Unknown

Dataset Information

0

Optimizing a reliable ex vivo human blood model to analyze expression of Staphylococcus epidermidis genes.


ABSTRACT: Human blood is often used as an ex vivo model to mimic the environment encountered by pathogens inside the host. A significant variety of experimental conditions has been reported. However, optimization strategies are often not described. This study aimed to evaluate key parameters that are expected to influence Staphylococcus epidermidis gene expression when using human blood ex vivo models. Our data confirmed that blood antimicrobial activity was dependent on initial bacterial concentration. Furthermore, blood degradation over time resulted in lower antimicrobial activity, with a 2% loss of leukocytes viability correlating with a 5-fold loss of antimicrobial activity against S. epidermidis. We further demonstrated that the volume of human blood could be reduced to as little as 0.18 mL without affecting the stability of gene expression of the tested genes. Overall, the data described herein highlight experimental parameters that should be considered when using a human blood ex vivo model for S. epidermidis gene expression analysis.

SUBMITTER: Bras S 

PROVIDER: S-EPMC7301895 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

altmetric image

Publications

Optimizing a reliable ex vivo human blood model to analyze expression of <i>Staphylococcus epidermidis</i> genes.

Brás Susana S   França Ângela    Cerca Nuno N  

PeerJ 20200615


Human blood is often used as an ex vivo model to mimic the environment encountered by pathogens inside the host. A significant variety of experimental conditions has been reported. However, optimization strategies are often not described. This study aimed to evaluate key parameters that are expected to influence <i>Staphylococcus epidermidis</i> gene expression when using human blood ex vivo models. Our data confirmed that blood antimicrobial activity was dependent on initial bacterial concentra  ...[more]

Similar Datasets

| S-EPMC10537848 | biostudies-literature
| S-EPMC4591658 | biostudies-literature
| S-EPMC3958685 | biostudies-literature
| S-EPMC10130157 | biostudies-literature
2014-08-29 | GSE52111 | GEO
| S-EPMC9954615 | biostudies-literature
| S-EPMC5038083 | biostudies-other
2014-08-29 | E-GEOD-52111 | biostudies-arrayexpress
| S-EPMC177688 | biostudies-other
2014-12-12 | E-GEOD-64071 | biostudies-arrayexpress