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Spatially Resolved Immunometabolism to Understand Infectious Disease Progression
Infectious diseases, including those of viral, bacterial, fungal, and parasitic origin are often characterized by focal inflammation occurring in one or more distinct tissues. Tissue-specific outcomes of infection are also evident in many infectious diseases, suggesting that the local microenvironme...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8418271/ https://www.ncbi.nlm.nih.gov/pubmed/34489899 http://dx.doi.org/10.3389/fmicb.2021.709728 |
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author | Tans, Roel Dey, Shoumit Dey, Nidhi Sharma Calder, Grant O’Toole, Peter Kaye, Paul M. Heeren, Ron M. A. |
author_facet | Tans, Roel Dey, Shoumit Dey, Nidhi Sharma Calder, Grant O’Toole, Peter Kaye, Paul M. Heeren, Ron M. A. |
author_sort | Tans, Roel |
collection | PubMed |
description | Infectious diseases, including those of viral, bacterial, fungal, and parasitic origin are often characterized by focal inflammation occurring in one or more distinct tissues. Tissue-specific outcomes of infection are also evident in many infectious diseases, suggesting that the local microenvironment may instruct complex and diverse innate and adaptive cellular responses resulting in locally distinct molecular signatures. In turn, these molecular signatures may both drive and be responsive to local metabolic changes in immune as well as non-immune cells, ultimately shaping the outcome of infection. Given the spatial complexity of immune and inflammatory responses during infection, it is evident that understanding the spatial organization of transcripts, proteins, lipids, and metabolites is pivotal to delineating the underlying regulation of local immunity. Molecular imaging techniques like mass spectrometry imaging and spatially resolved, highly multiplexed immunohistochemistry and transcriptomics can define detailed metabolic signatures at the microenvironmental level. Moreover, a successful complementation of these two imaging techniques would allow multi-omics analyses of inflammatory microenvironments to facilitate understanding of disease pathogenesis and identify novel targets for therapeutic intervention. Here, we describe strategies for downstream data analysis of spatially resolved multi-omics data and, using leishmaniasis as an exemplar, describe how such analysis can be applied in a disease-specific context. |
format | Online Article Text |
id | pubmed-8418271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84182712021-09-05 Spatially Resolved Immunometabolism to Understand Infectious Disease Progression Tans, Roel Dey, Shoumit Dey, Nidhi Sharma Calder, Grant O’Toole, Peter Kaye, Paul M. Heeren, Ron M. A. Front Microbiol Microbiology Infectious diseases, including those of viral, bacterial, fungal, and parasitic origin are often characterized by focal inflammation occurring in one or more distinct tissues. Tissue-specific outcomes of infection are also evident in many infectious diseases, suggesting that the local microenvironment may instruct complex and diverse innate and adaptive cellular responses resulting in locally distinct molecular signatures. In turn, these molecular signatures may both drive and be responsive to local metabolic changes in immune as well as non-immune cells, ultimately shaping the outcome of infection. Given the spatial complexity of immune and inflammatory responses during infection, it is evident that understanding the spatial organization of transcripts, proteins, lipids, and metabolites is pivotal to delineating the underlying regulation of local immunity. Molecular imaging techniques like mass spectrometry imaging and spatially resolved, highly multiplexed immunohistochemistry and transcriptomics can define detailed metabolic signatures at the microenvironmental level. Moreover, a successful complementation of these two imaging techniques would allow multi-omics analyses of inflammatory microenvironments to facilitate understanding of disease pathogenesis and identify novel targets for therapeutic intervention. Here, we describe strategies for downstream data analysis of spatially resolved multi-omics data and, using leishmaniasis as an exemplar, describe how such analysis can be applied in a disease-specific context. Frontiers Media S.A. 2021-08-19 /pmc/articles/PMC8418271/ /pubmed/34489899 http://dx.doi.org/10.3389/fmicb.2021.709728 Text en Copyright © 2021 Tans, Dey, Dey, Calder, O’Toole, Kaye and Heeren. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Tans, Roel Dey, Shoumit Dey, Nidhi Sharma Calder, Grant O’Toole, Peter Kaye, Paul M. Heeren, Ron M. A. Spatially Resolved Immunometabolism to Understand Infectious Disease Progression |
title | Spatially Resolved Immunometabolism to Understand Infectious Disease Progression |
title_full | Spatially Resolved Immunometabolism to Understand Infectious Disease Progression |
title_fullStr | Spatially Resolved Immunometabolism to Understand Infectious Disease Progression |
title_full_unstemmed | Spatially Resolved Immunometabolism to Understand Infectious Disease Progression |
title_short | Spatially Resolved Immunometabolism to Understand Infectious Disease Progression |
title_sort | spatially resolved immunometabolism to understand infectious disease progression |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8418271/ https://www.ncbi.nlm.nih.gov/pubmed/34489899 http://dx.doi.org/10.3389/fmicb.2021.709728 |
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