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Label-free, live optical imaging of reprogrammed bipolar disorder patient-derived cells reveals a functional correlate of lithium responsiveness.

Wang JL, Shamah SM, Sun AX, Waldman ID, Haggarty SJ, Perlis RH - Transl Psychiatry (2014)

Bottom Line: However, efficiently identifying and characterizing relevant neuronal phenotypes in the absence of well-defined pathophysiology remains a challenge.In this study, we collected fibroblast samples from patients with bipolar 1 disorder, characterized by their lithium response (n=12), and healthy control subjects (n=6).We identified a cellular phenotype in reprogrammed neurons using a label-free imaging assay based on a nanostructured photonic crystal biosensor and found that an optical measure of cell adhesion was associated with clinical response to lithium treatment.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Psychiatry, Center for Experimental Drugs and Diagnostics, Massachusetts General Hospital, Boston, MA, USA [2] Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA, USA [3] Stanley Center for Psychiatric Research, Broad Institute of MIT & Harvard, Cambridge, MA, USA.

ABSTRACT
Development of novel treatments and diagnostic tools for psychiatric illness has been hindered by the absence of cellular models of disease. With the advent of cellular reprogramming, it may be possible to recapitulate the disease biology of psychiatric disorders using patient skin cells transdifferentiated to neurons. However, efficiently identifying and characterizing relevant neuronal phenotypes in the absence of well-defined pathophysiology remains a challenge. In this study, we collected fibroblast samples from patients with bipolar 1 disorder, characterized by their lithium response (n=12), and healthy control subjects (n=6). We identified a cellular phenotype in reprogrammed neurons using a label-free imaging assay based on a nanostructured photonic crystal biosensor and found that an optical measure of cell adhesion was associated with clinical response to lithium treatment. This cellular phenotype may represent a useful biomarker to evaluate drug response and screen for novel therapeutics.

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BIND imaging phenotypes of human iNLCs. (a) BIND images of a representative field (scale bar, 100 μm) at 1.2-h intervals beginning at plating of the cells. Imaging resolution is sufficient to capture outgrowth of cellular processes. (b) Time series quantification of BIND metrics—cell count, cell fraction, perimeter and PWV—over the first 4 h of continuous imaging shows that the most dynamic region of cellular attachment and growth occurs in the first 1.5 h. (c) Distribution of baseline-normalized changes in BIND metrics for each phenotype, by patient group. BD, bipolar disorder; iNLC, induced neuronal-like cell; PWV, peak wavelength value.
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fig1: BIND imaging phenotypes of human iNLCs. (a) BIND images of a representative field (scale bar, 100 μm) at 1.2-h intervals beginning at plating of the cells. Imaging resolution is sufficient to capture outgrowth of cellular processes. (b) Time series quantification of BIND metrics—cell count, cell fraction, perimeter and PWV—over the first 4 h of continuous imaging shows that the most dynamic region of cellular attachment and growth occurs in the first 1.5 h. (c) Distribution of baseline-normalized changes in BIND metrics for each phenotype, by patient group. BD, bipolar disorder; iNLC, induced neuronal-like cell; PWV, peak wavelength value.

Mentions: BIND Scan data was segmented and cellular metrics quantified using BIND View software. Background leveling was implemented with a 17-pixel structural morphological parameter. Segmented objects were classified as cells if they had a PWV minimum of 0.2–0.35 nm and a maximum of 5 nm above background and had an area greater than 10 pixels. A local background area around each segmented cell was calculated from a 2-pixel radius located 3 pixels outside the boundary of the cell. The average PWV from this local background area was subtracted from the average PWV inside the boundary of the cell to calculate the cellular PWV metric. Cell count, cell fraction and cell perimeter were computed from the mask of the segmented cells. These metrics were exported for each image in the time-lapse series and comprised the time series data in Figure 1b. Delta metrics were calculated as:


Label-free, live optical imaging of reprogrammed bipolar disorder patient-derived cells reveals a functional correlate of lithium responsiveness.

