We thank staff at the Anatomical Pathology Laboratories of the Royal Prince Alfred and Concord Repatriation Hospitals for collecting fresh samples of CRC and normal intestinal mucosa. The work was funded by a Cancer Institute New South Wales Translational Program Grant.

<img src="/files/ftp_upload/3322/3322fig1.jpg" alt="Figure 1" /> 
Figure 1. Work flow for preparation of a suspension of live cells from a surgical sample of CRC.
1. Clinical sample disaggregation 
All samples were collected from the Royal Prince Alfred Hospital (Camperdown, NSW, Australia) and Concord Repatriation Hospital (Concord West, NSW, Australia) with informed consent under Protocol No. X08-164. 
<ol>
 <li>Collect fresh colorectal cancer (CRC) or adenoma specimens, and normal intestinal mucosa at least 10 cm from the tumour. Store samples in Hank&#x2019;s balanced salt solution pH 7.3 (HBSS) at 4&deg;C for up to 12 h after resection.</li>
 <li>Follow safety regulations for human pathogens, process all clinical samples in a biological safety cabinet class II. Dissect the samples into 2 mm cubes in a Petri dish using two scalpel blades. </li>
 <li>Incubate tumour and normal tissue in separate Eppendorf tubes with occasional gentle mixing for 60 min at 37&deg;C with an equal volume of RPMI 1640 medium containing 2% (v/v) collagenase type 4 (Worthington, Lakewood, NJ, USA) and 0.1% (w/v) deoxyribonuclease I from bovine pancrease (DNAse I; Sigma-Aldrich). </li>
 <li>Force semi-digested tissue through a fine wire mesh strainer using a plunger from a 10 mL syringe; wash cells through with HBSS. </li>
 <li>Pass resulting cell suspension through 200 &mu;m and 50 &mu;m Filcon filters (BD Biosciences) to remove cell aggregates. Most of the DNA, mucus and cell aggregates are removed in this series of filtrations. </li>
 <li>Centrifuge cell suspensions at 400 x g at 20&deg; for 5 min.</li>
 <li>Resuspend cell pellets in heat-inactivated FCS containing 10% dimethyl sulphoxide (DMSO), freeze slowly in cryovials and store at -80&deg;. The freezing process tends to reduce mucus in the sample and lyses red blood cells. </li>
</ol>
2. Sample preparation for cell capture
<ol>
 <li>Thaw out samples quickly in a 37&deg; water bath and resuspend cells in 10 mL of HBSS to wash out the DMSO.</li>
 <li>Centrifuge cell suspensions at 410 x g at 20&deg; for 5 min.</li>
 <li>Decant the supernatant and resuspend the cell pellet in 500 &mu;L of HBSS.</li>
 <li>Treat the sample with 0.1% (w/v) DNAse I for 20 min at room temperature. </li>
 <li>Mix 10 &mu;L of each cell suspension with an equal volume of trypan blue and load 10 &mu;L of the mixture into a hemocytometer. Using a light microscope at 100-fold magnification, count viable cells, which appear clear due to trypan blue exclusion, while dead cells take up the dye. A minimum 4 x 106 viable cells is required for cell capture on the microarray.</li>
 <li>Following DNAse treatment, resuspend the cell suspension in 10 mL HBSS and centrifuge at 410 x g at 20&deg; for 5 min.</li>
 <li>Decant the supernatants and resuspend cell pellets in RPMI 1640 to a final volume of 200 &mu;L.</li>
</ol>
3. Antibody microarray cell capture
<ol>
 <li>Moisten the DotScan antibody microarray by dipping the nitrocellulose section into phosphate buffered saline (PBS) for approximately 20 s. Carefully wipe the glass edges of the microarray with folded Kimwipes, avoiding touching the nitrocellulose section. </li>
 <li>Add water to the microarray incubation tray to provide a humid chamber. Place the microarray into the chamber and pipette the cell suspension in RPMI 1640 onto the moist nitrocellulose section. Pipette drops on each corner of the nitrocellulose to ensure an even spread of cells. </li>
 <li>Incubate the microarrays at 37&deg;C for 1 h. The incubation allows cells to settle and come in contact with antibodies on the microarray. Cells expressing surface antigens corresponding to the antibodies they land on will be captured. </li>
 <li>After incubation, dip the microarrays gently and vertically into three troughs containing at least 15 mL PBS to wash off unbound cells (20 s per wash).</li>
 <li>Prepare 3.7% (w/v) formaldehyde in PBS to fix the cells and antibody by cross-linking. Gently pipette approximately 1 mL to cover the nitrocellulose section of the microarray. Incubate for 20 min at room temperature.</li>
 <li>Next dip microarrays into 3 changes of PBS (15 mL; 30 s each) to wash out excess formaldehyde. </li>
 <li>Wipe the edges and back of the glass slide with Kimwipes and scan the microarray using the DotScan scanner while, the nitrocellulose section is moist. The optical scan provides the antigen expression pattern of a mixed cell population e.g. CRC cells, leukocytes and other stromal cells of the tumour. </li>
</ol>
4. Fluorescence multiplexing 
<ol>
 <li>Remove the microarray from the scanner and apply 200 &mu;L of blocking buffer (2% w/v BSA, 2% heat-inactivated human AB serum, PBS, pH 7.3). Incubate it in the microarray tray at room temperature for 20 min. </li>
 <li>Prepare the multiplexing solution in an Eppendorf tube covered with aluminum foil: 20 &mu;L Phycoerythrin-anti-CD3 (Beckman Coulter, Gladesville, NSW, Australia, #IM12824; 1/7.5 final dilution), 10 &mu;L Alexa Fluor 647-anti-EpCAM (Biolegend, San Diego, CA, USA; 1/15 dilution), 2 &mu;L of heat-inactivated human AB serum (Sigma-Aldrich, Castle Hill, NSW, Australia) and 118 &mu;L of blocking buffer. </li>
