Skip to main content

Advertisement

SpringerLink
Log in

Utilizing metagenomic next-generation sequencing for pathogen detection and diagnosis in lower respiratory tract infections in real-world clinical practice

  • Research
  • Published:
Infection Aims and scope Submit manuscript

Abstract

Background

Infectious etiologies of lower respiratory tract infections (LRTIs) by the conventional microbiology tests (CMTs) can be challenging. Metagenomic next-generation sequencing (mNGS) has great potential in clinical use for its comprehensiveness in identifying pathogens, particularly those difficult-to-culture organisms.

Methods

We analyzed a total of 205 clinical samples from 201 patients with suspected LRTIs using mNGS in parallel with CMTs. mNGS results were used to guide treatment adjustments for patients who had negative CMT results. The efficacy of treatment was subsequently evaluated in these patients.

Results

mNGS-detected microorganisms in 91.7% (188/205) of the clinical samples, whereas CMTs demonstrated a lower detection rate, identifying microorganisms in only 37.6% (77/205) of samples. Compared to CMT results, mNGS exhibited a detection sensitivity of 93.5% and 95.4% in all 205 clinical samples and 180 bronchoalveolar lavage fluid (BALF) samples, respectively. A total of 114 patients (114/201; 56.7%) showed negative CMT results, among which 92 received treatment adjustments guided by their positive mNGS results. Notably, 67.4% (62/92) of patients demonstrated effective treatment, while 25% (23/92) experienced a stabilized condition. Subgroup analysis of cancer patients revealed that 41.9% (13/31) exhibited an effective response to treatment, and 35.5% (11/31) maintained a stable condition following medication adjustments guided by mNGS.

Conclusion

mNGS demonstrated great potential in identifying microorganisms of clinical significance in LRTIs. The rapid turnaround time and reduced susceptibility to the impact of antimicrobial administration make mNGS a valuable supplementary tool for diagnosis and treatment decision-making for suspected LRTIs in clinical practice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

All sequence reads were deposited into the NCBI Sequence Read Archive (SRA) database under the accession number PRJNA952317. All the other relevant data of the study are available from the corresponding authors upon reasonable request.

Abbreviations

LRTIs:

Lower respiratory tract infections

CMT:

Conventional microbiological test

mNGS:

Metagenomic next-generation sequencing

BALF:

Bronchoalveolar lavage fluid

PSI:

Pneumonia severity index

NTC:

No-template control

References

  1. Collaborators GL. Estimates of the global, regional, and national morbidity, mortality, and aetiologies of lower respiratory tract infections in 195 countries: a systematic analysis for the Global Burden of Disease Study 2015. Lancet Infect Dis. 2017;17:1133–61.

    Article  Google Scholar 

  2. Feldman C, Shaddock E. Epidemiology of lower respiratory tract infections in adults. Expert Rev Respir Med. 2019;13:63–77.

    Article  CAS  PubMed  Google Scholar 

  3. Greene G, Hood K, Little P, Verheij T, Goossens H, Coenen S, Butler CC. Towards clinical definitions of lower respiratory tract infection (LRTI) for research and primary care practice in Europe: an international consensus study. Prim Care Respir J. 2011;20:299–306.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Korppi M, Heikkila P, Palmu S, Huhtala H, Csonka P. Antibiotic prescriptions for children with lower respiratory tract infections fell from 2014 to 2020, but misuse was still an issue. Acta Paediatr. 2022;111:1230–7.

    Article  PubMed  Google Scholar 

  5. Wei Gu SM, Chiu CY. Clinical metagenomic next-generation sequencing for pathogen detection. Annu Rev Pathol Mech Dis. 2019;14:319–38.

    Article  Google Scholar 

  6. Gire SK, Goba A, Andersen KG, Sealfon RS, Park DJ, Kanneh L, et al. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science. 2014;345(6202):1369–72.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  7. Salipante SJ, SenGupta DJ, Cummings LA, Land TA, Hoogestraat DR, Cookson BT. Application of whole-genome sequencing for bacterial strain typing in molecular epidemiology. J Clin Microbiol. 2015;53:1072–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Sahoo MK, Lefterova MI, Yamamoto F, Waggoner JJ, Chou S, Holmes SP, et al. Detection of cytomegalovirus drug resistance mutations by next-generation sequencing. J Clin Microbiol. 2013;51:3700–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Chen H, Yin Y, Gao H, Guo Y, Dong Z, Wang X, et al. Clinical Utility of In-house Metagenomic Next-generation Sequencing for the Diagnosis of Lower Respiratory Tract Infections and Analysis of the Host Immune Response. Clin Infect Dis. 2020;71:S416–26.