Wang JL, Shamah SM, Sun AX, Waldman ID, Haggarty SJ, Perlis RH - Transl Psychiatry (2014)

BIND imaging phenotypes of human iNLCs. (a) BIND images of a representative field (scale bar, 100 μm) at 1.2-h intervals beginning at plating of the cells. Imaging resolution is sufficient to capture outgrowth of cellular processes. (b) Time series quantification of BIND metrics—cell count, cell fraction, perimeter and PWV—over the first 4 h of continuous imaging shows that the most dynamic region of cellular attachment and growth occurs in the first 1.5 h. (c) Distribution of baseline-normalized changes in BIND metrics for each phenotype, by patient group. BD, bipolar disorder; iNLC, induced neuronal-like cell; PWV, peak wavelength value.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4150245&req=5

fig1: BIND imaging phenotypes of human iNLCs. (a) BIND images of a representative field (scale bar, 100 μm) at 1.2-h intervals beginning at plating of the cells. Imaging resolution is sufficient to capture outgrowth of cellular processes. (b) Time series quantification of BIND metrics—cell count, cell fraction, perimeter and PWV—over the first 4 h of continuous imaging shows that the most dynamic region of cellular attachment and growth occurs in the first 1.5 h. (c) Distribution of baseline-normalized changes in BIND metrics for each phenotype, by patient group. BD, bipolar disorder; iNLC, induced neuronal-like cell; PWV, peak wavelength value.
Mentions: BIND Scan data was segmented and cellular metrics quantified using BIND View software. Background leveling was implemented with a 17-pixel structural morphological parameter. Segmented objects were classified as cells if they had a PWV minimum of 0.2–0.35 nm and a maximum of 5 nm above background and had an area greater than 10 pixels. A local background area around each segmented cell was calculated from a 2-pixel radius located 3 pixels outside the boundary of the cell. The average PWV from this local background area was subtracted from the average PWV inside the boundary of the cell to calculate the cellular PWV metric. Cell count, cell fraction and cell perimeter were computed from the mask of the segmented cells. These metrics were exported for each image in the time-lapse series and comprised the time series data in Figure 1b. Delta metrics were calculated as:

Bottom Line: However, efficiently identifying and characterizing relevant neuronal phenotypes in the absence of well-defined pathophysiology remains a challenge.In this study, we collected fibroblast samples from patients with bipolar 1 disorder, characterized by their lithium response (n=12), and healthy control subjects (n=6).We identified a cellular phenotype in reprogrammed neurons using a label-free imaging assay based on a nanostructured photonic crystal biosensor and found that an optical measure of cell adhesion was associated with clinical response to lithium treatment.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Psychiatry, Center for Experimental Drugs and Diagnostics, Massachusetts General Hospital, Boston, MA, USA [2] Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA, USA [3] Stanley Center for Psychiatric Research, Broad Institute of MIT & Harvard, Cambridge, MA, USA.

ABSTRACT
Development of novel treatments and diagnostic tools for psychiatric illness has been hindered by the absence of cellular models of disease. With the advent of cellular reprogramming, it may be possible to recapitulate the disease biology of psychiatric disorders using patient skin cells transdifferentiated to neurons. However, efficiently identifying and characterizing relevant neuronal phenotypes in the absence of well-defined pathophysiology remains a challenge. In this study, we collected fibroblast samples from patients with bipolar 1 disorder, characterized by their lithium response (n=12), and healthy control subjects (n=6). We identified a cellular phenotype in reprogrammed neurons using a label-free imaging assay based on a nanostructured photonic crystal biosensor and found that an optical measure of cell adhesion was associated with clinical response to lithium treatment. This cellular phenotype may represent a useful biomarker to evaluate drug response and screen for novel therapeutics.

Show MeSH
Related in: MedlinePlus