Gene Expression Dynamics Induced by Ciprofloxacin and Loss of LexA Function in Pseudomonas aeruginosa PAO1 Using Data Mining and Network Analysis
Pseudomonas aeruginosa is an opportunistic pathogen that causes a variety of infections in humans and frequently develops mechanisms of resistance to antibiotics, which makes its treatment difficult. In this study we applied gene expression analysis using data mining techniques and network anal...
| Main Authors: | , , |
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| Format: | Otro |
| Language: | Inglés |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8464130 https://hdl.handle.net/10669/82197 |
| Summary: | Pseudomonas aeruginosa is an opportunistic
pathogen that causes a variety of infections in humans and
frequently develops mechanisms of resistance to antibiotics, which
makes its treatment difficult. In this study we applied gene
expression analysis using data mining techniques and network
analysis to evaluate the temporal effects of exposure to
ciprofloxacin and the changes caused by the loss of function of
LexA, a regulator of the SOS response to the cellular stress.
Initially, global differential expression profiles using clustering
algorithms suggested that the effects of antibiotic exposure were
determined primarily by time and not by loss of LexA function.
This was verified by performing attribute selection and
differential expression analysis among conditions, where less than
3.3% of maximum difference between strains but up to 21% of
differences were observed over time. Together with network
analysis, a significant increase in topological metrics was
determined when evaluating temporal changes. Functional
annotation showed metabolic pathways enriched over time but not
when comparing strains. Overall, the results obtained revealed
that the response to ciprofloxacin tends to be exacerbated over
time and that it remains stable in the face of the loss of function of
LexA activity. |
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