Journal: The Journal of Neuroscience

Article Title: Mitochondrial Dynamics and Bioenergetic Dysfunction Is Associated with Synaptic Alterations in Mutant SOD1 Motor Neurons

doi: 10.1523/JNEUROSCI.1233-11.2012

Figure Lengend Snippet: Impaired mitochondrial fusion in the soma and motor axons of G93A SOD1 motor neurons. A, Cell bodies from non-transgenic control and G93A SOD1 motor neurons containing mitoDendra-labeled mitochondria before (−1 min) and after (0 min) photo-activation. Subsets of mitochondria (green and red fluorescence) were followed over time (10, 40, 70, and 100 min) by live imaging microscopy. Note that the appearance of yellow fluorescence, as a result of the mixing between green and red mitochondria (i.e. fusion, indicated by arrows), was delayed in mutant SOD1 motor neurons. Scale bar, 10 μm. B, Fusion rates were obtained in single optical z-sections by measuring the colocalization (in %) of red over green fluorescent mitochondria at the indicated time points. The correlation coefficient (r) for each group is indicated. n (somas) = 8 non-transgenic, and 7 G93A. *P<0.05 by ANOVA with repeated measurements. C, In the inset, example of a time-lapse recording of axonal mitochondria (numbers indicate time in min) showing a fusion event (arrow). Scale bar, 5 μm. The graph shows the analysis of fusion (% of fusion events of total moving mitochondria) in control and G93A SOD1 motor axons. n (axons) = 24 non-transgenic, 28 WT and 16 G93A axonal segments. *P<0.05 versus non-transgenic. D, Time-lapse microscopy of mitochondrial transport in the soma of non-transgenic and G93A SOD1 motor neurons. All mitochondria in a ROI of the soma were photo-converted, while only non-photo-converted (green fluorescent) mitochondria were followed over time. Note a decrease of mobile mitochondria towards the ROI in mutant SOD1 motor neurons compared to controls. Scale bar, 10 μm. E, Analysis of the transport of green mitochondria over the photo-activated area (no green mitochondria present). The correlation coefficient (r) for each group is indicated. n (somas) = 8 non-transgenic, and 7 G93A. *P<0.05 by ANOVA with repeated measurements. F, Analysis of the transport of red mitochondria over the non-photo-activated area (no red mitochondria present). The correlation coefficient (r) for each group is indicated. n (somas) = 8 non-transgenic, and 7 G93A. *P<0.05 by ANOVA with repeated measurements. All data obtained from 3–5 independent experiments. The error bars represent ± SE.

Article Snippet: Colocalization and Integrated Morphometric Analysis applications were from Metamorph software (Universal Imaging Co.).

Techniques: Transgenic Assay, Control, Labeling, Activation Assay, Fluorescence, Imaging, Microscopy, Mutagenesis, Time-lapse Microscopy

Journal: Journal of Cell Science

Article Title: Myosin VI mediates the movement of NHE3 down the microvillus in intestinal epithelial cells

doi: 10.1242/jcs.149930

Figure Lengend Snippet: A pool of myosin VI localizes on the microvillus of intestinal epithelial cells. (A) Immunofluorescence (confocal microscopic) detection of myosin VI expression and localization in Caco-2/Bbe cells and mouse ileum. In Caco-2/Bbe cells, myosin VI is present throughout the brush border, including in the microvillus and in a vesicular pattern in the terminal web and other intracellular compartments (a1–a4). In mouse ileum, myosin VI is present to a lesser extent on the microvillus and in the terminal web (b1–b4). As a negative control, anti-myosin VI antibody was used to show there is no myosin VI staining in ileum from myosin VI KO mice (d) and myosin VI KD Caco-2/Bbe cells (f). (c) wild-type (WT) control; (e) empty-vector-infected control. Scale bar: 20 µm. (B) Analysis of the overlap of myosin VI and protein markers of microvillus by MetaMorph colocalization software. Please note this software shows presence of two proteins in the same intracellular compartment but does not establish physical association. In Caco-2/Bbe cells, ∼46% of myosin VI overlaps with villin, and in mouse ileum ∼9% of myosin VI overlaps with aquaporin 7. For both Caco-2/Bbe cells and mouse ileum, results are mean±s.e.m. of three separate experiments with five or six images analyzed in each experiment (the total number of images analyzed was 16).

Article Snippet: Overlap of myosin VI with the microvillus marker aquaporin 7 was determined with MetaMorph software colocalization analysis.

Techniques: Immunofluorescence, Expressing, Negative Control, Staining, Plasmid Preparation, Infection, Software

Journal: BMC Bioinformatics

Article Title: Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

doi: 10.1186/s12859-021-04302-5

Figure Lengend Snippet: Schematic representation of the main analysis workflow proposed described in MATISSE. The Cartesian coordinates of all reads found in the section analyzed is used to create the initial Matisse object. Several functionalities including KDE plots, colocalization analysis, gene quantification and gradient identification and analysis can be applied using this object as an input. Data can also be segmented, based on the cell boundaries, the location of individual spots or using a grid equally distributed along the section. Its output, stored in a second Matisse object, can be used for cell typing and clustering the data, among others

Article Snippet: A wide number of different analysis can be performed with Matisse , including colocalization analysis, Kernel Density Estimation (KDE), and the exploration of gradients for unsegmented datasets, as well as, for example, de novo clustering, dimensional reduction, low dimensional RGB representation, probabilistic cell typing (pciSeq) [ ] and gene co-expression for segmented datasets.

