The <named-content content-type="genus-species">Staphylococcus aureus</named-content> Transcriptome during Cystic Fibrosis Lung Infection

ABSTRACT Laboratory models have been invaluable for the field of microbiology for over 100 years and have provided key insights into core aspects of bacterial physiology such as regulation and metabolism. However, it is important to identify the extent to which these models recapitulate bacterial ph...

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Autores principales:	Carolyn B. Ibberson, Marvin Whiteley
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2019
Materias:	Staphylococcus aureus RNA-seq transcriptomics machine learning virulence cystic fibrosis Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/e1982324aba342a087a3752d694ff0c3
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spelling	oai:doaj.org-article:e1982324aba342a087a3752d694ff0c32021-11-15T15:54:47ZThe <named-content content-type="genus-species">Staphylococcus aureus</named-content> Transcriptome during Cystic Fibrosis Lung Infection10.1128/mBio.02774-192150-7511https://doaj.org/article/e1982324aba342a087a3752d694ff0c32019-12-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mBio.02774-19https://doaj.org/toc/2150-7511ABSTRACT Laboratory models have been invaluable for the field of microbiology for over 100 years and have provided key insights into core aspects of bacterial physiology such as regulation and metabolism. However, it is important to identify the extent to which these models recapitulate bacterial physiology within a human infection environment. Here, we performed transcriptomics (RNA-seq), focusing on the physiology of the prominent pathogen Staphylococcus aureus in situ in human cystic fibrosis (CF) infection. Through principal-component and hierarchal clustering analyses, we found remarkable conservation in S. aureus gene expression in the CF lung despite differences in the patient clinic, clinical status, age, and therapeutic regimen. We used a machine learning approach to identify an S. aureus transcriptomic signature of 32 genes that can reliably distinguish between S. aureus transcriptomes in the CF lung and in vitro. The majority of these genes were involved in virulence and metabolism and were used to improve a common CF infection model. Collectively, these results advance our knowledge of S. aureus physiology during human CF lung infection and demonstrate how in vitro models can be improved to better capture bacterial physiology in infection. IMPORTANCE Although bacteria have been studied in infection for over 100 years, the majority of these studies have utilized laboratory and animal models that often have unknown relevance to the human infections they are meant to represent. A primary challenge has been to assess bacterial physiology in the human host. To address this challenge, we performed transcriptomics of S. aureus during human cystic fibrosis (CF) lung infection. Using a machine learning framework, we defined a “human CF lung transcriptome signature” that primarily included genes involved in metabolism and virulence. In addition, we were able to apply our findings to improve an in vitro model of CF infection. Understanding bacterial gene expression within human infection is a critical step toward the development of improved laboratory models and new therapeutics.Carolyn B. IbbersonMarvin WhiteleyAmerican Society for MicrobiologyarticleStaphylococcus aureusRNA-seqtranscriptomicsmachine learningvirulencecystic fibrosisMicrobiologyQR1-502ENmBio, Vol 10, Iss 6 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Staphylococcus aureus RNA-seq transcriptomics machine learning virulence cystic fibrosis Microbiology QR1-502
spellingShingle	Staphylococcus aureus RNA-seq transcriptomics machine learning virulence cystic fibrosis Microbiology QR1-502 Carolyn B. Ibberson Marvin Whiteley The <named-content content-type="genus-species">Staphylococcus aureus</named-content> Transcriptome during Cystic Fibrosis Lung Infection
description	ABSTRACT Laboratory models have been invaluable for the field of microbiology for over 100 years and have provided key insights into core aspects of bacterial physiology such as regulation and metabolism. However, it is important to identify the extent to which these models recapitulate bacterial physiology within a human infection environment. Here, we performed transcriptomics (RNA-seq), focusing on the physiology of the prominent pathogen Staphylococcus aureus in situ in human cystic fibrosis (CF) infection. Through principal-component and hierarchal clustering analyses, we found remarkable conservation in S. aureus gene expression in the CF lung despite differences in the patient clinic, clinical status, age, and therapeutic regimen. We used a machine learning approach to identify an S. aureus transcriptomic signature of 32 genes that can reliably distinguish between S. aureus transcriptomes in the CF lung and in vitro. The majority of these genes were involved in virulence and metabolism and were used to improve a common CF infection model. Collectively, these results advance our knowledge of S. aureus physiology during human CF lung infection and demonstrate how in vitro models can be improved to better capture bacterial physiology in infection. IMPORTANCE Although bacteria have been studied in infection for over 100 years, the majority of these studies have utilized laboratory and animal models that often have unknown relevance to the human infections they are meant to represent. A primary challenge has been to assess bacterial physiology in the human host. To address this challenge, we performed transcriptomics of S. aureus during human cystic fibrosis (CF) lung infection. Using a machine learning framework, we defined a “human CF lung transcriptome signature” that primarily included genes involved in metabolism and virulence. In addition, we were able to apply our findings to improve an in vitro model of CF infection. Understanding bacterial gene expression within human infection is a critical step toward the development of improved laboratory models and new therapeutics.
format	article
author	Carolyn B. Ibberson Marvin Whiteley
author_facet	Carolyn B. Ibberson Marvin Whiteley
author_sort	Carolyn B. Ibberson
title	The <named-content content-type="genus-species">Staphylococcus aureus</named-content> Transcriptome during Cystic Fibrosis Lung Infection
title_short	The <named-content content-type="genus-species">Staphylococcus aureus</named-content> Transcriptome during Cystic Fibrosis Lung Infection
title_full	The <named-content content-type="genus-species">Staphylococcus aureus</named-content> Transcriptome during Cystic Fibrosis Lung Infection
title_fullStr	The <named-content content-type="genus-species">Staphylococcus aureus</named-content> Transcriptome during Cystic Fibrosis Lung Infection
title_full_unstemmed	The <named-content content-type="genus-species">Staphylococcus aureus</named-content> Transcriptome during Cystic Fibrosis Lung Infection
title_sort	<named-content content-type="genus-species">staphylococcus aureus</named-content> transcriptome during cystic fibrosis lung infection
publisher	American Society for Microbiology
publishDate	2019
url	https://doaj.org/article/e1982324aba342a087a3752d694ff0c3
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The <named-content content-type="genus-species">Staphylococcus aureus</named-content> Transcriptome during Cystic Fibrosis Lung Infection

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