visium spatial proteogenomics platform visium spg (10X Genomics)

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10X Genomics visium spatial proteogenomics platform visium spg

(A) Schematic of experimental design using <t>Visium</t> Spatial <t>Proteogenomics</t> (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide cDNA synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.

Visium Spatial Proteogenomics Platform Visium Spg, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/visium+image+alignment+function/pmc11426291-99-31-29?v=10X+Genomics
Average 86 stars, based on 1 article reviews

visium spatial proteogenomics platform visium spg - by Bioz Stars, 2026-08

86/100 stars

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1) Product Images from "Influence of Alzheimer’s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex"

Article Title: Influence of Alzheimer’s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex

Journal: GEN biotechnology

doi: 10.1089/genbio.2023.0019

(A) Schematic of experimental design using Visium Spatial Proteogenomics (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide cDNA synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.

Figure Legend Snippet: (A) Schematic of experimental design using Visium Spatial Proteogenomics (Visium-SPG) to investigate the impact of Aβ and pTau aggregates on the local microenvironment transcriptome in the post-mortem human brain. Human ITC blocks were acquired from 3 donors with AD and 1 age-matched neurotypical control. Tissue blocks were cryosectioned at 10μm to obtain 2–3 replicates per donor and sections were collected onto individual capture arrays of a Visium spatial gene expression slide, yielding a total of 3 gene expression experiments. The entire slide (4 tissue sections) was stained and scanned using multispectral imaging methods to detect Aβ and pTau immunofluorescence (IF) signals as well as autofluorescence. Following imaging, tissue sections were permeabilized and subjected to on-slide cDNA synthesis after which libraries were generated and sequenced. Transcriptomic data was aligned with the respective IF image data to generate gene expression maps of the local transcriptome with respect to Aβ plaques and pTau elements, including neurofibrillary tangles. (B) High magnification images show Aβ plaques (white triangles) and various neurofibrillary elements such as tangles (white arrowheads), neuropil threads (red arrowheads), and neuritic tau plaques (yellow arrowheads). Lipofuscin (cyan) was identified through spectral unmixing and pixels confounded with this autofluorescent signal were excluded from analysis, scale bar, 20μm. (C) ITC tissue block from Br3880 (left) and corresponding spotplots (right) from the Visium data show gene expression of MOBP and SNAP25, which demarcates the border between gray matter (GM) and white matter (WM), scale bar, 1mm. Color scale indicates spot-level gene expression in logcounts. (D) Image processing and quantification of Aβ and pTau per Visium spot. Aβ and pTau signals were thresholded in their single IF channels for segmentation against autofluorescence background, including lipofuscin. Thresholded Aβ and pTau signals were aligned to the gene expression map of the same tissue section from Br3880 and quantified as the proportion of number of pixels per Visium spot, which is visualized in a spotplot, scale bar, 1mm.

Techniques Used: Control, Gene Expression, Staining, Imaging, Immunofluorescence, cDNA Synthesis, Generated, Blocking Assay

(A) Flowchart of experimental design and data analysis. Human ITC tissues from 3 original AD donors plus additional male AD donor (Br8549) were subjected to multiplexed staining using RNAscope smFISH combined with immunofluorescence (FISH-IF) to detect genes of interest (GOIs) and Aβ plaques. Images were analyzed with HALO image analysis software to assess spatial relationships between Aβ and cells expressing GOI. The FISH-IF module of HALO was used for image segmentation and quantification of Aβ and GOIs. The proximity analysis module was used to determine a distance between Aβ and cells expressing or not expressing GOIs. The outputs of the two modules were integrated to measure the gene expression of GOIs within a predefined proximity of Aβ at cellular resolution. (B) Schematic describing proximity analysis. An Aβ-associated microenvironment was demarcated by approximating the Visium spot grid-line system in which the center of a single Visium spot is 127.5μm away from its neighboring spot. This distance was further subdivided into 6 evenly spaced intervals, resulting in a total of 7 bins to finely resolve the spatial gene expression gradients of GOIs. The proximity between Aβ and nearby cells expressing and not expressing GOIs was measured and used to classify into the 7 bins for quantifying the average GOI gene expression. (C) RNA-protein co-detection of Aβ and IDI1, C3, NINJ1, PPP3CA reveals the spatial distribution patterns of Aβ (cyan) and GOIs (magenta) at lower (Top, scale bar: 50μm) and higher magnifications (Bottom, scale bar: 12.5μm). Proximity lines indicate the distance between Aβ and nearby cells expressing GOIs (max: 127.5μm). (D) Bar plots show quantification of gene expression levels for GOIs in Figure 3C across 7 consecutive bins representing increased distance from Aβ, as modeled in Figure 3B. Gene expression levels were determined with log2 (X+1) transformation where X represents the counts of puncta in a single cell for a given GOI. Data are mean ± SEM. The first bin was compared to all the rest by default for statistical tests (Kruskal-Wallis test, *p<0.05, &p<0.005, and #p<0.0001). The bracket denotes statistical testing between two specified bins. Violin plots are provided in Figure S18C describing the cellular distribution and numbers counted for each bin.

Figure Legend Snippet: (A) Flowchart of experimental design and data analysis. Human ITC tissues from 3 original AD donors plus additional male AD donor (Br8549) were subjected to multiplexed staining using RNAscope smFISH combined with immunofluorescence (FISH-IF) to detect genes of interest (GOIs) and Aβ plaques. Images were analyzed with HALO image analysis software to assess spatial relationships between Aβ and cells expressing GOI. The FISH-IF module of HALO was used for image segmentation and quantification of Aβ and GOIs. The proximity analysis module was used to determine a distance between Aβ and cells expressing or not expressing GOIs. The outputs of the two modules were integrated to measure the gene expression of GOIs within a predefined proximity of Aβ at cellular resolution. (B) Schematic describing proximity analysis. An Aβ-associated microenvironment was demarcated by approximating the Visium spot grid-line system in which the center of a single Visium spot is 127.5μm away from its neighboring spot. This distance was further subdivided into 6 evenly spaced intervals, resulting in a total of 7 bins to finely resolve the spatial gene expression gradients of GOIs. The proximity between Aβ and nearby cells expressing and not expressing GOIs was measured and used to classify into the 7 bins for quantifying the average GOI gene expression. (C) RNA-protein co-detection of Aβ and IDI1, C3, NINJ1, PPP3CA reveals the spatial distribution patterns of Aβ (cyan) and GOIs (magenta) at lower (Top, scale bar: 50μm) and higher magnifications (Bottom, scale bar: 12.5μm). Proximity lines indicate the distance between Aβ and nearby cells expressing GOIs (max: 127.5μm). (D) Bar plots show quantification of gene expression levels for GOIs in Figure 3C across 7 consecutive bins representing increased distance from Aβ, as modeled in Figure 3B. Gene expression levels were determined with log2 (X+1) transformation where X represents the counts of puncta in a single cell for a given GOI. Data are mean ± SEM. The first bin was compared to all the rest by default for statistical tests (Kruskal-Wallis test, *p<0.05, &p<0.005, and #p<0.0001). The bracket denotes statistical testing between two specified bins. Violin plots are provided in Figure S18C describing the cellular distribution and numbers counted for each bin.

Techniques Used: Staining, RNAscope, Immunofluorescence, Software, Expressing, Gene Expression, Transformation Assay

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visium spatial proteogenomics platform visium spg (10X Genomics)

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1) Product Images from "Influence of Alzheimer’s disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex"

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