Novel in vivo mouse model of implant related spine infection

植入物相关脊柱感染的新型体内小鼠模型

阅读:7
作者:Eric M Dworsky, Vishal Hegde, Amanda H Loftin, Sherif Richman, Yan Hu, Elizabeth Lord, Kevin P Francis, Lloyd S Miller, Jeff C Wang, Anthony Scaduto, Nicholas M Bernthal

Abstract

Post-operative spine infections are a challenge, as hardware must often be retained to prevent destabilization of the spine, and bacteria form biofilm on implants, rendering them inaccessible to antibiotic therapy, and immune cells. A model of posterior-approach spinal surgery was created in which a stainless steel k-wire was transfixed into the L4 spinous process of 12-week-old C57BL/six mice. Mice were then randomized to receive either one of three concentrations (1 × 102 , 1 × 103 , and 1 × 104 colony forming units (CFU)) of a bioluminescent strain of Staphylococcus aureus or normal saline at surgery. The mice were then longitudinally imaged for bacterial bioluminescence to quantify infection. The 1 × 102 CFU group had a decrease in signal down to control levels by POD 25, while the 1 × 103 and 1 × 104 CFU groups maintained a 10-fold higher signal through POD 35. Bacteria were then harvested from the pin and surrounding tissue for confirmatory CFU counts. All mice in the 1 × 104 CFU group experienced wound breakdown, while no mice in the other groups had this complication. Once an optimal bacterial concentration was determined, mice expressing enhanced green fluorescent protein in their myeloid cells (Lys-EGFP) were utilized to contemporaneously quantify bacterial burden, and immune response. Neutrophil fluorescence peaked for both groups on POD 3, and then declined. The infected group continued to have a response above the control group through POD 35. This study, establishes a noninvasive in vivo mouse model of spine implant infection that can quantify bacterial burden and host inflammation longitudinally in real time without requiring animal sacrifice. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:193-199, 2017.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。