Single-cell profiling reveals a conserved role for hypoxia-inducible factor signaling during human craniotomy infection

Neurosurgeries complicated by infection are associated with prolonged treatment and significant morbidity. Craniotomy is a common neurosurgical procedure; however, the cellular and molecular signatures associated with craniotomy infection in human subjects are unknown. A retrospective study of over 2,500 craniotomies reveals diverse patient demographics, pathogen identity, and surgical landscapes associated with infection. Leukocyte profiling in patient tissues from craniotomy infection characterizes a predominance of granulocytic myeloid-derived suppressor cells that may arise from transmigrated blood neutrophils, based on single-cell RNA sequencing (scRNA-seq) trajectory analysis. Single-cell transcriptomic analysis identifies metabolic shifts in tissue leukocytes, including a conserved hypoxia-inducible factor (HIF) signature. The importance of HIF signaling was validated using a mouse model of Staphylococcus aureus craniotomy infection, where HIF inhibition increases chemokine production and leukocyte recruitment, exacerbating tissue pathology. These findings establish conserved metabolic and transcriptional signatures that may represent promising future therapeutic targets for human craniotomy infection in the face of increasing antimicrobial resistance.

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Publication Details

Journal
Cell Reports Medicine
Published
2024-10-18
DOI
https://doi.org/10.1016/j.xcrm.2024.101790
Citations
8
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
1.87

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article

Single-cell profiling reveals a conserved role for hypoxia-inducible factor signaling during human craniotomy infection

Rachel W. Fallet, Carol Geary, Tammy Kielian, Joseph Menousek et al.
8 citations
Cell Reports Medicine
Single-cell and spatial transcriptomics
1.87
article

Single-cell profiling reveals a conserved role for hypoxia-inducible factor signaling during human craniotomy infection

Rachel W. Fallet, Carol Geary, Tammy Kielian, Joseph Menousek, Lee E. Korshoj, Larisa Y. Poluektova, Cortney E. Heim, James R. Campbell, Santhi Gorantla, William Thorell, W. Scott Campbell, Bin Duan, Zachary Van Roy, Gunjan Kak, Бо Лю
article en
8 citations

Abstract

Neurosurgeries complicated by infection are associated with prolonged treatment and significant morbidity. Craniotomy is a common neurosurgical procedure; however, the cellular and molecular signatures associated with craniotomy infection in human subjects are unknown. A retrospective study of over 2,500 craniotomies reveals diverse patient demographics, pathogen identity, and surgical landscapes associated with infection. Leukocyte profiling in patient tissues from craniotomy infection characterizes a predominance of granulocytic myeloid-derived suppressor cells that may arise from transmigrated blood neutrophils, based on single-cell RNA sequencing (scRNA-seq) trajectory analysis. Single-cell transcriptomic analysis identifies metabolic shifts in tissue leukocytes, including a conserved hypoxia-inducible factor (HIF) signature. The importance of HIF signaling was validated using a mouse model of Staphylococcus aureus craniotomy infection, where HIF inhibition increases chemokine production and leukocyte recruitment, exacerbating tissue pathology. These findings establish conserved metabolic and transcriptional signatures that may represent promising future therapeutic targets for human craniotomy infection in the face of increasing antimicrobial resistance.

Cell Reports MedicineVol. 5(11)
Nebraska Medical Center (US), University of Nebraska Medical Center (US)
Patient-Centered Outcomes Research Institute, National Institutes of Health, National Institute of Mental Health, National Institute on Drug Abuse, NIH Office of the Director, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases, National Institute of Neurological Disorders and Stroke
Openalex Percentile: Top 14%
Single-cell and spatial transcriptomics
1.87
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