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In vitro and ex vivo systems at the forefront of infection modeling and drug discovery.


ABSTRACT: Bacterial infections and antibiotic resistant bacteria have become a growing problem over the past decade. As a result, the Centers for Disease Control predict more deaths resulting from microorganisms than all cancers combined by 2050. Currently, many traditional models used to study bacterial infections fail to precisely replicate the in vivo bacterial environment. These models often fail to incorporate fluid flow, bio-mechanical cues, intercellular interactions, host-bacteria interactions, and even the simple inclusion of relevant physiological proteins in culture media. As a result of these inadequate models, there is often a poor correlation between in vitro and in vivo assays, limiting therapeutic potential. Thus, the urgency to establish in vitro and ex vivo systems to investigate the mechanisms underlying bacterial infections and to discover new-age therapeutics against bacterial infections is dire. In this review, we present an update of current in vitro and ex vivo models that are comprehensively changing the landscape of traditional microbiology assays. Further, we provide a comparative analysis of previous research on various established organ-disease models. Lastly, we provide insight on future techniques that may more accurately test new formulations to meet the growing demand of antibiotic resistant bacterial infections.

SUBMITTER: Shi D 

PROVIDER: S-EPMC7172914 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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In vitro and ex vivo systems at the forefront of infection modeling and drug discovery.

Shi Di D   Mi Gujie G   Wang Mian M   Webster Thomas J TJ  

Biomaterials 20181024


Bacterial infections and antibiotic resistant bacteria have become a growing problem over the past decade. As a result, the Centers for Disease Control predict more deaths resulting from microorganisms than all cancers combined by 2050. Currently, many traditional models used to study bacterial infections fail to precisely replicate the in vivo bacterial environment. These models often fail to incorporate fluid flow, bio-mechanical cues, intercellular interactions, host-bacteria interactions, an  ...[more]

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