 <li>Drain off excess blocking buffer from the microarray and pipette the multiplexing solution onto the nitrocellulose section, spreading uniformly. Incubate for 30 min in the dark at room temperature.</li>
 <li>Dip the microarray vertically into three troughs of 15 ml fresh PBS; (30 s each).</li>
 <li>Let the microarrays dry in the dark and store at 4&deg;C in a slide box. The microarray can be stored in the dark for up to 3 months without loss of fluorescence.</li>
 <li>Scan the dry microarray using a Typhoon FLA 9000 scanner (GE Healthcare, Rydalmere, NSW, Australia) with resolution set to 50 (532 nm laser, 580 BP30 emission filter for PE. 633 nm laser and 670 BP30 emission filter for Alexa 647). The microarrays are scanned with the nitrocellulose side facing downwards on the glass scanner tray.</li>
 <li>Save the fluorescent images as TIFF files and using Photoshop set image size to 17 x 25 cm and resolution to 72 pixels/cm. Import the image into the DotScan analysis software to analyse the intensity of dots.</li>
 <li>The DotReader captures a digital image of the dot binding pattern and quantifies the density of cell binding on each antibody dot on an 8 bit greyness scale (1-256 U). Occasional non-specific isotype control binding was subtracted from binding values for antibodies with corresponding immunoglobulin isotypes. Dot fluorescence intensities for each microarray were normalized against the brightest dot set at 100% intensity. Signal/spot strength was recorded in an .xml file (raw data) or represented as a bar chart in an .pdf file (final report)</li>
 <li>Microarray heatsmaps and hierarchical clustering were conducted using MultiExperiment Viewer (MeV) version 4.4 from the TM4 Microarray Software Suite (<a href="http://www.tm4.org/mev.html">http://www.tm4.org/mev.html</a>). Hierarchical clustering was performed on background-adjusted data using MeV with complete linkage analysis. Euclidean distance was used for similarity measure. The 2-tailed Student&#x2019;s t-test with equal variance was used to determine the statistical significance of the results.</li>
</ol>
5. Representative Results:
Results from the DotScan microarray should show consistent cell binding patterns between duplicate arrays. Strong alignment dot binding (CD44/CD29) enables a grid to be placed over the array area. Figure 2 shows an example of optimal cell capture and multiplexing. Figure 3 shows some common problems encountered during cell capture and the possible solutions. 
The microarray cell binding results can be quantified by measuring dot intensities expressed on a greyness scale ranging from 1 to 256. Figure 4 shows numerical data from 58 surgical CRC samples, stained with EpCAM-Alexa 647 antibody, as a heatmap with hierarchical clustering. Even though the number of samples is limited, CRCs of the same stage tend to cluster in the same group. 
<img src="/files/ftp_upload/3322/3322fig2.jpg" alt="Figure 2" /> 
Figure 2. Cell binding pattern of clinical colorectal cancer tumour (Australian Clinic-Pathological Staging, ACP stage B1). (a) DotScan antibody key showing locations of antibodies for the left half of the duplicate microarray (outlined). The top section contains the original 82 antibodies of the DotScan leukemia microarray. An additional 40 antibodies, corresponding to specific surface antigens found to be up-regulated in the literature, were added as a CRC &#x2018;satellite&#x2019; microarray. The bottom section consists of isotype control antibodies (b) Optical image of CRC cells binding to the microarray. (c) CD3 fluorescence image showing T-cells. (d) EpCAM fluorescence image showing CRC cells.
<img src="/files/ftp_upload/3322/3322fig3.jpg" alt="Figure 3" /> 
Figure 3. Examples of poor DotScan results and possible solutions. (a) Low cell binding; solution: make sure at least 4x106 viable cells are on the array (b) Isotype control binding and non-specific cell binding; solution: add heat-inactivated human AB serum to sample before incubation on microarray to minimise isotype control binding. Occasionally, a small amount of non-specific binding of cells to the nitrocellulose occurs with CRC samples and does not significantly affect the results. (c) Nitrocellulose drying out during incubation; solution: ensure sample covers the whole nitrocellulose section and microarray is incubated on a flat surface. (d) High background artifacts; solution: ensure the microarray is thoroughly washed following incubation.
<img src="/files/ftp_upload/3322/3322fig4.jpg" alt="Figure 4" /> 
Figure 4. DotScan analysis software generated bar charts representing cell binding densities on a greyness scale ranging from 1 to 256. Numbers on the axis refer to CD antigens. Other abbreviations are TCR, T-cell receptor; &kappa;, &lambda;, immunoglobulin light chains; sIg, surface immunoglobulin; DCC, deleted in colorectal cancer protein; EGFR, epidermal growth factor receptor; FAP, fibroblast activation protein; HLA-A,B,C HLA-DR, human leukocyte antigens DR and A,B,C respectively; MICA, MHC class I chain-related protein A; MMP-14, matrix metallopeptidase 14; PIGR, polymeric immunoglobulin receptor; TSP-1, thrombospondin-1; Mabthera, humanised anti-CD20. <a href="https://www.jove.com/files/ftp_upload/3322/3322fig4large.jpg">Click here to view larger image</a>.

