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

Front Cell Infect Microbiol. 2018 Feb 15:8:43. doi: 10.3389/fcimb.2018.00043. eCollection 2018.

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 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.

Keywords: Salmonella; adhesion; bacterial quantification; cell culture infection model; gentamicin protection assay; intracellular replication; invasion; virtual colony count.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Bacterial Infections / diagnosis*
  • Bacterial Infections / microbiology*
  • Cell Line
  • Cells, Cultured
  • Colony Count, Microbial*
  • High-Throughput Screening Assays*
  • Host-Pathogen Interactions*
  • Humans
  • Macrophages / microbiology
  • Mice
  • Mutation
  • Probiotics
  • Salmonella / genetics