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tom20 polyclonal antibody  (Proteintech)


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    Structured Review

    Proteintech tom20 polyclonal antibody
    Mitochondrial oxidative stress induced by DHA and RSL-3 activates mitochondrial fusion (A) The thumbnail sketch of mitochondrial functions that may be regulated by mitochondrial oxidation. (B) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 48 h in the absence or presence of mitochondrial regulators (2 μM oligo A, 2 μM CCCP, 10 μM αKG, 1 μM rotenone), n = 6 wells from one representative of two independent experiments. (C–E) Western blot and quantifications of the OXPHOS, <t>Tom20,</t> β-actin, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (F–I) Western blot and quantifications of the MFN1, MFN2, DRP1, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (J) N27 cells were treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h and detected by JC-1 using flow cytometry. Statistical analysis of the ratio of the MFI of JC-1 red to JC-1 green is shown, n = 6 wells from one representative of two independent experiments. (K–M) Western blot and quantifications of the MFN1, MFN2, and GAPDH expression in N27 cells treated with MitoQ (5 μM), DHA (1.5 μM), and RSL-3 (100 nM) for 12 h. (N) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) in the absence or presence of mitochondrial fusion promoter M1 (5 μM) for 48 h, n = 6 wells from one representative of two independent experiments. Data are means ± SEM, n = 3 wells from one representative of two independent experiments unless specified. One-way ANOVA was performed unless specified.
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    Images

    1) Product Images from "HMOX1 drives dihydroartemisinin-sensitized ferroptosis antagonized by mitochondrial fusion"

    Article Title: HMOX1 drives dihydroartemisinin-sensitized ferroptosis antagonized by mitochondrial fusion

    Journal: iScience

    doi: 10.1016/j.isci.2025.114382

    Mitochondrial oxidative stress induced by DHA and RSL-3 activates mitochondrial fusion (A) The thumbnail sketch of mitochondrial functions that may be regulated by mitochondrial oxidation. (B) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 48 h in the absence or presence of mitochondrial regulators (2 μM oligo A, 2 μM CCCP, 10 μM αKG, 1 μM rotenone), n = 6 wells from one representative of two independent experiments. (C–E) Western blot and quantifications of the OXPHOS, Tom20, β-actin, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (F–I) Western blot and quantifications of the MFN1, MFN2, DRP1, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (J) N27 cells were treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h and detected by JC-1 using flow cytometry. Statistical analysis of the ratio of the MFI of JC-1 red to JC-1 green is shown, n = 6 wells from one representative of two independent experiments. (K–M) Western blot and quantifications of the MFN1, MFN2, and GAPDH expression in N27 cells treated with MitoQ (5 μM), DHA (1.5 μM), and RSL-3 (100 nM) for 12 h. (N) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) in the absence or presence of mitochondrial fusion promoter M1 (5 μM) for 48 h, n = 6 wells from one representative of two independent experiments. Data are means ± SEM, n = 3 wells from one representative of two independent experiments unless specified. One-way ANOVA was performed unless specified.
    Figure Legend Snippet: Mitochondrial oxidative stress induced by DHA and RSL-3 activates mitochondrial fusion (A) The thumbnail sketch of mitochondrial functions that may be regulated by mitochondrial oxidation. (B) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 48 h in the absence or presence of mitochondrial regulators (2 μM oligo A, 2 μM CCCP, 10 μM αKG, 1 μM rotenone), n = 6 wells from one representative of two independent experiments. (C–E) Western blot and quantifications of the OXPHOS, Tom20, β-actin, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (F–I) Western blot and quantifications of the MFN1, MFN2, DRP1, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (J) N27 cells were treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h and detected by JC-1 using flow cytometry. Statistical analysis of the ratio of the MFI of JC-1 red to JC-1 green is shown, n = 6 wells from one representative of two independent experiments. (K–M) Western blot and quantifications of the MFN1, MFN2, and GAPDH expression in N27 cells treated with MitoQ (5 μM), DHA (1.5 μM), and RSL-3 (100 nM) for 12 h. (N) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) in the absence or presence of mitochondrial fusion promoter M1 (5 μM) for 48 h, n = 6 wells from one representative of two independent experiments. Data are means ± SEM, n = 3 wells from one representative of two independent experiments unless specified. One-way ANOVA was performed unless specified.