<ol>
	<li>Steinert, R., Buschmann, T., vander Linden, M., Fels, L. M., Lippert, H., Reymond, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+proteomics+in+the+diagnosis+and+outcome+prediction+in+colorectal+cancer.">The role of proteomics in the diagnosis and outcome prediction in colorectal cancer.</a> Technol. Cancer. Res. Treat. 1, 297 (2002).</li><li>Eifel, P., Axelson, J. A., Costa, J., Crowley, J., Curran, W. J., Deshler, A., Fulton, S., Hendricks, C. B., Kemeny, M., Kornblith, A. B., Louis, T. A., Markman, M., Mayer, R., Roter, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=National+Institutes+of+Health+Consensus+Development+Conference+Statement:+adjuvant+therapy+for+breast+cancer.">National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer.</a> J. Natl. Canc. Inst. 93, 979 (2001).</li><li>Swerdlow, S. H., Campo, E., Harris, H. L., Jaffe, E. S., Pileri, S. A., Stein, H., Thiele, J., Vardiman, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=WHO+classification+of+tumour+of+haematopoietic+and+lymphoid+tissues.">WHO classification of tumour of haematopoietic and lymphoid tissues.</a> IARC WHO Classification of Tumours. 2, (2008).</li><li>Xiao, G. G., Recker, R. R., Deng, H. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recent+advances+in+proteomics+and+cancer+biomarker+discovery.">Recent advances in proteomics and cancer biomarker discovery.</a> Clin. Med. Oncol. , (2008).</li><li>Belov, L., Mulligan, S. P., Barber, N., Woolfson, A., Scott, M., Stoner, K., Chrisp, J. S., Sewell, W. A., Bradstock, K. F., Bandall, L., Pascovici, D. S., Thomas, M., Erber, W., Huang, P., 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=Analysis+of+human+leukaemias+and+lymphomas+using+extensive+immunophenotypes+from+an+antibody+microarray.">Analysis of human leukaemias and lymphomas using extensive immunophenotypes from an antibody microarray.</a> Br. J. Haematol. 135, 184 (2006).</li><li>Belov, L., Huang, P., Barber, N., Mulligan, S. P., Christopherson, R. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+repertories+of+surface+antigens+on+leukemias+using+an+antibody+microarray.">Identification of repertories of surface antigens on leukemias using an antibody microarray.</a> Proteomics. 3, 2147 (2003).</li><li>Zhou, J., Belov, L., Huang, P. Y., Shin, J., Solomon, M. J., Chapuis, P. H., Bokey, L., Chan, C., Clarke, C., Clarke, S. J., Christopherson, R. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Surface+antigen+profiling+of+colorectal+cancer+using+antibody+microarrays+with+fluorescence+multiplexing.">Surface antigen profiling of colorectal cancer using antibody microarrays with fluorescence multiplexing.</a> J. Immunol. Methods. 355 (1-2), 40-51 (2010).</li><li>Ellmark, P., Belov, L., Huang, P., Lee, C. S., Solomon, M. J., Morgan, D. K., Christopherson, R. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplex+detection+of+surface+molecules+on+colorectal+cancers.">Multiplex detection of surface molecules on colorectal cancers.</a> Proteomics. 6, 1791 (2006).</li><li>Pearson, J. P., Allen, A., Hutton, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rheology+of+mucin.">Rheology of mucin.</a> Methods Mol. Biol. 125, 99 (2000).</li><li>Yang, Y. H., Dudoit, S., Luu, P., Lin, D. M., Peng, V., Ngai, J., Speed, T. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Normalization+for+cDNA+microarray+data:+a+robust+composite+method+addressing+single+and+multiple+slide+systematic+variation.">Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.</a> Nucleic Acids Res. 30, 15 (2002).</li><li>Al Saeed, ., 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=TMA:+A+free,+open-source+system+for+microarray+data+management+and+analysis.">TMA: A free, open-source system for microarray data management and analysis.</a> BioTechniques. 34, 374-378 (2003).</li></ol>

No conflicts of interest declared.

In this video, we demonstrate how the DotScan antibody microarray can be used in a simple, semi-quantitative way to study surface antigen profiles for cell populations from CRC tissue.
Obtaining a viable single cell suspension from tissue is critical to the success of the experiment, because energy-dependent processes (eg., antigen capping and/or pseudopodia formation) appear to be required for firm binding of whole cells to antibody dots during incubation, while dead cells are subsequently wa...

The author's email has been corrected in the publication of <a href="http://www.jove.com/video/3322">Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing</a>. There was an error with the author, Jerry Zhou's, email. The author's email has been updated to:
j.zhou@uws.edu.au
from:
jzho7551@mail.usyd.edu.au

