat anti-mouse IgG</td>
			<td class="xl67">Invitrogen</td>
			<td class="xl75">A-21235</td>
			<td class="xl67">Far red fluorescence conjugated secondary antibody</td>
		</tr>
	</tbody>
</table>

quantitative localization of a golgi protein by imaging its center of fluorescence mass

The Golgi complex consists of serially stacked membrane cisternae which can be further categorized into sub-Golgi regions, including the cis-Golgi, medial-Golgi, trans-Golgi and trans-Golgi network. Cellular functions of the Golgi are determined by the characteristic distribution of its resident proteins. The spatial resolution of conventional light microscopy is too low to resolve sub-Golgi structure or cisternae. Thus, the immuno-gold electron microscopy is a method of choice to localize a protein at the sub-Golgi level. However, the technique and instrument are beyond the capability of most cell biology labs. We describe here our recently developed super-resolution method called Golgi protein localization by imaging centers of mass (GLIM) to systematically and quantitatively localize a Golgi protein. GLIM is based on standard fluorescence labeling protocols and conventional wide-field or confocal microscopes. It involves the calibration of chromatic-shift aberration of the microscopic system, the image acquisition and the post-acquisition analysis. The sub-Golgi localization of a test protein is quantitatively expressed as the localization quotient. There are four main advantages of GLIM; it is rapid, based on conventional methods and tools, the localization result is quantitative, and it affords ~ 30 nm practical resolution along the Golgi axis. Here we describe the detailed protocol of GLIM to localize a test Golgi protein.

The modern research grade light microscope equipped with a plan apochromatic lens, such as the one used in our lab, shows minimal chromatic aberration (Figure 2A). However, a careful examination of the multi-color fluorescent bead image can reveal the shift of different color images of the same bead (Figure 2B). We define that the red channel is free of chromatic aberration and therefore centers ...

Watch this Scientific Journal Video about Quantitative Localization of a Golgi Protein by Imaging Its Center of Fluorescence Mass at JoVE.com

Quantitative Localization of a Golgi Protein by Imaging Its Center of Fluorescence Mass

The precise localization of Golgi residents is essential for understanding the cellular functions of the Golgi. However, conventional optical microscopy is unable to resolve the sub-Golgi structure. Here we describe the protocol for a conventional microscopy based super-resolution method to quantitatively determine the sub-Golgi localization of a protein.

The Golgi complex consists of serially stacked membrane cisternae which can be further categorized into sub-Golgi regions, including the cis-Golgi, ...