    Techniques Used: Western Blot, Expressing, Flow Cytometry



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    Mitochondrial oxidative stress induced by DHA and RSL-3 activates mitochondrial fusion (A) The thumbnail sketch of mitochondrial functions that may be regulated by mitochondrial oxidation. (B) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 48 h in the absence or presence of mitochondrial regulators (2 μM oligo A, 2 μM CCCP, 10 μM αKG, 1 μM rotenone), n = 6 wells from one representative of two independent experiments. (C–E) Western blot and quantifications of the OXPHOS, <t>Tom20,</t> β-actin, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (F–I) Western blot and quantifications of the MFN1, MFN2, DRP1, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (J) N27 cells were treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h and detected by JC-1 using flow cytometry. Statistical analysis of the ratio of the MFI of JC-1 red to JC-1 green is shown, n = 6 wells from one representative of two independent experiments. (K–M) Western blot and quantifications of the MFN1, MFN2, and GAPDH expression in N27 cells treated with MitoQ (5 μM), DHA (1.5 μM), and RSL-3 (100 nM) for 12 h. (N) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) in the absence or presence of mitochondrial fusion promoter M1 (5 μM) for 48 h, n = 6 wells from one representative of two independent experiments. Data are means ± SEM, n = 3 wells from one representative of two independent experiments unless specified. One-way ANOVA was performed unless specified.
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    A three-channel fluorescence microscopy measurement of stained HEK293 cells measured by Ph2 objective is automatically optimized by EVEN (prediction dataset 2, red: peroxisomal proteins (anti-GFP nanobody); green: <t>TOMM20</t> protein; blue: peroxisomal proteins (eGFP)). a Raw multi-channel image. The inset shows the 2 × 2 tile section of the image used in this figure, with dashed white lines marking tile borders. Multiple corrections are obtained by applying BaSiC, CIDRE, Fourier methods, and then optimizing the multi-channel image with EVEN. EVEN selects CIDRE for the red and green channel, and Fourier for the blue channel. b Steps to analyse the measurements of stained cells: multi-channel images are converted to greyscale by summing the single channels (that contain signals from different components of the cytoplasm) and are analysed with automatic cells segmentation using Cellpose . The greyscale image is obtained for the raw measurement, the single-channel corrections and the EVEN optimization. c Intensity sum (along y) of the greyscale inset for each method. The black dashed line indicates the border between neighbouring tiles. The corrected images show higher intensities at the edges of the tiles and the enhancement of sample features. EVEN and CIDRE show the greatest intensity recovery between tiles. d Top row: multi-channel images obtained with single-method corrections and EVEN optimization; the white dashed boxes highlight two regions significantly improved by EVEN. Bottom row: Cellpose prediction on the greyscale sum of the three channels for each method. After correction of uneven illumination, Cellpose can outline a greater number of cells, especially at the borders of neighbouring tiles. White dashed boxes highlight three regions where EVEN optimization provides better identification of the cells compared to non-optimized images. Bottom labels show, for each image, the normalized EVEN score summed over three channels and the cell count in the zoomed region. While counts are not strictly correlated with segmentation performance, good correction of uneven illumination enhances downstream analysis and generally increases the number of detected cells. Further quantification is provided in Supplementary Fig. . Scale bar: 180 µm, size of a single tile.