Erratum: Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

<table border="1">
 <tbody>
 <tr>
 <th>Name of reagent or equipment</th>
 <th>Company</th>
 <th>Catalogue number</th>
 <th>Comments</th>
 </tr>
 <tr>
 <td>Hanks' balanced salt solution</td>
 <td>Sigma-Aldrich</td>
 <td>H6136-10X1L</td>
 <td>Buffered with 25 mM Hepes (Sigma #H3375)</td>
 </tr>
 <tr>
 <td>Airpure biological safety cabinet class II</td>
 <td>Westinghouse</td>
 <td>1687-2340/612</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Surgical blades</td>
 <td>Livingstone</td>
 <td>090609</td>
 <td>Pack of 100</td>
 </tr>
 <tr>
 <td>RPMI 1640 with 2 mM Hepes</td>
 <td>Sigma-Aldrich</td>
 <td>R4130-10X1L</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Collagenase type 4</td>
 <td>Worthington</td>
 <td>4188</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Deoxyribonuclease 1</td>
 <td>Sigma-Aldrich</td>
 <td>DN25-1G</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Terumo Syringe (10 mL)</td>
 <td>Terumo</td>
 <td>SS+10L</td>
 <td>Box of 100</td>
 </tr>
 <tr>
 <td>Filcon filter (200 &mu;m)</td>
 <td>BD Biosciences</td>
 <td>340615</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Filcon filter (50 &mu;m)</td>
 <td>Filcon filter (50 &mu;m)</td>
 <td>Filcon filter (50 &mu;m) Filcon filter (50 &mu;m) 340603 </td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Fetal calf serum</td>
 <td>Gibco/Invitrogen</td>
 <td>10099-141</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Centrifuge 5810 R</td>
 <td>Eppendorf</td>
 <td>7017</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Dimethyl sulphoxide</td>
 <td>Sigma-Aldrich</td>
 <td>D2650</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Trypan blue</td>
 <td>Sigma-Aldrich</td>
 <td>T8154</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Hemocymeter Technocolor Neubar</td>
 <td>Hirschmann</td>
 <td>not available</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Light microscope</td>
 <td>Nikon</td>
 <td>Nikon TMS</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Cyrovial tubes</td>
 <td>Greiner bio-one</td>
 <td>121278</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Cryo freezing contrainer</td>
 <td>Nalgene</td>
 <td>5100-0001</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>DotScan antibody microarray kit</td>
 <td>Medsaic</td>
 <td>not available</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>DotScan microarray wash tray</td>
 <td>Medsaic</td>
 <td>not available</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>KimWipes</td>
 <td>Kimberly-Clark</td>
 <td>4103</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Formaldehyde 37%</td>
 <td>Sigma-Aldrich</td>
 <td>F1635-500ML</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>DotReaderTM</td>
 <td>Medsaic</td>
 <td>not available</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Bovine serum albumin</td>
 <td>Sigma-Aldrich</td>
 <td>A9418-10G</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Heat-inactivated AB serum 2%</td>
 <td>Invitrogen</td>
 <td>34005100</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Phycoerythrin-conjugated CD3</td>
 <td>Beckman Coulter</td>
 <td>ET386</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>AlexaFluor647-conjugated EpCAM</td>
 <td>BioLegend</td>
 <td>324212</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Typhoon FLA 9000</td>
 <td>GE Healthcare</td>
 <td>28-9558-08</td>
 <td>532 nm laser, 580 BP30 emission filter for PE. 633 nm laser and 670 BP30 emission filter for Alexa647</td>
 </tr>
 <tr>
 <td>MultiExperiment Viewer v4.4</td>
 <td>TM4 Microarray Software Suite</td>
 <td>Open &#x2013; source software (Ref 11)</td>
 <td>&nbsp;</td>
 </tr>
 </tbody>
</table>

colorectal cancer cell surface protein profiling using an antibody microarray and fluorescence multiplexing

The current prognosis and classification of CRC relies on staging systems that integrate histopathologic and clinical findings. However, in the majority of CRC cases, cell dysfunction is the result of numerous mutations that modify protein expression and post-translational modification1.
A number of cell surface antigens, including cluster of differentiation (CD) antigens, have been identified as potential prognostic or metastatic biomarkers in CRC. These antigens make ideal biomarkers as their expression often changes with tumour progression or interactions with other cell types, such as tumour-infiltrating lymphocytes (TILs) and tumour-associated macrophages (TAMs).
The use of immunohistochemistry (IHC) for cancer sub-classification and prognostication is well established for some tumour types2,3. However, no single &#x2018;marker&#x2019; has shown prognostic significance greater than clinico-pathological staging or gained wide acceptance for use in routine pathology reporting of all CRC cases. 
A more recent approach to prognostic stratification of disease phenotypes relies on surface protein profiles using multiple 'markers'. While expression profiling of tumours using proteomic techniques such as iTRAQ is a powerful tool for the discovery of biomarkers4, it is not optimal for routine use in diagnostic laboratories and cannot distinguish different cell types in a mixed population. In addition, large amounts of tumour tissue are required for the profiling of purified plasma membrane glycoproteins by these methods. 
In this video we described a simple method for surface proteome profiling of viable cells from disaggregated CRC samples using a DotScan CRC antibody microarray. The 122-antibody microarray consists of a standard 82-antibody region recognizing a range of lineage-specific leukocyte markers, adhesion molecules, receptors and markers of inflammation and immune response5, together with a satellite region for detection of 40 potentially prognostic markers for CRC. Cells are captured only on antibodies for which they express the corresponding antigen. The cell density per dot, determined by optical scanning, reflects the proportion of cells expressing that antigen, the level of expression of the antigen and affinity of the antibody6. 
For CRC tissue or normal intestinal mucosa, optical scans reflect the immunophenotype of mixed populations of cells. Fluorescence multiplexing can then be used to profile selected sub-populations of cells of interest captured on the array. For example, Alexa 647-anti-epithelial cell adhesion molecule (EpCAM; CD326), is a pan-epithelial differentiation antigen that was used to detect CRC cells and also epithelial cells of normal intestinal mucosa, while Phycoerythrin-anti-CD3, was used to detect infiltrating T-cells7. The DotScan CRC microarray should be the prototype for a diagnostic alternative to the anatomically-based CRC staging system.