The overall goal of this imaging-based method is to quantitatively localize a golgi protein at nanometer resolution. This method can help to answer the key questions in the study of the golgi apparatus such as the golgi's organization and how it works. The main advantage of this method is that it uses a conventional light microscope and software tools.To begin, culture HeLa cells in a T25 flask in DMEM supplemented with 10%FBS and incubate the culture at 37 degrees Celsius and 5%carbon dioxide. When cells reach approximately 80%confluency, aspirate the culture medium and add one milliliter of 25%Trypsin EDTA to the flask. Incubate the cells at 37 degrees Celsius for two minutes.Remove the cells from the incubator and add one milliliter of complete medium to gently flush the cells off the wall of the flask. Transfer the detached cells to a sterile centrifugation tube and spin the tube at 500 g's for two minutes to pellet the cells. After aspirating the supernatant, use one milliliter of complete medium to suspend the cell pellet.Remove the medium from the well of a 24-well plate containing a sterilized glass cover slip and seed approximately 100, 000 cells into the well. Use complete medium to top up the volume of the well to 5 milliliters. Then, incubate the plate at 37 degrees Celsius with 5%carbon dioxide.When the cells have reached 80%confluency, use 80 nanograms of GalT-mCherry and 320 nanograms of TPST1-EGFP plasmid DNA and transfection reagent to transfect the cells according to the manufacturer's protocol. After incubating the cells for four to six hours, change the medium and return the cells to the incubator for 12 hours. Aspirate the medium in the well and add 5 milliliters of 33 micromold Nocodazole containing complete medium and then incubate the cells at 37 degrees Celsius and 5%carbon dioxide for three hours.After cleaning glass cover slips according to the text protocol, use one times PBS containing 1 microgram per microliter of BSA to dilute 110 nanometers multi-color fluorescent beads 80 fold. Briefly vortex the tube to disperse the bead aggregates. Using a pipette tip, spread 60 microliters of diluted beads onto a clean cover slip.In the dark, place the cover slip in a 35 millimeter dish and cover it with aluminum foil. Dry the cover slip in the dark in a desiccator connected to a vacuum pump. Then use 50 microliters of mounting medium to mount the cover slip onto a glass slide.Properly clean cover slips are essential to eliminate fluorescent debris. To image multi-color beads in green, red, and far red channels, at the beginning of the imaging session, acquire 3D stacks of images, taking three sections above and below the best focal plane. Save the stacks as TIFF files.To image golgi mini-stacks, use TPST1-EGFP and GalT-mCherry transfected in fluorescently labeled slides to find cells that express TPST1-EGFP and a low or medium level GalT-mCherry. Acquire 3D image stacks as just demonstrated. To analyze the images, open image J, choose File, Image, Open, to open a set of bead images consisting of three TIFF files.Choose Image, Stacks, Z Project, to average three consecutive sections around the best focused section in the red channel. Input the section number of start slice and stop slice and among options of projection type, select average intensity. Draw background ROIs that contain no beads in the image.Then in Analyze, Set Measurements, check only mean gray value and Standard Deviation or SD.Execute Analyze, Measure, to obtain the background mean intensity and standard deviation. Choose Process, Math, Subtract, to subtract the image with the corresponding values of the background mean intensity plus six times the standard deviation. Then input the calculated value corresponding to this channel.Repeat the averaging and subtraction for green and far red channel image stacks by using the same start and stop slice and the same background ROI. Merge the three processed images using Image, Color, Merge Channels, by selecting channel R as red, channel G as green, and channel B as blue. Launch the ROI Manager by choosing Analyze, Tools, ROI Manager.Draw square ROIs around single beads. Then add the ROI to the ROI Manager by pressing T on the keyboard. Under Analyze, Set Measurements, check only center of mass.In the ROI Manager, select channel R and click Measure to obtain the X and Y coordinates of the centers of ROIs in the results window. Copy and paste the two columns into a spreadsheet. Obtain the coordinates of the centers of ROIs for channel G and channel B.Save the spreadsheet as beads.csv.In image J, use plugins install to install the two macros, macro golgi ROI inspection and macro output three channels data. Clear the ROI Manager and results window. Open a set of golgi mini-stack images consisting of three TIFF files.Generate background subtracted images as demonstrated earlier in this video for later use. Then duplicate the images. Under Process, Image Calculator, add the background subtracted channel G, channel R, and channel B images.To the resulting image under Image, Adjust, Threshold, select Set to input one as the lowest threshold level. Under Analyze, Analyze Particles, input the size range for size pixel too. Input 50 to infinity, check excludes on edges, and add to manager.Next, use Image, Color, Merge Channels, to merge the three background subtracted images generated earlier by selecting channel R as red, channel G as green, and channel B as blue. Then run the macro macro golgi ROI inspection by selecting Plugins, Macro, Golgi ROI Inspection. It is important to select as many ROIs as possible that contains single golgi mini-stacks in a set of images.Under Analyze, Set Measurements, check only area, mean gray value, and center of mass. Acquire data by launching the macro tool macro output three channels data. Copy coordinates of centers into a spreadsheet in the order listed here.Then save the spreadsheet as ministacks.csv. Proceed to chromatic shift correction of the centers and Localization Quotient or LQ calculation according to the text protocol. The modern research grade light microscope equipped with the plain apochromatic lens such as the one used here shows minimal chromatic shift.However, a careful examination of the multi-colored bead image reveals it. Centers of red fluorescence are defined as the true positions of beads. The relative chromatic shifts of green and far red fluorescence can be represented by vectors.The chromatic shift within the imaging plane is illustrated by the green and blue vector for each bead. As illustrated here, chromatic shift correction significantly reduces the chromatic shift. In mammalian cells, the golgi complex is aggregated at the perinuclear area which is usually not resolvable under a conventional optical microscope.After Nocodazole treatment, the perinuclear golgi complex disappears and dozens of golgi mini-stacks assemble at the endoplasmic reticulum exit sites throughout the cytoplasm. An example image that was generated using the image analysis demonstrated in this video is shown here. Using the macro golgi ROI inspection tool, 40 selected golgi mini-stacks were listed.After applying the three criteria, 21 golgi mini-stacks were analyzable for the calculation of LQs of TPST1-EGFP. Once mastered, this technique can be done in one hour after fluorescence labeling. After its development, this method paved the way for researchers who study the golgi apparatus to quantitatively localize a golgi protein with resolution equivalent to that of immunoelectron microscopy.