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    A three-channel fluorescence microscopy measurement of stained HEK293 cells measured by Ph2 objective is automatically optimized by EVEN (prediction dataset 2, red: peroxisomal proteins (anti-GFP nanobody); green: <t>TOMM20</t> protein; blue: peroxisomal proteins (eGFP)). a Raw multi-channel image. The inset shows the 2 × 2 tile section of the image used in this figure, with dashed white lines marking tile borders. Multiple corrections are obtained by applying BaSiC, CIDRE, Fourier methods, and then optimizing the multi-channel image with EVEN. EVEN selects CIDRE for the red and green channel, and Fourier for the blue channel. b Steps to analyse the measurements of stained cells: multi-channel images are converted to greyscale by summing the single channels (that contain signals from different components of the cytoplasm) and are analysed with automatic cells segmentation using Cellpose . The greyscale image is obtained for the raw measurement, the single-channel corrections and the EVEN optimization. c Intensity sum (along y) of the greyscale inset for each method. The black dashed line indicates the border between neighbouring tiles. The corrected images show higher intensities at the edges of the tiles and the enhancement of sample features. EVEN and CIDRE show the greatest intensity recovery between tiles. d Top row: multi-channel images obtained with single-method corrections and EVEN optimization; the white dashed boxes highlight two regions significantly improved by EVEN. Bottom row: Cellpose prediction on the greyscale sum of the three channels for each method. After correction of uneven illumination, Cellpose can outline a greater number of cells, especially at the borders of neighbouring tiles. White dashed boxes highlight three regions where EVEN optimization provides better identification of the cells compared to non-optimized images. Bottom labels show, for each image, the normalized EVEN score summed over three channels and the cell count in the zoomed region. While counts are not strictly correlated with segmentation performance, good correction of uneven illumination enhances downstream analysis and generally increases the number of detected cells. Further quantification is provided in Supplementary Fig. . Scale bar: 180 µm, size of a single tile.
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    ( A ) A549 cells depleted (48 h) by siRNA for Arf, Drp1, or Dnm1 were infected (MOI 10, 24 h) with GFP-producing L. pneumophila JR32 or Δ icmT (pNT28), and intracellular replication was assessed by GFP fluorescence using a microtiter plate reader. Graphs show the relative intracellular replication (normalized to GFP signal 1 h p.i.) and represent means + SEM of three independent experiments (Student’s t -test, *, p < 0.05; **, p < 0.01). ( B ) Mitochondria were isolated by differential centrifugation and sucrose density gradient ultracentrifugation from HeLa cells infected (MOI 100, 6 h) with GFP-producing L. pneumophila JR32, ΔicmT , ΔridL , or ΔridL _ ridL (pNT28 or pIF009). Western blot of RidL in cytoplasmic (cyt) and purified mitochondrial (mito) fractions; apoptosis-inducing factor (AIF) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) served as a mitochondrial or cytoplasmic marker, respectively. The figure shown is representative for 3 independent experiments. ( C ) HEK293 cells were transfected (24 h) for ectopic production of GFP-RidL (RidL, pKB248), GFP-RidL 9-258 (RidL N , pKB249) or GFP-RidL 259-1167 (RidL C , pKB250), mitochondria were isolated, and the GFP fusion proteins were detected by anti-GFP Western blot in the cell lysate (lys) and purified mitochondrial (mito) fractions. The figure shown is representative for 3 independent experiments. ( D ) Quantification of (C). Signal intensities of GFP and AIF were calculated by Image J. Bars show relative GFP signal in pure mitochondria fractions. Means + SEM of 3 independent experiments are shown (Student’s t- test, **, p < 0.01). ( E, F ) Fluorescence micrographs of HeLa cells infected (MOI 25, 2 h) with mCerulean-producing L. pneumophila JR23, Δ icmT , Δ ridL or Δ ridL_ridL (pNP99 or pKB208). Mitochondria were visualized with MitoTracker Deep Red, and immuno-labelled with specific antibodies against ( E ) Drp1 or ( F ) <t>Tom20</t> (green) to quantify the localization of these proteins to mitochondria. ( G ) Quantification of signal overlap in (E) and ( H ) quantification of signal overlap in (F) show 75 infected cells from three independent experiments (each dot is a cell; Student’s t -test, ****, p < 0.0001). The brightness of fluorescence signals was linearly increased in Image J for enhanced visibility (A, B); original signal intensities of the images were processed for quantification (C, D).
