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Singhal V, Chou N, Lee J, Yue Y, Liu J, Chock WK, Lin L, Chang YC, Teo EML, Aow J, Lee HK, Chen KH, Prabhakar S. BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis. Nat Genet 2024; 56:431-441. [PMID: 38413725 PMCID: PMC10937399 DOI: 10.1038/s41588-024-01664-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 01/16/2024] [Indexed: 02/29/2024]
Abstract
Spatial omics data are clustered to define both cell types and tissue domains. We present Building Aggregates with a Neighborhood Kernel and Spatial Yardstick (BANKSY), an algorithm that unifies these two spatial clustering problems by embedding cells in a product space of their own and the local neighborhood transcriptome, representing cell state and microenvironment, respectively. BANKSY's spatial feature augmentation strategy improved performance on both tasks when tested on diverse RNA (imaging, sequencing) and protein (imaging) datasets. BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data and for spatially aware batch effect correction. Importantly, it is substantially faster and more scalable than existing methods, enabling the processing of millions of cell datasets. In summary, BANKSY provides an accurate, biologically motivated, scalable and versatile framework for analyzing spatially resolved omics data.
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Affiliation(s)
- Vipul Singhal
- Spatial and Single Cell Systems Domain, Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Nigel Chou
- Spatial and Single Cell Systems Domain, Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Joseph Lee
- Faculty of Science, National University of Singapore, Singapore, Republic of Singapore
| | - Yifei Yue
- Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, Republic of Singapore
| | - Jinyue Liu
- Spatial and Single Cell Systems Domain, Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Wan Kee Chock
- Spatial and Single Cell Systems Domain, Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Li Lin
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | | | | | - Jonathan Aow
- Spatial and Single Cell Systems Domain, Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Hwee Kuan Lee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
- School of Computing, National University of Singapore, Singapore, Republic of Singapore
- Singapore Eye Research Institute, Singapore, Republic of Singapore
- International Research Laboratory on Artificial Intelligence, Singapore, Republic of Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore, Republic of Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Republic of Singapore
| | - Kok Hao Chen
- Spatial and Single Cell Systems Domain, Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore.
| | - Shyam Prabhakar
- Spatial and Single Cell Systems Domain, Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore.
- Population and Global Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Republic of Singapore.
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Republic of Singapore.
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Tan MWY, Tan WR, Kong ZQ, Toh JH, Wee WKJ, Teo EML, Cheng HS, Wang X, Tan NS. High Glucose Restraint of Acetylcholine-Induced Keratinocyte Epithelial-Mesenchymal Transition Is Mitigated by p38 Inhibition. J Invest Dermatol 2020; 141:1438-1449.e9. [PMID: 33333125 DOI: 10.1016/j.jid.2020.10.026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 10/21/2020] [Accepted: 10/22/2020] [Indexed: 01/10/2023]
Abstract
Non-neuronal acetylcholine (Ach) plays important roles in various aspects of cell biology and homeostasis outside the neural system. Keratinocytes (KCs) have a functional cholinergic mechanism, suggesting that they respond to Ach. However, the physiological role and mechanism by which Ach modulates wound KC behavior in both nondiabetic and diabetic conditions are unexplored. We found an enrichment in neurotransmitter-related pathways in microdissected-migrating nondiabetic and diabetic KCs. We showed that Ach upregulated TGFβRII through Src-extracellular signal‒regulated kinase 1/2 pathway to potentiate TGFβ1-mediated epithelial‒mesenchymal transition in normoglycemic condition. Unexpectedly, KCs were nonresponsive to the elevated endogenous Ach in a hyperglycemic environment. We further showed that the activation of p38 MAPK in high glucose condition interferes with Src-extracellular signal‒regulated kinase 1/2 signaling, resulting in Ach resistance that could be rescued by inhibiting p38 MAPK. A better understanding of the cholinergic physiology in diabetic KCs could improve wound management and care. The finding suggests that mitigating the inhibitory effect of diabetic wound microenvironment has a direct clinical implication on the efficacy and safety of various wound healing agents to improve chronic diabetic wounds.
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Affiliation(s)
- Mark Wei Yi Tan
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore; NTU Institute for Health Technologies, Interdisciplinary Graduate School, Nanyang Technological University, Singapore, Singapore
| | - Wei Ren Tan
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Ze Qing Kong
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Jun Hong Toh
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Wei Kiat Jonathan Wee
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Erica Mei Ling Teo
- NTU Institute for Health Technologies, Interdisciplinary Graduate School, Nanyang Technological University, Singapore, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Hong Sheng Cheng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Xiaomeng Wang
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore; Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore, Singapore; Department of Cell Biology, Institute of Ophthalmology, University College London, London, United Kingdom; Singapore Eye Research Institute, The Academia, Singapore, Singapore
| | - Nguan Soon Tan
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
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Su JW, Wang Q, Tian Y, Madden L, Ling Teo EM, Becker DL, Liu Q. Depth-sensitive Raman spectroscopy for skin wound evaluation in rodents. Biomed Opt Express 2019; 10:6114-6128. [PMID: 31853389 PMCID: PMC6913421 DOI: 10.1364/boe.10.006114] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 10/25/2019] [Accepted: 10/30/2019] [Indexed: 05/22/2023]
Abstract
Raman spectroscopy has demonstrated great potential for skin wound assessment. Given that biochemical changes in wound healing is depth dependent as the skin is a layered structure, depth sensitive Raman spectroscopy could enhance the power of Raman spectroscopy in this application. Considering the critical importance of rodent studies in the field of skin wound assessment, it is necessary to develop and validate a system that can perform depth sensitive measurements in rat skin with a proper target depth range. In this manuscript, we report the design, optimization and evaluation of a new snapshot depth-sensitive Raman instrument for rat skin measurements. The optical design and optimization process are presented first. The depth sensitive measurement performance is characterized on both ex vivo porcine skin with a gradient of layer thickness and ex vivo rat skin samples with wounds. The statistical analysis of the measured Raman spectra demonstrates the feasibility of differentiation between the wound edge and healthy skin. Moreover, the accuracy of classification improves monotonically as more data from new depths are used, which implies that each depth offers additional information useful for classification. This instrument demonstrates the ability to perform snapshot depth sensitive Raman measurements from rat skin, which paves the way towards in vivo preclinical studies of rat skin wounds.
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Affiliation(s)
- Joshua Weiming Su
- School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, 637459, Singapore
- NTU Institute for Health Technologies, Interdisciplinary Graduate School, Nanyang Technological University, Singapore
- Skin Research Institute Singapore, 11 Mandalay Road, 308232, Singapore
| | - Qiang Wang
- School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, 637459, Singapore
- Currently with the Centre for Nanoscale Biophotonics, Macquarie University, Sydney, NSW 2109, Australia
| | - Yao Tian
- School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, 637459, Singapore
| | - Leigh Madden
- Skin Research Institute Singapore, 11 Mandalay Road, 308232, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, 308232, Singapore
| | - Erica Mei Ling Teo
- NTU Institute for Health Technologies, Interdisciplinary Graduate School, Nanyang Technological University, Singapore
- Skin Research Institute Singapore, 11 Mandalay Road, 308232, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, 308232, Singapore
| | - David Laurence Becker
- Skin Research Institute Singapore, 11 Mandalay Road, 308232, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, 308232, Singapore
| | - Quan Liu
- School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, 637459, Singapore
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