Journal: Molecules

Article Title: Identification of Bacterial Metabolites Modulating Breast Cancer Cell Proliferation and Epithelial-Mesenchymal Transition

doi: 10.3390/molecules28155898

Figure Lengend Snippet: Validation of the methods used to assess cell proliferation. ( A ) The indicated number of cells were plated in 96-well plates for the SRB assay or PerkinElmer CellCarrier Ultra 96-well plates for the two high-content screening methods. On the following day, either the SRB assay or high-content screening method was conducted. For high-content screening, the nuclei were stained with DAPI, images were segmented using CellProfiler or the deep learning-based method, and nuclei numbers were counted using CellProfiler. The red lines indicate a 45° line, indicating the same number of cells as seeded. ( B ) Representative phase-contrast images of the wells containing the indicated number of cells. Abbreviations: DL—deep learning.

Article Snippet: Cells were grown on PerkinElmer CellCarrier Ultra 96-well (Waltham, MA, USA) plates until 70% confluency.

Techniques: Sulforhodamine B Assay, High Content Screening, Staining

Journal: Molecules

Article Title: Identification of Bacterial Metabolites Modulating Breast Cancer Cell Proliferation and Epithelial-Mesenchymal Transition

doi: 10.3390/molecules28155898

Figure Lengend Snippet: Identification of cytostatic bacterial metabolites in 4T1 breast cancer cells. The cells (800 4T1 cells/well) were plated in PerkinElmer CellCarrier Ultra 96-well plates and treated with the indicated metabolites at the specified concentrations for 48 h. Measurements were repeated at least three times using four technical replicates. Images were acquired and segmented using CellProfiler or the DL algorithm. Nuclei were counted in segmented images using CellProfiler. Data are represented as averages ± SDs of biological replicates. Values were normalized to vehicle-treated cells and expressed as fold changes. Each metabolite was statistically analyzed separately. ( A ) A heatmap representation of the effects of the metabolites on 4T1 cell proliferation. ( B ) The effects of the metabolites on 4T1 cell proliferation. Metabolite concentrations are displayed on the logarithmic axes. * and ** indicate statistically significant differences between vehicle-treated cells (control) and cells treated with the metabolite at p < 0.05 and p < 0.01, respectively. Abbreviations: DL—deep learning segmentation, CP—CellProfiler’s built-in method segmentation.

Article Snippet: Cells were grown on PerkinElmer CellCarrier Ultra 96-well (Waltham, MA, USA) plates until 70% confluency.

Techniques:

Journal: Molecules

Article Title: Identification of Bacterial Metabolites Modulating Breast Cancer Cell Proliferation and Epithelial-Mesenchymal Transition

doi: 10.3390/molecules28155898

Figure Lengend Snippet: High-content screening-based methods can detect changes in cell morphology and indicate EMT. ( A ) 1.5 × 10 6 4T1 cells were plated in Petri dishes and treated with TGFβ or SB-431542 for 48 h. Cellular proteins were assessed using Western blotting with the indicated antibodies. Sample blots are shown along with their densitometric evaluation presented as means ± SD. Values were normalized to vehicle-treated (control) cells. ( B ) 800 4T1 cells/well were plated in PerkinElmer CellCarrier Ultra 96-well plates and treated with TGFβ or SB-431542 for 48 h. Nuclei were stained with DAPI, and cells were visualized using Texas Red-X Phalloidin. The images were segmented using the Harmony software (version 3.1.8) (PerkinElmer, Waltham, MA, USA) to identify cells with epithelial or mesenchymal morphology. Proportions of mesenchymal cells were normalized to total cell number and for inter-sample cell number differences. Normality was tested, and statistical significance was calculated as described in the Methods. Representative fluorescence microscopy images are presented. The scale bar equals 10 µm. *, **, and *** indicate statistically significant differences between vehicle-treated (control) cells and treated cells at p < 0.05, p < 0.01, and p < 0.001, respectively. Abbreviations: CTL—control, SB—SB-431542, TGFβ—transforming growth factor β.

Article Snippet: Cells were grown on PerkinElmer CellCarrier Ultra 96-well (Waltham, MA, USA) plates until 70% confluency.