quantitative-localization-golgi-protein-imaging-its-center

Research

JoVE Journal

Biology

A Quantitative Assessment of The Yeast Lipidome using Electrospray Ionization Mass Spectrometry

Lipids are one of the major classes of biomolecules and play important roles membrane dynamics, energy storage, and signalling1-4. The budding yeast Saccharomyces cerevisiae, a genetically and biochemically manipulable unicellular eukaryote with annotated genome and very simple lipidome, is a valuable model for studying biological functions of various lipid species in multicellular eukaryotes2,3,5. S. cerevisiae has 10 major classes of lipids with chain lengths mainly of 16 or 18 carbon atoms and either zero or one degree of unsaturation6,7. Existing methods for lipid identification and quantification - such as high performance liquid chromatography, thin-layer chromatography, fluorescence microscopy, and gas chromatography followed by MS - are well established but have low sensitivity, insufficiently separate various molecular forms of lipids, require lipid derivitization prior to analysis, or can be quite time consuming. Here we present a detailed description of our experimental approach to solve these inherent limitations by using survey-scan ESI/MS for the identification and quantification of the entire complement of lipids in yeast cells. The described method does not require chromatographic separation of complex lipid mixtures recovered from yeast cells, thereby greatly accelerating the process of data acquisition. This method enables lipid identification and quantification at the concentrations as low as g/ml and has been successfully applied to assessing lipidomes of whole yeast cells and their purified organelles. Lipids extraction from whole yeast cells for using this method of lipid analysis takes two to three hours. It takes only five to ten minutes to run each sample of extracted and dried lipids on a Q-TOF mass spectrometer equipped with a nano-electrospray source.

We describe a new quantitative lipidomics method for identifying numerous lipid species in yeast using survey-scan electrospray ionization mass spectrometry (ESI/MS). This method exceeds currently available methods for lipid identification and quantification in the ability to resolve various molecular forms of lipids, sensitivity, and speed.

Lipids are one of the major classes of biomolecules and play important roles membrane dynamics, energy storage, and signalling1-4. The budding yeast ...

Time-lapse Imaging of Mitosis After siRNA Transfection

Changes in cellular organization and chromosome dynamics that occur during mitosis are tightly coordinated to ensure accurate inheritance of genomic and cellular content. Hallmark events of mitosis, such as chromosome movement, can be readily tracked on an individual cell basis using time-lapse fluorescence microscopy of mammalian cell lines expressing specific GFP-tagged proteins. In combination with RNAi-based depletion, this can be a powerful method for pinpointing the stage(s) of mitosis where defects occur after levels of a particular protein have been lowered. In this protocol, we present a basic method for assessing the effect of depleting a potential mitotic regulatory protein on the timing of mitosis. Cells are transfected with siRNA, placed in a stage-top incubation chamber, and imaged using an automated fluorescence microscope. We describe how to use software to set up a time-lapse experiment, how to process the image sequences to make either still-image montages or movies, and how to quantify and analyze the timing of mitotic stages using a cell-line expressing mCherry-tagged histone H2B. Finally, we discuss important considerations for designing a time-lapse experiment. This strategy is complementary to other approaches and offers the advantages of 1) sensitivity to changes in kinetics that might not be observed when looking at cells as a population and 2) analysis of mitosis without the need to synchronize the cell cycle using drug treatments. The visual information from such imaging experiments not only allows the sub-stages of mitosis to be assessed, but can also provide unexpected insight that would not be apparent from cell cycle analysis by FACS.

Here we describe a basic protocol to image and quantify the mitotic timing of live mammalian tissue culture cells after siRNA transfection.

