2019年5月13日
This molecular-based approach for determining bacterial fitness facilitates precise and accurate detection of microorganisms using unique genomic DNA barcodes that are quantified via digital PCR. The protocol describes calculating the competitive index for Salmonella strains; however, the technology is readily adaptable to protocols requiring absolute quantification of any genetically-malleable organism.
This technique enables accurate and precise quantification of microorganisms from a mixed population of highly similar strains using rapid and high throughput molecular-based techniques. Ultimately, in enabling comparisons of fitness to be made between strains. The ability to simultaneously assess many strains in a single pool substantially reduces well-to-well or organism-to-organism variability because all strains are exposed to precisely the same conditions.
The adaptability of this technique allows it to be used for nearly any genetically malleable organism and nearly any experimental design that requires accurate quantification of microbes. Begin this procedure with engineering of genetic markers onto bacterial chromosomes, as described in the text protocol. Create a pool of genomic DNA that contains every barcode except for one.
Use this pool as the diluent to perform a dilution series with genomic DNA containing the single remaining barcode. Prepare reactions for digital PCR in duplicate according to the manufacturer's recommendations for using a digital PCR supermix designed for probe-based chemistry. Use the pooled genomic DNA as template DNA.
Also, add the 20 X primer probe Master Mix as described in the text protocol. Prepare replicate control reactions for digital PCR according to the manufacturer's recommendations. Control reactions for each probe mix must consist of No template controls, negative controls, and positive controls.
Repeat these steps to create digital PCR reactions for each barcoded genomic DNA sample. Generate droplets for each reaction condition using a droplet generator, according to the manufacturer's instructions. Transfer newly created droplets into the appropriate 96 well plate.
Use 200 microliter pipette tips on a 5 through 50 microliter multi-channeled pipette. After all the droplets have been generated and transferred, seal the plate with a foil plate sealer. Use the manufacturer recommended thermal cycler to perform the cycling conditions.
While thermocycling is being performed, program the data analysis software with the plate setup information, such as sample name, experiment type, and Supermix used. Also include Target 1 name and Target 1 type, as well as Target 2 name and Target 2 type. After thermocycling is complete, transfer the completed reactions to the droplet reader and start the reading process, according to the manufacturer's instructions.
When all wells have been read and the run is complete, open the QLP data file using the data analysis software. Select all wells that utilize the same primer probe Mastermix. On the Droplets tab, examine the number of droplets analyzed in each well, including both positive and negative droplets.
Exclude from analysis any well that is fewer than 10, 000 total droplets. Move to the 1D Amplitude tab and examine the amplitudes of positive and negative droplets. Ensure they comprise 2 distinct populations.
Within the software, use the thresholding feature to make a cutoff between positive and negative droplets for each probe that was utilized. Once appropriate thresholds have been applied to all wells, the software will calculate the number of DNA copies in each reaction. Export data to a spreadsheet to facilitate further analysis.
Using these values, calculate the initial copy number of each unique genomic barcode in the sample. Determine the mean false positive rate from the negative control reactions and subtract this value from the values obtained in experimental reactions. Multiply the values as necessary, based on the dilutions that were performed when setting up each experiment.
Now, determine the relative fitness of an organism by calculating the competitive index or canceled out competitive index from digital PCR-based quantification of the barcoded strain. Perform this step for each barcoded strain at all time points. Genomic DNA containing the AA barcode was diluted in a background of all other barcoded genomic DNA.
Channel 1 represents the FAM probe for the AA barcode, while Channel 2 represents the HEX probe for the AO barcode. Results of each probe are presented as both individual droplet fluorescent amplitude and a histogram representing the frequency of fluorescent intensity of all droplets in the selected wells. For each condition, positive and negative droplets should form 2 distinct populations.
The populations should be separated using the thresholds feature to define positive and negative droplets. Threshold values will vary depending on the probes that were used, but all wells that utilize the same probe mix should have identical thresholds. In the case of AA that was diluted, the histogram appears to only depict the single population because positive droplets are substantially outnumbered by negative droplets.
However, 2 distinct populations are still visible by examining droplet fluorescent amplitude in the left panels. As the AA barcoded genomic DNA was diluted, there was a decrease in positive droplets, while the number of positive AO droplets remains constant. Once appropriate thresholds have been applied to all wells the software will calculate the number of DNA copies in each reaction.
If you routinely perform PCR as part of your research, you can perform this technique to assess the fitness of your model organism. This procedure would normally be used to determine end results of upstream experiments. Its true utility is to promote ease and versatility for any experiments that rely on bacterial quantification.
We are using this technique to assess salmonella fitness in a murine model of infection. Additionally, this technique is being adapted for use with other pathogenic microorganisms in our laboratory.
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这种基于分子的方法利用基因组DNA条形码,能够对具有相似菌株的混合群体中的微生物进行准确定量。该方案有助于比较不同菌株之间的适应性,并可适用于多种遗传上可操作的生物体。
这种基于数字PCR的竞争性指数方法通过在单次竞争性实验中实现高通量、同时定量多种菌株,解决了细菌适应性评估中的一个关键瓶颈问题。该方法减少了孔间变异,并消除了对表型标记的依赖,从而提高了在靶点验证和先导化合物筛选工作流程中的预测可信度。其在遗传可操作生物体中的广泛适用性,支持从发现阶段到临床前去风险化过程的转化连续性。
该方法适用于从发现到临床前研究的连续流程,可在菌株改造后、先导化合物优化前进行适应性评估,尤其适用于抗菌和毒力靶点的验证。