Dataset Information

Evaluation of respiratory samples in etiology diagnosis and microbiome characterization by metagenomic sequencing.

ABSTRACT:

Background

The application of clinical mNGS for diagnosing respiratory infections improves etiology diagnosis, however at the same time, it brings new challenges as an unbiased sequencing method informing all identified microbiomes in the specimen.

Methods

Strategy evaluation and metagenomic analysis were performed for the mNGS data generated between March 2017 and October 2019. Diagnostic strengths of four specimen types were assessed to pinpoint the more appropriate type for mNGS diagnosis of respiratory infections. Microbiome complexity was revealed between patient cohorts and infection types. A bioinformatic pipeline resembling diagnosis results was built based upon multiple bioinformatic parameters.

Results

The positive predictive values (PPVs) for mNGS diagnosing of non-mycobacterium, Nontuberculous Mycobacteria (NTM), and Aspergillus were obviously higher in bronchoalveolar lavage fluid (BALF) demonstrating the potency of BALF in mNGS diagnosis. Lung tissues and sputum were acceptable for diagnosis of the Mycobacterium tuberculosis (MTB) infections. Interestingly, significant taxonomy differences were identified in sufficient BALF specimens, and unique bacteriome and virome compositions were found in the BALF specimens of tumor patients. Our pipeline showed comparative diagnostic strength with the clinical microbiological diagnosis.

Conclusions

To achieve reliable mNGS diagnosis result, BALF specimens for suspicious common infections, and lung tissues and sputum for doubtful MTB infections are recommended to avoid the false results given by the complexed respiratory microbiomes. Our developed bioinformatic pipeline successful helps mNGS data interpretation and reduces manual corrections for etiology diagnosis.

SUBMITTER: Miao Q

PROVIDER: S-EPMC9748891 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Evaluation of respiratory samples in etiology diagnosis and microbiome characterization by metagenomic sequencing.

Miao Qing Q Liang Tianzhu T Pei Na N Liu Chunjiao C Pan Jue J Li Na N Wang Qingqing Q Chen Yanqiong Y Chen Yu Y Ma Yuyan Y Jin Wenting W Zhang Yao Y Su Yi Y Yao Yumeng Y Huang Yingnan Y Zhou Chunmei C Bao Rong R Xu Xiaoling X Chen Weijun W Hu Bijie B Li Junhua J

Respiratory research 20221214 1

<h4>Background</h4>The application of clinical mNGS for diagnosing respiratory infections improves etiology diagnosis, however at the same time, it brings new challenges as an unbiased sequencing method informing all identified microbiomes in the specimen.<h4>Methods</h4>Strategy evaluation and metagenomic analysis were performed for the mNGS data generated between March 2017 and October 2019. Diagnostic strengths of four specimen types were assessed to pinpoint the more appropriate type for mNG ...[more]

PMID: 36517824

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Project description:Background: Tuberculosis (TB) is now the leading cause of death from infectious disease. Rapid screening and diagnostic methods for TB are urgently required. Rapid development of metagenomics next-generation sequencing (mNGS) in recent years showed promising and satisfying application of mNGS in several kinds of infectious diseases. However, research directly evaluating the ability of mNGS in TB infection is still scarce. Methods: We conducted an adult prospective study in mainland China to evaluate the diagnostic performance of mNGS for detection of Mycobacterium tuberculosis complex (MTB) in multiple forms of direct clinical samples compared with GeneXpert MTB/RIF assay (Xpert), traditional diagnostic methods, and the clinical final diagnosis. Results: Of 123 patients presenting with suspected active TB infection between June 1, 2017, and May 21, 2018, 105 patients underwent synchronous tuberculous testing with culture, Xpert, and mNGS on direct clinical samples including sputum, cerebrospinal fluids, pus, etc. During follow-up, 45 of 105 participants had clinical final diagnosis of active TB infection, including 13 pulmonary TB cases and 32 extrapulmonary TB cases. Compared to clinical final diagnosis, mNGS produced a sensitivity of 44% for all active TB cases, which was similar to Xpert (42%) but much higher than conventional methods (29%). With only one false-positive result, mNGS had a specificity of 98% in our study. mNGS yielded significantly much higher sensitivity in pre-treatment samples (76%) than post-treatment ones (31%) (P = 0.005), which was also true for Xpert and conventional methods. Combining Xpert and mNGS together, the study identified 27 of 45 active TB cases (60%), including all 13 conventional method-identified cases, and the result reached statistical significance compared to conventional methods (McNemar-test P < 0.001). Conclusions: mNGS had a similar diagnostic ability of MTB compared with Xpert and showed potential for a variety of clinical samples. Combined mNGS and Xpert showed an overall superior advantage over conventional methods and significantly improved the etiology diagnosis of both MTB and other pathogens. The result that anti-TB treatment significantly reduced diagnostic efficacy of culture, Xpert, and mNGS highlighted the importance of collecting samples before empirical treatment.

Project description:BackgroundLower respiratory tract infections (LRTI)are known to be diagnosed late or inaccurately. This has fueled the unscrupulous use of antibiotics, as they are often used empirically and clinically, leading to antibiotic abuse and multidrug resistance in patients. Metagenomic next-generation sequencing (mNGS), now widely used in clinical studies, could be a potential intervention to revolutionize microbiology by rapidly identifying unknown species.MethodsThis review and meta-analysis were conducted on eligible studies with respect to metagenomic sequencing on clinical LRTI diagnostics up to May 01, 2022. QUADAS-2 was employed to assess the methodological bias as well as applicability. After that, a meta-analysis was conducted to analyze the accuracy of mNGS, compared with the composite reference standard (CRS), among the enrolled studies.ResultsThis work collected 1248 samples in 13/21 qualified articles to factor in the accuracy of the diagnostic test. Typically, methods like molecular testing, culture, composite measures, and clinical decision-making were adopted as the reference criteria. With regard to Bronchoalveolar Lavage Samples, their sensitivity was 89% (82-93%) while their specificity was 90% (66-98%), with obvious heterogeneities in these two factors as demonstrated by different studies. The summary receiver operating characteristic (SROC) curve was plotted for mNGS as a function of LRTI, and the area under the curve (AUC) was 0.94. A Funnel plot with a p-value greater than 0.05 indicated the absence of publication bias. Positive and negative likelihood ratios (PLR and NLR) were >10 and > 0.1, respectively. In this pre-test probability-post-probability-likelihood ratio relationship graph, the values were Prior prob (%) = 20, Post-prob-Pos (%) = 77 and Post-prob-Neg (%) = 4.ConclusionThe AUC value of SROC suggested a high accuracy of mNGS in diagnosis, with no publication bias and high reliability. The application of mNGS exhibits notable diagnostic efficacy in discerning pathogens present in bronchoalveolar lavage fluid (BALF) among patients afflicted with LRTI. However, mNGS is more meaningful for the definitive diagnosis of the disease rather than the exclusion of the disease. This post-test probability is significantly higher than the pre-test probability.

Dataset Information

Evaluation of respiratory samples in etiology diagnosis and microbiome characterization by metagenomic sequencing.

Background

Methods

Results

Conclusions

Publications

Evaluation of respiratory samples in etiology diagnosis and microbiome characterization by metagenomic sequencing.

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