    Article  CAS  PubMed  Google Scholar 

  10. Wilson MR, Sample HA, Zorn KC, Arevalo S, Yu G, Neuhaus J, et al. Clinical metagenomic sequencing for diagnosis of meningitis and encephalitis. N Engl J Med. 2019;380:2327–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Xing XW, Zhang JT, Ma YB, He MW, Yao GE, Wang W, et al. Metagenomic next-generation sequencing for diagnosis of infectious encephalitis and meningitis: a large, prospective case series of 213 patients. Front Cell Infect Microbiol. 2020;10:88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Cao B, Huang Y, She DY, Cheng QJ, Fan H, Tian XL, et al. Diagnosis and treatment of community-acquired pneumonia in adults: 2016 clinical practice guidelines by the Chinese Thoracic Society Chinese Medical Association. Clin Respir J. 2018;12:1320–60.

    Article  PubMed  Google Scholar 

  13. Lim WS, van der Eerden MM, Laing R, Boersma WG, Karalus N, Town GI, et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003;58:377–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Fine MJ, Auble TE, Yealy DM, Hanusa BH, Weissfeld LA, Singer DE, et al. A prediction rule to identify low-risk patients with community-acquired pneumonia. N Engl J Med. 1997;336:243–50.

    Article  CAS  PubMed  Google Scholar 

  15. Xu J, Zhou P, Liu J, Zhao L, Fu H, Han Q, et al. Utilizing metagenomic next-generation sequencing (mNGS) for rapid pathogen identification and to inform clinical decision-making: results from a large real-world cohort. Infect Dis Ther. 2023. https://doi.org/10.1007/s40121-023-00790-5.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Whyte JD. Advances in Flavivirus research applications: new techniques using the FastPrep-24 5G™ sample preparation system. Nat Methods. 2016;13:i–iii.

    Article  Google Scholar 

  17. Jiang H, Xing Z, Liu X, Chai Q, Xin Z, Zhu C, et al. Comparison and development of a metagenomic next-generation sequencing protocol for combined detection of DNA and RNA pathogens in cerebrospinal fluid. BMC Infect Dis. 2022;22:326.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Li Y, Yao XW, Tang L, Dong WJ, Lan TL, Fan J, et al. Diagnostic efficiency of metagenomic next-generation sequencing for suspected spinal tuberculosis in China: A multicenter prospective study. Front Microbiol. 2022;13:1018938.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Xiao Q, Lu W, Kong X, Shao YW, Hu Y, Wang A, et al. Alterations of circulating bacterial DNA in colorectal cancer and adenoma: a proof-of-concept study. Cancer Lett. 2021;499:201–8.

    Article  CAS  PubMed  Google Scholar 

  20. Zeng X, Wu J, Li X, Xiong W, Tang L, Li X, et al. Application of metagenomic next-generation sequencing in the etiological diagnosis of infective endocarditis during the perioperative period of cardiac surgery: a prospective cohort study. Front Cardiovasc Med. 2022;9:811492.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Wood DE, Lu J, Langmead B. Improved metagenomic analysis with Kraken 2. Genome Biol. 2019;20:257.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Qian L, Shi Y, Li F, Wang Y, Ma M, Zhang Y, et al. Metagenomic next-generation sequencing of cerebrospinal fluid for the diagnosis of external ventricular and lumbar drainage-associated ventriculitis and meningitis. Front Microbiol. 2020;11: 596175.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Liu L, Sun B, Ying W, Liu D, Wang Y, Sun J, et al. Rapid diagnosis of Talaromyces marneffei infection by metagenomic next-generation sequencing technology in a Chinese cohort of inborn errors of immunity. Front Cell Infect Microbiol. 2022;12: 987692.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kunst H, Mack D, Kon OM, Banerjee AK, Chiodini P, Grant A. Parasitic infections of the lung: a guide for the respiratory physician. Thorax. 2011;66:528–36.

