Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis

Lindsey R. Conroy; Harrison A. Clarke; Derek B. Allison; Samuel Santos Valenca; Qi Sun; Tara R. Hawkinson; Lyndsay E.A. Young; Juanita E. Ferreira; Autumn V. Hammonds; Jaclyn B. Dunne; Robert J. McDonald; Kimberly J. Absher; Brittany E. Dong; Ronald C. Bruntz; Kia H. Markussen; Jelena A. Juras; Warren J. Alilain; Jinze Liu; Matthew S. Gentry; Peggi M. Angel; Christopher M. Waters; Ramon C. Sun

doi:10.1038/s41467-023-38437-1

Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis

Lindsey R. Conroy, Harrison A. Clarke, Derek B. Allison, Samuel Santos Valenca, Qi Sun, Tara R. Hawkinson, Lyndsay E.A. Young, Juanita E. Ferreira, Autumn V. Hammonds, Jaclyn B. Dunne, Robert J. McDonald, Kimberly J. Absher, Brittany E. Dong, Ronald C. Bruntz, Kia H. Markussen, Jelena A. Juras, Warren J. Alilain, Jinze Liu, Matthew S. Gentry, Peggi M. AngelChristopher M. Waters, Ramon C. Sun

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

Matrix assisted laser desorption/ionization imaging has greatly improved our understanding of spatial biology, however a robust bioinformatic pipeline for data analysis is lacking. Here, we demonstrate the application of high-dimensionality reduction/spatial clustering and histopathological annotation of matrix assisted laser desorption/ionization imaging datasets to assess tissue metabolic heterogeneity in human lung diseases. Using metabolic features identified from this pipeline, we hypothesize that metabolic channeling between glycogen and N-linked glycans is a critical metabolic process favoring pulmonary fibrosis progression. To test our hypothesis, we induced pulmonary fibrosis in two different mouse models with lysosomal glycogen utilization deficiency. Both mouse models displayed blunted N-linked glycan levels and nearly 90% reduction in endpoint fibrosis when compared to WT animals. Collectively, we provide conclusive evidence that lysosomal utilization of glycogen is required for pulmonary fibrosis progression. In summary, our study provides a roadmap to leverage spatial metabolomics to understand foundational biology in pulmonary diseases.

Original language	English
Article number	2759
Journal	Nature Communications
Volume	14
Issue number	1
DOIs	https://doi.org/10.1038/s41467-023-38437-1
State	Published - Dec 2023

Bibliographical note

Publisher Copyright:
© 2023, The Author(s).

Funding

We would like to thank Dr. Craig Vander Kooi for vigorous discussions regarding the work, Mrs. Dana Napier for performing histological staining on tissue slices, and the Markey Cancer Center. This study was supported by National Institute of Health (NIH) grants R01AG066653, R01CA266004, R01AG078702, CureAlz fund, St Baldrick’s Career Development Award, V-Scholar Grant, Rally Foundation Independent Investigator Grant to R.C.S., HL131526 and HL151419 to C.M.W., R21NS121966 to W.J.A., R35NS116824 to M.S.G., L.E.A.Y. was supported by NIH/NCI F99CA264165, L.R.C. was supported by NIH/NCI training grant T32CA165990, and J.B.D. was supported by NIH training grant T32GM132055. This research was also supported by funding from the University of Kentucky Markey Cancer Center and the NIH-funded Biospecimen Procurement & Translational Pathology Shared Resource Facility of the University of Kentucky Markey Cancer Center P30CA177558. S.S.V. was granted with a sabbatical from Federal University of Rio de Janeiro, Brazil. We would like to thank Dr. Craig Vander Kooi for vigorous discussions regarding the work, Mrs. Dana Napier for performing histological staining on tissue slices, and the Markey Cancer Center. This study was supported by National Institute of Health (NIH) grants R01AG066653, R01CA266004, R01AG078702, CureAlz fund, St Baldrick’s Career Development Award, V-Scholar Grant, Rally Foundation Independent Investigator Grant to R.C.S., HL131526 and HL151419 to C.M.W., R21NS121966 to W.J.A., R35NS116824 to M.S.G., L.E.A.Y. was supported by NIH/NCI F99CA264165, L.R.C. was supported by NIH/NCI training grant T32CA165990, and J.B.D. was supported by NIH training grant T32GM132055. This research was also supported by funding from the University of Kentucky Markey Cancer Center and the NIH-funded Biospecimen Procurement & Translational Pathology Shared Resource Facility of the University of Kentucky Markey Cancer Center P30CA177558. S.S.V. was granted with a sabbatical from Federal University of Rio de Janeiro, Brazil.

Funders	Funder number
National Institutes of Health (NIH)	R01AG078702, P30CA177558, R01CA266004, R01AG066653
National Institutes of Health (NIH)
National Childhood Cancer Registry – National Cancer Institute	F99CA264165, T32GM132055, T32CA165990
National Childhood Cancer Registry – National Cancer Institute
Rally Foundation	R35NS116824, R21NS121966, HL151419, HL131526
Rally Foundation
University of Kentucky Markey Cancer Center
Universidade Federal do Rio de Janeiro

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41467-023-38437-1

Cite this

Conroy, L. R., Clarke, H. A., Allison, D. B., Valenca, S. S., Sun, Q., Hawkinson, T. R., Young, L. E. A., Ferreira, J. E., Hammonds, A. V., Dunne, J. B., McDonald, R. J., Absher, K. J., Dong, B. E., Bruntz, R. C., Markussen, K. H., Juras, J. A., Alilain, W. J., Liu, J., Gentry, M. S., ... Sun, R. C. (2023). Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis. Nature Communications, 14(1), Article 2759. https://doi.org/10.1038/s41467-023-38437-1

