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Bo Hu
Sun Yat-Sen University
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Introduction: The host response to bacterial sepsis is reported to be nonspecific regardless of the causative pathogen. However, newer paradigms indicated that host response of Gram-negative sepsis may be different from Gram-positive sepsis and the difference has not been clearly clarified. The current study aimed to explore the difference by identifying the differential gene sets using genome-wide technique.
Methods: The training dataset GSE6535 and the validation dataset GSE13015 were used for bioinformatics analysis. The distinct gene sets of sepsis with different infections were screened using Gene set variation analysis (GSVA) and Gene set enrichment analysis (GSEA). The intersection gene sets based on the two algorithms were confirmed through Venn analysis. Finally, the common gene sets between GSE6535 and GSE13015 were determined by GSVA.
Results: Two immunologic gene sets in GSE6535 were identified based on GSVA, which could be used to discriminate sepsis caused by Gram-positive, Gram-negative or mixed infection. A total of 19 gene sets were obtained in GSE6535 through Venn analysis, revealed the heterogeneity of sepsis between gram-negative bacteria and gram-positive bacteria at the molecular level. The result was also verified by analysis the validation set GSE13015, 31 gene sets were identified by GSVA and GSEA. Furthermore, 10 common differential gene sets were finally confirmed based on GSVA for dataset GSE6535 and GSE13015.
Conclusions: Our data indicated that host response may differ dramatically depending on the inciting organism. The findings offer new insight to investigate the pathophysiology of bacterial sepsis.
Keywords
sepsis, gene sets, Gram-positive, Gram-negative, microarray analysis
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A new preprint design is coming!
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Bo Hu
Sun Yat-Sen University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
View the published article at Frontiers in Cellular and Infection Microbiology.
Version 1
Posted 05 Apr, 2021
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Critical Care & Emergency Medicine
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Frontiers in Cellular and Infection Microbiology.
Introduction: The host response to bacterial sepsis is reported to be nonspecific regardless of the causative pathogen. However, newer paradigms indicated that host response of Gram-negative sepsis may be different from Gram-positive sepsis and the difference has not been clearly clarified. The current study aimed to explore the difference by identifying the differential gene sets using genome-wide technique.
Methods: The training dataset GSE6535 and the validation dataset GSE13015 were used for bioinformatics analysis. The distinct gene sets of sepsis with different infections were screened using Gene set variation analysis (GSVA) and Gene set enrichment analysis (GSEA). The intersection gene sets based on the two algorithms were confirmed through Venn analysis. Finally, the common gene sets between GSE6535 and GSE13015 were determined by GSVA.
Results: Two immunologic gene sets in GSE6535 were identified based on GSVA, which could be used to discriminate sepsis caused by Gram-positive, Gram-negative or mixed infection. A total of 19 gene sets were obtained in GSE6535 through Venn analysis, revealed the heterogeneity of sepsis between gram-negative bacteria and gram-positive bacteria at the molecular level. The result was also verified by analysis the validation set GSE13015, 31 gene sets were identified by GSVA and GSEA. Furthermore, 10 common differential gene sets were finally confirmed based on GSVA for dataset GSE6535 and GSE13015.
Conclusions: Our data indicated that host response may differ dramatically depending on the inciting organism. The findings offer new insight to investigate the pathophysiology of bacterial sepsis.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
This is a list of supplementary files associated with this preprint. Click to download.
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