Live Cell Painting: image-based profiling in live cells using Acridine Orange DOI Open Access
Fernanda Garcia-Fóssa,

Thaís Moraes-Lacerda,

Mariana Rodrigues-da-Silva

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 29, 2024

Image-based profiling has been used to analyze cell health, drug mechanism of action, CRISPR-edited cells, and overall cytotoxicity. Cell Painting is a broadly image-based assay that uses morphological features capture how cells respond treatments. However, this method requires fixation for staining, which prevents examining live cells. To address limitation, here we present Live (LCP), high-content based on Acridine orange, metachromatic dye labels different organelles cellular structures. We began by showing LCP can be applied follow acidic vesicle redistribution exposed vesicles inhibitors. Next, show identify subtle changes in silver nanoparticles are not detected techniques such as MTT assay. In treatments, was helpful assessing the dose-response relationship creating profiles allow clustering drugs cause liver injury. Here, an affordable easy-to-use capable health promise use various applications nanoparticles. envisage initial screening while providing insights into new biological questions.

Язык: Английский

Anomaly detection for high-content image-based phenotypic cell profiling DOI Creative Commons
Alon Shpigler,

Naor Kolet,

Shahar Golan

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июнь 3, 2024

Abstract High-content image-based phenotypic profiling combines automated microscopy and analysis to identify alterations in cell morphology provide insight into the cell’s physiological state. Classical representations of profile can not capture full underlying complexity organization, while recent weakly machine-learning based representation-learning methods are hard biologically interpret. We used abundance control wells learn in-distribution experiments use it formulate a self-supervised reconstruction anomaly-based representation that encodes intricate morphological inter-feature dependencies preserving interpretability. The performance our was evaluated for downstream tasks with respect two classical across four public Cell Painting datasets. Anomaly-based improved reproducibility, Mechanism Action classification, complemented representations. Unsupervised explainability autoencoder-based anomalies identified specific causing anomalies. general concept be adapted other applications biology.

Язык: Английский

Процитировано

0
Live Cell Painting: image-based profiling in live cells using Acridine Orange DOI Open Access
Fernanda Garcia-Fóssa,

Thaís Moraes-Lacerda,

Mariana Rodrigues-da-Silva

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 29, 2024

Image-based profiling has been used to analyze cell health, drug mechanism of action, CRISPR-edited cells, and overall cytotoxicity. Cell Painting is a broadly image-based assay that uses morphological features capture how cells respond treatments. However, this method requires fixation for staining, which prevents examining live cells. To address limitation, here we present Live (LCP), high-content based on Acridine orange, metachromatic dye labels different organelles cellular structures. We began by showing LCP can be applied follow acidic vesicle redistribution exposed vesicles inhibitors. Next, show identify subtle changes in silver nanoparticles are not detected techniques such as MTT assay. In treatments, was helpful assessing the dose-response relationship creating profiles allow clustering drugs cause liver injury. Here, an affordable easy-to-use capable health promise use various applications nanoparticles. envisage initial screening while providing insights into new biological questions.

Язык: Английский

Процитировано

0