Watch this Scientific Journal Video about Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing at JoVE.com

Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

We described a procedure for the disaggregation of colorectal cancer (CRC) to produce viable single cells, which are then captured on customized antibody microarrays recognizing surface antigens (DotScan CRC microarray). Sub-populations of cells bound to the microarray can be profiled by fluorescence multiplexing using monoclonal antibodies tagged with fluorescent dyes.

The current prognosis and classification of CRC relies on staging systems that integrate histopathologic and clinical findings. However, in the majority ...

colorectal-cancer-cell-surface-protein-profiling-using-an-antibody

Research

JoVE Journal

Immunology and Infection

13.9K Views.  University of Sydney. We described a procedure for the disaggregation of colorectal cancer (CRC) to produce viable single cells, which are then captured on customized antibody microarrays recognizing surface antigens (DotScan CRC microarray). Sub-populations of cells bound to the microarray can be profiled by fluorescence multiplexing using monoclonal antibodies tagged with fluorescent dyes.

Video: Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

Using a Pan-Viral Microarray Assay (Virochip) to Screen Clinical Samples for Viral Pathogens

The diagnosis of viral causes of many infectious diseases is difficult due to the inherent sequence diversity of viruses as well as the ongoing emergence of novel viral pathogens, such as SARS coronavirus and 2009 pandemic H1N1 influenza virus, that are not detectable by traditional methods. To address these challenges, we have previously developed and validated a pan-viral microarray platform called the Virochip with the capacity to detect all known viruses as well as novel variants on the basis of conserved sequence homology1. Using the Virochip, we have identified the full spectrum of viruses associated with respiratory infections, including cases of unexplained critical illness in hospitalized patients, with a sensitivity equivalent to or superior to conventional clinical testing2-5. The Virochip has also been used to identify novel viruses, including the SARS coronavirus6,7, a novel rhinovirus clade5, XMRV (a retrovirus linked to prostate cancer)8, avian bornavirus (the cause of a wasting disease in parrots)9, and a novel cardiovirus in children with respiratory and diarrheal illness10. The current version of the Virochip has been ported to an Agilent microarray platform and consists of ~36,000 probes derived from over ~1,500 viruses in GenBank as of December of 2009. Here we demonstrate the steps involved in processing a Virochip assay from start to finish (~24 hour turnaround time), including sample nucleic acid extraction, PCR amplification using random primers, fluorescent dye incorporation, and microarray hybridization, scanning, and analysis.

Using a Pan-Viral Microarray Assay Virochip to Screen Clinical Samples for Viral Pathogens

The Virochip is a pan-viral microarray designed to simultaneously detect all known viruses as well as novel viruses on the basis of conserved sequence homology. Here we demonstrate how to run a Virochip assay to analyze clinical samples for the presence of both known and unknown viruses.

The diagnosis of viral causes of many infectious diseases is difficult due to the inherent sequence diversity of viruses as well as the ongoing emergence ...

Immuno-fluorescence Assay of Leptospiral Surface-exposed Proteins

Bacterial surface proteins are involved in direct contact with host cells and in uptake of nutrients from the environment 1. For this reason, cellular localization can provide insights into the functional role of bacterial proteins. Surface localization of bacterial proteins is a key step towards identification of virulence factors involved in mechanisms of pathogenicity. 
Methods for fractionating leptospiral membranes 2-5 may be selective for a certain class of outer-membrane proteins (OMPs), such as lipoproteins vs. transmembrane OMPs, and therefore lead to misclassification. This likely is due to structural differences and how they are associated to the outer membrane. Lipoproteins are associated with membranes via a hydrophobic interaction between the N-terminal lipid moiety (three fatty acids) and the lipid bilayer phospholipids 6, 7. In contrast, transmembrane OMPs are typically integrated into the lipid bilayer by amphipathic &beta;-sheets arranged in a barrel-like structure 8, 9. In addition, presence of a protein in the outer-membrane does not necessarily guarantee that the protein or its domains are exposed on the surface. Spirochetal outer membranes are known to be fragile and therefore necessitate methods involving gentle manipulation of cells and inclusion of sub-surface protein controls to assess the integrity of the outer membrane.
Here, we present an immunofluorescence assay (IFA) method to directly assess surface exposure of proteins on intact leptospires. This method is based on recognition of leptospiral surface proteins by antigen-specific antibodies. Herein, antibodies specific for OmpL5410 are detetcted aftero binding to native, surface exposed epitopes. Comparison of antibody reactivity to intact versus permeabilized cells enables evaluation of cellular distribution and whether or not a protein is selectively present on leptospiral surface. The integrity of outer membrane should be assessed using antibody to one or more subsurface proteins, preferably located in the periplasm.
The surface IFA method can be used to analyze surface exposure of any leptospiral protein to which specific antibodies are available. Both the usefulness and limitation of the method depends on whether the antibodies employed are able to bind to native epitopes. Since antibodies often are raised against recombinant proteins, epitopes of native, surface-exposed proteins may not be recognized. Nevertheless, the surface IFA method is a valuable tool for studying components of intact bacterial surfaces. This method can be applied not only for leptospires but also other spirochetes and gram-negative bacteria. For stronger conclusions regarding surface-exposure of OMPs, a comprehensive approach involving several cell localization methods is recommended 10.

An efficient method to assess surface-exposure of leptospiral proteins is described. The method is specifically designed to avoid disruption of the fragile outer membrane of leptospiral cells. This technique requires employment of several negative controls to assess the integrity of the outer membrane and specificity of antibody reaction.

