The authors thank Robert Giulitto (Hoxworth blood center) for human blood samples and Dr. Liang Niu for the normalization of gene expression reads. We also thank grant support from the National Institute of Environmental Health Sciences (ES006096), Center for Environmental Genetics (CEG) pilot project (S.H.), National Institute of Allergy and Infectious Diseases (AI115358) (S.H.), University of Cincinnati University Research Council award (S.H.), and University of Cincinnati College of Medicine Core Enhancement Funding (X. Z.).

Human protocols in this study were approved by the Institutional Review Board of the University of Cincinnati and all methods were performed in accordance with the relevant guidelines and regulations. Blood samples from healthy donors were obtained from the Hoxworth Blood Center at the University of Cincinnati Medical Center.
1. Transcriptomic Profiling of Pollutant-exposed Human Monocyte-derived DCs
<ol>
	<li>Total RNA extraction of BaP-exposed DCs
	<ol>
		<li>Differentiate human DCs using ...

<ol>
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Functional confirmation of an altered gene pathway is challenging, because of widely impacted gene expression involving multiple pathways and the difficulty to&#160;integrate individual and populational cellular activities. We employed imaging flow cytometry to specifically test CD1d trafficking in endocytic compartments. Imaging flow cytometry integrates the populational measurement of cells and the individual demonstration of subcellular colocalization of multiple proteins. Confocal microscopy has previously provided h...

Antigen presentation typically involves intracellular protein trafficking, which has been often investigated using morphological characterization and phenotypic profiling of antigen presenting cells1,2,3. To integrate the advantages of imaging and phenotyping methods, we describe an imaging analysis platform at both single cell and population levels to demonstrate an altered protein colocalization in human dendritic cells (DCs). In peptide antigen presentation, major histocompatibility complex (MHC) class I molecules bind a short peptide (8-10 residues) in the endoplasmic reticulum to activate conventional CD8+ T cells, while MHC class II molecules bind a relatively longer peptide (~20 residues) in endocytic compartments to activate conventional CD4+ T cells1,4. In contrast, lipid-specific T cells are activated by CD1 proteins with lipid antigens loaded mainly in endocytic compartments5,6. Lipid antigen presentation requires the supply of lipid metabolites produced in lipid metabolism7,8,9,10 and the loading of functional lipid metabolites to CD1 proteins in endocytic compartments5,6. In this context, various cellular factors modulating lipid antigen presentation, especially in environmental exposure of lipophilic pollutants and immune disorders, are critical to be defined. In this study, we used transcriptomic analysis, image profiling, and cellular and populational imaging analysis of human monocyte-derived DCs to determine the endocytic protein trafficking contributing to lipid antigen presentation in pollutant exposure. Certainly, this combined platform can be applied to studying subcellular protein trafficking and colocalization in different biological processes.
Technically, subcellular protein localization was usually demonstrated using confocal microscopy and statistically analyzed in a limited number of detected cells1,2,3,11. Moreover, flow cytometry has been broadly applied to gate cell populations with co-stained signals of multiple proteins at a cellular level12; however, this lacks a detailed visualization of subcellular protein colocalization. To achieve comprehensive and statistical analyses of percentage protein colocalization at both cellular and population levels, we incorporate imaging profiling and analysis approaches to determine the features of protein colocalization with biological relevance. Specifically, we use imaging flow cytometry to detect the colocalization of CD1d and lysosomal-associated membrane protein 1 (Lamp1) proteins in this study. Quantitative analysis of colocalized molecules was previously difficult to be performed at a populational scale. In this study, we adapted the ImageJ-Fiji program to examine the percentage of protein colocalization with a large number of co-stained cells at both populational and individual cellular levels. Specifically, we measured co-localized areas, intensity, and populational size to support the conclusion that the CD1d protein was largely retained in late endocytic compartments of human DCs in exposure to a lipophilic pollutant benzo[a]pyrene (BaP)13. This combined cellular and population imaging analysis provided highly reproducible, comprehensive, and statistically significant results of CD1d-Lamp1 colocalization relevant to inhibited lipid antigen presentation.
The transcriptome of BaP-exposed human DCs strongly supported the hypothesis that endocytic lipid metabolism and CD1d endocytic trafficking were impaired in BaP exposure. To test this hypothesis, we applied imaging flow cytometry to profile the images of DC population that were co-stained with multiple proteins including CD1d, endocytic markers, and DC markers. Finally, co-stained cells were statistically analyzed to demonstrate the percentage of intensity and areas of CD1d and Lamp1 colocalization.

