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

Overview of attention for article published in Frontiers in Cellular and Infection Microbiology, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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Title
High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts
Published in
Frontiers in Cellular and Infection Microbiology, February 2018
DOI 10.3389/fcimb.2018.00043
Pubmed ID
Authors

Stefanie Hoffmann, Steffi Walter, Anne-Kathrin Blume, Stephan Fuchs, Christiane Schmidt, Annemarie Scholz, Roman G. Gerlach

Abstract

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 organismSalmonella entericasv. 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 differentS. Typhimurium mutants. Furthermore, we demonstrated the use of VCC to test the inhibition ofSalmonellainvasion by the probioticE. colistrain Nissle 1917. Taken together, VCC provides a flexible, label-free, automation-compatible methodology to quantify bacteria inin vitroinfection assays.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 20%
Student > Ph. D. Student 7 15%
Student > Master 5 11%
Professor > Associate Professor 4 9%
Student > Doctoral Student 3 7%
Other 8 17%
Unknown 10 22%
Readers by discipline Count As %
Immunology and Microbiology 9 20%
Biochemistry, Genetics and Molecular Biology 9 20%
Agricultural and Biological Sciences 7 15%
Veterinary Science and Veterinary Medicine 2 4%
Computer Science 2 4%
Other 8 17%
Unknown 9 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 December 2018.
All research outputs
#5,363,181
of 25,295,968 outputs
Outputs from Frontiers in Cellular and Infection Microbiology
#1,137
of 7,987 outputs
Outputs of similar age
#120,423
of 487,135 outputs
Outputs of similar age from Frontiers in Cellular and Infection Microbiology
#31
of 128 outputs
Altmetric has tracked 25,295,968 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,987 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 487,135 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 128 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.