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    ( A ) A549 cells depleted (48 h) by siRNA for Arf, Drp1, or Dnm1 were infected (MOI 10, 24 h) with GFP-producing L. pneumophila JR32 or Δ icmT (pNT28), and intracellular replication was assessed by GFP fluorescence using a microtiter plate reader. Graphs show the relative intracellular replication (normalized to GFP signal 1 h p.i.) and represent means + SEM of three independent experiments (Student’s t -test, *, p < 0.05; **, p < 0.01). ( B ) Mitochondria were isolated by differential centrifugation and sucrose density gradient ultracentrifugation from HeLa cells infected (MOI 100, 6 h) with GFP-producing L. pneumophila JR32, ΔicmT , ΔridL , or ΔridL _ ridL (pNT28 or pIF009). Western blot of RidL in cytoplasmic (cyt) and purified mitochondrial (mito) fractions; apoptosis-inducing factor (AIF) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) served as a mitochondrial or cytoplasmic marker, respectively. The figure shown is representative for 3 independent experiments. ( C ) HEK293 cells were transfected (24 h) for ectopic production of GFP-RidL (RidL, pKB248), GFP-RidL 9-258 (RidL N , pKB249) or GFP-RidL 259-1167 (RidL C , pKB250), mitochondria were isolated, and the GFP fusion proteins were detected by anti-GFP Western blot in the cell lysate (lys) and purified mitochondrial (mito) fractions. The figure shown is representative for 3 independent experiments. ( D ) Quantification of (C). Signal intensities of GFP and AIF were calculated by Image J. Bars show relative GFP signal in pure mitochondria fractions. Means + SEM of 3 independent experiments are shown (Student’s t- test, **, p < 0.01). ( E, F ) Fluorescence micrographs of HeLa cells infected (MOI 25, 2 h) with mCerulean-producing L. pneumophila JR23, Δ icmT , Δ ridL or Δ ridL_ridL (pNP99 or pKB208). Mitochondria were visualized with MitoTracker Deep Red, and immuno-labelled with specific antibodies against ( E ) Drp1 or ( F ) <t>Tom20</t> (green) to quantify the localization of these proteins to mitochondria. ( G ) Quantification of signal overlap in (E) and ( H ) quantification of signal overlap in (F) show 75 infected cells from three independent experiments (each dot is a cell; Student’s t -test, ****, p < 0.0001). The brightness of fluorescence signals was linearly increased in Image J for enhanced visibility (A, B); original signal intensities of the images were processed for quantification (C, D).
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    ( A ) A549 cells depleted (48 h) by siRNA for Arf, Drp1, or Dnm1 were infected (MOI 10, 24 h) with GFP-producing L. pneumophila JR32 or Δ icmT (pNT28), and intracellular replication was assessed by GFP fluorescence using a microtiter plate reader. Graphs show the relative intracellular replication (normalized to GFP signal 1 h p.i.) and represent means + SEM of three independent experiments (Student’s t -test, *, p < 0.05; **, p < 0.01). ( B ) Mitochondria were isolated by differential centrifugation and sucrose density gradient ultracentrifugation from HeLa cells infected (MOI 100, 6 h) with GFP-producing L. pneumophila JR32, ΔicmT , ΔridL , or ΔridL _ ridL (pNT28 or pIF009). Western blot of RidL in cytoplasmic (cyt) and purified mitochondrial (mito) fractions; apoptosis-inducing factor (AIF) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) served as a mitochondrial or cytoplasmic marker, respectively. The figure shown is representative for 3 independent experiments. ( C ) HEK293 cells were transfected (24 h) for ectopic production of GFP-RidL (RidL, pKB248), GFP-RidL 9-258 (RidL N , pKB249) or GFP-RidL 259-1167 (RidL C , pKB250), mitochondria were isolated, and the GFP fusion proteins were detected by anti-GFP Western blot in the cell lysate (lys) and purified mitochondrial (mito) fractions. The figure shown is representative for 3 independent experiments. ( D ) Quantification of (C). Signal intensities of GFP and AIF were calculated by Image J. Bars show relative GFP signal in pure mitochondria fractions. Means + SEM of 3 independent experiments are shown (Student’s t- test, **, p < 0.01). ( E, F ) Fluorescence micrographs of HeLa cells infected (MOI 25, 2 h) with mCerulean-producing L. pneumophila JR23, Δ icmT , Δ ridL or Δ ridL_ridL (pNP99 or pKB208). Mitochondria were visualized with MitoTracker Deep Red, and immuno-labelled with specific antibodies against ( E ) Drp1 or ( F ) <t>Tom20</t> (green) to quantify the localization of these proteins to mitochondria. ( G ) Quantification of signal overlap in (E) and ( H ) quantification of signal overlap in (F) show 75 infected cells from three independent experiments (each dot is a cell; Student’s t -test, ****, p < 0.0001). The brightness of fluorescence signals was linearly increased in Image J for enhanced visibility (A, B); original signal intensities of the images were processed for quantification (C, D).
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    Image Search Results


