ArticleCommunications medicine2023
Strain-level bacterial typing directly from patient samples using optical DNA mapping.
Article in Communications medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 20 citations in OpenAlex.
- Chromosome-scale assembly of yeast genomes using enzyme-free, dense optical genome mapping.Nature communications · 2026Article
- Programmable CRISPR-Cas diagnostic platforms for rapid detection of uropathogens and antimicrobial resistance.Archives of microbiology · 2026Review
- Understanding recurrence inJournal of clinical microbiology · 2026Review
- Strain-Level Typing ofACS infectious diseases · 2025Article
- The Emergence of Nanofluidics for Single-Biomolecule Manipulation and Sensing.Analytical chemistry · 2025Review
- Detection of antimicrobial resistance via state-of-the-art technologies versus conventional methods.Frontiers in microbiology · 2025Review
- High-throughput single-molecule nanofluidic studies onQRB discovery · 2025Article
- DOGMA: de novo assembly of densely labelled optical DNA maps using a matrix profile approach.PloS one · 2025Article
- Mitigating Antibiotic Resistance: The Utilization of CRISPR Technology in Detection.Biosensors · 2024Review
- Short-sighted evolution of virulence for invasive gut microbes: From hypothesis to tests.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Proteome analysis, genetic characterization, and antibiotic resistance patterns of Klebsiella pneumoniae clinical isolates.AMB Express · 2024Article
- Optical Mapping: Detecting Genomic Resistance Cassettes in MRSA.ACS omega · 2024Article
- OM2Seq: learning retrieval embeddings for optical genome mapping.Bioinformatics advances · 2024Article
- Design of optimal labeling patterns for optical genome mapping via information theory.Bioinformatics (Oxford, England) · 2023Article
- Strain-level bacterial typing directly from patient samples using optical DNA mapping.Communications medicine · 2023Article
Corrections and comments
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Authors and funding
15 authors at 7 institutions in 1 country.
Funding
Abstract
backgroundIdentification of pathogens is crucial to efficiently treat and prevent bacterial infections. However, existing diagnostic techniques are slow or have a too low resolution for well-informed clinical decisions.
methodsIn this study, we have developed an optical DNA mapping-based method for strain-level bacterial typing and simultaneous plasmid characterisation. For the typing, different taxonomical resolutions were examined and cultivated pure Escherichia coli and Klebsiella pneumoniae samples were used for parameter optimization. Finally, the method was applied to mixed bacterial samples and uncultured urine samples from patients with urinary tract infections.
resultsWe demonstrate that optical DNA mapping of single DNA molecules can identify Escherichia coli and Klebsiella pneumoniae at the strain level directly from patient samples. At a taxonomic resolution corresponding to E. coli sequence type 131 and K. pneumoniae clonal complex 258 forming distinct groups, the average true positive prediction rates are 94% and 89%, respectively. The single-molecule aspect of the method enables us to identify multiple E. coli strains in polymicrobial samples. Furthermore, by targeting plasmid-borne antibiotic resistance genes with Cas9 restriction, we simultaneously identify the strain or subtype and characterize the corresponding plasmids.
conclusionThe optical DNA mapping method is accurate and directly applicable to polymicrobial and clinical samples without cultivation. Hence, it has the potential to rapidly provide comprehensive diagnostics information, thereby optimizing early antibiotic treatment and opening up for future precision medicine management.
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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.