Co-PATHOgenex web application for assessing complex stress responses in pathogenic bacteria

ABSTRACT Pathogenic bacteria encounter various stressors while residing in the host. They respond through intricate mechanisms of gene expression regulation, ensuring their survival and adaptation. Understanding how bacteria adapt to different stress conditions through regulatory processes of specif...

Full description

Bibliographic Details
Main Authors: Leyden Fernandez, Martin Rosvall, Johan Normark, Maria Fällman, Kemal Avican
Format: Article
Language:English
Published: American Society for Microbiology 2024-01-01
Series:Microbiology Spectrum
Subjects:
Online Access:https://journals.asm.org/doi/10.1128/spectrum.02781-23
_version_ 1797357386580623360
author Leyden Fernandez
Martin Rosvall
Johan Normark
Maria Fällman
Kemal Avican
author_facet Leyden Fernandez
Martin Rosvall
Johan Normark
Maria Fällman
Kemal Avican
author_sort Leyden Fernandez
collection DOAJ
description ABSTRACT Pathogenic bacteria encounter various stressors while residing in the host. They respond through intricate mechanisms of gene expression regulation, ensuring their survival and adaptation. Understanding how bacteria adapt to different stress conditions through regulatory processes of specific genes requires exploring complex transcriptional responses using gene co-expression networks. We employed a large transcriptome data set comprising 32 diverse human bacterial pathogens exposed to the same 11 host-mimicking stress conditions. Using the weighted gene co-expression network analysis algorithm, we generated bacterial gene co-expression networks. By associating modular eigengene expression with specific stress conditions, we identified gene co-expression modules and stress-specific stimulons, including genes with unique expression patterns under specific stress conditions. Suggesting a new potential role of the frm operon in responding to bile stress in enteropathogenic bacteria demonstrates the effectiveness of our approach. We also revealed the regulation of streptolysin S genes, involved in the production, processing, and export of streptolysin S, a toxin responsible for the β-hemolytic phenotype of group A Streptococcus. In a comparative analysis of stress responses in three Escherichia coli strains from the core transcriptome, we revealed shared and unique expression patterns across the strains, offering insights into convergent and divergent stress responses. To help researchers perform similar analyses, we created the user-friendly web application Co-PATHOgenex. This tool aids in deepening our understanding of bacterial adaptation to stress conditions and in deciphering complex transcriptional responses of bacterial pathogens. IMPORTANCE Unveiling gene co-expression networks in bacterial pathogens has the potential for gaining insights into their adaptive strategies within the host environment. Here, we developed Co-PATHOgenex, an interactive and user-friendly web application that enables users to construct networks from gene co-expressions using custom-defined thresholds (https://avicanlab.shinyapps.io/copathogenex/). The incorporated search functions and visualizations within the tool simplify the usage and facilitate the interpretation of the analysis output. Co-PATHOgenex also includes stress stimulons for various bacterial species, which can help identify gene products not previously associated with a particular stress condition.
first_indexed 2024-03-08T14:44:22Z
format Article
id doaj.art-d51a681ce4da4b11b1688db65932140a
institution Directory Open Access Journal
issn 2165-0497
language English
last_indexed 2024-03-08T14:44:22Z
publishDate 2024-01-01
publisher American Society for Microbiology
record_format Article
series Microbiology Spectrum
