Construction and characterization of a genome-scale ordered mutant collection of Bacteroides thetaiotaomicron

构建和表征全基因组规模的拟杆菌有序突变体集合

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作者:Heidi A Arjes #, Jiawei Sun #, Hualan Liu, Taylor H Nguyen, Rebecca N Culver, Arianna I Celis, Sophie Jean Walton, Kimberly S Vasquez, Feiqiao Brian Yu, Katherine S Xue, Daniel Newton, Ricardo Zermeno, Meredith Weglarz, Adam Deutschbauer, Kerwyn Casey Huang, Anthony L Shiver

Background

Ordered transposon-insertion collections, in which specific transposon-insertion mutants are stored as monocultures in a genome-scale collection, represent a promising tool for genetic dissection of human gut microbiota members. However, publicly available collections are scarce and the construction methodology remains in early stages of development.

Conclusion

We expect that utilization of this ordered collection will accelerate research into B. theta physiology and that lessons learned while assembling the collection will inform future efforts to assemble ordered mutant collections for an increasing number of gut microbiota members.

Results

Here, we describe the assembly of a genome-scale ordered collection of transposon-insertion mutants in the model gut anaerobe Bacteroides thetaiotaomicron VPI-5482 that we created as a resource for the research community. We used flow cytometry to sort single cells from a pooled library, located mutants within this initial progenitor collection by applying a pooling strategy with barcode sequencing, and re-arrayed specific mutants to create a condensed collection with single-insertion strains covering >2500 genes. To demonstrate the potential of the condensed collection for phenotypic screening, we analyzed growth dynamics and cell morphology. We identified both growth defects and altered cell shape in mutants disrupting sphingolipid synthesis and thiamine scavenging. Finally, we analyzed the process of assembling the B. theta condensed collection to identify inefficiencies that limited coverage. We demonstrate as part of this analysis that the process of assembling an ordered collection can be accurately modeled using barcode sequencing data.

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