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Translating microbiota analysis for clinical applications

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Harnessing the potential of microbiota analysis creates new opportunities in diagnosing diseases, improving treatment efficacy, reducing treatment complications and preventing disease recurrence. However, microbiota analysis has not yet been integrated into clinical management workflows. Here, we discuss crucial characteristics of microbiota analysis systems for clinical translation.

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Fig. 1: Clinical translation of microbiota analysis.

References

  1. Sender, R., Fuchs, S. & Milo, R. Are we really vastly outnumbered? Revisiting the ratio of bacterial to host cells in humans. Cell 164, 337–340 (2016).

    Article  Google Scholar 

  2. Talebian, S., Dehghani, F., Weiss, P. S. & Conde, J. Evolution of CRISPR-enabled biosensors for amplification-free nucleic acid detection. Trends Biotechnol. 42, 10–13 (2023).

    Article  Google Scholar 

  3. Dar, D., Dar, N., Cai, L. & Newman, D. K. Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution. Science 373, eabi4882 (2021).

    Article  Google Scholar 

  4. Shi, H. et al. Highly multiplexed spatial mapping of microbial communities. Nature 588, 676–681 (2020).

    Article  Google Scholar 

  5. Takahashi, M. K. et al. A low-cost paper-based synthetic biology platform for analyzing gut microbiota and host biomarkers. Nat. Commun. 9, 3347 (2018).

    Article  Google Scholar 

  6. Bauermeister, A., Mannochio-Russo, H., Costa-Lotufo, L. V., Jarmusch, A. K. & Dorrestein, P. C. Mass spectrometry-based metabolomics in microbiome investigations. Nat. Rev. Microbiol. 20, 143–160 (2022).

    Article  Google Scholar 

  7. Vandeputte, D. et al. Quantitative microbiome profiling links gut community variation to microbial load. Nature 551, 507–511 (2017).

    Article  Google Scholar 

  8. Lin, D. B. & Medeiros, D. M. The microbiome as a major function of the gastrointestinal tract and its implication in micronutrient metabolism and chronic diseases. Nutr. Res. 112, 30–45 (2023).

    Article  Google Scholar 

  9. Man, W. H., Piters, W. A. A. D. & Bogaert, D. The microbiota of the respiratory tract: gatekeeper to respiratory health. Nat. Rev. Microbiol. 15, 259–270 (2017).

    Article  Google Scholar 

  10. Karstens, L. et al. Community profiling of the urinary microbiota: considerations for low-biomass samples. Nat. Rev. Urol. 15, 735–749 (2018).

    Article  Google Scholar 

  11. Sekirov, I., Russell, S. L., Antunes, L. C. & Finlay, B. B. Gut microbiota in health and disease. Physiol. Rev. 90, 859–904 (2010).

    Article  Google Scholar 

  12. Ben-Amor, K. et al. Genetic diversity of viable, injured, and dead fecal bacteria assessed by fluorescence-activated cell sorting and 16S rRNA gene analysis. Appl. Environ. Microbiol. 71, 4679–4689 (2005).

    Article  Google Scholar 

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Acknowledgements

This research was supported, in part, by the National Institutes of Health (NIH), grant number R01AI153133.

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Authors and Affiliations

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

    Jyong-Huei Lee, Siew Mei Chin & Pak Kin Wong

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

    Kathleen E. Mach & Joseph C. Liao

  3. Department of Pathology and Laboratory Medicine, Penn State Health, Hershey, PA, USA

    April M. Bobenchik

  4. Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA

    Joseph C. Liao

  5. Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, CA, USA

    Samuel Yang

  6. Department of Mechanical Engineering and Department of Surgery, The Pennsylvania State University, University Park, PA, USA

    Pak Kin Wong

Authors
  1. Jyong-Huei Lee
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  2. Siew Mei Chin
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  3. Kathleen E. Mach
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  4. April M. Bobenchik
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  5. Joseph C. Liao
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  6. Samuel Yang
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  7. Pak Kin Wong
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Contributions

All authors contributed equally to the preparation of this manuscript.

Corresponding authors

Correspondence to Joseph C. Liao, Samuel Yang or Pak Kin Wong.

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The authors declare no competing interests.

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Lee, JH., Chin, S.M., Mach, K.E. et al. Translating microbiota analysis for clinical applications. Nat Rev Bioeng 2, 284–286 (2024). https://doi.org/10.1038/s44222-024-00168-3

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