Method of Assessing Bacterial Viability on Low Biomass Environments

Method of Assessing Bacterial Viability on Low Biomass Environments

Princeton Docket # 22-3843

 

Researchers in the Department of Molecular Biology, Princeton University have developed a novel method of assessing bacterial community viability. This highly reliable and accurate method allows for the assessment of extremely low biomass samples, which cannot be done with traditional methods such as qPCR. Using the commercially-available small molecule propidium monoazide (PMA), together with droplet digital PCR (PMA-ddPCR), this method  allows for very accurate quantification of DNA even at very low abundances. Comparing DNA abundance in untreated samples to DNA abundance in PMA-treated samples allows one to calculate the overall viability of bacteria in any given sample. Additionally, combining PMA with 16S rRNA gene amplicon sequencing allows for a species-level understanding of the viable (and nonviable) components of any complex bacterial community. This is especially important for low biomass environments such as the skin microbiome, where viable bacterial cells are underrepresented using traditional sequencing. These novel applications of PMA have the potential to expand our understanding of all types of bacterial communities, including the human microbiome.

 

Applications:

 

  • Assessment of the viability of complex bacterial communities of low- and high-abundance including the human microbiome (gut, skin, oral, nasal, etc.) and microbiomes of built surfaces.

 

 

Advantages       

  • Assessment of bacterial-level viability
  • Understanding of overall viability of a bacterial  community
  • Highly reliable and accurate

 

Intellectual Property & Development Status

 

Patent protection is pending.

 

The researchers have used PMA-ddPCR and PMA-seq extensively to assess the viability of various human and mouse microbiomes, and the results are highly repeatable. We have also tested PMA-ddPCR against known ratios of viable and nonviable cells, which demonstrated that this technique results in accurate assessment of bacterial population viability. Furthermore, we have used pure bacterial cultures to demonstrate that DNA quantification with PMA-ddPCR is highly correlated to culturable CFU (colony forming units). These experiments indicate that PMA-ddPCR is both accurate and reliable. We have performed PMA-seq on human microbiome samples and were able to track changes in species-level viability, which allowed us to also assess changes in population diversity.

 

Princeton is currently seeking commercial partners for the further development and commercialization of this opportunity.

 

Publications

 

bioRxiv preprint doi: https://doi.org/10.1101/2021.08.16.455933; this version posted August 16, 2021.

 

 

The Inventors

 

Zemer Gitai is the Edwin Grant Conklin Professor of Biology in Department of Molecular Biology. His research focuses on the cell biology of bacteria.  His lab studies how cells self-organize across spatial scales, using quantitative, molecular, and engineering approaches.  His work discovered new components of the bacterial cytoskeleton, new functions for bacterial polymers in metabolism, compartmentalization, and chromosome dynamics, and established the importance of protein assembly for unexpected processes like metabolism and pathogenesis.  Prof. Gitai's achievements have been recognized by many prestigious awards, including the NIH New Innovator Award, the Beckman Young Investigator Award, and the HFSP Young Investigator Award.

 

 

Ellen M Acosta is a graduate student in the Gitai Lab. Her research focuses on using imaging and molecular techniques to investigate the bacteria of the skin microbiome. She is an NJ ACTS Clinical and Translational Science Fellow. She is involved with the Department of Molecular Biology Diversity and Inclusion Committee and is an instructor for the Prison Teaching Initiative.

 

Contact:

 

Laurie Tzodikov

Princeton University Office of Technology Licensing

(609) 258-7256 • tzodikov@princeton.edu

 

 

 

Patent Information: