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High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts

The quantification of bacteria in cell culture infection models is of paramount importance for the characterization of host-pathogen interactions and pathogenicity factors involved. The standard to enumerate bacteria in these assays is plating of a dilution series on solid agar and counting of the r...

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Autores principales: Hoffmann, Stefanie, Walter, Steffi, Blume, Anne-Kathrin, Fuchs, Stephan, Schmidt, Christiane, Scholz, Annemarie, Gerlach, Roman G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5818393/
https://www.ncbi.nlm.nih.gov/pubmed/29497603
http://dx.doi.org/10.3389/fcimb.2018.00043
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author Hoffmann, Stefanie
Walter, Steffi
Blume, Anne-Kathrin
Fuchs, Stephan
Schmidt, Christiane
Scholz, Annemarie
Gerlach, Roman G.
author_facet Hoffmann, Stefanie
Walter, Steffi
Blume, Anne-Kathrin
Fuchs, Stephan
Schmidt, Christiane
Scholz, Annemarie
Gerlach, Roman G.
author_sort Hoffmann, Stefanie
collection PubMed
description The quantification of bacteria in cell culture infection models is of paramount importance for the characterization of host-pathogen interactions and pathogenicity factors involved. The standard to enumerate bacteria in these assays is plating of a dilution series on solid agar and counting of the resulting colony forming units (CFU). In contrast, the virtual colony count (VCC) method is a high-throughput compatible alternative with minimized manual input. Based on the recording of quantitative growth kinetics, VCC relates the time to reach a given absorbance threshold to the initial cell count using a series of calibration curves. Here, we adapted the VCC method using the model organism Salmonella enterica sv. Typhimurium (S. Typhimurium) in combination with established cell culture-based infection models. For HeLa infections, a direct side-by-side comparison showed a good correlation of VCC with CFU counting after plating. For MDCK cells and RAW macrophages we found that VCC reproduced the expected phenotypes of different S. Typhimurium mutants. Furthermore, we demonstrated the use of VCC to test the inhibition of Salmonella invasion by the probiotic E. coli strain Nissle 1917. Taken together, VCC provides a flexible, label-free, automation-compatible methodology to quantify bacteria in in vitro infection assays.
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spelling pubmed-58183932018-03-01 High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts Hoffmann, Stefanie Walter, Steffi Blume, Anne-Kathrin Fuchs, Stephan Schmidt, Christiane Scholz, Annemarie Gerlach, Roman G. Front Cell Infect Microbiol Microbiology The quantification of bacteria in cell culture infection models is of paramount importance for the characterization of host-pathogen interactions and pathogenicity factors involved. The standard to enumerate bacteria in these assays is plating of a dilution series on solid agar and counting of the resulting colony forming units (CFU). In contrast, the virtual colony count (VCC) method is a high-throughput compatible alternative with minimized manual input. Based on the recording of quantitative growth kinetics, VCC relates the time to reach a given absorbance threshold to the initial cell count using a series of calibration curves. Here, we adapted the VCC method using the model organism Salmonella enterica sv. Typhimurium (S. Typhimurium) in combination with established cell culture-based infection models. For HeLa infections, a direct side-by-side comparison showed a good correlation of VCC with CFU counting after plating. For MDCK cells and RAW macrophages we found that VCC reproduced the expected phenotypes of different S. Typhimurium mutants. Furthermore, we demonstrated the use of VCC to test the inhibition of Salmonella invasion by the probiotic E. coli strain Nissle 1917. Taken together, VCC provides a flexible, label-free, automation-compatible methodology to quantify bacteria in in vitro infection assays. Frontiers Media S.A. 2018-02-15 /pmc/articles/PMC5818393/ /pubmed/29497603 http://dx.doi.org/10.3389/fcimb.2018.00043 Text en Copyright © 2018 Hoffmann, Walter, Blume, Fuchs, Schmidt, Scholz and Gerlach. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Hoffmann, Stefanie
Walter, Steffi
Blume, Anne-Kathrin
Fuchs, Stephan
Schmidt, Christiane
Scholz, Annemarie
Gerlach, Roman G.
High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts
title High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts
title_full High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts
title_fullStr High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts
title_full_unstemmed High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts
title_short High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts
title_sort high-throughput quantification of bacterial-cell interactions using virtual colony counts
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5818393/
https://www.ncbi.nlm.nih.gov/pubmed/29497603
http://dx.doi.org/10.3389/fcimb.2018.00043
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