Bacterial surface proteins are involved in direct contact with host cells and in uptake of nutrients from the environment 1. For this reason, cellular ...

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Biofilm formation is a general attribute to almost all bacteria 1-6. When bacteria form biofilms, cells are encased in extracellular matrix that is mostly constituted by proteins and exopolysaccharides, among other factors 7-10. The microbial community encased within the biofilm often shows the differentiation of distinct subpopulation of specialized cells 11-17. These subpopulations coexist and often show spatial and temporal organization within the biofilm 18-21.
Biofilm formation in the model organism Bacillus subtilis requires the differentiation of distinct subpopulations of specialized cells. Among them, the subpopulation of matrix producers, responsible to produce and secrete the extracellular matrix of the biofilm is essential for biofilm formation 11,19. Hence, differentiation of matrix producers is a hallmark of biofilm formation in B. subtilis.
We have used fluorescent reporters to visualize and quantify the subpopulation of matrix producers in biofilms of B. subtilis 15,19,22-24. Concretely, we have observed that the subpopulation of matrix producers differentiates in response to the presence of self-produced extracellular signal surfactin 25. Interestingly, surfactin is produced by a subpopulation of specialized cells different from the subpopulation of matrix producers 15.
We have detailed in this report the technical approach necessary to visualize and quantify the subpopulation of matrix producers and surfactin producers within the biofilms of B. subtilis. To do this, fluorescent reporters of genes required for matrix production and surfactin production are inserted into the chromosome of B. subtilis. Reporters are expressed only in a subpopulation of specialized cells. Then, the subpopulations can be monitored using fluorescence microscopy and flow cytometry (See Fig 1).
The fact that different subpopulations of specialized cells coexist within multicellular communities of bacteria gives us a different perspective about the regulation of gene expression in prokaryotes. This protocol addresses this phenomenon experimentally and it can be easily adapted to any other working model, to elucidate the molecular mechanisms underlying phenotypic heterogeneity within a microbial community.

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Microbial biofilms are generally constituted by distinct subpopulations of specialized cells. Single-cell analysis of these subpopulations requires the use of fluorescent reporters. Here we describe a protocol to visualize and monitor several subpopulationswithin B. subtilis biofilms using fluorescence microscopy and flow cytometry.

Biofilm formation is a general attribute to almost all bacteria 1-6. When bacteria form biofilms, cells are encased in extracellular matrix that is mostly ...

Visualization of Bacterial Toxin Induced Responses Using Live Cell Fluorescence Microscopy

Bacterial toxins bind to cholesterol in membranes, forming pores that allow for leakage of cellular contents and influx of materials from the external environment. The cell can either recover from this insult, which requires active membrane repair processes, or else die depending on the amount of toxin exposure and cell type1. In addition, these toxins induce strong inflammatory responses in infected hosts through activation of immune cells, including macrophages, which produce an array of pro-inflammatory cytokines2. Many Gram positive bacteria produce cholesterol binding toxins which have been shown to contribute to their virulence through largely uncharacterized mechanisms.
Morphologic changes in the plasma membrane of cells exposed to these toxins include their sequestration into cholesterol-enriched surface protrusions, which can be shed into the extracellular space, suggesting an intrinsic cellular defense mechanism3,4. This process occurs on all cells in the absence of metabolic activity, and can be visualized using EM after chemical fixation4. In immune cells such as macrophages that mediate inflammation in response to toxin exposure, induced membrane vesicles are suggested to contain cytokines of the IL-1 family and may be responsible both for shedding toxin and disseminating these pro-inflammatory cytokines5,6,7. A link between IL-1&beta; release and a specific type of cell death, termed pyroptosis has been suggested, as both are caspase-1 dependent processes8. To sort out the complexities of this macrophage response, which includes toxin binding, shedding of membrane vesicles, cytokine release, and potentially cell death, we have developed labeling techniques and fluorescence microscopy methods that allow for real time visualization of toxin-cell interactions, including measurements of dysfunction and death (Figure 1). Use of live cell imaging is necessary due to limitations in other techniques. Biochemical approaches cannot resolve effects occurring in individual cells, while flow cytometry does not offer high resolution, real-time visualization of individual cells. The methods described here can be applied to kinetic analysis of responses induced by other stimuli involving complex phenotypic changes in cells.

Methods for purifying the cholesterol binding toxin streptolysin O from recombinant E. coli and visualization of toxin binding to live eukaryotic cells are described. Localized delivery of toxin induces rapid and complex changes in targeted cells revealing novel aspects of toxin biology.

Bacterial toxins bind to cholesterol in membranes, forming pores that allow for leakage of cellular contents and influx of materials from the external ...

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Significant efforts were gathered to generate large-scale comprehensive protein-protein interaction network maps. This is instrumental to understand the pathogen-host relationships and was essentially performed by genetic screenings in yeast two-hybrid systems. The recent improvement of protein-protein interaction detection by a Gaussia luciferase-based fragment complementation assay now offers the opportunity to develop integrative comparative interactomic approaches necessary to rigorously compare interaction profiles of proteins from different pathogen strain variants against a common set of cellular factors.
This paper specifically focuses on the utility of combining two orthogonal methods to generate protein-protein interaction datasets: yeast two-hybrid (Y2H) and a new assay, high-throughput Gaussia princeps protein complementation assay (HT-GPCA) performed in mammalian cells.
A large-scale identification of cellular partners of a pathogen protein is performed by mating-based yeast two-hybrid screenings of cDNA libraries using multiple pathogen strain variants. A subset of interacting partners selected on a high-confidence statistical scoring is further validated in mammalian cells for pair-wise interactions with the whole set of pathogen variants proteins using HT-GPCA. This combination of two complementary methods improves the robustness of the interaction dataset, and allows the performance of a stringent comparative interaction analysis. Such comparative interactomics constitute a reliable and powerful strategy to decipher any pathogen-host interplays.

