# In vitro PCLS models of Pneumocystis

> **NIH NIH R21** · TULANE UNIVERSITY OF LOUISIANA · 2024 · $228,198

## Abstract

Pneumocystis pneumonia remains the number one cause of fungal pneumonia in infancy and is
a common infection in immunocompromised individuals. Research in the field has been
hampered by the inability to culture this fungus leading to a delay in obtaining
genomic/transcriptomic information on fungal life cycle, mechanisms of fungal attachment as
well as a lack of in vitro antibiotic susceptibility. When placed in media, Pneumocystis murina
dies within hours. However we have preliminary data that with P. murina is placed in culture
lung tissue form precision cut lung slices (PCLS) that both the troph and ascus can survive up to
14 days. Moreover, we have observed evidence of fungal biofilms in this model. Additional
preliminary data shows that this model can be used for in vitro antibiotic susceptibility. Thus the
goal of this proposal is to refine this model and test submerged versus air liquid interface model
to optimize fungal attachment, survival, and growth. Additionally we will investigate if this model
can be used for antibiotic susceptibility testing with both folate metabolism antagonists as well
as echinocandins. Furthermore, we will investigate of this model can be used to assess
macrophage mediated killing as well as the role of both mannan and β-glucan recognition
receptors in this process.

## Key facts

- **NIH application ID:** 10992856
- **Project number:** 1R21AI182432-01A1
- **Recipient organization:** TULANE UNIVERSITY OF LOUISIANA
- **Principal Investigator:** JAY K KOLLS
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $228,198
- **Award type:** 1
- **Project period:** 2024-06-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10992856

## Citation

> US National Institutes of Health, RePORTER application 10992856, In vitro PCLS models of Pneumocystis (1R21AI182432-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10992856. Licensed CC0.

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