Deciphering the impact of microbial interactions on COPD exacerbation: An in-depth analysis of the lung microbiome
In microbiome studies, the diversity and types of microbes have been extensively explored; however, the significance of microbial ecology is equally paramount. The comprehension of metabolic interactions among the wide array of microorganisms in the lung microbiota is indispensable for understanding...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-02-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024008065 |
| _version_ | 1797267851589976064 |
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| author | Hamidreza Taherkhani Azadeh KavianFar Sargol Aminnezhad Hossein Lanjanian Ali Ahmadi Sadegh Azimzadeh Ali Masoudi-Nejad |
| author_facet | Hamidreza Taherkhani Azadeh KavianFar Sargol Aminnezhad Hossein Lanjanian Ali Ahmadi Sadegh Azimzadeh Ali Masoudi-Nejad |
| author_sort | Hamidreza Taherkhani |
| collection | DOAJ |
| description | In microbiome studies, the diversity and types of microbes have been extensively explored; however, the significance of microbial ecology is equally paramount. The comprehension of metabolic interactions among the wide array of microorganisms in the lung microbiota is indispensable for understanding chronic pulmonary disease and for the development of potent treatments. In this investigation, metabolic networks were simulated, and ecological theory was employed to assess the diagnosis of COPD, subsequently suggesting innovative treatment strategies for COPD exacerbation. Lung sputum 16S rRNA paired-end data from 112 COPD patients were utilized, and a supervised machine-learning algorithm was applied to identify taxa associated with sex and mortality. Subsequently, an OTU table with Greengenes 99 % dataset was generated. Finally, the interactions between bacterial species were analyzed using a simulated metabolic network. A total of 1781 OTUs and 1740 bacteria at the genus level were identified. We employed an additional dataset to validate our analyses. Notably, among the more abundant genera, Pseudomonas was detected in females, while Lactobacillus was detected in males. Additionally, a decrease in bacterial diversity was observed during COPD exacerbation, and mortality was associated with the high abundance of the Staphylococcus and Pseudomonas genera. Moreover, an increase in Proteobacteria abundance was observed during COPD exacerbations. In contrast, COPD patients exhibited decreased levels of Firmicutes and Bacteroidetes. Significant connections between microbial ecology and bacterial diversity in COPD patients were discovered, highlighting the critical role of microbial ecology in the understanding of COPD. Through the simulation of metabolic interactions among bacteria, the observed dysbiosis in COPD was elucidated. Furthermore, the prominence of anaerobic bacteria in COPD patients was revealed to be influenced by parasitic relationships. These findings have the potential to contribute to improved clinical management strategies for COPD patients. |
| first_indexed | 2024-03-08T03:30:49Z |
| format | Article |
| id | doaj.art-ef449902a8974e9ab46f7bdae00586d3 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-25T01:23:09Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-ef449902a8974e9ab46f7bdae00586d32024-03-09T09:25:12ZengElsevierHeliyon2405-84402024-02-01104e24775Deciphering the impact of microbial interactions on COPD exacerbation: An in-depth analysis of the lung microbiomeHamidreza Taherkhani0Azadeh KavianFar1Sargol Aminnezhad2Hossein Lanjanian3Ali Ahmadi4Sadegh Azimzadeh5Ali Masoudi-Nejad6Laboratory of Systems Biology and Bioinformatics (LBB), Department of Bioinformatics, Kish International Campus, University of Tehran, Kish Island, IranLaboratory of Systems Biology and Bioinformatics (LBB), Department of Bioinformatics, Kish International Campus, University of Tehran, Kish Island, IranLaboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, IranCellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, IranMolecular Biology Research Center, Systems Biology and Poisonings Institute, Tehran, IranChemical Injuries Research Center, Systems Biology and Poisonings Institute, Tehran, IranLaboratory of Systems Biology and Bioinformatics (LBB), Department of Bioinformatics, Kish International Campus, University of Tehran, Kish Island, Iran; Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran; Corresponding author. Laboratory of Systems Biology and Bioinformatics (LBB) Institute of Biochemistry and Biophysics University of Tehran, Tehran, Iran.In microbiome studies, the diversity and types of microbes have been extensively explored; however, the significance of microbial ecology is equally paramount. The comprehension of metabolic interactions among the wide array of microorganisms in the lung microbiota is indispensable for understanding chronic pulmonary disease and for the development of potent treatments. In this investigation, metabolic networks were simulated, and ecological theory was employed to assess the diagnosis of COPD, subsequently suggesting innovative treatment strategies for COPD exacerbation. Lung sputum 16S rRNA paired-end data from 112 COPD patients were utilized, and a supervised machine-learning algorithm was applied to identify taxa associated with sex and mortality. Subsequently, an OTU table with Greengenes 99 % dataset was generated. Finally, the interactions between bacterial species were analyzed using a simulated metabolic network. A total of 1781 OTUs and 1740 bacteria at the genus level were identified. We employed an additional dataset to validate our analyses. Notably, among the more abundant genera, Pseudomonas was detected in females, while Lactobacillus was detected in males. Additionally, a decrease in bacterial diversity was observed during COPD exacerbation, and mortality was associated with the high abundance of the Staphylococcus and Pseudomonas genera. Moreover, an increase in Proteobacteria abundance was observed during COPD exacerbations. In contrast, COPD patients exhibited decreased levels of Firmicutes and Bacteroidetes. Significant connections between microbial ecology and bacterial diversity in COPD patients were discovered, highlighting the critical role of microbial ecology in the understanding of COPD. Through the simulation of metabolic interactions among bacteria, the observed dysbiosis in COPD was elucidated. Furthermore, the prominence of anaerobic bacteria in COPD patients was revealed to be influenced by parasitic relationships. These findings have the potential to contribute to improved clinical management strategies for COPD patients.http://www.sciencedirect.com/science/article/pii/S2405844024008065Metabolic network simulationPathogenic bacteriaLung microbiome16S rRNACOPDMicrobe‒microbe interaction |
| spellingShingle | Hamidreza Taherkhani Azadeh KavianFar Sargol Aminnezhad Hossein Lanjanian Ali Ahmadi Sadegh Azimzadeh Ali Masoudi-Nejad Deciphering the impact of microbial interactions on COPD exacerbation: An in-depth analysis of the lung microbiome Heliyon Metabolic network simulation Pathogenic bacteria Lung microbiome 16S rRNA COPD Microbe‒microbe interaction |
| title | Deciphering the impact of microbial interactions on COPD exacerbation: An in-depth analysis of the lung microbiome |
| title_full | Deciphering the impact of microbial interactions on COPD exacerbation: An in-depth analysis of the lung microbiome |
| title_fullStr | Deciphering the impact of microbial interactions on COPD exacerbation: An in-depth analysis of the lung microbiome |
| title_full_unstemmed | Deciphering the impact of microbial interactions on COPD exacerbation: An in-depth analysis of the lung microbiome |
| title_short | Deciphering the impact of microbial interactions on COPD exacerbation: An in-depth analysis of the lung microbiome |
| title_sort | deciphering the impact of microbial interactions on copd exacerbation an in depth analysis of the lung microbiome |
| topic | Metabolic network simulation Pathogenic bacteria Lung microbiome 16S rRNA COPD Microbe‒microbe interaction |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024008065 |
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