This article focuses on the identification of high-confident interaction datasets between host and pathogen proteins using a combination of two orthogonal methods: yeast two-hybrid followed by a high-throughput interaction assay in mammalian cells called HT-GPCA.

Significant efforts were gathered to generate  large-scale comprehensive protein-protein interaction network maps. This is  instrumental to understand the ...

A Miniaturized Glycan Microarray Assay for Assessing Avidity and Specificity of Influenza A Virus Hemagglutinins

Influenza A virus (IAV) hemagglutinins recognize sialic acids on the cell surface as functional receptors to gain entry into cells. Wild waterfowl are the natural reservoir for IAV, but IAV can cross the species barrier to poultry, swine, horses and humans. Avian viruses recognize sialic acid attached to a penultimate galactose by a &#945;2-3 linkage (avian-type receptors) whereas human viruses preferentially recognize sialic acid with a &#945;2-6 linkage (human-type receptors). To monitor if avian viruses are adapting to human type receptors, several methods can be used. Glycan microarrays with diverse libraries of synthetic sialosides are increasingly used to evaluate receptor specificity. However, this technique is not used for measuring avidities. Measurement of avidity is typically achieved by evaluating the binding of serially diluted hemagglutinin or virus to glycans adsorbed to conventional polypropylene 96-well plates. In this assay, glycans with &#945;2-3 or &#945;2-6 sialic acids are coupled to biotin and adsorbed to streptavidin plates, or are coupled to polyacrylamide (PAA) which directly adsorb to the plastic. We have significantly miniaturized this assay by directly printing PAA-linked sialosides and their non PAA-linked counterparts on micro-well glass slides. This set-up, with 48 arrays on a single slide, enables simultaneous assays of 6 glycan binding proteins at 8 dilutions, interrogating 6 different glycans, including two non-sialylated controls. This is equivalent to 18x 96-well plates in the traditional plate assay. The glycan array format decreases consumption of compounds and biologicals and thus greatly enhances efficiency.

Using a printed glycan microarray strategy, a conventional 96-well plate assay was miniaturized for analysis of influenza A virus hemagglutinin avidity and specificity for sialic acid containing receptors.

Influenza A virus (IAV) hemagglutinins recognize sialic acids on the cell surface as functional receptors to gain entry into cells. Wild waterfowl are the ...

Antibody Labeling with Fluorescent Dyes Using Magnetic Protein A and Protein G Beads

Antibodies labeled with small molecules like fluorescent dyes, cytotoxic drugs, and radioactive tracers are essential tools in biomedical research, immunodiagnostics and more recently as therapeutic agents. Traditional methods for labeling antibodies with small molecules require purified antibodies at relatively high concentration, involve multiple dialysis steps and have limited throughput. However, several applications, including the field of Antibody Drug Conjugates (ADCs), will benefit from new methods that will allow labeling of antibodies directly from cell media. Such methods may allow antibodies to be screened in biologically relevant assays, for example, the receptor-mediated antibody internalization assay in the case of ADCs. Here, we describe a method (on-bead method) that enables labeling of small amounts of antibodies directly from cell media. This approach utilizes high capacity magnetic Protein A and Protein G affinity beads to capture antibodies from the cell media followed by labeling with small molecules using either amine or thiol chemistry and subsequent elution of the labeled antibodies. Taking fluorescent dyes as surrogates for small molecules, we demonstrate the on-bead labeling of three different mouse antibodies directly from cell media using both amine and thiol labeling chemistry. The high binding affinity of antibodies to Protein A and Protein G ensures high recoveries as well as high purity of the labeled antibodies. In addition, use of magnetic beads allows multiple samples to be handled manually, thereby significantly improving labeling throughput.

The on-bead method for labeling antibodies with small molecules enables labeling of a small amount of antibodies directly from cell media. This method is compatible with amine and thiol chemistry, and can handle multiple samples in parallel, manually or using automated platforms.

Antibodies labeled with small molecules like fluorescent dyes, cytotoxic drugs, and radioactive tracers are essential tools in biomedical research, ...

A Protein Microarray Assay for Serological Determination of Antigen-specific Antibody Responses Following Clostridium difficile Infection

We provide a detailed overview of a novel high-throughput protein microarray assay for the determination of anti-Clostridium difficile antibody levels in human sera and in separate preparations of polyclonal intravenous immunoglobulin (IVIg). The protocol describes the methodological steps involved in sample preparation, printing of arrays, assay procedure, and data analysis. In addition, this protocol could be further developed to incorporate diverse clinical samples including plasma and cell culture supernatants. We show how protein microarray can be used to determine a combination of isotype (IgG, IgA, IgM), subclass (IgG1, IgG2, IgG3, IgG4, IgA1, IgA2), and strain-specific antibodies to highly purified whole C. difficile toxins A and B (toxinotype 0, strain VPI 10463, ribotype 087), toxin B from a C. difficile toxin-B-only expressing strain (CCUG 20309), a precursor form of a B fragment of binary toxin, pCDTb, ribotype-specific whole surface layer proteins (SLPs; 001, 002, 027), and control proteins (tetanus toxoid and Candida albicans). During the experiment, microarrays are probed with sera from individuals with C. difficile infection (CDI), individuals with cystic fibrosis (CF) without diarrhea, healthy controls (HC), and from individuals pre- and post-IVIg therapy for the treatment of CDI, combined immunodeficiency disorder, and chronic inflammatory demyelinating polyradiculopathy. We encounter significant differences in toxin neutralization efficacies and multi-isotype specific antibody levels between patient groups, commercial preparations of IVIg, and sera before and following IVIg administration. Also, there is a significant correlation between microarray and enzyme-linked immunosorbent assay (ELISA) for antitoxin IgG levels in serum samples. These results suggest that microarray could become a promising tool for profiling antibody responses to C.difficile antigens in vaccinated or infected humans. With further refinement of antigen panels and a reduction in production costs, we anticipate that microarray technology may help optimize and select the most clinically useful immunotherapies for C. difficile infection in a patient-specific manner.