Changes in cellular organization and chromosome dynamics that occur during mitosis are tightly coordinated to ensure accurate inheritance of genomic and ...

Analyzing Large Protein Complexes by Structural Mass Spectrometry

Living cells control and regulate their biological processes through the coordinated action of a large number of proteins that assemble themselves into an array of dynamic, multi-protein complexes1. To gain a mechanistic understanding of the various cellular processes, it is crucial to determine the structure of such protein complexes, and reveal how their structural organization dictates their function. Many aspects of multi-protein complexes are, however, difficult to characterize, due to their heterogeneous nature, asymmetric structure, and dynamics. Therefore, new approaches are required for the study of the tertiary levels of protein organization.
One of the emerging structural biology tools for analyzing macromolecular complexes is mass spectrometry (MS)2-5. This method yields information on the complex protein composition, subunit stoichiometry, and structural topology. The power of MS derives from its high sensitivity and, as a consequence, low sample requirement, which enables examination of protein complexes expressed at endogenous levels. Another advantage is the speed of analysis, which allows monitoring of reactions in real time. Moreover, the technique can simultaneously measure the characteristics of separate populations co-existing in a mixture. 
Here, we describe a detailed protocol for the application of structural MS to the analysis of large protein assemblies. The procedure begins with the preparation of gold-coated capillaries for nanoflow electrospray ionization (nESI). It then continues with sample preparation, emphasizing the buffer conditions which should be compatible with nESI on the one hand, and enable to maintain complexes intact on the other. We then explain, step-by-step, how to optimize the experimental conditions for high mass measurements and acquire MS and tandem MS spectra. Finally, we chart the data processing and analyses that follow. Rather than attempting to characterize every aspect of protein assemblies, this protocol introduces basic MS procedures, enabling the performance of MS and MS/MS experiments on non-covalent complexes. Overall, our goal is to provide researchers unacquainted with the field of structural MS, with knowledge of the principal experimental tools.

Mass spectrometry has proven to be a valuable tool for analyzing large protein complexes. This method enables insights into the composition, stoichiometry and overall architecture of multi-subunit assemblies. Here, we describe, step-by-step, how to perform a structural mass spectrometry analysis, and characterize macromolecular structures.

Living cells control and regulate their biological processes through the coordinated action of a large number of proteins that assemble themselves into an ...

A Protocol for the Identification of Protein-protein Interactions Based on 15N Metabolic Labeling, Immunoprecipitation, Quantitative Mass Spectrometry and Affinity Modulation

Protein-protein interactions are fundamental for many biological processes in the cell. Therefore, their characterization plays an important role in current research and a plethora of methods for their investigation is available1. Protein-protein interactions often are highly dynamic and may depend on subcellular localization, post-translational modifications and the local protein environment2. Therefore, they should be investigated in their natural environment, for which co-immunoprecipitation approaches are the method of choice3. Co-precipitated interaction partners are identified either by immunoblotting in a targeted approach, or by mass spectrometry (LC-MS/MS) in an untargeted way. The latter strategy often is adversely affected by a large number of false positive discoveries, mainly derived from the high sensitivity of modern mass spectrometers that confidently detect traces of unspecifically precipitating proteins. A recent approach to overcome this problem is based on the idea that reduced amounts of specific interaction partners will co-precipitate with a given target protein whose cellular concentration is reduced by RNAi, while the amounts of unspecifically precipitating proteins should be unaffected. This approach, termed QUICK for QUantitative Immunoprecipitation Combined with Knockdown4, employs Stable Isotope Labeling of Amino acids in Cell culture (SILAC)5 and MS to quantify the amounts of proteins immunoprecipitated from wild-type and knock-down strains. Proteins found in a 1:1 ratio can be considered as contaminants, those enriched in precipitates from the wild type as specific interaction partners of the target protein. Although innovative, QUICK bears some limitations: first, SILAC is cost-intensive and limited to organisms that ideally are auxotrophic for arginine and/or lysine. Moreover, when heavy arginine is fed, arginine-to-proline interconversion results in additional mass shifts for each proline in a peptide and slightly dilutes heavy with light arginine, which makes quantification more tedious and less accurate5,6. Second, QUICK requires that antibodies are titrated such that they do not become saturated with target protein in extracts from knock-down mutants.
Here we introduce a modified QUICK protocol which overcomes the abovementioned limitations of QUICK by replacing SILAC for 15N metabolic labeling and by replacing RNAi-mediated knock-down for affinity modulation of protein-protein interactions. We demonstrate the applicability of this protocol using the unicellular green alga Chlamydomonas reinhardtii as model organism and the chloroplast HSP70B chaperone as target protein7 (Figure 1). HSP70s are known to interact with specific co-chaperones and substrates only in the ADP state8. We exploit this property as a means to verify the specific interaction of HSP70B with its nucleotide exchange factor CGE19.

