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High content analysis at single cell level identifies different cellular responses dependent on nanomaterial concentrations.

Manshian BB, Munck S, Agostinis P, Himmelreich U, Soenen SJ - Sci Rep (2015)

Bottom Line: A mechanistic understanding of nanomaterial (NM) interaction with biological environments is pivotal for the safe transition from basic science to applied nanomedicine.Upon binning the single cell data into different categories related to NM concentration, this study demonstrates, for the first time, that quantum dots activate both cytoprotective and cytotoxic mechanisms, resulting in a zero net result on the overall cell population, yet with significant effects in cells with higher cellular NM levels.Our results suggest that future NM cytotoxicity studies should correlate NM toxicity with cellular NM numbers on the single cell level, as conflicting mechanisms in particular cell subpopulations are commonly overlooked using classical toxicological methods.

View Article: PubMed Central - PubMed

Affiliation: MoSAIC/Biomedical MRI Unit, Faculty of Medicine, KU Leuven, Herestraat 49, B3000 Leuven, Belgium.

ABSTRACT
A mechanistic understanding of nanomaterial (NM) interaction with biological environments is pivotal for the safe transition from basic science to applied nanomedicine. NM exposure results in varying levels of internalized NM in different neighboring cells, due to variances in cell size, cell cycle phase and NM agglomeration. Using high-content analysis, we investigated the cytotoxic effects of fluorescent quantum dots on cultured cells, where all effects were correlated with the concentration of NMs at the single cell level. Upon binning the single cell data into different categories related to NM concentration, this study demonstrates, for the first time, that quantum dots activate both cytoprotective and cytotoxic mechanisms, resulting in a zero net result on the overall cell population, yet with significant effects in cells with higher cellular NM levels. Our results suggest that future NM cytotoxicity studies should correlate NM toxicity with cellular NM numbers on the single cell level, as conflicting mechanisms in particular cell subpopulations are commonly overlooked using classical toxicological methods.

No MeSH data available.


Related in: MedlinePlus

Overview of cellular effects in view of cellular QDot concentration at “non-toxic” conditions.(a) Heat maps of high-content imaging-based data for MSCs and MEFs exposed to QDots at 10 and 12.5 nM concentrations, respectively, at which slight but non-significant effects had been observed for nearly all the tested parameters based on the total cell population. Cells were analyzed for; cell viability, cell membrane damage, mitochondrial ROS, size of the mitochondrial network, area of the cell, skewness of the cell, and level of autophagy. For every cell, the relative level of QDots was also calculated based on the cellular QDot intensity and area, after which cells were divided into 10 categories based on their cellular QDot levels, ranging from c1 (lowest) to c10 (highest). Observed cellular effects were grouped based on the different categories of intracellular QDot concentrations. The data are shown as relative values after z-normalization compared to untreated control cells (=1) where the fold-change is indicated by the respective color-code. Data were acquired for minimum 5000 cells/condition and were gathered from three independent experiments. (b,c) Representative InCell high-content images of (b) MSCs and (c) MEFs exposed to the QDots at 10 and 12.5 nM, respectively. Red: QDots, Blue: Hoechst nuclear stain, Green: dead cells (left), mitochondrial ROS (middle), β-actin (right). Scale bars = 100 μm, the area in the white rectangle is depicted in a magnified view below the original image.
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f3: Overview of cellular effects in view of cellular QDot concentration at “non-toxic” conditions.(a) Heat maps of high-content imaging-based data for MSCs and MEFs exposed to QDots at 10 and 12.5 nM concentrations, respectively, at which slight but non-significant effects had been observed for nearly all the tested parameters based on the total cell population. Cells were analyzed for; cell viability, cell membrane damage, mitochondrial ROS, size of the mitochondrial network, area of the cell, skewness of the cell, and level of autophagy. For every cell, the relative level of QDots was also calculated based on the cellular QDot intensity and area, after which cells were divided into 10 categories based on their cellular QDot levels, ranging from c1 (lowest) to c10 (highest). Observed cellular effects were grouped based on the different categories of intracellular QDot concentrations. The data are shown as relative values after z-normalization compared to untreated control cells (=1) where the fold-change is indicated by the respective color-code. Data were acquired for minimum 5000 cells/condition and were gathered from three independent experiments. (b,c) Representative InCell high-content images of (b) MSCs and (c) MEFs exposed to the QDots at 10 and 12.5 nM, respectively. Red: QDots, Blue: Hoechst nuclear stain, Green: dead cells (left), mitochondrial ROS (middle), β-actin (right). Scale bars = 100 μm, the area in the white rectangle is depicted in a magnified view below the original image.

Mentions: Following this categorization, the results showed a clear impact of cellular NM levels on both the nature and degree of the cellular response (Fig. 3). For cells containing low to medium QDot levels, no significant effects were observed for any of the assessed parameters. However, at higher intracellular NM levels (categories 8–10), significant effects were observed, which, however, did not all correlate with intracellular NM levels. Mitochondrial stress and ROS (Supp Figs S09, S10), cell morphology and skewness (Supp Figs S11, S12) and autophagy (Supp Fig. S13) showed higher significance with an increase in intracellular QDot levels, whereas the highest levels of cell death and associated membrane damage were seen in categories 8 and 10, but less pronounced in category 9 (Supp Figs S14, S15).