<table border="0" cellpadding="0" cellspacing="0" style="width:1340px;" width="1340">
	<tbody>
		<tr height="19">
			<td height="19" style="height:19px;width:284px;">Transcriptomics</td>
			<td style="width:448px;">Illumina</td>
			<td style="width:417px;">HiSeq 2500 v4</td>
			<td style="width:191px;">Illumina HiSeq system</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:284px;">ImagingStream X</td>
			<td style="width:448px;">Millipore</td>
			<td>100220</td>
			<td>Imaging flow cytometry</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">mirVana miRNA Isolation Kit</td>
			<td style="width:448px;">Thermo Fisher</td>
			<td></td>
			<td>Total RNA extraction</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Agilent RNA 6000 Pico Kit</td>
			<td style="width:448px;">Agilent</td>
			<td></td>
			<td>Total RNA QC analysis</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Veriti 96-Well Fast Thermal Cycler</td>
			<td style="width:448px;">Thermo Fisher</td>
			<td></td>
			<td>PCR, enzyme reaction</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">NEBNext Poly(A) mRNA Magnetic Isolation Module&#160;</td>
			<td style="width:448px;">New England Biolab</td>
			<td></td>
			<td>PolyA RNA purification</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Automated SMARTer Apollo system</td>
			<td style="width:448px;">Takara</td>
			<td></td>
			<td>PolyA RNA purification</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">NEBNext Ultra RNA Library Prep Kit for Illumina</td>
			<td style="width:448px;">New England Biolab</td>
			<td></td>
			<td>Library preparation</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Agencourt AMPure XP magnetic beads</td>
			<td style="width:448px;">Beckman Coulter</td>
			<td></td>
			<td>DNA purification&#160;</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">2100 Bioanalyzer</td>
			<td style="width:448px;">Agilent</td>
			<td></td>
			<td>Library QC, size distribution analysis</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Agilent High Sensitivity DNA Kit</td>
			<td style="width:448px;">Agilent</td>
			<td></td>
			<td>Library QC, size distribution analysis</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">QuantStudio 5 Real-Time PCR System (Thermo Fisher)</td>
			<td style="width:448px;">Thermo Fisher</td>
			<td></td>
			<td>Library quantification</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">NEBNext Library Quant Kit</td>
			<td style="width:448px;">New England Biolab</td>
			<td></td>
			<td>Library quantification</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">cBot</td>
			<td style="width:448px;">Illumina</td>
			<td></td>
			<td>Library cluster generation</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">TruSeq SR Cluster Kit v3 - cBot &#8211; HS</td>
			<td style="width:448px;">Illumina</td>
			<td></td>
			<td>Library cluster generation</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">HiSeq 1000</td>
			<td style="width:448px;">Illumina</td>
			<td></td>
			<td>Sequencing</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">TruSeq SBS Kit v3 - HS (50-cycles)</td>
			<td style="width:448px;">Illumina</td>
			<td></td>
			<td>Sequencing</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:284px;">Phycoerythrin/Cyanine 7 (PE/Cy7)</td>
			<td style="width:448px;">Bio Legend</td>
			<td style="width:417px;">L243</td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:284px;">Phycoerythrin/Cyanine 5 (PE/Cy5)</td>
			<td style="width:448px;">Bio Legend</td>
			<td align="right" style="width:417px;">3.9</td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:284px;">Brilliant violet 421</td>
			<td style="width:448px;">Bio Legend</td>
			<td style="width:417px;">L161</td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:284px;">PE-anti-mouse IgG2b</td>
			<td style="width:448px;">Bio Legend</td>
			<td align="right" style="width:417px;">51.1</td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:284px;">Alexa Fluor 647 (AF647)</td>
			<td style="width:448px;">Bio Legend</td>
			<td style="width:417px;">CD107a(H4A3)</td>
			<td></td>
		</tr>
	</tbody>
</table>

integrate imaging flow cytometry and transcriptomic profiling to evaluate altered endocytic cd1d trafficking

