Background: Controlling pulmonary infections is critical for increasing quality of life and life expectancy of people with cystic fibrosis (CF). According to the Cystic Fibrosis Foundation 2018 Annual Report, respiratory/cardiorespiratory or transplant-related causes account for over 75% of CF patient mortality. Microbial infections are a major contributor to declines in lung function, and Pseudomonas aeruginosa is particularly notorious for being both highly virulent and difficult to eradicate. These infections are difficult to treat in part due to the evolution of diverse strains within the P. aeruginosapopulation, so it is critical to understand how this diversity first arises to improve eradication rates. We hypothesize that the evolution of P. aeruginosa population heterogeneity during chronic CF infections can be precisely defined, targeted, and altered to improve clinical outcomes.
Methods: We emphasize the need to understand the rules that govern early evolution dynamics, as eradication therapies are most likely to be successful in the time period that precedes the rise of multiple mutations in a single lineage. To do this, better tools are needed for tracking the fates of individual cells, especially at early time points. Toward that goal, we have developed an innovative, Tn7-based genomic barcoding technique that we have successfully implemented in Pseudomonas aeruginosa, producing a library of >105 barcodes that allows for single-cell resolution of intraspecies population demography over time.
Results: Our technology allows for single-cell resolution of intraspecies population demography over time. This method is high-throughput, requires a small sample volume comprised of whole cells, supports frequent sampling of continuous cultures, and allows many samples to be multiplexed into a single next-generation sequencing run, saving time and money while allowing for single-cell lineage tracking. With this method we can measure the rise and coexistence of certain lineages that progressively eliminate diversity as they outcompete others. This barcoding method is also readily adapted for use in many other CF-relevant organisms.
Conclusions: Genomic barcoding is a valuable tool for assessing early evolutionary dynamics as intraspecies diversity arises. This technology also holds promise for conducting complex competition assays that seamlessly incorporate intraspecies and interspecies diversity in the same test tube, bringing us one step closer to recapitulating the complexities of microbial communities. Our chromosomal barcoding method is a versatile and practical platform for understanding early evolution dynamics, and this work furnishes the field with a valuable new tool for the study of microbial diversity and demography.