    Mitochondrial oxidative stress induced by DHA and RSL-3 activates mitochondrial fusion (A) The thumbnail sketch of mitochondrial functions that may be regulated by mitochondrial oxidation. (B) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 48 h in the absence or presence of mitochondrial regulators (2 μM oligo A, 2 μM CCCP, 10 μM αKG, 1 μM rotenone), n = 6 wells from one representative of two independent experiments. (C–E) Western blot and quantifications of the OXPHOS, Tom20, β-actin, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (F–I) Western blot and quantifications of the MFN1, MFN2, DRP1, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (J) N27 cells were treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h and detected by JC-1 using flow cytometry. Statistical analysis of the ratio of the MFI of JC-1 red to JC-1 green is shown, n = 6 wells from one representative of two independent experiments. (K–M) Western blot and quantifications of the MFN1, MFN2, and GAPDH expression in N27 cells treated with MitoQ (5 μM), DHA (1.5 μM), and RSL-3 (100 nM) for 12 h. (N) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) in the absence or presence of mitochondrial fusion promoter M1 (5 μM) for 48 h, n = 6 wells from one representative of two independent experiments. Data are means ± SEM, n = 3 wells from one representative of two independent experiments unless specified. One-way ANOVA was performed unless specified.

    Journal: iScience

    Article Title: HMOX1 drives dihydroartemisinin-sensitized ferroptosis antagonized by mitochondrial fusion

    doi: 10.1016/j.isci.2025.114382

    Figure Lengend Snippet: Mitochondrial oxidative stress induced by DHA and RSL-3 activates mitochondrial fusion (A) The thumbnail sketch of mitochondrial functions that may be regulated by mitochondrial oxidation. (B) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 48 h in the absence or presence of mitochondrial regulators (2 μM oligo A, 2 μM CCCP, 10 μM αKG, 1 μM rotenone), n = 6 wells from one representative of two independent experiments. (C–E) Western blot and quantifications of the OXPHOS, Tom20, β-actin, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (F–I) Western blot and quantifications of the MFN1, MFN2, DRP1, and GAPDH expression in N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h. (J) N27 cells were treated with DHA (1.5 μM) and RSL-3 (100 nM) for 12 h and detected by JC-1 using flow cytometry. Statistical analysis of the ratio of the MFI of JC-1 red to JC-1 green is shown, n = 6 wells from one representative of two independent experiments. (K–M) Western blot and quantifications of the MFN1, MFN2, and GAPDH expression in N27 cells treated with MitoQ (5 μM), DHA (1.5 μM), and RSL-3 (100 nM) for 12 h. (N) Cell viability of N27 cells treated with DHA (1.5 μM) and RSL-3 (100 nM) in the absence or presence of mitochondrial fusion promoter M1 (5 μM) for 48 h, n = 6 wells from one representative of two independent experiments. Data are means ± SEM, n = 3 wells from one representative of two independent experiments unless specified. One-way ANOVA was performed unless specified.

    Article Snippet: TOM20 Polyclonal antibody (1:5000) , Proteintech , 11802-1-AP; RRID: AB_2207530.

    Techniques: Western Blot, Expressing, Flow Cytometry

    A three-channel fluorescence microscopy measurement of stained HEK293 cells measured by Ph2 objective is automatically optimized by EVEN (prediction dataset 2, red: peroxisomal proteins (anti-GFP nanobody); green: TOMM20 protein; blue: peroxisomal proteins (eGFP)). a Raw multi-channel image. The inset shows the 2 × 2 tile section of the image used in this figure, with dashed white lines marking tile borders. Multiple corrections are obtained by applying BaSiC, CIDRE, Fourier methods, and then optimizing the multi-channel image with EVEN. EVEN selects CIDRE for the red and green channel, and Fourier for the blue channel. b Steps to analyse the measurements of stained cells: multi-channel images are converted to greyscale by summing the single channels (that contain signals from different components of the cytoplasm) and are analysed with automatic cells segmentation using Cellpose . The greyscale image is obtained for the raw measurement, the single-channel corrections and the EVEN optimization. c Intensity sum (along y) of the greyscale inset for each method. The black dashed line indicates the border between neighbouring tiles. The corrected images show higher intensities at the edges of the tiles and the enhancement of sample features. EVEN and CIDRE show the greatest intensity recovery between tiles. d Top row: multi-channel images obtained with single-method corrections and EVEN optimization; the white dashed boxes highlight two regions significantly improved by EVEN. Bottom row: Cellpose prediction on the greyscale sum of the three channels for each method. After correction of uneven illumination, Cellpose can outline a greater number of cells, especially at the borders of neighbouring tiles. White dashed boxes highlight three regions where EVEN optimization provides better identification of the cells compared to non-optimized images. Bottom labels show, for each image, the normalized EVEN score summed over three channels and the cell count in the zoomed region. While counts are not strictly correlated with segmentation performance, good correction of uneven illumination enhances downstream analysis and generally increases the number of detected cells. Further quantification is provided in Supplementary Fig. . Scale bar: 180 µm, size of a single tile.

