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Single-cell pathogen diagnostics for combating antibiotic resistance

Nature Reviews Methods Primers volume 3, Article number: 6 (2023) Cite this article

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Abstract

Bacterial infections and antimicrobial resistance are a major cause for morbidity and mortality worldwide. Antimicrobial resistance often arises from antimicrobial misuse, where physicians empirically treat suspected bacterial infections with broad-spectrum antibiotics until standard culture-based diagnostic tests can be completed. There has been a tremendous effort to develop rapid diagnostics in support of the transition from empirical treatment of bacterial infections towards a more precise and personalized approach. Single-cell pathogen diagnostics hold particular promise, enabling unprecedented quantitative precision and rapid turnaround times. This Primer provides a guide for assessing, designing, implementing and applying single-cell pathogen diagnostics. First, single-cell pathogen diagnostic platforms are introduced based on three essential capabilities: cell isolation, detection assay and output measurement. Representative results, common analysis methods and key applications are highlighted, with an emphasis on initial screening of bacterial infection, bacterial species identification and antimicrobial susceptibility testing. Finally, the limitations of existing platforms are discussed, with perspectives offered and an outlook towards clinical deployment. This Primer hopes to inspire and propel new platforms that can realize the vision of precise and personalized bacterial infection treatments in the near future.

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Fig. 1: Workflow of pathogen diagnostics using standard clinical microbiology procedures and single-cell pathogen diagnostics.
Fig. 2: Essential capabilities of single-cell pathogen diagnostic platforms, including single-cell isolation, detection and measurement.
Fig. 3: Representative results from single-cell pathogen diagnostics and corresponding analysis and interpretation.
Fig. 4: Applications of single-cell pathogen diagnostics for pathogen detection and identification.
Fig. 5: Applications of single-cell pathogen diagnostics for AST.

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Acknowledgements

H.L., K.H., P.K.W., K.E.M., J.C.L. and T.-H.W. acknowledge support from the National Institutes of Health (NIH) (R01AI117032, R01AI137272 and R01AI153133). K.H. acknowledges support from a developmental grant from the Center for AIDS Research at Johns Hopkins University, a NIH-funded programme (P30AI094189).

Author information

Author notes

  1. Hui Li

    Present address: School of Electrical, Computer and Biomedical Engineering, Southern Illinois University, Carbondale, IL, USA

  2. These authors contributed equally: Hui Li, Kuangwen Hsieh.

Authors and Affiliations

  1. Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA

    Hui Li, Kuangwen Hsieh & Tza-Huei Wang

  2. Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, USA

    Pak Kin Wong

  3. Department of Urology, Stanford University School of Medicine, Stanford, CA, USA

    Kathleen E. Mach & Joseph C. Liao

  4. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA

    Tza-Huei Wang

  5. Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA

    Tza-Huei Wang

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  1. Hui Li
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Contributions

Introduction (H.L., K.H., T.-H.W.); Experimentation (H.L., K.H., P.K.W.); Results (H.L., K.H., T.-H.W.); Applications (H.L., K.E.M., J.C.L.); Reproducibility and data deposition (K.H., T.-H.W.); Limitations and optimizations (K.H., P.K.W., T.-H.W.); Outlook (K.E.M., J.C.L., T.-H.W.). Overview of the Primer (T.-H.W.).

Corresponding author

Correspondence to Tza-Huei Wang.

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Nature Reviews Methods Primers thanks Lih Feng Cheow and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Glossary

Categorical agreement

A metric for evaluating single-cell antimicrobial susceptibility testing platforms, defined as the percentage of clinical isolates classified in the same susceptibility category as the reference method.

Capillary effect

A physical phenomenon where liquid flows in a narrow space due to capillary force. This flow action is accomplished autonomously without the assistance of an external instrument.

Discretization

The compartmentalization of a bulk sample into numerous discrete and isolated volumes, typically using microfluidic technology, that enables single cells to be encapsulated and spatially constrained.

Essential agreements

A metric for evaluating single-cell antimicrobial susceptibility testing platforms, defined as the percentage of measured minimum inhibitory concentrations (MICs) within a single doubling dilution of the reference MICs.

Heteroresistance

A phenotype in which subpopulations of bacterial cells have higher antibiotic resistance compared with the susceptible main population.

Inoculum effect

The effect where the minimum inhibitory concentration of an antimicrobial reagent for inhibiting bacterial growth increases with the bacterial concentrations in the test.

Limit of detection

The minimum amount of a target of interest, such as bacteria, that can be distinguished from the absence of the target at a specified confidence level.

Soft lithography

A technique for fabricating microfluidic devices by conformably replicating elastic structures from a rigid mould. The fabrication is highly repeatable. It is called soft as this technique fabricates elastic materials.

Wheatstone bridge circuit

An electrical circuit that is able to measure the electrical resistance of a variable target with high accuracy. This circuit consists of two parallelized branches and each branch includes two electrical resistors. The electrical potential between the electrical resistors is measured on each branch and the potential difference between the two points is used to monitor the change of the target resistor on one branch.

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Li, H., Hsieh, K., Wong, P.K. et al. Single-cell pathogen diagnostics for combating antibiotic resistance. Nat Rev Methods Primers 3, 6 (2023). https://doi.org/10.1038/s43586-022-00190-y

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