Evidence map›Paper›PMID 42681097›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Mechanistic Studies of Antibacterial PNAs by RNA-Seq Analysis.

Toby Wilkinson, Jörg Vogel

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Toby WilkinsonFaculty of Medicine, Institute for Molecular Infection Biology (IMIB), University of Würzburg, Würzburg, Germany.
Jörg VogelFaculty of Medicine, Institute for Molecular Infection Biology (IMIB), University of Würzburg, Würzburg, Germany. joerg.vogel@uni-wuerzburg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA sequencing (RNA-seq) has become the principal method for bacterial transcriptome analysis, enabling investigation of antibiotic mechanisms of action, stress responses, and resistance development. It has also played a key role in advancing antibacterial antisense oligomers (ASOs), particularly peptide nucleic acid (PNA)-based compounds. When conjugated to cell-penetrating peptides (CPPs) to enable intracellular delivery, PNAs provide a sequence-specific strategy to modulate bacterial gene expression. While growth-based assays can demonstrate bacterial killing by PNA-CPPs targeting essential genes, RNA-seq is required to elucidate the global transcriptional response to PNA-CPP exposure. This includes downregulation of PNA-targeted mRNAs, identification of cellular pathways linked to the targeted gene, assessment of off-target effects, and characterization of broader stress and membrane damage responses. Together, these insights provide a mechanistic understanding of PNA delivery, activity, and bacterial killing. This chapter describes optimized RNA-seq workflows for studying PNA-CPPs in Escherichia coli and Salmonella enterica; discusses considerations for RNA isolation, sequencing strategies, and data analysis; and emphasizes the importance of robust, reproducible pipelines for reliable data interpretation.

Indexed as

Anti-Bacterial AgentsPeptide Nucleic AcidsRNA-SeqCell-Penetrating PeptidesEscherichia coliGene Expression ProfilingGene Expression Regulation, BacterialRNA, BacterialSalmonella entericaSequence Analysis, RNAAnti-Bacterial AgentsCell-Penetrating PeptidesPeptide Nucleic AcidsRNA, BacterialAntimicrobialsAntisense technologyMicrobiologyPeptide nucleic acidRNA-sequencingTranscriptomics

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.