ArticleJournal of visualized experiments : JoVE2020
Generating Transposon Insertion Libraries in Gram-Negative Bacteria for High-Throughput Sequencing.
Article in Journal of visualized experiments : JoVE, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- Transposon insertion sequencing of Pseudomonas aeruginosa identifies multiple intersecting pathways essential for extreme colistin resistance.PLoS pathogens · 2026Article
- A Clinically Silent Resistance Phenotype That PromotesbioRxiv : the preprint server for biology · 2026Article
- Molecular interplay between peptidoglycan integrity and outer membrane asymmetry in maintaining cell envelope homeostasis.Journal of bacteriology · 2025Article
- Acinetobacter phages use distinct strategies to breach the capsule barrier.PLoS pathogens · 2025Article
- Complex interplay between gene deletions and the environment uncovers cellular roles for genes of unknown function inmSystems · 2025Article
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- Biological Upcycling of Plastics Waste.Annual review of chemical and biomolecular engineering · 2024Review
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- Recent Advances in Genetic Tools forFrontiers in genetics · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Transposon sequencing (Tn-seq) is a powerful method that combines transposon mutagenesis and massive parallel sequencing to identify genes and pathways that contribute to bacterial fitness under a wide range of environmental conditions. Tn-seq applications are extensive and have not only enabled examination of genotype-phenotype relationships at an organism level but also at the population, community and systems levels. Gram-negative bacteria are highly associated with antimicrobial resistance phenotypes, which has increased incidents of antibiotic treatment failure. Antimicrobial resistance is defined as bacterial growth in the presence of otherwise lethal antibiotics. The "last-line" antimicrobial colistin is used to treat Gram-negative bacterial infections. However, several Gram-negative pathogens, including Acinetobacter baumannii can develop colistin resistance through a range of molecular mechanisms, some of which were characterized using Tn-seq. Furthermore, signal transduction pathways that regulate colistin resistance vary within Gram-negative bacteria. Here we propose an efficient method of transposon mutagenesis in A. baumannii that streamlines generation of a saturating transposon insertion library and amplicon library construction by eliminating the need for restriction enzymes, adapter ligation, and gel purification. The methods described herein will enable in-depth analysis of molecular determinants that contribute to A. baumannii fitness when challenged with colistin. The protocol is also applicable to other Gram-negative ESKAPE pathogens, which are primarily associated with drug resistant hospital-acquired infections.
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Registered trials
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.