A Protocol for the Identification of Protein-protein Interactions Based on 15N Metabolic Labeling, Immunoprecipitation, Quantitative Mass Spectrometry and Affinity Modulation

We present a variation of the QUICK (QUantitative Immunoprecipitation Combined with Knockdown) approach that was introduced previously to distinguish between true and false protein-protein interactions. Our approach is based on 15N metabolic labeling, the modulation of affinities of protein-protein interactions by the presence/absence of ATP, immunoprecipitation, and quantitative mass spectrometry.

Protein-protein interactions are fundamental for many biological processes in the cell. Therefore, their characterization plays an important role in ...

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, traditional chemotherapeutic approaches have been largely unsuccessful. Hormone therapy is effective at early stage, but often fails with the eventual development of hormone-refractory tumors. We have been interested in developing therapeutics targeting specific metabolic deficiency of tumor cells. We recently showed that prostate tumor cells specifically lack an enzyme (argininosuccinate synthase, or ASS) involved in the synthesis of the amino acid arginine1. This condition causes the tumor cells to become dependent on exogenous arginine, and they undergo metabolic stress when free arginine is depleted by arginine deiminase (ADI)1,10. Indeed, we have shown that human prostate cancer cells CWR22Rv1 are effectively killed by ADI with caspase-independent apoptosis and aggressive autophagy (or macroautophagy)1,2,3. Autophagy is an evolutionarily-conserved process that allows cells to metabolize unwanted proteins by lysosomal breakdown during nutritional starvation4,5. Although the essential components of this pathway are well-characterized6,7,8,9, many aspects of the molecular mechanism are still unclear - in particular, what is the role of autophagy in the death-response of prostate cancer cells after ADI treatment? In order to address this question, we required an experimental method to measure the level and extent of autophagic response in cells - and since there are no known molecular markers that can accurately track this process, we chose to develop an imaging-based approach, using quantitative 3D fluorescence microscopy11,12.
Using CWR22Rv1 cells specifically-labeled with fluorescent probes for autophagosomes and lysosomes, we show that 3D image stacks acquired with either widefield deconvolution microscopy (and later, with super-resolution, structured-illumination microscopy) can clearly capture the early stages of autophagy induction. With commercially available digital image analysis applications, we can readily obtain statistical information about autophagosome and lysosome number, size, distribution, and degree of colocalization from any imaged cell. This information allows us to precisely track the progress of autophagy in living cells and enables our continued investigation into the role of autophagy in cancer chemotherapy.

Autophagy is a ubiquitous process that enables cells to degrade and recycle proteins and organelles. We apply advanced fluorescence microscopy to visualize and quantify the small, but essential, physical changes associated with the induction of autophagy, including the formation and distribution of autophagosomes and lysosomes, and their fusion into autolysosomes.

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, ...

Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells.
BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction.

Flow cytometric analysis of Bimolecular Fluorescence Complementation provides a high throughput quantitative method to study protein-protein interaction. This methodology can be applied to mapping protein binding sites and for screening factors that regulate protein-protein interaction.

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC ...

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or&#160;photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.

We demonstrate the use of fluorescence photo activation localization microscopy (FPALM) to simultaneously image multiple types of fluorescently labeled molecules&#160;within cells. The techniques described yield the localization of thousands to hundreds of thousands of individual fluorescent labeled proteins, with a precision of tens of nanometers&#160;within single cells.

Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled ...