A Protein Microarray Assay for Serological Determination of Antigen-specific Antibody Responses Following Clostridium difficile Infection

This article describes a simple protein microarray method for profiling humoral immune responses to a 7-plex panel of highly purified Clostridium difficile antigens in human sera. The protocol can be extended for the determination of specific antibody responses in preparations of polyclonal intravenous immunoglobulin.

We provide a detailed overview of a novel high-throughput protein microarray assay for the determination of anti-Clostridium difficile antibody levels in ...

Single-cell Quantitation of mRNA and Surface Protein Expression in Simian Immunodeficiency Virus-infected CD4+ T Cells Isolated from Rhesus macaques

Single-cell analysis is an important tool for dissecting heterogeneous populations of cells. The identification and isolation of rare cells can be difficult. To overcome this challenge, a methodology combining indexed flow cytometry and high-throughput multiplexed quantitative polymerase chain reaction (qPCR) was developed. The objective was to identify and characterize simian immunodeficiency virus (SIV)-infected cells present within rhesus macaques. Through quantitation of surface protein by fluorescence-activated cell sorting (FACS) and mRNA by qPCR, virus-infected cells are identified by viral gene expression, which is combined with host gene and protein measurements to create a multidimensional profile. We term the approach, targeted Single-Cell Proteo-transcriptional Evaluation, or tSCEPTRE. To perform the method, viable cells are stained with fluorescent antibodies specific for surface markers used for FACS isolation of a cell subset and/or downstream phenotypic analysis. Single cells are sorted followed by immediate lysis, multiplex reverse transcription (RT), PCR pre-amplification, and high throughput qPCR of up to 96 transcripts. FACS measurements are recorded at the time of sorting and subsequently linked to the gene expression data by well position to create a combined protein and transcriptional profile. To study SIV-infected cells directly ex vivo, cells were identified by qPCR detection of multiple viral RNA species. The combination of viral transcripts and the quantity of each provide a framework for classifying cells into distinct stages of the viral life cycle (e.g., productive versus non-productive). Moreover, tSCEPTRE of SIV+ cells were compared to uninfected cells isolated from the same specimen to assess differentially expressed host genes and proteins. The analysis revealed previously unappreciated viral RNA expression heterogeneity among infected cells as well as in vivo SIV-mediated post-transcriptional gene regulation with single-cell resolution. The tSCEPTRE method is relevant for the analysis of any cell population amenable to identification by expression of surface protein marker(s), host or pathogen gene(s), or combinations thereof.

Single-cell Quantitation of mRNA and Surface Protein Expression in Simian Immunodeficiency Virus-infected CD4+ T Cells Isolated from Rhesus macaques

Described is a methodology to quantitate the expression of 96 genes and 18 surface proteins by single cells ex vivo, allowing for the identification of differentially expressed genes and proteins in virus-infected cells relative to uninfected cells. We apply the approach to study SIV-infected CD4+ T cells isolated from rhesus macaques.

Single-cell analysis is an important tool for dissecting heterogeneous populations of cells. The identification and isolation of rare cells can be ...

Using Enhanced Green Fluorescence Protein-expressing Escherichia Coli to Assess Mouse Peritoneal Macrophage Phagocytosis

This manuscript describes a simple and reproducible method to perform a phagocytosis assay. The first part of this method involves building a pET-SUMO-EGFP vector (SUMO = small ubiquitin-like modifier) and expressing enhanced green fluorescence protein (EGFP) in Escherichia coli (BL21DE). EGFP-expressing E. coli is coincubated with macrophages for 1 h at 37 &#176;C; the negative control group is incubated on ice for the same amount of time. Then, the macrophages are ready for assessment. The advantages of this technique include its simple and straightforward steps, and phagocytosis can be measured by both flow cytometer and fluorescence microscope. The EGFP-expressing E. coli are stable and display a strong fluorescence signal even after the macrophages are fixed with paraformaldehyde. This method is not only suitable for the assessment of macrophage cell lines or primary macrophages in vitro but also suitable for the evaluation of granulocyte and monocyte phagocytosis in peripheral blood mononuclear cells. The results show that the phagocytic capability of peritoneal macrophages from young (eight-week-old) mice is higher than that of macrophages from aged (16-month-old) mice. In summary, this method measures macrophage phagocytosis and is suitable for studying the innate immune system function.

Using Enhanced Green Fluorescence Protein-expressing Escherichia Coli to Assess Mouse Peritoneal Macrophage Phagocytosis

Here, we present a protocol to assess mouse peritoneal macrophage phagocytosis using enhanced green fluorescence protein-expressing Escherichia coli.