Dataset Information

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

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.

SUBMITTER: Hoffmann S

PROVIDER: S-EPMC5818393 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Hoffmann Stefanie S Walter Steffi S Blume Anne-Kathrin AK Fuchs Stephan S Schmidt Christiane C Scholz Annemarie A Gerlach Roman G RG

Frontiers in cellular and infection microbiology 20180215

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 ...[more]

PMID: 29497603

Similar Datasets

Project description:In this work, we used our recently developed method Spec-seq to characterize the binding specificity of Glucocorticoid receptor in vitro. This GR Spec-seq experiment has been run twice separately (Dec 2014 and Mar 2015) with different library compositions. The basic workflow is the same as our previous work for lac repressor published in Genetics 198.3 (2014): 1329-1343. Recombinant human GR protein was used to facilitate in vitro DNA-binding and separation experiments. Bound and Unbound DNA fragments were separated in EMSA gels, purified, barcoded for further Illumina sequencing. An initial experiment was performed using the putative consensus sequence: AGAACA GGG TGTTCT; randomized library 1: AGAACN NSN NGTTCT [diversity =512]; randomized library 2: AGAANN GGG NNNTCT [diversity = 1024]; randomized library 3: AGAACA GGG TGNNNN [diversity =256]; randomized library 4: AGAACA GGGC NNNTCT [diversity = 64]. The initial total library diversity was ~1853 with a library composition of 10% positive control sequence + randomized libraries 1-4 + 5% negative control sequence. A 5th library containing 2304 sequences based on DDNACW KKN KGTTCT, where D="not C", N="any base", W="A or T" and K="G or T" was subsequently prepared and analyzed using similar ratios of control sequences. Binding conditions for EMSA were 100ng FAM-labelled dsDNA+ 0/0.5/1/2/4uM GR DBD protein for each lane, 1X NEB buffer 4. GR DBD was prepared as previously described. The EMSA was performed using a 9% 33:1 acrylamide gel and TB buffer, and was run at 200V for 30mins @ 0 degrees C. The 2uM protein lane used for final sequencing. Bound/unbound fractions resulting from EMSA of these libraries and conditions were used to generate PWMs as described. The GR PWM that was generated through this analysis was used to define relative binding energies using the patser program (35), which can be accessed online at (http://stormo.wustl.edu/consensus/cgi-bin/Server/Interface/patser.cgi ). Derived binding affinities are proportional to the inverse of the natural log of the calculated energies.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets