Limits...
Cytometry-based single-cell analysis of intact epithelial signaling reveals MAPK activation divergent from TNF-α-induced apoptosis in vivo.

Simmons AJ, Banerjee A, McKinley ET, Scurrah CR, Herring CA, Gewin LS, Masuzaki R, Karp SJ, Franklin JL, Gerdes MJ, Irish JM, Coffey RJ, Lau KS - Mol. Syst. Biol. (2015)

Bottom Line: A 21-plex CyTOF analysis encompassing core signaling and cell-identity markers was performed on the small intestinal epithelium after systemic tumor necrosis factor-alpha (TNF-α) stimulation.Specifically, p-ERK and apoptosis are divergently regulated in neighboring enterocytes within the epithelium, suggesting a mechanism of contact-dependent survival.Our novel single-cell approach can broadly be applied, using both CyTOF and multi-parameter flow cytometry, for investigating normal and diseased cell states in a wide range of epithelial tissues.

View Article: PubMed Central - PubMed

Affiliation: Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, TN, USA Department of Cell and Developmental Biology, Vanderbilt University Medical Center, Nashville, TN, USA.

No MeSH data available.


Related in: MedlinePlus

Quantitative comparison between single-cell cytometric data and IF data of phospho-protein signaling markersQuantification of single cells prepared from the intestinal epithelium using DISSECT followed by flow cytometry (solid lines) was compared to quantification of the same tissue by IF imaging analysis (broken lines). The dynamics of activation for each protein signaling marker by TNF-α from the duodenum and ileum were captured throughout a time course post-TNF-α exposure (left column). Quantitative data from different time points and/or different regions were used to generate a range of variation for correlation analysis between DISSECT-flow and IF for each signaling marker (right column). Error bars represent SEM from n = 3 animals. A total of n = 30 samples were used for each correlation. Data scales are Z-score values derived from mean centering and variance scaling of each time course experiment (see Appendix Fig S8). ns, not significant (P > 0.05), *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001, ****P ≤ 0.0001.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4631206&req=5

fig03: Quantitative comparison between single-cell cytometric data and IF data of phospho-protein signaling markersQuantification of single cells prepared from the intestinal epithelium using DISSECT followed by flow cytometry (solid lines) was compared to quantification of the same tissue by IF imaging analysis (broken lines). The dynamics of activation for each protein signaling marker by TNF-α from the duodenum and ileum were captured throughout a time course post-TNF-α exposure (left column). Quantitative data from different time points and/or different regions were used to generate a range of variation for correlation analysis between DISSECT-flow and IF for each signaling marker (right column). Error bars represent SEM from n = 3 animals. A total of n = 30 samples were used for each correlation. Data scales are Z-score values derived from mean centering and variance scaling of each time course experiment (see Appendix Fig S8). ns, not significant (P > 0.05), *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001, ****P ≤ 0.0001.

Mentions: We expect comparable quantitative approaches to have relatively comparable signal-to-noise detection. With regard to noise, we compared the standard deviation of signals generated from biological replicates using different quantitative approaches. Results generated by DISSECT followed by flow cytometry matched with those obtained by lysate-based ELISA and quantitative immunofluorescence imaging, demonstrating that these assays pick up comparable levels of noise (Appendix Fig S6). With regard to signal, we performed rigorous, quantitative comparisons of TNF-α-induced signaling measurements between DISSECT-flow cytometry and two gold standard methods: quantitative immunofluorescence imaging (Fig3) and quantitative immunoblotting (Appendix Fig S7). A summary of how we derived quantitative information from each of the three methods is documented in Appendix Fig S8. The same set of antibodies was used for all three methods to evaluate protein states, such as phosphorylation and cleavage, that act as direct surrogates of signaling pathway activation. Three cohorts of mice (30 samples) were used for each analysis, and tissues from each animal were split three ways for different types of analyses. Because lysate-based approaches assess the average of all cell types in whole tissue, our cytometry analyses were also performed in a bulk cell population manner to enable direct comparison between approaches. To sample a wide dynamic range, we leveraged tissues from the duodenum and ileum (which exhibit differential TNF-α signaling responses), as well as from different time points post-TNF-α exposure to generate quantitative correlation analyses. Ten out of eleven protein analytes generated statistically significant correlations between DISSECT-flow quantification and imaging quantification (6 out of 6 with quantitative immunoblotting) (Fig3, Appendix Fig S7). Combined correlation analyses using all protein analytes resulted in a highly significant correlation (P < 0.0001) between DISSECT-flow and imaging data, and between DISSECT-flow and immunoblotting data. Pearson's coefficients of comparing DISSECT-flow to imaging and immunoblotting were 0.72 and 0.81, respectively. Factors that contribute to the imperfect correlation include inherent experimental noise and differences in quantification between each of the methods, which will be discussed below. Furthermore, for a truly unbiased analysis, we did not exclude obvious data outliers that affected the normalization procedure, which can skew relatively small datasets and can subsequently weaken the correlations. Nevertheless, our conservative approach for validation still generated highly significant (P < 0.0001) correlations. These results demonstrate the validity of DISSECT to preserve native signaling during single-cell disaggregation, and to generate single-cell-level data, when aggregated as populations, detect similar signal-to-noise as gold standard population-based methods.