Techniques:

Journal: BMC Bioinformatics

Article Title: Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps

doi: 10.1186/s12859-021-04302-5

Figure Lengend Snippet: Analysis of the expression of 17 genes in the mouse cortex. A One dimensional KDE estimation of the expression of the 17 genes along the dorso-ventral axis of the cortex. Genes are randomly divided in two line plots to facilitate their comprehension. B Heat map representing the colocalization between the genes analyzed. Positive Z-scores (red) represent colocalization of the genes and negative Z-score (blue) represent mutually exclusive expression. C KDE of the expression of several different genes, represented pairwise. Different co-expression patterns are represented including mutually exclusive genes (top,left),colocalizing genes (down,left), partially colocalizing genes (top,right) and genes with non-related expression patterns (down,right). D Two-dimensional map of the bins generated when segmenting the mouse coronal section. Color code corresponds to the RGB loadings of each bin’s score on the top three UMAP components found when doing dimensionality reduction analysis. Different colors, indicating different loadings for each of components are found in different areas of the brain, highlighting the difference in expression found for the genes included in the panel. E Two-dimensional map of the bins generated previously, where each color represents one of the 15 clusters defined by performing hierarchical clustering on the segmented dataset. F Mean expression of each of the clusters defined in E for all the genes included in the analysis. The colors of each cluster, on the Y axis, correspond to the colors used in E for each cluster

Article Snippet: A wide number of different analysis can be performed with Matisse , including colocalization analysis, Kernel Density Estimation (KDE), and the exploration of gradients for unsegmented datasets, as well as, for example, de novo clustering, dimensional reduction, low dimensional RGB representation, probabilistic cell typing (pciSeq) [ ] and gene co-expression for segmented datasets.

Techniques: Expressing, Generated

Journal: Journal of Translational Medicine

Article Title: Genome-wide association, single-cell, and spatial transcriptomics analyses reveal the role of the STK24-expressing positive cells in LUAD progression and the tumor microenvironment, identifying STK24 as a potential therapeutic target

doi: 10.1186/s12967-025-07111-z

Figure Lengend Snippet: STK24 is elevated in LUAD epithelial cells. A UMAP showing cell types after batch correction and dimensionality reduction clustering. B Bubble plot showing STK24 expression levels across various cell types. C Violin plot showing STK24 expression in normal and tumor cells across various cell types. D , E STK24 expression levels and regional variation analysis in spatial transcriptomics. F Violin plot showing STK24 expression in normal and tumor samples in the TCGA-LUAD cohort. G Immunohistochemistry results showing STK24 staining in LUAD and normal tissue samples from the HPA database. H Independent prognostic analysis to evaluate whether the association between STK24 and tumor survival is independent of traditional clinical variables. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05

Article Snippet: E – H Spatial transcriptomics heterotypic cell network analysis shows colocalization of STK24posEpi and fibroblasts.

Techniques: Expressing, Immunohistochemistry, Staining

Journal: Journal of Translational Medicine

Article Title: Genome-wide association, single-cell, and spatial transcriptomics analyses reveal the role of the STK24-expressing positive cells in LUAD progression and the tumor microenvironment, identifying STK24 as a potential therapeutic target

doi: 10.1186/s12967-025-07111-z

Figure Lengend Snippet: Exploring the origins of STK24 Group cells through spatial transcriptomics (ST). A Schematic diagram of RCTD deconvolution and spatial trajectory analysis of spatial transcriptomics data. B – D Cell types after ST deconvolution. E , F Cell developmental trajectory and trajectory tree in ST ERS17014180. G , H Cell developmental trajectory and trajectory tree in ST ERS17014184. I , J Cell developmental trajectory and trajectory tree in ST ERS17014196. (K-M) Scatter plots showing the correlation between STK24 gene expression and developmental trajectory genes

Article Snippet: E – H Spatial transcriptomics heterotypic cell network analysis shows colocalization of STK24posEpi and fibroblasts.

Techniques: Gene Expression

Journal: Journal of Translational Medicine

Article Title: Genome-wide association, single-cell, and spatial transcriptomics analyses reveal the role of the STK24-expressing positive cells in LUAD progression and the tumor microenvironment, identifying STK24 as a potential therapeutic target

doi: 10.1186/s12967-025-07111-z

Figure Lengend Snippet: Interactions between STK24-positive tumor epithelial cells (STK24posEpi) and fibroblasts. A Analysis of interaction strength between STK24posEpi and various cell types. B Activated pathways in various cell communications. C Analysis of activated ligand-receptor pairs. D Schematic diagram of Heterotypic cellular network analysis and cell co-localization analysis of spatial tran-scriptomics data. E – H Spatial transcriptomics heterotypic cell network analysis shows colocalization of STK24posEpi and fibroblasts. I Heatmap displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial transcriptomics data

Article Snippet: E – H Spatial transcriptomics heterotypic cell network analysis shows colocalization of STK24posEpi and fibroblasts.

