An RNA-Seq framework for profiling target selectivity and physiological effects of antisense peptide nucleic acids (PNAs)

Antisense peptide nucleic acids (PNAs) inhibiting mRNAs of essential genes provide a straight-forward way to repurpose our knowledge of bacterial regulatory RNAs for development of programmable species-specific antibiotics. While there is ample proof of PNA efficacy, their target selectivity and impact on bacterial physiology are poorly understood. Moreover, while antibacterial PNAs are typically designed to block mRNA translation, effects on target mRNA levels are not well-investigated.

Researchers from the University of Würzburg and the Helmholtz Institute for RNA-based Infection Research pioneer the use of global RNA-seq analysis to decipher PNA activity in a transcriptome-wide manner. They found that PNA-based antisense oligomer conjugates robustly decrease mRNA levels of the widely-used target gene, acpP, in Salmonella enterica, with limited off-target effects. Systematic analysis of several different PNA-carrier peptides attached not only shows different bactericidal efficiency, but also activation of stress pathways. In particular, KFF-, RXR- and Tat-PNA conjugates especially induce the PhoP/Q response, whereas the latter two additionally trigger several distinct pathways. The researchers show that constitutive activation of the PhoP/Q response can lead to Tat-PNA resistance, illustrating the utility of RNA-seq for understanding PNA antibacterial activity. In sum, this study establishes an experimental framework for the design and assessment of PNA antimicrobials in the long-term quest to use these for precision editing of microbiota.

Transcriptomic profiling of Salmonella in response to treatment with peptide–PNA conjugates

Transcriptomic profiling of Salmonella in response to treatment with peptide–PNA conjugates. (A) Experimental workflow showing the different conditions used for the analyses. ‘w/o’ denotes the untreated water control. Parts of the image have been created with BioRender.com. (B) Principal component analysis (PCA) of all 10 conditions including three independent biological replicates, after TMM normalization. Clusters 1, 2 and 3 were added manually after creating the plot.

(A) Experimental workflow showing the different conditions used for the analyses. ‘w/o’ denotes the untreated water control. Parts of the image have been created with BioRender.com. (B) Principal component analysis (PCA) of all 10 conditions including three independent biological replicates, after TMM normalization. Clusters 1, 2 and 3 were added manually after creating the plot.

Popella L, Jung J, Popova K, Ðurica-Mitić S, Barquist L, Vogel J. (2021) Global RNA profiles show target selectivity and physiological effects of peptide-delivered antisense antibiotics. Nucleic Acids Res [Epub ahead of print]. [article]

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