    Journal: Nature Communications

    Article Title: Automatic optimization of flat-field corrections by evaluation and enhancement (EVEN) in multimodal optical microscopy

    doi: 10.1038/s41467-025-68150-0

    Figure Lengend Snippet: A three-channel fluorescence microscopy measurement of stained HEK293 cells measured by Ph2 objective is automatically optimized by EVEN (prediction dataset 2, red: peroxisomal proteins (anti-GFP nanobody); green: TOMM20 protein; blue: peroxisomal proteins (eGFP)). a Raw multi-channel image. The inset shows the 2 × 2 tile section of the image used in this figure, with dashed white lines marking tile borders. Multiple corrections are obtained by applying BaSiC, CIDRE, Fourier methods, and then optimizing the multi-channel image with EVEN. EVEN selects CIDRE for the red and green channel, and Fourier for the blue channel. b Steps to analyse the measurements of stained cells: multi-channel images are converted to greyscale by summing the single channels (that contain signals from different components of the cytoplasm) and are analysed with automatic cells segmentation using Cellpose . The greyscale image is obtained for the raw measurement, the single-channel corrections and the EVEN optimization. c Intensity sum (along y) of the greyscale inset for each method. The black dashed line indicates the border between neighbouring tiles. The corrected images show higher intensities at the edges of the tiles and the enhancement of sample features. EVEN and CIDRE show the greatest intensity recovery between tiles. d Top row: multi-channel images obtained with single-method corrections and EVEN optimization; the white dashed boxes highlight two regions significantly improved by EVEN. Bottom row: Cellpose prediction on the greyscale sum of the three channels for each method. After correction of uneven illumination, Cellpose can outline a greater number of cells, especially at the borders of neighbouring tiles. White dashed boxes highlight three regions where EVEN optimization provides better identification of the cells compared to non-optimized images. Bottom labels show, for each image, the normalized EVEN score summed over three channels and the cell count in the zoomed region. While counts are not strictly correlated with segmentation performance, good correction of uneven illumination enhances downstream analysis and generally increases the number of detected cells. Further quantification is provided in Supplementary Fig. . Scale bar: 180 µm, size of a single tile.

    Article Snippet: Additionally, immunolabeling was performed on TOMM20-protein with anti-Tomm20 rabbit polyclonal antibodies (proteintech, USA), dilution 1:200, and goat anti-rabbit IgG secondary antibodies labelled with Abberior STAR Orange (Abberior, Germany) at a dilution of 1:350.

    Techniques: Fluorescence, Microscopy, Staining, Cell Counting

    ( A ) A549 cells depleted (48 h) by siRNA for Arf, Drp1, or Dnm1 were infected (MOI 10, 24 h) with GFP-producing L. pneumophila JR32 or Δ icmT (pNT28), and intracellular replication was assessed by GFP fluorescence using a microtiter plate reader. Graphs show the relative intracellular replication (normalized to GFP signal 1 h p.i.) and represent means + SEM of three independent experiments (Student’s t -test, *, p < 0.05; **, p < 0.01). ( B ) Mitochondria were isolated by differential centrifugation and sucrose density gradient ultracentrifugation from HeLa cells infected (MOI 100, 6 h) with GFP-producing L. pneumophila JR32, ΔicmT , ΔridL , or ΔridL _ ridL (pNT28 or pIF009). Western blot of RidL in cytoplasmic (cyt) and purified mitochondrial (mito) fractions; apoptosis-inducing factor (AIF) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) served as a mitochondrial or cytoplasmic marker, respectively. The figure shown is representative for 3 independent experiments. ( C ) HEK293 cells were transfected (24 h) for ectopic production of GFP-RidL (RidL, pKB248), GFP-RidL 9-258 (RidL N , pKB249) or GFP-RidL 259-1167 (RidL C , pKB250), mitochondria were isolated, and the GFP fusion proteins were detected by anti-GFP Western blot in the cell lysate (lys) and purified mitochondrial (mito) fractions. The figure shown is representative for 3 independent experiments. ( D ) Quantification of (C). Signal intensities of GFP and AIF were calculated by Image J. Bars show relative GFP signal in pure mitochondria fractions. Means + SEM of 3 independent experiments are shown (Student’s t- test, **, p < 0.01). ( E, F ) Fluorescence micrographs of HeLa cells infected (MOI 25, 2 h) with mCerulean-producing L. pneumophila JR23, Δ icmT , Δ ridL or Δ ridL_ridL (pNP99 or pKB208). Mitochondria were visualized with MitoTracker Deep Red, and immuno-labelled with specific antibodies against ( E ) Drp1 or ( F ) Tom20 (green) to quantify the localization of these proteins to mitochondria. ( G ) Quantification of signal overlap in (E) and ( H ) quantification of signal overlap in (F) show 75 infected cells from three independent experiments (each dot is a cell; Student’s t -test, ****, p < 0.0001). The brightness of fluorescence signals was linearly increased in Image J for enhanced visibility (A, B); original signal intensities of the images were processed for quantification (C, D).