Cytometry-based single-cell analysis of intact epithelial signaling reveals MAPK activation divergent from TNF-α-induced apoptosis in vivo.

Simmons AJ, Banerjee A, McKinley ET, Scurrah CR, Herring CA, Gewin LS, Masuzaki R, Karp SJ, Franklin JL, Gerdes MJ, Irish JM, Coffey RJ, Lau KS - Mol. Syst. Biol. (2015)

Quantitative comparison between single-cell cytometric data and IF data of phospho-protein signaling markersQuantification of single cells prepared from the intestinal epithelium using DISSECT followed by flow cytometry (solid lines) was compared to quantification of the same tissue by IF imaging analysis (broken lines). The dynamics of activation for each protein signaling marker by TNF-α from the duodenum and ileum were captured throughout a time course post-TNF-α exposure (left column). Quantitative data from different time points and/or different regions were used to generate a range of variation for correlation analysis between DISSECT-flow and IF for each signaling marker (right column). Error bars represent SEM from n = 3 animals. A total of n = 30 samples were used for each correlation. Data scales are Z-score values derived from mean centering and variance scaling of each time course experiment (see Appendix Fig S8). ns, not significant (P > 0.05), *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001, ****P ≤ 0.0001.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4631206&req=5

fig03: Quantitative comparison between single-cell cytometric data and IF data of phospho-protein signaling markersQuantification of single cells prepared from the intestinal epithelium using DISSECT followed by flow cytometry (solid lines) was compared to quantification of the same tissue by IF imaging analysis (broken lines). The dynamics of activation for each protein signaling marker by TNF-α from the duodenum and ileum were captured throughout a time course post-TNF-α exposure (left column). Quantitative data from different time points and/or different regions were used to generate a range of variation for correlation analysis between DISSECT-flow and IF for each signaling marker (right column). Error bars represent SEM from n = 3 animals. A total of n = 30 samples were used for each correlation. Data scales are Z-score values derived from mean centering and variance scaling of each time course experiment (see Appendix Fig S8). ns, not significant (P > 0.05), *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001, ****P ≤ 0.0001.
Mentions: We expect comparable quantitative approaches to have relatively comparable signal-to-noise detection. With regard to noise, we compared the standard deviation of signals generated from biological replicates using different quantitative approaches. Results generated by DISSECT followed by flow cytometry matched with those obtained by lysate-based ELISA and quantitative immunofluorescence imaging, demonstrating that these assays pick up comparable levels of noise (Appendix Fig S6). With regard to signal, we performed rigorous, quantitative comparisons of TNF-α-induced signaling measurements between DISSECT-flow cytometry and two gold standard methods: quantitative immunofluorescence imaging (Fig3) and quantitative immunoblotting (Appendix Fig S7). A summary of how we derived quantitative information from each of the three methods is documented in Appendix Fig S8. The same set of antibodies was used for all three methods to evaluate protein states, such as phosphorylation and cleavage, that act as direct surrogates of signaling pathway activation. Three cohorts of mice (30 samples) were used for each analysis, and tissues from each animal were split three ways for different types of analyses. Because lysate-based approaches assess the average of all cell types in whole tissue, our cytometry analyses were also performed in a bulk cell population manner to enable direct comparison between approaches. To sample a wide dynamic range, we leveraged tissues from the duodenum and ileum (which exhibit differential TNF-α signaling responses), as well as from different time points post-TNF-α exposure to generate quantitative correlation analyses. Ten out of eleven protein analytes generated statistically significant correlations between DISSECT-flow quantification and imaging quantification (6 out of 6 with quantitative immunoblotting) (Fig3, Appendix Fig S7). Combined correlation analyses using all protein analytes resulted in a highly significant correlation (P < 0.0001) between DISSECT-flow and imaging data, and between DISSECT-flow and immunoblotting data. Pearson's coefficients of comparing DISSECT-flow to imaging and immunoblotting were 0.72 and 0.81, respectively. Factors that contribute to the imperfect correlation include inherent experimental noise and differences in quantification between each of the methods, which will be discussed below. Furthermore, for a truly unbiased analysis, we did not exclude obvious data outliers that affected the normalization procedure, which can skew relatively small datasets and can subsequently weaken the correlations. Nevertheless, our conservative approach for validation still generated highly significant (P < 0.0001) correlations. These results demonstrate the validity of DISSECT to preserve native signaling during single-cell disaggregation, and to generate single-cell-level data, when aggregated as populations, detect similar signal-to-noise as gold standard population-based methods.

Bottom Line: A 21-plex CyTOF analysis encompassing core signaling and cell-identity markers was performed on the small intestinal epithelium after systemic tumor necrosis factor-alpha (TNF-α) stimulation.Specifically, p-ERK and apoptosis are divergently regulated in neighboring enterocytes within the epithelium, suggesting a mechanism of contact-dependent survival.Our novel single-cell approach can broadly be applied, using both CyTOF and multi-parameter flow cytometry, for investigating normal and diseased cell states in a wide range of epithelial tissues.

View Article: PubMed Central - PubMed

Affiliation: Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, TN, USA Department of Cell and Developmental Biology, Vanderbilt University Medical Center, Nashville, TN, USA.

No MeSH data available.


Related in: MedlinePlus