    Article  CAS  PubMed  Google Scholar 

  26. Song P, Li H, Liu T, Liu Y, Ma X, Su L. Disseminated strongyloidiasis misdiagnosed as guillain-barre syndrome: the value of high-throughput genetic sequencing of pathogenic microorganisms in parasitic infections. Infect Drug Resist. 2022;15:5601–7.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Chrastek D, Hickman S, Sitaranjan D, Vokshi I, Kakisi O, Kadlec J, et al. Streptococcus constellatus causing empyema and sepsis, necessitating early surgical decortication. Case Rep Infect Dis. 2020;2020:4630809.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Pendleton KM, Huffnagle GB, Dickson RP. The significance of Candida in the human respiratory tract: our evolving understanding. Pathog Dis. 2017. https://doi.org/10.1093/femspd/ftx029.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Azoulay E, Timsit JF, Tafflet M, de Lassence A, Darmon M, Zahar JR, et al. Candida colonization of the respiratory tract and subsequent pseudomonas ventilator-associated pneumonia. Chest. 2006;129:110–7.

    Article  PubMed  Google Scholar 

  30. Schlaberg R, Chiu CY, Miller S, Procop GW, Weinstock G, Professional Practice C, et al. Validation of metagenomic next-generation sequencing tests for universal pathogen detection. Arch Pathol Lab Med. 2017;141(6):776–86.

    Article  CAS  PubMed  Google Scholar 

  31. Ewig S, Torres A, Angeles Marcos M, Angrill J, Rano A, de Roux A, et al. Factors associated with unknown aetiology in patients with community-acquired pneumonia. Eur Respir J. 2002;20:1254–62.

    Article  CAS  PubMed  Google Scholar 

  32. van Gageldonk-Lafeber AB, Heijnen ML, Bartelds AI, Peters MF, van der Plas SM, Wilbrink B. A case-control study of acute respiratory tract infection in general practice patients in The Netherlands. Clin Infect Dis. 2005;41:490–7.

    Article  PubMed  Google Scholar 

  33. Zhang D, Yang D, Makam AN. Utility of Blood Cultures in Pneumonia. Am J Med. 2019;132:1233–8.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Miao Q, Ma Y, Wang Q, Pan J, Zhang Y, Jin W, et al. Microbiological diagnostic performance of metagenomic next-generation sequencing when applied to clinical practice. Clin Infect Dis. 2018;67:S231–40.

    Article  CAS  PubMed  Google Scholar 

  35. Charalampous T, Kay GL, Richardson H, Aydin A, Baldan R, Jeanes C, et al. Nanopore metagenomics enables rapid clinical diagnosis of bacterial lower respiratory infection. Nat Biotechnol. 2019;37:783–92.

    Article  CAS  PubMed  Google Scholar 

  36. Wang J, Han Y, Feng J. Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis. BMC Pulm Med. 2019;19:252.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Zhang P, Chen Y, Li S, Li C, Zhang S, Zheng W, et al. Metagenomic next-generation sequencing for the clinical diagnosis and prognosis of acute respiratory distress syndrome caused by severe pneumonia: a retrospective study. PeerJ. 2020;8: e9623.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Zhou H, Larkin PMK, Zhao D, Ma Q, Yao Y, Wu X, et al. Clinical impact of metagenomic next-generation sequencing of bronchoalveolar lavage in the diagnosis and management of pneumonia: a multicenter prospective observational study. J Mol Diagn. 2021;23:1259–68.

    Article  CAS  PubMed  Google Scholar 

  39. Ge M, Gan M, Yan K, Xiao F, Yang L, Wu B, et al. Combining metagenomic sequencing with whole exome sequencing to optimize clinical strategies in neonates with a suspected central nervous system infection. Front Cell Infect Microbiol. 2021;11: 671109.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Li J, Zhang Y, Zhang Q, Lu S, Huang F, Wang J. Application of metagenomic next-generation sequencing for the diagnosis of intracranial infection of Listeria monocytogenes. Ann Transl Med. 2022;10:672.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Al-Hilu SA, Al-Shujairi WH. Dual role of bacteria in carcinoma: stimulation and inhibition. Int J Microbiol. 2020;2020:4639761.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Mao Q, Ma W, Wang Z, Liang Y, Zhang T, Yang Y, et al. Differential flora in the microenvironment of lung tumor and paired adjacent normal tissues. Carcinogenesis. 2020;41:1094–103.

