Transcriptome Mining to Identify Molecular Markers for the Diagnosis of <i>Staphylococcus epidermidis</i> Bloodstream Infections
Bloodstream infections caused by <i>Staphylococcus epidermidis</i> are often misdiagnosed since no diagnostic marker found so far can unequivocally discriminate “true” infection from sample contamination. While attempts have been made to find genomic and/or phenotypic differences between...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Antibiotics |
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| Online Access: | https://www.mdpi.com/2079-6382/11/11/1596 |
| _version_ | 1797466119841251328 |
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| author | Susana Brás Angela França |
| author_facet | Susana Brás Angela França |
| author_sort | Susana Brás |
| collection | DOAJ |
| description | Bloodstream infections caused by <i>Staphylococcus epidermidis</i> are often misdiagnosed since no diagnostic marker found so far can unequivocally discriminate “true” infection from sample contamination. While attempts have been made to find genomic and/or phenotypic differences between invasive and commensal isolates, possible changes in the transcriptome of these isolates under in vivo-mimicking conditions have not been investigated. Herein, we characterized the transcriptome, by RNA sequencing, of three clinical and three commensal isolates after 2 h of exposure to whole human blood. Bioinformatics analysis was used to rank the genes with the highest potential to distinguish invasive from commensal isolates and among the ten genes identified as candidates, the gene <i>SERP2441</i> showed the highest potential. A collection of 56 clinical and commensal isolates was then used to validate, by quantitative PCR, the discriminative power of the selected genes. A significant variation was observed among isolates, and the discriminative power of the selected genes was lost, undermining their potential use as markers. Nevertheless, future studies should include an RNA sequencing characterization of a larger collection of isolates, as well as a wider range of conditions to increase the chances of finding further candidate markers for the diagnosis of bloodstream infections caused by <i>S. epidermidis</i>. |
| first_indexed | 2024-03-09T18:31:17Z |
| format | Article |
| id | doaj.art-746afece34494326b3db73342a5f9ba7 |
| institution | Directory Open Access Journal |
| issn | 2079-6382 |
| language | English |
| last_indexed | 2024-03-09T18:31:17Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Antibiotics |
| spelling | doaj.art-746afece34494326b3db73342a5f9ba72023-11-24T07:30:22ZengMDPI AGAntibiotics2079-63822022-11-011111159610.3390/antibiotics11111596Transcriptome Mining to Identify Molecular Markers for the Diagnosis of <i>Staphylococcus epidermidis</i> Bloodstream InfectionsSusana Brás0Angela França1LIBRO—Laboratório de Investigação em Biofilmes Rosário Oliveira, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, PortugalLIBRO—Laboratório de Investigação em Biofilmes Rosário Oliveira, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, PortugalBloodstream infections caused by <i>Staphylococcus epidermidis</i> are often misdiagnosed since no diagnostic marker found so far can unequivocally discriminate “true” infection from sample contamination. While attempts have been made to find genomic and/or phenotypic differences between invasive and commensal isolates, possible changes in the transcriptome of these isolates under in vivo-mimicking conditions have not been investigated. Herein, we characterized the transcriptome, by RNA sequencing, of three clinical and three commensal isolates after 2 h of exposure to whole human blood. Bioinformatics analysis was used to rank the genes with the highest potential to distinguish invasive from commensal isolates and among the ten genes identified as candidates, the gene <i>SERP2441</i> showed the highest potential. A collection of 56 clinical and commensal isolates was then used to validate, by quantitative PCR, the discriminative power of the selected genes. A significant variation was observed among isolates, and the discriminative power of the selected genes was lost, undermining their potential use as markers. Nevertheless, future studies should include an RNA sequencing characterization of a larger collection of isolates, as well as a wider range of conditions to increase the chances of finding further candidate markers for the diagnosis of bloodstream infections caused by <i>S. epidermidis</i>.https://www.mdpi.com/2079-6382/11/11/1596bloodstream infection diagnosiscommensal isolatesclinical isolatesex vivo human blood modelRNA sequencingmolecular diagnosis markers |
| spellingShingle | Susana Brás Angela França Transcriptome Mining to Identify Molecular Markers for the Diagnosis of <i>Staphylococcus epidermidis</i> Bloodstream Infections Antibiotics bloodstream infection diagnosis commensal isolates clinical isolates ex vivo human blood model RNA sequencing molecular diagnosis markers |
| title | Transcriptome Mining to Identify Molecular Markers for the Diagnosis of <i>Staphylococcus epidermidis</i> Bloodstream Infections |
| title_full | Transcriptome Mining to Identify Molecular Markers for the Diagnosis of <i>Staphylococcus epidermidis</i> Bloodstream Infections |
| title_fullStr | Transcriptome Mining to Identify Molecular Markers for the Diagnosis of <i>Staphylococcus epidermidis</i> Bloodstream Infections |
| title_full_unstemmed | Transcriptome Mining to Identify Molecular Markers for the Diagnosis of <i>Staphylococcus epidermidis</i> Bloodstream Infections |
| title_short | Transcriptome Mining to Identify Molecular Markers for the Diagnosis of <i>Staphylococcus epidermidis</i> Bloodstream Infections |
| title_sort | transcriptome mining to identify molecular markers for the diagnosis of i staphylococcus epidermidis i bloodstream infections |
| topic | bloodstream infection diagnosis commensal isolates clinical isolates ex vivo human blood model RNA sequencing molecular diagnosis markers |
| url | https://www.mdpi.com/2079-6382/11/11/1596 |
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