ArticleACS infectious diseases2020
Cultivation-Free Typing of Bacteria Using Optical DNA Mapping.
Article in ACS infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Chromosome-scale assembly of yeast genomes using enzyme-free, dense optical genome mapping.Nature communications · 2026Article
- Strain-Level Typing ofACS infectious diseases · 2025Article
- 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
- Sequencing and Optical Genome Mapping for the Adventurous Chemist.Chemical & biomedical imaging · 2024Review
- Optical Mapping: Detecting Genomic Resistance Cassettes in MRSA.ACS omega · 2024Article
- Fluorescent polymer as a biosensing tool for the diagnosis of microbial pathogens.Scientific reports · 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
- DeepOM: single-molecule optical genome mapping via deep learning.Bioinformatics (Oxford, England) · 2023Article
- Strain-level bacterial typing directly from patient samples using optical DNA mapping.Communications medicine · 2023Article
- Identification and characterization of plasmids carrying the mobile colistin resistance geneJAC-antimicrobial resistance · 2023Article
- A Parallelized Nanofluidic Device for High-Throughput Optical DNA Mapping of Bacterial Plasmids.Micromachines · 2021Article
- Article
- Single-molecule optical genome mapping in nanochannels: multidisciplinarity at the nanoscale.Essays in biochemistry · 2021Article
- Combining dense and sparse labeling in optical DNA mapping.PloS one · 2021Article
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Authors and funding
11 authors.
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Abstract
A variety of pathogenic bacteria can infect humans, and rapid species identification is crucial for the correct treatment. However, the identification process can often be time-consuming and depend on the cultivation of the bacterial pathogen(s). Here, we present a stand-alone, enzyme-free, optical DNA mapping assay capable of species identification by matching the intensity profiles of large DNA molecules to a database of fully assembled bacterial genomes (>10 000). The assay includes a new data analysis strategy as well as a general DNA extraction protocol for both Gram-negative and Gram-positive bacteria. We demonstrate that the assay is capable of identifying bacteria directly from uncultured clinical urine samples, as well as in mixtures, with the potential to be discriminative even at the subspecies level. We foresee that the assay has applications both within research laboratories and in clinical settings, where the time-consuming step of cultivation can be minimized or even completely avoided.
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