    Article  CAS  PubMed  Google Scholar 

  43. Jin J, Gan Y, Liu H, Wang Z, Yuan J, Deng T, et al. Diminishing microbiome richness and distinction in the lower respiratory tract of lung cancer patients: A multiple comparative study design with independent validation. Lung Cancer. 2019;136:129–35.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the patients, their families, and the investigators and research staff involved.

Funding

Not available.

Author information

Author notes

  1. Tangfeng Lv, Qi Zhao, and Jia Liu have contributed equally to this work.

Authors and Affiliations

  1. Department of Respiratory and Critical Care Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, Jiangsu, China

    Tangfeng Lv, Ping Zhan & Mingxiang Ye

  2. Department of Pulmonary and Critical Care Medicine, Nanjing Drum Tower Hospital, Nanjing, 210008, Jiangsu, China

    Qi Zhao

  3. Dinfectome Inc., Nanjing, 210000, Jiangsu, China

    Jia Liu, Song Wang, Weiwei Wu, Manman Huang & Qiuxiang Ou

  4. Department of Respiratory and Critical Care Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210008, Jiangsu, China

    Liyun Miao

  5. Yancheng Branch of Nanjing Drum Tower Hospital, Yancheng, 224002, Jiangsu, China

    Liyun Miao

  6. Department of Respiratory and Critical Care Medicine, Jiangsu Provincial Hospital of Integrated Chinese and Western Medicine, 100 Cross Street, Hongshan Road, Nanjing, 210028, Jiangsu, China

    Xiaoli Chen & Yeqing Zhang

Authors
  1. Tangfeng Lv
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qi Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jia Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Song Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Weiwei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Liyun Miao
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ping Zhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Xiaoli Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Manman Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Mingxiang Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Qiuxiang Ou
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Yeqing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

TFL, QZ, and JL designed this study. TFL, QZ, and JL performed the data acquisition. TFL, QZ, JL, SW, and WWW performed data analysis. TFL, QZ, JL, SW, MMH, and QXO edited the manuscript. YQZ supervised the present study. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yeqing Zhang.

Ethics declarations

Conflict of interest

JL, SW, WWW, MMH, and QXO are employees of Dinfectome Inc. The remaining authors declare no conflict of interests.

Ethical approval and consent to participate

The study was approved by the Ethics Committee of Jinling Hospital (2022DZGZR-114). Written informed consent was obtained from each patient before sample collection.

Consent for publication

Not applicable.

Supplementary Information

Below is the link to the electronic supplementary material.

15010_2024_2185_MOESM1_ESM.eps

Supplementary file1 Figure S1. Pathogens detected by mNGS but not CMTs. The y-axis represents species detected by mNGS in CMT-negative samples, whereas the x-axis represents the number of samples with the indicated species (EPS 2064 KB)

15010_2024_2185_MOESM2_ESM.eps

Supplementary file2 Figure S2. Flowchart of cancer patient inclusion for evaluating mNGS-directed treatment adjustment outcomes. 31 out of 39 mNGS-positive cancer patients showing inconsistent results with CMTs were included in the following evaluation of mNGS-directed treatment adjustment outcomes. CMT-negative but mNGS-positive patients and those without typical clinical symptoms supporting CMT diagnosis received treatments based primarily on mNGS results. Four CMT-positive patients remained on CMT-directed treatments for their clinical presentation supportive of CMT diagnosis (EPS 1692 KB)

Supplementary file1 (DOCX 24 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lv, T., Zhao, Q., Liu, J. et al. Utilizing metagenomic next-generation sequencing for pathogen detection and diagnosis in lower respiratory tract infections in real-world clinical practice. Infection 52, 625–636 (2024). https://doi.org/10.1007/s15010-024-02185-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s15010-024-02185-1

Keywords

Search

Navigation