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Identification of Staphylococcus aureus virulence-modulating RNA from transcriptomics data with machine learning

The virulence factors of Staphylococcus aureus are tightly controlled by two-component systems (TCSs) and small RNA (sRNA). TCSs have been well studied over the past several decades, but our understanding of sRNA functions lags far behind that of TCS functions. Here, we studied the biological role o...

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Autores principales: Yu, Jinlong, Li, Mingzhang, Wang, Jin, Hamushan, Musha, Jiang, Feng, Wang, Boyong, Hu, Yujie, Han, Pei, Tang, Jin, Guo, Geyong, Shen, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337500/
https://www.ncbi.nlm.nih.gov/pubmed/37431942
http://dx.doi.org/10.1080/21505594.2023.2228657
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author Yu, Jinlong
Li, Mingzhang
Wang, Jin
Hamushan, Musha
Jiang, Feng
Wang, Boyong
Hu, Yujie
Han, Pei
Tang, Jin
Guo, Geyong
Shen, Hao
author_facet Yu, Jinlong
Li, Mingzhang
Wang, Jin
Hamushan, Musha
Jiang, Feng
Wang, Boyong
Hu, Yujie
Han, Pei
Tang, Jin
Guo, Geyong
Shen, Hao
author_sort Yu, Jinlong
collection PubMed
description The virulence factors of Staphylococcus aureus are tightly controlled by two-component systems (TCSs) and small RNA (sRNA). TCSs have been well studied over the past several decades, but our understanding of sRNA functions lags far behind that of TCS functions. Here, we studied the biological role of sRNA from 506 S. aureus RNA-seq datasets using independent component analysis (ICA). We found that a previously neglected sRNA, Sau-41, functions in the Agr system. Sau-41 is located within the PSMα operon and controlled by the Agr system. It was predicted to share 22-base complementarity with RNAIII, a major regulator of S. aureus virulence. The EMSA results demonstrated that Sau-41 directly binds to RNAIII. Furthermore, our results found that Sau-41 is capable of repressing S. aureus haemolysin activity by downregulating α-haemolysin and δ-toxin. The repression of α-haemolysin was attributed to the competition between the 5’ UTR of hla and Sau-41 for binding RNAIII. We observed that Sau-41 mitigated S. aureus virulence in an orthopaedic implant infection mouse model and alleviated osteolysis. Together, our results indicate that Sau-41 is a virulence-regulating RNA and suggest that Sau-41 might be involved in a negative feedback mechanism to control the Agr system. This work is a demonstration of using ICA in sRNA identification by mining high-throughput data and could be extended to other organisms as well.
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spelling pubmed-103375002023-07-13 Identification of Staphylococcus aureus virulence-modulating RNA from transcriptomics data with machine learning Yu, Jinlong Li, Mingzhang Wang, Jin Hamushan, Musha Jiang, Feng Wang, Boyong Hu, Yujie Han, Pei Tang, Jin Guo, Geyong Shen, Hao Virulence Research Paper The virulence factors of Staphylococcus aureus are tightly controlled by two-component systems (TCSs) and small RNA (sRNA). TCSs have been well studied over the past several decades, but our understanding of sRNA functions lags far behind that of TCS functions. Here, we studied the biological role of sRNA from 506 S. aureus RNA-seq datasets using independent component analysis (ICA). We found that a previously neglected sRNA, Sau-41, functions in the Agr system. Sau-41 is located within the PSMα operon and controlled by the Agr system. It was predicted to share 22-base complementarity with RNAIII, a major regulator of S. aureus virulence. The EMSA results demonstrated that Sau-41 directly binds to RNAIII. Furthermore, our results found that Sau-41 is capable of repressing S. aureus haemolysin activity by downregulating α-haemolysin and δ-toxin. The repression of α-haemolysin was attributed to the competition between the 5’ UTR of hla and Sau-41 for binding RNAIII. We observed that Sau-41 mitigated S. aureus virulence in an orthopaedic implant infection mouse model and alleviated osteolysis. Together, our results indicate that Sau-41 is a virulence-regulating RNA and suggest that Sau-41 might be involved in a negative feedback mechanism to control the Agr system. This work is a demonstration of using ICA in sRNA identification by mining high-throughput data and could be extended to other organisms as well. Taylor & Francis 2023-07-11 /pmc/articles/PMC10337500/ /pubmed/37431942 http://dx.doi.org/10.1080/21505594.2023.2228657 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
spellingShingle Research Paper
Yu, Jinlong
Li, Mingzhang
Wang, Jin
Hamushan, Musha
Jiang, Feng
Wang, Boyong
Hu, Yujie
Han, Pei
Tang, Jin
Guo, Geyong
Shen, Hao
Identification of Staphylococcus aureus virulence-modulating RNA from transcriptomics data with machine learning
title Identification of Staphylococcus aureus virulence-modulating RNA from transcriptomics data with machine learning
title_full Identification of Staphylococcus aureus virulence-modulating RNA from transcriptomics data with machine learning
title_fullStr Identification of Staphylococcus aureus virulence-modulating RNA from transcriptomics data with machine learning
title_full_unstemmed Identification of Staphylococcus aureus virulence-modulating RNA from transcriptomics data with machine learning
title_short Identification of Staphylococcus aureus virulence-modulating RNA from transcriptomics data with machine learning
title_sort identification of staphylococcus aureus virulence-modulating rna from transcriptomics data with machine learning
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337500/
https://www.ncbi.nlm.nih.gov/pubmed/37431942
http://dx.doi.org/10.1080/21505594.2023.2228657
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