Populational analyses of the morphological and functional alteration of endocytic proteins are challenging due to the demand of image capture at a single cell level and statistical image analysis at a populational level. To overcome this difficulty, we used imaging flow cytometry and transcriptomic profiling (RNA-seq) to determine altered subcellular localization of the cluster of differentiation 1d protein (CD1d) associated with impaired endocytic gene expression in human dendritic cells (DCs), which were exposed to the common lipophilic air pollutant benzo[a]pyrene. The colocalization of CD1d and endocytic marker Lamp1 proteins from thousands of cell images captured with imaging flow cytometry was analyzed using IDEAS and ImageJ-Fiji programs. Numerous cellular images with co-stained CD1d and Lamp1 proteins were visualized after gating on CD1d+Lamp1+ DCs using IDEAS. The enhanced CD1d and Lamp1 colocalization upon BaP exposure was further demonstrated using thresholded scatterplots, tested with Mander&#39;s coefficients for co-localized intensity, and plotted based on the percentage of co-localized areas using ImageJ-Fiji. Our data provide an advantageous instrumental and bioinformatic approach to measure protein colocalization at both single and populational cellular levels, supporting an impaired functional outcome of transcriptomic alteration in pollutant-exposed human DCs.

The lipophilic pollutant BaP alters endocytic gene clusters in human DCs. Human monocyte-derived DCs from each donor (n=3) were incubated with BaP and sorted for&#160;conventional DCs, which were further used for RNA extraction and transcriptomic analysis as described. Upon the normalization of gene expression, altered genes between BaP-exposed and non-exposed groups were clustered according to the functional correlation of differentially expressed genes. We input the altered gene list to...

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Integrate Imaging Flow Cytometry and Transcriptomic Profiling to Evaluate Altered Endocytic CD1d Trafficking

Imaging flow cytometry provides an ideal approach to detect the morphological and functional alteration of cells at individual and populational levels. Disrupted endocytic function for lipid antigen presentation in pollutant-exposed human dendritic cells was demonstrated with a combined transcriptomic profiling of gene expression and morphological demonstration of protein trafficking.

Populational analyses of the morphological and functional alteration of endocytic proteins are challenging due to the demand of image capture at a single ...

