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- W4380079419 abstract "ABSTRACT Establishing suitable in vitro culture conditions for microorganisms is crucial for dissecting their biology and potential applications. However, a significant number of bacterial and fungal species, including Pneumocystis jirovecii , remain unculturable, hampering research efforts. Pneumocystis is a deadly pathogen of humans that causes life-threatening pneumonia in immunocompromised individuals and transplant patients. Despite its major impact on human health, we remain ignorant about the pathobiology of this fungus, largely because its experimental dissection is constrained by the inability to culture Pneumocystis in vitro . In this study, we present a comprehensive in silico genome-scale metabolic model of Pneumocystis growth and metabolism, aiming to identify metabolic requirements and imbalances that hinder its growth in vitro. We utilise recently published genome data, available information in the literature as well as bioinformatics and software tools to develop and validate the model. We also employ Flux Balance Analysis and Machine Learning approaches to make important predictions regarding metabolic flux to predict critical components of the Pneumocystis growth medium. Our findings offer insights into the biology of Pneumocystis and provide a novel strategy to overcome the longstanding challenge of culturing this pathogen in vitro ." @default.
- W4380079419 created "2023-06-10" @default.
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- W4380079419 date "2023-06-09" @default.
- W4380079419 modified "2023-09-23" @default.
- W4380079419 title "METABOLIC MODELLING AS A POWERFUL TOOL TO IDENTIFY CRITICAL COMPONENTS OF THE<i>PNEUMOCYSTIS</i>GROWTH MEDIUM" @default.
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- W4380079419 doi "https://doi.org/10.1101/2023.06.07.544035" @default.
- W4380079419 hasPublicationYear "2023" @default.
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