Techniques: High Content Screening, Western Blot, Staining, Software, Fluorescence, Microscopy

Journal: Molecules

Article Title: Identification of Bacterial Metabolites Modulating Breast Cancer Cell Proliferation and Epithelial-Mesenchymal Transition

doi: 10.3390/molecules28155898

Figure Lengend Snippet: Identification of bioactive bacterial metabolites that suppress EMT. 800 4T1 cells/well were seeded in PerkinElmer CellCarrier Ultra 96-well plates and treated with the indicated metabolites at the concentrations specified in for 48 h. The acquired images were segmented using the Harmony software (version 3.1.8) (PerkinElmer) to identify cells with epithelial or mesenchymal morphology. Proportions of the mesenchymal cells were normalized to total cell numbers within a sample and to inter-sample cell number differences. Normality was assessed, and statistical significance was calculated as described in the Methods. Each metabolite was statistically analyzed separately. ** and *** indicate statistically significant differences between vehicle-treated (control) cells and cells treated with a compound at p < 0.01 and p < 0.001, respectively. Abbreviations: CC 1–5—concentrations indicated in , the number references increasing doses.

Article Snippet: Cells were grown on PerkinElmer CellCarrier Ultra 96-well (Waltham, MA, USA) plates until 70% confluency.

Techniques: Software

Journal: Molecules

Article Title: Identification of Bacterial Metabolites Modulating Breast Cancer Cell Proliferation and Epithelial-Mesenchymal Transition

doi: 10.3390/molecules28155898

Figure Lengend Snippet: Identification of bioactive bacterial metabolites that suppress EMT. ( A ) 800 4T1 cells were plated on PerkinElmer CellCarrier Ultra 96-well plates and treated with the indicated metabolites at the concentrations specified in for 48 h. The acquired images were segmented using the Harmony software (version 3.1.8) (PerkinElmer) to identify cells with epithelial or mesenchymal morphology. Proportions of the mesenchymal cells were normalized to total cell number within a sample and to inter-sample cell number differences. Normality was assessed, and statistical significance was calculated as described in the Methods. Each metabolite was statistically analyzed separately. ( B ) 1.5 × 10 6 4T1 cells were plated in Petri dishes and treated with the indicated metabolites at the concentrations specified in for 48 h. Cellular proteins were assessed using Western blotting with the indicated antibodies. Sample blots and densitometry are shown (mean ± SD). Values were normalized to vehicle-treated (control) cells. *, **, and *** indicate statistically significant differences between vehicle-treated (control) cells and cells treated with a compound at p < 0.05, p < 0.01, and p < 0.001, respectively.

Article Snippet: Cells were grown on PerkinElmer CellCarrier Ultra 96-well (Waltham, MA, USA) plates until 70% confluency.

Techniques: Software, Western Blot

Journal: bioRxiv

Article Title: Identifying repurposed drugs with moderate anti-influenza virus activity through computational prioritization of drug-target pairs

doi: 10.1101/2023.07.31.551116

Figure Lengend Snippet:

Article Snippet: Briefly, about 10,000 A549 and MDCK cells were seeded in 96 well plates (CellCarrier-96 Ultra Microplates Catalog No.: 6055300, PerkinElmer) and were grown at 37 °C in humidified 5% CO 2 for 24hrs.

Techniques:

Journal: bioRxiv

Article Title: Identifying repurposed drugs with moderate anti-influenza virus activity through computational prioritization of drug-target pairs

doi: 10.1101/2023.07.31.551116

Figure Lengend Snippet: A549 and MDCK cells were infected with A/WSN/1933(H1N1) at MOI of 0.1 for 1 hour and treated with the drugs for 24 hours. Cells were stained with anti-influenza NP and DAPI. The anti-influenza activity of the drugs in different concentrations was evaluated as the percentage of cells exhibiting NP staining relative to the solvent controls. The experiment was performed in triplicate and GraphPad Prism V8 was used for dose-response curve fitting. Each data point represents the average % of infection relative to the solvent controls. A. Anti-influenza activity of the drugs in A549 cells at increasing concentrations. B. Anti-influenza activity of the drugs in MDCK cells at increasing concentrations.

Article Snippet: Briefly, about 10,000 A549 and MDCK cells were seeded in 96 well plates (CellCarrier-96 Ultra Microplates Catalog No.: 6055300, PerkinElmer) and were grown at 37 °C in humidified 5% CO 2 for 24hrs.

Techniques: Infection, Staining, Activity Assay, Solvent