Techniques:

Journal: Journal of Translational Medicine

Article Title: Genome-wide association, single-cell, and spatial transcriptomics analyses reveal the role of the STK24-expressing positive cells in LUAD progression and the tumor microenvironment, identifying STK24 as a potential therapeutic target

doi: 10.1186/s12967-025-07111-z

Figure Lengend Snippet: Communication and signal flow changes between STK24posEpi and fibroblasts in spatial transcriptomics (ST). A Schematic diagram of Cell–cell communication analysis and signal flow direction analysis of spatial transcriptomics data. B Analysis of communication intensity between STK24posEpi and fibroblasts by integrating multiple spatial transcriptomics samples. C , D Communication between STK24posEpi and fibroblasts in the PDGF signaling pathway across different spatial transcriptomics samples. E Importance of Sender, Receiver, Mediator, and Influencer in different cell types in the PDGF signaling pathway. F , G Expression and co-expression of ligand-receptor pairs related to the PDGF signaling pathway in various spatial transcriptomics samples. H Importance of Sender, Receiver, Mediator, and Influencer in different cell types in the VEGF signaling pathway. I , J Communication between STK24posEpi and fibroblasts in the VEGF signaling pathway across different spatial transcriptomics samples. K Importance of Sender, Receiver, Mediator, and Influencer in different cell types in the MIF signaling pathway. L , M Communication between STK24posEpi and fibroblasts in the MIF signaling pathway across different spatial transcriptomics samples. N , O COMMOT analysis showing the direction of MIF signal flow and expression of Senders and Receivers in various spatial transcriptomics samples

Article Snippet: E – H Spatial transcriptomics heterotypic cell network analysis shows colocalization of STK24posEpi and fibroblasts.

Techniques: Expressing

Journal: Journal of Translational Medicine

Article Title: Genome-wide association, single-cell, and spatial transcriptomics analyses reveal the role of the STK24-expressing positive cells in LUAD progression and the tumor microenvironment, identifying STK24 as a potential therapeutic target

doi: 10.1186/s12967-025-07111-z

Figure Lengend Snippet: Exploration of apoptosis and STK24posEpi-related pathways in spatial transcriptomics (ST). A Schematic diagram of Pathway dependency analysis of spatial transcriptomics data. B Enrichment results for the ST apoptosis pathway and comparison of differences between regions. C Heatmap displaying apoptosis-dependent cell pathways within regions in the spatial context. D , F Network diagrams showing apoptosis-dependent cell pathways in intra ( D ), juxta_5 ( E ), and para_15 ( F ) regions. G Enrichment results for the ST cell proliferation pathway and comparison of differences between the STK24 Group. H Enrichment results for the ST cell damage pathway and comparison of differences between the STK24 Group. I Comparison of ST cell cycle and DNA repair pathways between the STK24 Groups. J , K Heatmaps showing cell pathway dependency analysis for different cell types within the intra ( J ) and para_15 ( K ) regions in the spatial context. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05

Article Snippet: E – H Spatial transcriptomics heterotypic cell network analysis shows colocalization of STK24posEpi and fibroblasts.

Techniques: Comparison

Journal: Journal of Translational Medicine

Article Title: Genome-wide association, single-cell, and spatial transcriptomics analyses reveal the role of the STK24-expressing positive cells in LUAD progression and the tumor microenvironment, identifying STK24 as a potential therapeutic target

doi: 10.1186/s12967-025-07111-z

Figure Lengend Snippet: Clinical significance of STK24posEpi. A Schematic diagram of Homotypic cellular network analysis of spatial transcriptomics data. B Homotypic cell network analysis of STK24posEpi in spatial transcriptomics. C Survival analysis of STK24posEpi across multiple bulk transcriptome cohorts after Bayesian deconvolution. D Comparison of tumor-infiltrating lymphocyte scores between STK24posEpi Groups in the TCGA-LUAD cohort. E Histological slides showing differences in tumor-infiltrating lymphocytes between STK24posEpi Groups in the TCGA-LUAD cohort. F Correlation analysis of STK24posEpi and B cells in multiple bulk transcriptomes. G Differential expression of BCR signaling pathway-related genes between STK24posEpi Groups in the TCGA-LUAD cohort. H Differential expression of antigen processing and presentation pathway-related genes between STK24posEpi Groups in the TCGA-LUAD cohort. I Comparison of clinical factors between STK24posEpi Groups in the TCGA-LUAD cohort. **** P < 0.0001, *** P < 0.001, ** P < 0.01, * P < 0.05, ns P > 0.05

Article Snippet: E – H Spatial transcriptomics heterotypic cell network analysis shows colocalization of STK24posEpi and fibroblasts.

Techniques: Comparison, Quantitative Proteomics