Spatial biology has emerged as a transformative field, offering insights into cellular interactions and organization within tissues. The field has evolved rapidly since the coining of the term “spatial omics.” Now, the ability to spatially resolve proteins, RNA, chromatin, and lipids is becoming widespread, and the technologies are continually refined. Reagents to support the analysis of veterinary species are available and more are emerging. These new tools will allow pathologists and scientists to unravel the intricate interplay between tissue architecture and diverse cellular phenotypes. By integrating histological observations with spatially resolved genomic data, spatial biology holds immense potential for advancing diagnostic and therapeutic strategies in veterinary medicine. These tools will undoubtedly equip veterinary pathologists to better decipher complex disease processes and identify novel therapeutic targets.
AngeloMBendallSCFinckR, et al. Multiplexed ion beam imaging of human breast tumors. Nat Med. 2014;20:436–442.
2.
Ben-ChetritNNiuXSwettAD, et al. Integration of whole transcriptome spatial profiling with protein markers. Nat Biotechnol. 2023;41:788–793.
3.
BlackSPhillipsDHickeyJW, et al. CODEX multiplexed tissue imaging with DNA-conjugated antibodies. Nat Protoc. 2021;16:3802–3835.
4.
BrownVMOssadtchiAKhanAH, et al. Multiplex three-dimensional brain gene expression mapping in a mouse model of Parkinson’s disease. Genome Res. 2002;12:868–884.
5.
ChenJSuoSTamPP, et al. Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq. Nat Protoc. 2017;12:566–580.
6.
ChenKHBoettigerANMoffittJR, et al. RNA imaging, spatially resolved, highly multiplexed RNA profiling in single cells. Science. 2015;348:aaa6090.
7.
ChenTYYouLHardilloJAU, et al. Spatial transcriptomic technologies. Cells. 2023;12:2042.
8.
ClarkeGMZubovitsJTShaikhKA, et al. A novel, automated technology for multiplex biomarker imaging and application to breast cancer. Histopathology. 2014;64:242–255.
9.
CorcesMRTrevinoAEHamiltonEG, et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat Methods. 2017;14:959–962.
10.
CornettDSReyzerMLChaurandP, et al. MALDI imaging mass spectrometry: molecular snapshots of biochemical systems. Nat Methods. 2007;4:828–833.
11.
DengYBartosovicMMaS, et al. Spatial profiling of chromatin accessibility in mouse and human tissues. Nature. 2022;609:375–383.
12.
Emmert-BuckMRBonnerRFSmithPD, et al. Laser capture microdissection. Science. 1996;274:998–1001.
13.
EngCLLawsonMZhuQ, et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH. Nature. 2019;568:235–239.
14.
GerdesMJSevinskyCJSoodA, et al. Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue. Proc Natl Acad Sci USA. 2013;110:11982–11987.
15.
GianiAMGalloGRGianfranceschiL, et al. Long walk to genomics: history and current approaches to genome sequencing and assembly. Comput Struct Biotechnol J. 2020;18:9–19.
16.
HeSBhattRBrownC, et al. High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging. Nat Biotechnol. 2022;40:1794–1806.
17.
KimIKangKSongY, et al. Application of artificial intelligence in pathology: trends and challenges. Diagnostics (Basel). 2022;12:2794.
18.
KinkhabwalaAHerbelCPankratzJ, et al. MACSima imaging cyclic staining (MICS) technology reveals combinatorial target pairs for CAR T cell treatment of solid tumors. Sci Rep. 2022;12:1911.
19.
KishiJYLiuNWestER, et al. Light-Seq: light-directed in situ barcoding of biomolecules in fixed cells and tissues for spatially indexed sequencing. Nat Methods. 2022;19:1393–1402.
20.
LeeJHDaugharthyERScheimanJ, et al. Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues. Nat Protoc. 2015;10:442–458.
21.
LohoffTGhazanfarSMissarovaA, et al. Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis. Nat Biotechnol. 2022;40:74–85.
22.
LondonCAGardnerHZhaoS, et al. Leading the pack: best practices in comparative canine cancer genomics to inform human oncology. Vet Comp Oncol. 2023;21:565–577.
23.
LubeckECaiL.Single-cell systems biology by super-resolution imaging and combinatorial labeling. Nat Methods. 2012;9:743–748.
24.
LubeckECoskunAFZhiyentayevT, et al. Single-cell in situ RNA profiling by sequential hybridization. Nat Methods. 2014;11:360–361.
25.
LuTAngCEZhuangX.Spatially resolved epigenomic profiling of single cells in complex tissues. Cell. 2023;186:2275–2279.
26.