spelling doaj.art-d51a681ce4da4b11b1688db65932140a2024-01-11T14:04:37ZengAmerican Society for MicrobiologyMicrobiology Spectrum2165-04972024-01-0112110.1128/spectrum.02781-23Co-PATHOgenex web application for assessing complex stress responses in pathogenic bacteriaLeyden Fernandez0Martin Rosvall1Johan Normark2Maria Fällman3Kemal Avican4Department of Molecular Biology, Umeå Centre for Microbial Research (UCMR), Umeå University , Umeå, SwedenDepartment of Physics, Integrated Science Lab (Icelab), Umeå University , Umeå, SwedenDepartment of Molecular Biology, Laboratory for Molecular Infection Medicine Sweden (MIMS), Umeå University , Umeå, SwedenDepartment of Molecular Biology, Umeå Centre for Microbial Research (UCMR), Umeå University , Umeå, SwedenDepartment of Molecular Biology, Umeå Centre for Microbial Research (UCMR), Umeå University , Umeå, SwedenABSTRACT Pathogenic bacteria encounter various stressors while residing in the host. They respond through intricate mechanisms of gene expression regulation, ensuring their survival and adaptation. Understanding how bacteria adapt to different stress conditions through regulatory processes of specific genes requires exploring complex transcriptional responses using gene co-expression networks. We employed a large transcriptome data set comprising 32 diverse human bacterial pathogens exposed to the same 11 host-mimicking stress conditions. Using the weighted gene co-expression network analysis algorithm, we generated bacterial gene co-expression networks. By associating modular eigengene expression with specific stress conditions, we identified gene co-expression modules and stress-specific stimulons, including genes with unique expression patterns under specific stress conditions. Suggesting a new potential role of the frm operon in responding to bile stress in enteropathogenic bacteria demonstrates the effectiveness of our approach. We also revealed the regulation of streptolysin S genes, involved in the production, processing, and export of streptolysin S, a toxin responsible for the β-hemolytic phenotype of group A Streptococcus. In a comparative analysis of stress responses in three Escherichia coli strains from the core transcriptome, we revealed shared and unique expression patterns across the strains, offering insights into convergent and divergent stress responses. To help researchers perform similar analyses, we created the user-friendly web application Co-PATHOgenex. This tool aids in deepening our understanding of bacterial adaptation to stress conditions and in deciphering complex transcriptional responses of bacterial pathogens. IMPORTANCE Unveiling gene co-expression networks in bacterial pathogens has the potential for gaining insights into their adaptive strategies within the host environment. Here, we developed Co-PATHOgenex, an interactive and user-friendly web application that enables users to construct networks from gene co-expressions using custom-defined thresholds (https://avicanlab.shinyapps.io/copathogenex/). The incorporated search functions and visualizations within the tool simplify the usage and facilitate the interpretation of the analysis output. Co-PATHOgenex also includes stress stimulons for various bacterial species, which can help identify gene products not previously associated with a particular stress condition.https://journals.asm.org/doi/10.1128/spectrum.02781-23stress responsesbacterial pathogensgene co-expressionstimulongene regulationRNA-seq
spellingShingle Leyden Fernandez
Martin Rosvall
Johan Normark
Maria Fällman
Kemal Avican
Co-PATHOgenex web application for assessing complex stress responses in pathogenic bacteria
Microbiology Spectrum
stress responses
bacterial pathogens
gene co-expression
stimulon
gene regulation
RNA-seq
title Co-PATHOgenex web application for assessing complex stress responses in pathogenic bacteria
title_full Co-PATHOgenex web application for assessing complex stress responses in pathogenic bacteria
title_fullStr Co-PATHOgenex web application for assessing complex stress responses in pathogenic bacteria
title_full_unstemmed Co-PATHOgenex web application for assessing complex stress responses in pathogenic bacteria
title_short Co-PATHOgenex web application for assessing complex stress responses in pathogenic bacteria
title_sort co pathogenex web application for assessing complex stress responses in pathogenic bacteria
topic stress responses
bacterial pathogens
gene co-expression
stimulon
gene regulation
RNA-seq
url https://journals.asm.org/doi/10.1128/spectrum.02781-23
work_keys_str_mv AT leydenfernandez copathogenexwebapplicationforassessingcomplexstressresponsesinpathogenicbacteria
AT martinrosvall copathogenexwebapplicationforassessingcomplexstressresponsesinpathogenicbacteria
AT johannormark copathogenexwebapplicationforassessingcomplexstressresponsesinpathogenicbacteria
AT mariafallman copathogenexwebapplicationforassessingcomplexstressresponsesinpathogenicbacteria
AT kemalavican copathogenexwebapplicationforassessingcomplexstressresponsesinpathogenicbacteria