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abstract = "Matrix assisted laser desorption/ionization imaging has greatly improved our understanding of spatial biology, however a robust bioinformatic pipeline for data analysis is lacking. Here, we demonstrate the application of high-dimensionality reduction/spatial clustering and histopathological annotation of matrix assisted laser desorption/ionization imaging datasets to assess tissue metabolic heterogeneity in human lung diseases. Using metabolic features identified from this pipeline, we hypothesize that metabolic channeling between glycogen and N-linked glycans is a critical metabolic process favoring pulmonary fibrosis progression. To test our hypothesis, we induced pulmonary fibrosis in two different mouse models with lysosomal glycogen utilization deficiency. Both mouse models displayed blunted N-linked glycan levels and nearly 90% reduction in endpoint fibrosis when compared to WT animals. Collectively, we provide conclusive evidence that lysosomal utilization of glycogen is required for pulmonary fibrosis progression. In summary, our study provides a roadmap to leverage spatial metabolomics to understand foundational biology in pulmonary diseases.",

author = "Conroy, {Lindsey R.} and Clarke, {Harrison A.} and Allison, {Derek B.} and Valenca, {Samuel Santos} and Qi Sun and Hawkinson, {Tara R.} and Young, {Lyndsay E.A.} and Ferreira, {Juanita E.} and Hammonds, {Autumn V.} and Dunne, {Jaclyn B.} and McDonald, {Robert J.} and Absher, {Kimberly J.} and Dong, {Brittany E.} and Bruntz, {Ronald C.} and Markussen, {Kia H.} and Juras, {Jelena A.} and Alilain, {Warren J.} and Jinze Liu and Gentry, {Matthew S.} and Angel, {Peggi M.} and Waters, {Christopher M.} and Sun, {Ramon C.}",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).",

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doi = "10.1038/s41467-023-38437-1",

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Conroy, LR, Clarke, HA, Allison, DB, Valenca, SS, Sun, Q, Hawkinson, TR, Young, LEA, Ferreira, JE, Hammonds, AV, Dunne, JB, McDonald, RJ, Absher, KJ, Dong, BE, Bruntz, RC, Markussen, KH, Juras, JA, Alilain, WJ, Liu, J, Gentry, MS, Angel, PM, Waters, CM & Sun, RC 2023, 'Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis', Nature Communications, vol. 14, no. 1, 2759. https://doi.org/10.1038/s41467-023-38437-1

TY - JOUR

T1 - Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis

AU - Conroy, Lindsey R.

AU - Clarke, Harrison A.

AU - Allison, Derek B.

AU - Valenca, Samuel Santos

AU - Sun, Qi

AU - Hawkinson, Tara R.

AU - Young, Lyndsay E.A.

AU - Ferreira, Juanita E.

AU - Hammonds, Autumn V.

AU - Dunne, Jaclyn B.

AU - McDonald, Robert J.

AU - Absher, Kimberly J.

AU - Dong, Brittany E.

AU - Bruntz, Ronald C.

AU - Markussen, Kia H.

AU - Juras, Jelena A.

AU - Alilain, Warren J.

AU - Liu, Jinze

AU - Gentry, Matthew S.

AU - Angel, Peggi M.

AU - Waters, Christopher M.

AU - Sun, Ramon C.

PY - 2023/12

Y1 - 2023/12

N2 - Matrix assisted laser desorption/ionization imaging has greatly improved our understanding of spatial biology, however a robust bioinformatic pipeline for data analysis is lacking. Here, we demonstrate the application of high-dimensionality reduction/spatial clustering and histopathological annotation of matrix assisted laser desorption/ionization imaging datasets to assess tissue metabolic heterogeneity in human lung diseases. Using metabolic features identified from this pipeline, we hypothesize that metabolic channeling between glycogen and N-linked glycans is a critical metabolic process favoring pulmonary fibrosis progression. To test our hypothesis, we induced pulmonary fibrosis in two different mouse models with lysosomal glycogen utilization deficiency. Both mouse models displayed blunted N-linked glycan levels and nearly 90% reduction in endpoint fibrosis when compared to WT animals. Collectively, we provide conclusive evidence that lysosomal utilization of glycogen is required for pulmonary fibrosis progression. In summary, our study provides a roadmap to leverage spatial metabolomics to understand foundational biology in pulmonary diseases.

AB - Matrix assisted laser desorption/ionization imaging has greatly improved our understanding of spatial biology, however a robust bioinformatic pipeline for data analysis is lacking. Here, we demonstrate the application of high-dimensionality reduction/spatial clustering and histopathological annotation of matrix assisted laser desorption/ionization imaging datasets to assess tissue metabolic heterogeneity in human lung diseases. Using metabolic features identified from this pipeline, we hypothesize that metabolic channeling between glycogen and N-linked glycans is a critical metabolic process favoring pulmonary fibrosis progression. To test our hypothesis, we induced pulmonary fibrosis in two different mouse models with lysosomal glycogen utilization deficiency. Both mouse models displayed blunted N-linked glycan levels and nearly 90% reduction in endpoint fibrosis when compared to WT animals. Collectively, we provide conclusive evidence that lysosomal utilization of glycogen is required for pulmonary fibrosis progression. In summary, our study provides a roadmap to leverage spatial metabolomics to understand foundational biology in pulmonary diseases.

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Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis

Abstract

Bibliographical note

Funding

ASJC Scopus subject areas

UN SDGs

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