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard.
Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

Here we describe a workflow for rapidly analyzing and exploring collections of fluorescence microscopy images using PhenoRipper, a recently developed image-analysis platform.

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized ...

Characterization of G Protein-coupled Receptors by a Fluorescence-based Calcium Mobilization Assay

For more than 20 years, reverse pharmacology has been the preeminent strategy to discover the activating ligands of orphan G protein-coupled receptors (GPCRs). The onset of a reverse pharmacology assay is the cloning and subsequent transfection of a GPCR of interest in a cellular expression system. The heterologous expressed receptor is then challenged with a compound library of candidate ligands to identify the receptor-activating ligand(s). Receptor activation can be assessed by measuring changes in concentration of second messenger reporter molecules, like calcium or cAMP. The fluorescence-based calcium mobilization assay described here is a frequently used medium-throughput reverse pharmacology assay. The orphan GPCR is transiently expressed in human embryonic kidney 293T (HEK293T) cells and a promiscuous G&#945;16 construct is co-transfected. Following ligand binding, activation of the G&#945;16 subunit induces the release of calcium from the endoplasmic reticulum. Prior to ligand screening, the receptor-expressing cells are loaded with a fluorescent calcium indicator, Fluo-4 acetoxymethyl. The fluorescent signal of Fluo-4 is negligible in cells under resting conditions, but can be amplified more than a 100-fold upon the interaction with calcium ions that are released after receptor activation. The described technique does not require the time-consuming establishment of stably transfected cell lines in which the transfected genetic material is integrated into the host cell genome. Instead, a transient transfection, generating temporary expression of the target gene, is sufficient to perform the screening assay. The setup allows medium-throughput screening of hundreds of compounds. Co-transfection of the promiscuous G&#945;16, which couples to most GPCRs, allows the intracellular signaling pathway to be redirected towards the release of calcium, regardless of the native signaling pathway in endogenous settings. The HEK293T cells are easy to handle and have proven their efficacy throughout the years in receptor deorphanization assays. However, optimization of the assay for specific receptors may remain necessary.

The here described fluorescence-based calcium mobilization assay is a medium-throughput reverse pharmacology screening system for the identification of functionally activating ligand(s) of orphan G protein-coupled receptors (GPCRs).

For more than 20 years, reverse pharmacology has been the preeminent strategy to discover the activating ligands of orphan G protein-coupled receptors ...

In Vivo 4-Dimensional Tracking of Hematopoietic Stem and Progenitor Cells in Adult Mouse Calvarial Bone Marrow

Through a delicate balance between quiescence and proliferation, self renewal and production of differentiated progeny, hematopoietic stem cells (HSCs) maintain the turnover of all mature blood cell lineages. The coordination of the complex signals leading to specific HSC fates relies upon the interaction between HSCs and the intricate bone marrow microenvironment, which is still poorly understood[1-2].
We describe how by combining a newly developed specimen holder for stable animal positioning with multi-step confocal and two-photon in vivo imaging techniques, it is possible to obtain high-resolution 3D stacks containing HSPCs and their surrounding niches and to monitor them over time through multi-point time-lapse imaging. High definition imaging allows detecting ex vivo labeled hematopoietic stem and progenitor cells (HSPCs) residing within the bone marrow. Moreover, multi-point time-lapse 3D imaging, obtained with faster acquisition settings, provides accurate information about HSPC movement and the reciprocal interactions between HSPCs and stroma cells.
Tracking of HSPCs in relation to GFP positive osteoblastic cells is shown as an exemplary application of this method. This technique can be utilized to track any appropriately labeled hematopoietic or stromal cell of interest within the mouse calvarium bone marrow space.

In Vivo 4-Dimensional Tracking of Hematopoietic Stem and Progenitor Cells in Adult Mouse Calvarial Bone Marrow

The nature of the interactions between hematopoietic stem and progenitor cells (HSPCs) and bone marrow niches is poorly understood. Custom hardware modifications and a multi-step acquisition protocol allow the use of two-photon and confocal microscopy to image ex vivo labeled HSPCs homed within bone marrow areas, tracking interactions and movement.

Through a delicate balance between quiescence and proliferation, self renewal and production of differentiated progeny, hematopoietic stem cells (HSCs) ...