    Journal: bioRxiv

    Article Title: The Legionella effector RidL promotes mitochondrial fragmentation through phosphorylation activation of the large GTPase Drp1

    doi: 10.1101/2025.10.07.680855

    Figure Lengend Snippet: ( A ) A549 cells depleted (48 h) by siRNA for Arf, Drp1, or Dnm1 were infected (MOI 10, 24 h) with GFP-producing L. pneumophila JR32 or Δ icmT (pNT28), and intracellular replication was assessed by GFP fluorescence using a microtiter plate reader. Graphs show the relative intracellular replication (normalized to GFP signal 1 h p.i.) and represent means + SEM of three independent experiments (Student’s t -test, *, p < 0.05; **, p < 0.01). ( B ) Mitochondria were isolated by differential centrifugation and sucrose density gradient ultracentrifugation from HeLa cells infected (MOI 100, 6 h) with GFP-producing L. pneumophila JR32, ΔicmT , ΔridL , or ΔridL _ ridL (pNT28 or pIF009). Western blot of RidL in cytoplasmic (cyt) and purified mitochondrial (mito) fractions; apoptosis-inducing factor (AIF) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) served as a mitochondrial or cytoplasmic marker, respectively. The figure shown is representative for 3 independent experiments. ( C ) HEK293 cells were transfected (24 h) for ectopic production of GFP-RidL (RidL, pKB248), GFP-RidL 9-258 (RidL N , pKB249) or GFP-RidL 259-1167 (RidL C , pKB250), mitochondria were isolated, and the GFP fusion proteins were detected by anti-GFP Western blot in the cell lysate (lys) and purified mitochondrial (mito) fractions. The figure shown is representative for 3 independent experiments. ( D ) Quantification of (C). Signal intensities of GFP and AIF were calculated by Image J. Bars show relative GFP signal in pure mitochondria fractions. Means + SEM of 3 independent experiments are shown (Student’s t- test, **, p < 0.01). ( E, F ) Fluorescence micrographs of HeLa cells infected (MOI 25, 2 h) with mCerulean-producing L. pneumophila JR23, Δ icmT , Δ ridL or Δ ridL_ridL (pNP99 or pKB208). Mitochondria were visualized with MitoTracker Deep Red, and immuno-labelled with specific antibodies against ( E ) Drp1 or ( F ) Tom20 (green) to quantify the localization of these proteins to mitochondria. ( G ) Quantification of signal overlap in (E) and ( H ) quantification of signal overlap in (F) show 75 infected cells from three independent experiments (each dot is a cell; Student’s t -test, ****, p < 0.0001). The brightness of fluorescence signals was linearly increased in Image J for enhanced visibility (A, B); original signal intensities of the images were processed for quantification (C, D).

    Article Snippet: Samples were incubated with either anti-Drp1 (C-terminal) polyclonal antibody (#12957-1-AP, 1:50 in 1% BSA; Proteintech), anti-Tom20 polyclonal antibody (#11802-1-AP, 1:200 in 1% BSA; Proteintech), or anti-phospho-Drp1 (Ser616) monoclonal antibody (#4494, 1:1000 in 1% BSA; Cell Signaling Technology) for 1.5 h at RT in the dark.

    Techniques: Infection, Fluorescence, Isolation, Centrifugation, Western Blot, Purification, Marker, Transfection