High content analysis at single cell level identifies different cellular responses dependent on nanomaterial concentrations.

Manshian BB, Munck S, Agostinis P, Himmelreich U, Soenen SJ - Sci Rep (2015)

Overview of cellular effects in view of cellular QDot concentration at “non-toxic” conditions.(a) Heat maps of high-content imaging-based data for MSCs and MEFs exposed to QDots at 10 and 12.5 nM concentrations, respectively, at which slight but non-significant effects had been observed for nearly all the tested parameters based on the total cell population. Cells were analyzed for; cell viability, cell membrane damage, mitochondrial ROS, size of the mitochondrial network, area of the cell, skewness of the cell, and level of autophagy. For every cell, the relative level of QDots was also calculated based on the cellular QDot intensity and area, after which cells were divided into 10 categories based on their cellular QDot levels, ranging from c1 (lowest) to c10 (highest). Observed cellular effects were grouped based on the different categories of intracellular QDot concentrations. The data are shown as relative values after z-normalization compared to untreated control cells (=1) where the fold-change is indicated by the respective color-code. Data were acquired for minimum 5000 cells/condition and were gathered from three independent experiments. (b,c) Representative InCell high-content images of (b) MSCs and (c) MEFs exposed to the QDots at 10 and 12.5 nM, respectively. Red: QDots, Blue: Hoechst nuclear stain, Green: dead cells (left), mitochondrial ROS (middle), β-actin (right). Scale bars = 100 μm, the area in the white rectangle is depicted in a magnified view below the original image.
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Related In: Results  -  Collection

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f3: Overview of cellular effects in view of cellular QDot concentration at “non-toxic” conditions.(a) Heat maps of high-content imaging-based data for MSCs and MEFs exposed to QDots at 10 and 12.5 nM concentrations, respectively, at which slight but non-significant effects had been observed for nearly all the tested parameters based on the total cell population. Cells were analyzed for; cell viability, cell membrane damage, mitochondrial ROS, size of the mitochondrial network, area of the cell, skewness of the cell, and level of autophagy. For every cell, the relative level of QDots was also calculated based on the cellular QDot intensity and area, after which cells were divided into 10 categories based on their cellular QDot levels, ranging from c1 (lowest) to c10 (highest). Observed cellular effects were grouped based on the different categories of intracellular QDot concentrations. The data are shown as relative values after z-normalization compared to untreated control cells (=1) where the fold-change is indicated by the respective color-code. Data were acquired for minimum 5000 cells/condition and were gathered from three independent experiments. (b,c) Representative InCell high-content images of (b) MSCs and (c) MEFs exposed to the QDots at 10 and 12.5 nM, respectively. Red: QDots, Blue: Hoechst nuclear stain, Green: dead cells (left), mitochondrial ROS (middle), β-actin (right). Scale bars = 100 μm, the area in the white rectangle is depicted in a magnified view below the original image.
Mentions: Following this categorization, the results showed a clear impact of cellular NM levels on both the nature and degree of the cellular response (Fig. 3). For cells containing low to medium QDot levels, no significant effects were observed for any of the assessed parameters. However, at higher intracellular NM levels (categories 8–10), significant effects were observed, which, however, did not all correlate with intracellular NM levels. Mitochondrial stress and ROS (Supp Figs S09, S10), cell morphology and skewness (Supp Figs S11, S12) and autophagy (Supp Fig. S13) showed higher significance with an increase in intracellular QDot levels, whereas the highest levels of cell death and associated membrane damage were seen in categories 8 and 10, but less pronounced in category 9 (Supp Figs S14, S15).

Bottom Line: A mechanistic understanding of nanomaterial (NM) interaction with biological environments is pivotal for the safe transition from basic science to applied nanomedicine.Upon binning the single cell data into different categories related to NM concentration, this study demonstrates, for the first time, that quantum dots activate both cytoprotective and cytotoxic mechanisms, resulting in a zero net result on the overall cell population, yet with significant effects in cells with higher cellular NM levels.Our results suggest that future NM cytotoxicity studies should correlate NM toxicity with cellular NM numbers on the single cell level, as conflicting mechanisms in particular cell subpopulations are commonly overlooked using classical toxicological methods.

View Article: PubMed Central - PubMed

Affiliation: MoSAIC/Biomedical MRI Unit, Faculty of Medicine, KU Leuven, Herestraat 49, B3000 Leuven, Belgium.

ABSTRACT
A mechanistic understanding of nanomaterial (NM) interaction with biological environments is pivotal for the safe transition from basic science to applied nanomedicine. NM exposure results in varying levels of internalized NM in different neighboring cells, due to variances in cell size, cell cycle phase and NM agglomeration. Using high-content analysis, we investigated the cytotoxic effects of fluorescent quantum dots on cultured cells, where all effects were correlated with the concentration of NMs at the single cell level. Upon binning the single cell data into different categories related to NM concentration, this study demonstrates, for the first time, that quantum dots activate both cytoprotective and cytotoxic mechanisms, resulting in a zero net result on the overall cell population, yet with significant effects in cells with higher cellular NM levels. Our results suggest that future NM cytotoxicity studies should correlate NM toxicity with cellular NM numbers on the single cell level, as conflicting mechanisms in particular cell subpopulations are commonly overlooked using classical toxicological methods.

No MeSH data available.


Related in: MedlinePlus