These methods integrate next generation sequencing and flow cytometry imaging analysis. It can help answer interesting questions, like whether some phenotypic alterations are implicate, instead of the transcriptome, especially in the pollutant exposure environment. The main advantage of this simple method for us is that we can use it to measure the colocalization of biologically important protein, to interpret the outcomes of key differential gene expression at a functional level.The implications of this technique extend toward the diagnosis of pathological and toxicological outcomes. As a normal imager approach, forsee has the ability to connect gene expression to protein function. Generally, individuals new to this method will struggle because of the high technical demands of the imaging and transcriptomic analysis.To sequence the the human monocyte derived dendritic cell library, first load the sequencing and indexing reagents onto the sequencing biosynthesis and indexing reagent racks, respectively, and place the racks in a laboratory grade water bath for one hour, until all of the ice has melted, and the reagents are mixed thoroughly. While the reagents are thawing, power on the sequencer, connecting the computer to a network drive when the Do Not Eject drive appears, and launch the sequencer control software. Next, add about 100 milliliters of maintenance wash solution to each of the bottles in the sequencing biosynthesis reagent rack, and screw a funnel cap onto each bottle.Add approximately 12 milliliters of maintenance wash solution to each 15 milliliter conical tube in the indexing reagent rack, and discard the caps. Then load both the racks onto the sequencer. Select Maintenance Wash within the sequencer control software, and follow the instructions for cleaning the sequencer fluid system.Use a flashlight to visually inspect the flow cell for bubbles passing through the lanes, to make sure there is no leakage. When the wash sequence is finished, open the Sequence tab, and start a new run, directing the output data to a network drive. Upload a sample sheet for demultiplexing, and enter the appropriate reagent information.Use a used flow cell to prime the system, with the sequencing reagents. Once the cluster generation is complete, remove the flow cell. And lightly spray the cell with water.Wipe the flow cell dry with lens paper, followed by a light spray with 95%ethanol. After wiping the flow cell dry again, check the flow cell's surface against the light to make sure that it is clean, without debris or salt residue. When the prime step is finished, load the clustered flow cell, and begin the sequencing.The sequence analysis viewer software will automatically be started. About 26 hours later, monitor the sequencing data quality via the high sequence control software, and sequencing analysis view software to assess the data quality, and for any troubleshooting. Then, when the sequence is finished, change the flow cell gasket, and perform a maintenance wash before beginning the next run.After flow cytometric imaging of the pollutant-exposed dendritic cells, open ImageJ Fiji, and merge the 100 saved cell images for the non-exposed and pollutant-exposed human dendritic cell sample groups into individual files according to the treatment group. To analyze CD1d, and Lamp1 colocalization within the two populations, open the pollutant-exposed 100 merged cell image, and select Image, Color, and Split Channels to split the image into two individual images with a single fluorophore per channel. To create a scatter plot of the colocalized pixels, select Analyze, Colocalization, and Colocalization Threshold, and press Print Screen to save the scatter plot.To calculate the Mander's colocalization coefficient for each single-cellular image, use the oval selection tool to select a single-cell image on the image file with the split channels, and select Analyze, Colocalization, and Colocalization Threshold again. Then select Channel 1 from the dialogue box for the region of interest, and click OK.When the coefficient has been calculated for all 100 cell images, import the results into an appropriate spreadsheet, and repeat the analysis for the control non-exposed cell sample. Using RNA sequencing and transcriptomic data analyses, several major altered gene clusters, including lipid metabolism and endocytic functions were identified in the pollutant-exposed DCs.At the individual cell image level, HLADR positive CD11c positive dendritic cells can be gated, according to their CD1d and Lamp1 coexpression. Control non-exposed dendritic cells demonstrate minimal CD1d and Lamp1 protein colocalization, indicating a basal level of CD1d endocytic trafficking, and a high level of surface expression under physiological conditions. Whereas CD1d is retained in the late endocytic compartments of pollutant-exposed dendritic cells, confirming altered endocytic gene profiles in this experimental cell population.After merging the individual cellular images into a single image file, the individual images can be split according to their fluorophore expression, and the colocalization of the pixel intensity between the two channels can be visualized in a scatter plot. The degree of colocalization between the CD1d and Lamp1 proteins in the two treatment groups can then be quantified using Mander's coefficients. If the protein intensity is hetergeneous between the colocalized and non-colocalized areas, the colocalized intensity will not be parallel to the colocalized areas, therefore it is also important to further assess the colocalization of the two proteins, based on the pixel intensity.Once mastered, the image analysis can be completed in two hours, and the RNA sequencing setup can be completed in three hours, if each technique is performed properly. While attempting this procedure, it is important to remember to make sure that all the reagents are properly loaded in the correct positions, and that there's no leakage in the sequencer. Following this procedure, other methods, like micro RNA, exome, or mast cell sequencing can be performed to answer additional questions about global micro RNA expression, gene mutation, or DNA methylation, respectively.So after it's development, this technique will help researchers in the field of cellular imaging analysis, and next generation sequencing to explore the effect of the environmental pollutant on gene expression and protein function. After watching this video, you should have a good understanding of how to set up the next generation sequencing, and the imager analysis of protein colocalization. Don't forget that working with a toxic pollutant chemicals in human blood samples can be extremely hazardous.Precautions such as using a chemical fume hood, and personal protective equipment, should always be taken when performing these procedures.

integrate-imaging-flow-cytometry-transcriptomic-profiling-to-evaluate

Research

JoVE Journal

Immunology and Infection

6.6K visualizações.  University of Cincinnati College of Medicine. Esses métodos integram a análise de imagem de sequenciamento e citometria de fluxo da próxima geração. Pode ajudar a responder perguntas interessantes, como se algumas alterações fenotípicas estão implicando, em vez do transcriptome, especialmente no ambiente de exposição ao poluente. A principal vantagem deste método simples para nós é que podemos usá-lo para medir a colocalização de proteína biologicamente importante, para interpretar os resultados da expressão genética ...