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Mapping the genetic landscape of biomineralization in Magnetospirillum magneticum AMB-1 with RB-Tnseq

H. C. McCausland, K. M. Wetmore, A. P. Arkin, A. Komeili

Abstract

Magnetotactic bacteria (MTB) are a phylogenetically diverse group of bacteria remarkable for their ability to biomineralize magnetite (Fe3O4) or greigite (Fe3S4) in organelles called magnetosomes. The majority of genes required for magnetosome formation are encoded by a magnetosome gene island (MAI). Most previous genetic studies in MTB have focused on the MAI, using screens to identify key MAI genes or targeted genetics to isolate specific genes and their function in one specific growth condition. Here, we conducted random barcoded transposon mutagenesis (RB-TnSeq) in Magnetospirillum magneticum AMB-1 to identify the global genetic requirements for magnetosome formation under different growth conditions. We generated a library of 184,710 unique strains in a wild-type background, generating ~34 mutant strains for each gene. RB-TnSeq also allowed us to determine the essential gene set of AMB-1 under standard laboratory growth conditions. To pinpoint novel genes that are important for magnetosome formation, we subjected the library to magnetic selection screens in varied growth conditions. We compared biomineralization in standard growth conditions to biomineralization in high iron and anaerobic conditions, respectively. Strains with transposon insertions in the MAI gene mamT had an exacerbated biomineralization defect under both high iron and anerobic conditions compared to standard conditions, adding to our knowledge of the role of MamT in magnetosome formation. Mutants in amb4151, a gene outside of the MAI, are more magnetic than wild-type cells under anaerobic conditions. All three of these phenotypes were validated by creating a markerless deletion strain of the gene and evaluating with TEM imaging. Overall, our results indicate that growth conditions affect which genes are required for biomineralization and that some MAI genes may have more nuanced functions than was previously understood.

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