An innovative, interdisciplinary platform for the dissection of Pneumocystis, a deadly fungal pathogen of humans

Lead Research Organisation: UNIVERSITY OF EXETER
Department Name: Biosciences

Abstract

The goal of my research project is to enable a vital breakthrough in the study of a major fungal pathogen of humans. Pneumocystis kills hundreds of thousands of people each year, and yet only a few groups are studying this pathogen because, currently, it is not possible to culture it in vitro independently of its host. My goal is to release this major experimental bottleneck by developing, for the first time, in vitro culture methods for Pneumocystis. I will address this using a powerful combination of in silico metabolic modelling and experimental phenotyping. The potential benefits of my project are vast. In addition to providing major insights into the co-evolution of Pneumocystis pathogens with their mammalian hosts, my project will empower the research community, leading, in the longer-term, to dramatic advances in Pneumocystis biology and therapy.

Technical Summary

Pneumocystis jirovecii is an opportunistic pathogen causing life-threatening pneumonia in immunocompromised patients and it colonizes the lungs of healthy infants. The worldwide incidence of Pneumocystis pneumonia exceeds 400,000 cases per year with mortality rates of 20 - 80%. This is a serious problem for developing countries where the population of HIV-infected individuals is over 6 times that in developed countries.
Challenge: The inability to culture Pneumocystis in vitro despite 3 decades of research makes this pathogen uniquely difficult to study. Diagnosis and treatment of Pneumocystis infections has relied primarily on microscopic detection in respiratory specimens. The lack of in vitro culture methods has been recognized as the major obstacle in Pneumocystis research.
Recent genome sequencing has identified a potential explanation for the inability to culture Pneumocystis: it has an extremely reduced genome that lacks essential metabolic pathways. This has prevented growth independently of its mammalian host. Pneumocystis has developed unique dependencies on the host for nutrients as well as highly efficient strategies to evade the host's innate and acquired immune defences. Thus, intimate host-fungus cross-interactions are essential for growth of the pathogen, and simple supplementation of growth media to overcome predicted auxotrophic requirements has not been sufficient to solve the problem.
Principal hypothesis: The metabolic issue is more subtle: the pathogen also relies on the host to maintain redox and/or energy homeostasis.
Innovative approach to resolve this issue: I will develop an in silico metabolic model of Pneumocystis growth and metabolism based on new genomic data.
Outcomes: This work will release a critical bottleneck in Pneumocystis research, and provide major insights into the co-evolution of Pneumocystis pathogens with their mammalian hosts.
 
Description Ken Haynes Travel Bursary
Amount £500 (GBP)
Organisation University of Exeter 
Sector Academic/University
Country United Kingdom
Start 09/2022 
End 10/2022
 
Description MRC CMM Travel Grant
Amount £400 (GBP)
Organisation University of Exeter 
Sector Academic/University
Country United Kingdom
Start 02/2022 
End 03/2022
 
Description Sub-Saharan African Development Fund
Amount £5,000 (GBP)
Organisation University of Exeter 
Sector Academic/University
Country United Kingdom
Start 03/2023 
End 07/2023
 
Title Mathematical model on Pneumocystis metabolism 
Description As part of the collaboration with Gencovery, I have been beta-testing new, confidential software being developed by Gencovery for metabolic modelling. An access to this new software has helped me to develop a mathematical model on Pneumocystis metabolism. 
Type Of Material Computer model/algorithm 
Year Produced 2021 
Provided To Others? No  
Impact Mathematical model on Pneumocystis metabolism allowed us to make predictions regarding the medium conditions favourable for in vitro growth of the pathogen. 
 
Description Collaboration with Cape Town University 
Organisation University of Cape Town
Country South Africa 
Sector Academic/University 
PI Contribution We have provided unique insights into the metabolism of Pneumocystis predicted by the metabolic model we developed.
Collaborator Contribution University of Cape Town provides me with the requisite training in Pneumocystis laboratory and molecular biology - essential skills that I have to develop to execute the project.
Impact University of Cape Town has provided me with the requisite training in Pneumocystis laboratory and molecular biology as well as has helped me to set up the experiments that are essential for my project.
Start Year 2021
 
Description Collaboration with Gencovery on metabolic modelling 
Organisation Gencovery
Country France 
Sector Private 
PI Contribution We have provided unique insights into the biology of Pneumocystis that are essential for our collaborative metabolic modelling, which aims to improve human health worldwide.
Collaborator Contribution Gencovery provides me with the requisite training in bioinformatics, metabolic modelling, and flux balance analysis - essential skills that I have to develop to execute the project.
Impact Gencovery has provided me with essential training in bioinformatics and metabolic modelling, which has resulted in: 1. A reviewed and refined genome annotation of the Pneumocystis murina genome 2. A reconstructed network on Pneumocystis murina metabolism 3. A developed mathematical model on Pneumocystis murina metabolism 4. Predictions regarding the culture medium conditions favourable for Pneumocystis murina growth in vitro
Start Year 2020
 
Description Collaboration with Imperial College London 
Organisation Imperial College London
Country United Kingdom 
Sector Academic/University 
PI Contribution We initiated this collaboration and are providing samples of spent Pneumocystis growth medium for metabolomic analysis at Imperial College London.
Collaborator Contribution Imperial College London is going to perform metabolomics analysis of the Pneumocystis growth samples we are providing, which will enhance our understanding of Pneumocystis nutrient uptake.
Impact No outputs or outcomes impact yet
Start Year 2023
 
Description Collaboration with Liverpool University 
Organisation University of Liverpool
Country United Kingdom 
Sector Academic/University 
PI Contribution We initiated this collaboration and are providing datasets generated by our Pneumocystis modelling.
Collaborator Contribution Liverpool University is developing a machine learning approach to optimize our metabolic modelling predictions.
Impact A machine learning approach developed by Liverpool University helped to optimize our metabolic model's predictions.
Start Year 2022
 
Description Collaboration with Tulane University on Pneumocystis 
Organisation Tulane University
Country United States 
Sector Academic/University 
PI Contribution A unique opportunity to work on the project which aims to improve human health worldwide has been provided.
Collaborator Contribution RNA-Seq data has kindly been provided by my partner at Tulane, which contributed to my process of reviewing and refining the genome annotation for Pneumocystis murina
Impact RNA-Seq data has been provided, which contributed to the process of reviewing and refining the genome annotation for Pneumocystis murina.
Start Year 2020