@lcolladotor lcolladotor.github.io lcolladotor.github.io/bioc_team_ds Harnessing the power of spatially-resolved transcriptomics one step at a time (part 2/2) Leonardo Collado Torres, Investigator #Visium_SPG_AD 2023 NIA/LNG Neurodegenerative Diseases Seminar Series June 09 2023 Slides available at speakerdeck.com/lcolladotor

twitter.com/sanghokwon17/status/1650589385379962881 from 2023-04-24 Sang Ho Kwon @sanghokwon17 DOI: 10.1101/2023.04.20.537710 #Visium_SPG_AD In collaboration with Download data with spatialLIBD::fetch_data() research.libd.org /Visium_SPG_AD

Visium spatial clustering works for variables with high % variance explained. But what about other ones? DOI: 10.1038/s41593-020-00787-0

Alzheimer’s disease related neuropathology Adopted and modified from B Wang (2018) and the Brain from the Top to Bottom in McGill University 20 um Sang Ho Kwon Amyloid beta pTau

Hypothesis Local tissue microenvironments in close proximity to AD-related neuropathology have distinct cellular and molecular signatures. Sang Ho Kwon

Visium Spatial Proteogenomics (Visium-SPG) Visium-SPG = Visium SRT + immunofluorescence (using identical tissue samples) Sang Ho Kwon

Experimental design & study overview Braak V-VI & CERAD frequent Sang Ho Kwon

Donor demographics BrNum Age of death (years old) Sex Ancestry PMI (hours) Dx Best RIN PFC Braak CERAD APOE # Visium Replicates Br3854 65.75 Female European 31.5 Alzheimer 7.0 Stage VI Frequent e3/e4 2 Br3873 88.78 Female European 29.0 Alzheimer 7.2 Stage V Frequent e3/e3 2 Br3880 90.47 Male European 35.0 Alzheimer 7.1 Stage VI Frequent e3/e3 3 Br3874 73.05 Male European 13.5 Control 7.2 Stage IV None e2/e3 3 DOI: 10.1101/2023.04.20.537710

AD pathology signal is too small to detect by spatially-resolved gene expression alone research.libd.org/Visium_SPG_AD/

Visium * ~5k spots in honeycomb * gene expression per spot * tissue (H&E staining) Immunofluorescence (IF) * multi-channel (6) images * identifies morphological features of interest * large: might be broken in tiles Channel 1 * triangle feature Channel 2 * cloud feature Channel 6 * xyz feature Tissue (bright field image) Visium spot Channel 1 feature Channel 2 feature + Visium Spatial Proteogenomics (Visium-SPG / IF) raw data: 2 types

Spot ID Gene 1 Gene 2 Gene X spot0001 0 12 39 spot0002 4 0 27 Spot ID Gene 1 Gene 2 Gene X In Tissue # cells spot0001 0 12 39 true 3 spot0002 4 0 27 false 0 * spaceranger * Loupe Browser * VistoSeg on H&E bright field image Visium Analysis @MadhaviTippani @HeenaDivecha cell VistoSeg DOI: 10.1101/2021.08.04.452489

Feature ID X center Y center type intensity feat0001 5 102 triangle 130.4 feat0002 10 30 cloud 99.1 Max (X, Y) Min (X, Y) Area ... SPG / IF Image Analysis * segment each channel * find features Challenges: * morphological features can be quite diverse * images are large * multiple tiles +

Spot ID # Triangle # Cloud % triangle % cloud spot0001 0 12 0 17 spot0002 4 0 27 0 Merge Visium & IF IF Spot ID Gene 1 Gene 2 Gene X In Tissue # cells spot0001 0 12 39 true 3 spot0002 4 0 27 false 0 Visium downstream * QC * analyses spatialLIBD DOI: 10.1186/s12864-022-08601-w VistoSeg DOI: 10.1101/2021.08.04.452489 Check version 2!! @MadhaviTippani

Estimating pathological burden per spot to generate transcriptome-scale maps of AD pathology 1. both > 2. A𝛽 or pTau > 3. next_both > 4. next_A𝛽 or next_pTau > 5. none

AD pathology signal is too small to detect by spatially-resolved gene expression alone research.libd.org/Visium_SPG_AD/

Pathology burden is more common in the gray matter BayesSpace with 2 clusters: Cluster 1: gray matter (GM) Cluster 2: white matter (WM) 1 2

Identifying transcriptional signatures of AD-related neuropathology Sang Ho Kwon

Identifying transcriptional signatures of Abeta-related neuropathology Sang Ho Kwon

Validation study design using RNAscope FISH-IF Sang Ho Kwon

HALO-based image analysis

6 Abeta-associated DEGs on RNAscope FISH-IF (Kruskal-Wallis test, *p<0.05, &p<0.005, and #p<0.0001) Sang Ho Kwon

Visium + RNAscope to provide additional insights into spatial gene expression gradients Sang Ho Kwon

Identifying transcriptional signatures of Abeta microenvironment Previously not significant Sang Ho Kwon A𝛽 + next_A𝛽 = A𝛽_env (environment)

bioconductor.org/packages/spatialLIBD Pardo et al, 2022 DOI 10.1186/s12864-022-08601-w Maynard, Collado-Torres, 2021 DOI 10.1038/s41593-020-00787-0 Brenda Pardo Abby Spangler @PardoBree @abspangler Louise A. Huuki-Myers @lahuuki

Conclusions • Visium-SPG can identify local transcriptional signatures of late-stage AD pathology • RNAscope FISH-IF can further explore spatial gene expression patterns of a few select features • Proof-of-concept study: our work lays the groundwork. Can now use Visium-SPG for other diseases too • Future studies are needed to produce mechanistic insights • Explore our code & data at research.libd.org/Visium_SPG_AD & download it with spatialLIBD::fetch_data() ○ There’s lots more to explore with this data! Sang Ho Kwon Slide adapted from:

twitter.com/sanghokwon17/status/1650589385379962881 from 2023-04-24 Sang Ho Kwon @sanghokwon17 DOI: 10.1101/2023.04.20.537710 #Visium_SPG_AD In collaboration with Download data with spatialLIBD::fetch_data() research.libd.org /Visium_SPG_AD

@MadhaviTippani Madhavi Tippani @HeenaDivecha Heena R Divecha @lmwebr Lukas M Weber @stephaniehicks Stephanie C Hicks @abspangler Abby Spangler @martinowk Keri Martinowich @CerceoPage Stephanie C Page @kr_maynard Kristen R Maynard @lcolladotor Leonardo Collado-Torres @Nick-Eagles (GH) Nicholas J Eagles Kelsey D Montgomery Sang Ho Kwon Image Analysis Expression Analysis Data Generation Thomas M Hyde @lahuuki Louise A Huuki-Myers @BoyiGuo Boyi Guo @mattntran Matthew N Tran @sowmyapartybun Sowmya Parthiban Slides available at speakerdeck.com /lcolladotor + Many more LIBD, JHU, and external collaborators @mgrantpeters Melissa Grant-Peters @prashanthi-ravichandran (GH) Prashanthi Ravichandran

#GBD23 Thank you for having us over in the UK 󰏅! !Gracias Pilar & Cornelis for the invitation to present at NIA/LNG!

lcolladotor.github.io @lcolladotor