MaynardKRCollado-TorresLWeberLM, et al. Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex. Nat Neurosci. 2021;24:425–436.
27.
MedagliaCGiladiAStoler-BarakL, et al. Spatial reconstruction of immune niches by combining photoactivatable reporters and scRNA-seq. Science. 2017;358:1622–1626.
28.
MerrittCROngGTChurchSE, et al. Multiplex digital spatial profiling of proteins and RNA in fixed tissue. Nat Biotechnol. 2020;38:586–599.
29.
MosesLPachterL.Museum of spatial transcriptomics. Nat Methods. 2022;19:534–546.
30.
NanoString. GeoMx IO Proteome Atlas. 2024.
31.
National Society for Histotechnology. Reducing static in the lab. In: Fixation on Histology blog. National Society for Histotechnology; 2019.
32.
NgLGOstuniRHidalgoA.Heterogeneity of neutrophils. Nat Rev Immunol. 2019;19:255–265.
33.
NiehausMSoltwischJBelovME, et al. Transmission-mode MALDI-2 mass spectrometry imaging of cells and tissues at subcellular resolution. Nat Methods. 2019;16:925–931.
34.
No authors. Method of the year 2013. Nat Methods. 2014;11:1.
35.
PatkarSMannheimerJHarmonS, et al. Large scale comparative deconvolution analysis of the canine and human osteosarcoma tumor microenvironment uncovers conserved clinically relevant subtypes. Biorxiv. 2023;2023:559797.
36.
RappezLStadlerMTrianaS, et al. SpaceM reveals metabolic states of single cells. Nat Methods. 2021;18:799–805.
37.
RivestFErogluDPelzB, et al. Fully automated sequential immunofluorescence (seqIF) for hyperplex spatial proteomics. Sci Rep. 2023;13:16994.
38.
RodriquesSGStickelsRRGoevaA, et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019;363:1463–1467.
39.
SaundersKDGLewisHMBesteDJ, et al. Spatial single cell metabolomics: current challenges and future developments. Curr Opin Chem Biol. 2023;75:102327.
Silvestre-RoigCFridlenderZGGlogauerM, et al. Neutrophil diversity in health and disease. Trends Immunol. 2019;40:565–583.
42.
SpruillMLMaletic-SavaticMMartinH, et al. Spatial analysis of drug absorption, distribution, metabolism, and toxicology using mass spectrometry imaging. Biochem Pharmacol. 2022;201:115080.
43.
StahlPLSalmenFVickovicS, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 2016;353:78–82.
44.
StickelsRRMurrayEKumarP, et al. Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2. Nat Biotechnol. 2021;39:313–319.
45.
SwalesJGTuckerJWStrittmatterN, et al. Mass spectrometry imaging of cassette-dosed drugs for higher throughput pharmacokinetic and biodistribution analysis. Anal Chem. 2014;86:8473–8480.
46.
TautzDPfeifleC.A non-radioactive in situ hybridization method for the localization of specific RNAs in Drosophila embryos reveals translational control of the segmentation gene hunchback. Chromosoma. 1989;98:81–85.
47.
TianHSherazNeeRabbaniSVickermanJC, et al. Multiomics imaging using high-energy water gas cluster ion beam secondary ion mass spectrometry [(H(2)O)(n)-GCIB-SIMS] of frozen-hydrated cells and tissue. Anal Chem. 2021;93:7808–7814.
48.
WangXAllenWEWrightMA, et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. Science. 2018;361:eaat5691.
49.
WeiXFuSLiH, et al. Single-cell Stereo-seq reveals induced progenitor cells involved in axolotl brain regeneration. Science. 2022;377:eabp9444.
50.
WigerbladGCaoQBrooksS, et al. Single-cell analysis reveals the range of transcriptional states of circulating human neutrophils. J Immunol. 2022;209:772–782.
51.
WilliamsCGLeeHJAsatsumaT, et al. An introduction to spatial transcriptomics for biomedical research. Genome Med. 2022;14:68.
52.
YouLSuPRBetjesM, et al. Linking the genotypes and phenotypes of cancer cells in heterogenous populations via real-time optical tagging and image analysis. Nat Biomed Eng. 2022;6:667–675.
53.
ZengHHuangJZhouH, et al. Integrative in situ mapping of single-cell transcriptional states and tissue histopathology in a mouse model of Alzheimer’s disease. Nat Neurosci. 2023;26:430–446.
54.
ZollingerDRLingleSESorgK, et al. GeoMx RNA assay: high multiplex, digital, spatial analysis of RNA in FFPE tissue. Methods Mol Biol. 2020;2148:331–345.
