Strain-level bacterial typing directly from patient samples using optical DNA mapping
Journal article, 2023

For bacterial infections, it is important to rapidly and accurately identify and characterize the type of bacteria involved so that optimal antibiotic treatment can be given quickly to the patient. However, current diagnostic methods are sometimes slow and cannot be used for mixtures of bacteria. We have, therefore, developed a method to identify bacteria directly from patient samples. The method was tested on two common species of disease-causing bacteria - Escherichia coli and Klebsiella pneumoniae - and it could correctly identify the bacterial strain or subtype in both urine samples and mixtures. Hence, the method has the potential to provide fast diagnostic information for choosing the most suited antibiotic, thereby reducing the risk of death and suffering. Nyblom, Johnning et al. develop an optical DNA mapping approach for bacterial strain typing of patient samples. They demonstrate rapid identification of clinically relevant E. coli and K. pneumoniae strains, without the need for cultivation. 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.
Results
We 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.
Conclusion
The 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.

Author

My Nyblom

Chalmers, Life Sciences, Chemical Biology

Anna Johnning

University of Gothenburg

Chalmers, Mathematical Sciences

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Centre for Antibiotic Resistance Research in Gothenburg (CARe)

Fraunhofer-Chalmers Centre

Karolin Frykholm

Chalmers, Life Sciences, Chemical Biology

Marie Wrande

Uppsala University

Vilhelm Müller

Chalmers, Life Sciences, Chemical Biology

Gaurav Goyal

Chalmers, Life Sciences, Chemical Biology

Miriam Robertsson

Albertas Dvirnas

Lund University

Tsegaye Sewunet

Karolinska Institutet

Sriram Kesarimangalam

Chalmers, Life Sciences, Chemical Biology

Tobias Ambjornsson

Lund University

Christian G. Giske

Karolinska Institutet

Karolinska University Hospital

Linus Sandegren

Uppsala University

Erik Kristiansson

Chalmers, Mathematical Sciences

Centre for Antibiotic Resistance Research in Gothenburg (CARe)

University of Gothenburg

Fredrik Westerlund

Chalmers, Life Sciences, Chemical Biology

Communications Medicine

2730664X (eISSN)

Vol. 3 31 31

Areas of Advance

Nanoscience and Nanotechnology

Health Engineering

Subject Categories

Infectious Medicine

Microbiology

Microbiology in the medical area

DOI

10.1038/s43856-023-00259-z

PubMed

36823379

More information

Latest update

11/8/2024