Biology subjects

Deutschbauer, A. M.

Publications and source records attributed to Deutschbauer, A. M..

56 records · Page 4Linked to original sources

bioRxiv2017

Magic pools: parallel assessment of transposon delivery vectors in bacteria

Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach for discovering the functions of bacterial genes. However, the development of a suitable TnSeq strategy for a given bacterium can be costly and time-consuming. To meet this challenge, we describe a parts-based strategy for constructing libraries of hundreds of transposon delivery vectors, which we term \"magic pools\". Within a magic pool, each transposon vector has a different combination of promoters and antibiotic resistance markers as well as a random DNA barcode sequence, which allows the tracking of each vector during mutagenesis experiments. To identify an efficient vector for a given bacterium, we mutagenize it with a magic pool and sequence the resulting insertions; we then use the best vector to generate a large mutant library. We used the magic pool strategy to construct transposon mutant libraries in five genera of bacteria, including three genera of the phylum Bacteroidetes.

genomics↗

bioRxiv2016

Validating Regulatory Predictions from Diverse Bacteria with Mutant Fitness Data

Although transcriptional regulation is fundamental to understanding bacterial physiology, the targets of most bacterial transcription factors are not known. Comparative genomics has been used to identify likely targets of some of these transcription factors, but these predictions typically lack experimental support. Here, we used mutant fitness data, which measures the importance of each gene for a bacteriums growth across many conditions, to validate regulatory predictions from RegPrecise, a curated collection of comparative genomics predictions. Because characterized transcription factors often have correlated fitness with one of their targets (either positively or negatively), correlated fitness patterns provide support for the comparative genomics predictions. At a false discovery rate of 3%, we identified significant cofitness for at least one target of 158 TFs in 107 ortholog groups and from 24 bacteria. Thus, high-throughput genetics can be used to identify a high-confidence subset of the sequence-based regulatory predictions.

microbiology↗