Publicação
Analysis of gene expression variability in Staphylococcus epidermidis biofilms
| Resumo: | S. epidermidis is the most frequently bacteria isolated from human epithelia, and for a long time, it has been regarded as an innocuous commensal bacterium. However, currently, this bacteria persist as a major cause of hospital and community-acquired infections. It is primarily associated with infections of indwelling medical devices, by the formation of a structure called a biofilm. The biofilms can quickly adapt to new conditions and consequently, can result in the appearance of infections, that are resistance to many antibiotics and mechanisms of the host immune defense. So, it is crucial to study gene expression and their influence in biofilm formation. In gene expression studies, there are three fundamental experimental steps which have some variability: RNA extraction, reverse-transcriptase reaction and quantitative polymerase chain reaction (qPCR). However, since biofilms are very heterogeneous communities, often gene expression studies reveal a high variability. The objective of this work was to demonstrate and understand the influence in the variability of gene expression quantification, by the individual experimental steps required for gene expression quantification, namely bacterial growth, RNA extraction, reverse transcriptase and real-time quantitative PCR. We tested the biofilm formation and the presence of key genes in several strains of S. epidermidis in order to select the strains to be used in the gene expression studies. Our results demonstrated that biologic variability was the step which more influence gene expression quantification. Additionally, we proposed an optimized protocol to enhance gene expression reproducibility in S. epidermidis biofilms and our results were favorable since we reduced the biologic variability with a pool of 20 biofilms, as determined by the quantification of gene expression in two independent strains. |
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| Autores principais: | Sousa, Cármen |
| Ano: | 2014 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | S. epidermidis is the most frequently bacteria isolated from human epithelia, and for a long time, it has been regarded as an innocuous commensal bacterium. However, currently, this bacteria persist as a major cause of hospital and community-acquired infections. It is primarily associated with infections of indwelling medical devices, by the formation of a structure called a biofilm. The biofilms can quickly adapt to new conditions and consequently, can result in the appearance of infections, that are resistance to many antibiotics and mechanisms of the host immune defense. So, it is crucial to study gene expression and their influence in biofilm formation. In gene expression studies, there are three fundamental experimental steps which have some variability: RNA extraction, reverse-transcriptase reaction and quantitative polymerase chain reaction (qPCR). However, since biofilms are very heterogeneous communities, often gene expression studies reveal a high variability. The objective of this work was to demonstrate and understand the influence in the variability of gene expression quantification, by the individual experimental steps required for gene expression quantification, namely bacterial growth, RNA extraction, reverse transcriptase and real-time quantitative PCR. We tested the biofilm formation and the presence of key genes in several strains of S. epidermidis in order to select the strains to be used in the gene expression studies. Our results demonstrated that biologic variability was the step which more influence gene expression quantification. Additionally, we proposed an optimized protocol to enhance gene expression reproducibility in S. epidermidis biofilms and our results were favorable since we reduced the biologic variability with a pool of 20 biofilms, as determined by the quantification of gene expression in two independent strains. |
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