Artikel ; Online: A novel flow cytometry assay based on bacteriophage-derived proteins for Staphylococcus detection in blood
Scientific Reports, Vol 10, Iss 1, Pp 1-
2020 Band 13
Abstract: Abstract Bloodstream infections (BSIs) are considered a major cause of death worldwide. Staphylococcus spp. are one of the most BSIs prevalent bacteria, classified as high priority due to the increasing multidrug resistant strains. Thus, a fast, specific ...
| Abstract | Abstract Bloodstream infections (BSIs) are considered a major cause of death worldwide. Staphylococcus spp. are one of the most BSIs prevalent bacteria, classified as high priority due to the increasing multidrug resistant strains. Thus, a fast, specific and sensitive method for detection of these pathogens is of extreme importance. In this study, we have designed a novel assay for detection of Staphylococcus in blood culture samples, which combines the advantages of a phage endolysin cell wall binding domain (CBD) as a specific probe with the accuracy and high-throughput of flow cytometry techniques. In order to select the biorecognition molecule, three different truncations of the C-terminus of Staphylococcus phage endolysin E-LM12, namely the amidase (AMI), SH3 and amidase+SH3 (AMI_SH3) were cloned fused with a green fluorescent protein. From these, a higher binding efficiency to Staphylococcus cells was observed for AMI_SH3, indicating that the amidase domain possibly contributes to a more efficient binding of the SH3 domain. The novel phage endolysin-based flow cytometry assay provided highly reliable and specific detection of 1–5 CFU of Staphylococcus in 10 mL of spiked blood, after 16 hours of enrichment culture. Overall, the method developed herein presents advantages over the standard BSIs diagnostic methods, potentially contributing to an early and effective treatment of BSIs. |
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| Schlagwörter | Medicine ; R ; Science ; Q |
| Thema/Rubrik (Code) | 500 |
| Sprache | Englisch |
| Erscheinungsdatum | 2020-04-01T00:00:00Z |
| Verlag | Nature Publishing Group |
| Dokumenttyp | Artikel ; Online |
| Datenquelle | BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl) |
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