Quantitative Framework for Model Evaluation in Microbiology Research Using <italic toggle="yes">Pseudomonas aeruginosa</italic> and Cystic Fibrosis Infection as a Test Case

ABSTRACT Laboratory models are a cornerstone of modern microbiology, but the accuracy of these models has not been systematically evaluated. As a result, researchers often choose models based on intuition or incomplete data. We propose a general quantitative framework to assess model accuracy from R...

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Autores principales:	Daniel M. Cornforth, Frances L. Diggle, Jeffrey A. Melvin, Jennifer M. Bomberger, Marvin Whiteley
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2020
Materias:	Pseudomonas aeruginosa model transcriptomics cystic fibrosis infection Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/fc699cfcf8404da5a9ed7966015b5d96
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spelling	oai:doaj.org-article:fc699cfcf8404da5a9ed7966015b5d962021-11-15T15:56:58ZQuantitative Framework for Model Evaluation in Microbiology Research Using <italic toggle="yes">Pseudomonas aeruginosa</italic> and Cystic Fibrosis Infection as a Test Case10.1128/mBio.03042-192150-7511https://doaj.org/article/fc699cfcf8404da5a9ed7966015b5d962020-02-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mBio.03042-19https://doaj.org/toc/2150-7511ABSTRACT Laboratory models are a cornerstone of modern microbiology, but the accuracy of these models has not been systematically evaluated. As a result, researchers often choose models based on intuition or incomplete data. We propose a general quantitative framework to assess model accuracy from RNA sequencing data and use this framework to evaluate models of Pseudomonas aeruginosa cystic fibrosis (CF) lung infection. We found that an in vitro synthetic CF sputum medium model and a CF airway epithelial cell model had the highest genome-wide accuracy but underperformed on distinct functional categories, including porins and polyamine biosynthesis for the synthetic sputum medium and protein synthesis for the epithelial cell model. We identified 211 “elusive” genes that were not mimicked in a reference strain grown in any laboratory model but found that many were captured by using a clinical isolate. These methods provide researchers with an evidence-based foundation to select and improve laboratory models. IMPORTANCE Laboratory models have become a cornerstone of modern microbiology. However, the accuracy of even the most commonly used models has never been evaluated. Here, we propose a quantitative framework based on gene expression data to evaluate model performance and apply it to models of Pseudomonas aeruginosa cystic fibrosis lung infection. We discovered that these models captured different aspects of P. aeruginosa infection physiology, and we identify which functional categories are and are not captured by each model. These methods will provide researchers with a solid basis to choose among laboratory models depending on the scientific question of interest and will help improve existing experimental models.Daniel M. CornforthFrances L. DiggleJeffrey A. MelvinJennifer M. BombergerMarvin WhiteleyAmerican Society for MicrobiologyarticlePseudomonas aeruginosamodeltranscriptomicscystic fibrosisinfectionMicrobiologyQR1-502ENmBio, Vol 11, Iss 1 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Pseudomonas aeruginosa model transcriptomics cystic fibrosis infection Microbiology QR1-502
spellingShingle	Pseudomonas aeruginosa model transcriptomics cystic fibrosis infection Microbiology QR1-502 Daniel M. Cornforth Frances L. Diggle Jeffrey A. Melvin Jennifer M. Bomberger Marvin Whiteley Quantitative Framework for Model Evaluation in Microbiology Research Using <italic toggle="yes">Pseudomonas aeruginosa</italic> and Cystic Fibrosis Infection as a Test Case
description	ABSTRACT Laboratory models are a cornerstone of modern microbiology, but the accuracy of these models has not been systematically evaluated. As a result, researchers often choose models based on intuition or incomplete data. We propose a general quantitative framework to assess model accuracy from RNA sequencing data and use this framework to evaluate models of Pseudomonas aeruginosa cystic fibrosis (CF) lung infection. We found that an in vitro synthetic CF sputum medium model and a CF airway epithelial cell model had the highest genome-wide accuracy but underperformed on distinct functional categories, including porins and polyamine biosynthesis for the synthetic sputum medium and protein synthesis for the epithelial cell model. We identified 211 “elusive” genes that were not mimicked in a reference strain grown in any laboratory model but found that many were captured by using a clinical isolate. These methods provide researchers with an evidence-based foundation to select and improve laboratory models. IMPORTANCE Laboratory models have become a cornerstone of modern microbiology. However, the accuracy of even the most commonly used models has never been evaluated. Here, we propose a quantitative framework based on gene expression data to evaluate model performance and apply it to models of Pseudomonas aeruginosa cystic fibrosis lung infection. We discovered that these models captured different aspects of P. aeruginosa infection physiology, and we identify which functional categories are and are not captured by each model. These methods will provide researchers with a solid basis to choose among laboratory models depending on the scientific question of interest and will help improve existing experimental models.
format	article
author	Daniel M. Cornforth Frances L. Diggle Jeffrey A. Melvin Jennifer M. Bomberger Marvin Whiteley
author_facet	Daniel M. Cornforth Frances L. Diggle Jeffrey A. Melvin Jennifer M. Bomberger Marvin Whiteley
author_sort	Daniel M. Cornforth
title	Quantitative Framework for Model Evaluation in Microbiology Research Using <italic toggle="yes">Pseudomonas aeruginosa</italic> and Cystic Fibrosis Infection as a Test Case
title_short	Quantitative Framework for Model Evaluation in Microbiology Research Using <italic toggle="yes">Pseudomonas aeruginosa</italic> and Cystic Fibrosis Infection as a Test Case
title_full	Quantitative Framework for Model Evaluation in Microbiology Research Using <italic toggle="yes">Pseudomonas aeruginosa</italic> and Cystic Fibrosis Infection as a Test Case
title_fullStr	Quantitative Framework for Model Evaluation in Microbiology Research Using <italic toggle="yes">Pseudomonas aeruginosa</italic> and Cystic Fibrosis Infection as a Test Case
title_full_unstemmed	Quantitative Framework for Model Evaluation in Microbiology Research Using <italic toggle="yes">Pseudomonas aeruginosa</italic> and Cystic Fibrosis Infection as a Test Case
title_sort	quantitative framework for model evaluation in microbiology research using <italic toggle="yes">pseudomonas aeruginosa</italic> and cystic fibrosis infection as a test case
publisher	American Society for Microbiology
publishDate	2020
url	https://doaj.org/article/fc699cfcf8404da5a9ed7966015b5d96
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Quantitative Framework for Model Evaluation in Microbiology Research Using <italic toggle="yes">Pseudomonas aeruginosa</italic> and Cystic Fibrosis Infection as a Test Case

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