Advances in Clinical Medicine
Vol. 11  No. 06 ( 2021 ), Article ID: 42929 , 5 pages
10.12677/ACM.2021.116362

NGS对下呼吸道感染诊断价值的探讨

何承成,何连福,严桥路*

大理大学临床医学院,云南 大理

收稿日期:2021年5月1日;录用日期:2021年5月13日;发布日期:2021年6月7日

摘要

下呼吸道感染作为目前导致人类死亡的第三大原因,其发病率、死亡率高,是全世界认可的常见呼吸系统疾病,危害性巨大。其病原微生物因地域、民族存在差异而不尽相同。在全球范围内,临床诊断病原体有效率低、新发传染病及少见病频出、菌群耐药等问题。因此精确的病原体诊断成为解决上述问题的关键。近年来,二代测序技术(NGS)作为一种新型检测病原体手段,在临床上被广泛应用,为我们明确病原体、拓展对微生物的认知以及临床诊治提供了一条新途径。本文就二代测序技术在下呼吸道感染中的研究现状及前景进行综述。

关键词

下呼吸道感染,二代测序技术,宏基因组测序,病原学诊断

A Review of the Value of Next-Generation Sequencing in the Diagnosis of Lower Respiratory Tract Infection

Chengcheng He, Lianfu He, Qiaolu Yan*

Clinical Medical College, Dali University, Dali Yunnan

Received: May 1st, 2021; accepted: May 13th, 2021; published: Jun. 7th, 2021

ABSTRACT

As the third leading cause of human death, lower respiratory tract infection (LRTIs) is a globally recognized common respiratory disease with high morbidity and mortality. The pathogenic microorganisms are different when there are differences in regions and nationalities. In the world, there are some problems, such as low efficiency of clinical diagnosis of pathogens, frequent occurrence of new and rare diseases, drug resistance of bacteria and so on. Therefore, accurate diagnosis of pathogens is the key to solve the above problems. In recent years, the next-generation sequencing (NGS) technology, as a new method to detect pathogens, has been widely used in clinic, which provides a new way for us to identify pathogens, expand our understanding of microorganisms and provide a new way for clinical diagnosis and treatment. This article reviews the research status and prospect of next-generation sequencing technology in lower respiratory tract infection.

Keywords:Lower Respiratory Tract Infection, Next-Generation Sequencing, Metagenomic Next Generation Sequencing, Etiological Diagnosis

Copyright © 2021 by author(s) and Hans Publishers Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).

http://creativecommons.org/licenses/by/4.0/

1. 二代基因测序技术(Next-Generation Sequencing, NGS)

二代测序技术(NGS),又称为高通量测序技术,该技术通过简便的样本采集及核酸提取,将数量庞大的基因片段进行测序后与已纳入系统的病原体进行对比,从而确定样本所含病原体。该技术测序流程主要包括标本核酸提取建库、DNA和(或)RNA富集、上机测序、生物学信息分析等。NGS大体上分为宏基因组测序(metagenomic next generation sequencing, mNGS)和靶向扩增子测序(targeted amplicon sequencing, TAS)。

mNGS适用于各种病原体的检测,包括细菌、病毒及真菌 [1] [2]。mNGS无需培养、检测迅速便捷、准确性高 [3],可检测未知新发病原体 [1] [2] [4],并可追溯源头进行分类,标本来源广泛 [5],因此被越来越频繁地应用于医学研究及临床诊断领域 [6] - [11]。但是,mNGS检测敏感度依赖于数据库收录的病原体。目前有关mNGS的研究中,虽纳入约8000多种病原体,但相对于整个自然界的病原体,其覆盖率仍较低 [3]。TAS具有扩增检测标本中病原体序列数的优点。主要方法是使用引物进行PCR扩增,然后从中检测与特定类型相匹配的所有微生物。目前许多医院及医疗机构已将该技术应用于样本检测中,特别是感染性疾病的病原体检测 [12]。相对于宏基因组测序,TAS测序花费较少,但其受到检测范围的限制(如只能检测细菌或真菌)及需对检测样本提前预估病原体类型。随着科技的发展,二代测序技术的缺陷将逐渐被完善,在感染性疾病中的应用也将愈发成熟、广泛。

2. 下呼吸道感染

下呼吸道感染,包括急性支气管炎、急性加重慢性支气管炎或慢性阻塞性肺疾病(COPD)、纤维化支气管扩张、社区获得性肺炎(CAP)等,是发病率高的传染病和一个长期的全球公共卫生问题。

下呼吸道感染的病原体复杂、多样。在细菌中,如肺炎链球菌、流感嗜血杆菌、金黄色葡萄球菌、铜绿假单胞菌和其他革兰氏阴性杆菌被广泛认为是下呼吸道感染的主要病原体 [13]。尼日利亚大学教学医院(UNTH)对954名疑似下呼吸道感染患者的痰样本的研究中 [14],微生物阳性率45.2%,其中单一致病菌以肺炎克雷伯菌215株(49.9%)居多,细菌组合以克雷伯菌和铜绿假单胞菌6株(1.4%)居多。病毒在下呼吸道感染中也发挥重要作用,疾病控制和预防中心(CDC)关于社区肺炎的一项病原学研究中 [15],23%的患者有病毒感染的证据,其中鼻病毒是最常见的病原体。在韩国一项对198名ICU的肺炎患者的研究中 [16] [17] [18],35%的患者发现了病毒病原体(其中24%为鼻病毒)。其他关于ICU病人的研究报告病毒感染率在18%到41%之间。此外,呼吸道病原体的联合感染很常见,特别是在欠发达国家如中国 [19]。在下呼吸道感染中,细菌、病毒等都可为其致病菌,患病率高,每年用于其治疗的金额巨大,如美国每年有数十亿美元用于下呼吸道感染的诊断和治疗 [20] [21]。因此,明确患者下呼吸道病原体对于治疗患者疾病、减轻国家经济负担有着重要作用。

下呼吸道感染患病率和死亡率依民族、地域、气候而有较大差异。依民族、地域不同的原因可能与其日常生活、家庭经济状况、当地空气污染程度、遗传因素等有关。在细菌性肺炎呼吸道细菌微生态研究中发现存在种族/民族的差异性,推测上述原因可能也是下呼吸道感染患病率具有民族差异性的原因。Burton等 [22] 通过研究发现美国成年人中黑种人患肺炎链球菌引起的社区获得性肺炎的几率比白种人明显升高,提示呼吸道内细菌微生态分布可能有种族/民族差异性。气候因素是下呼吸道感染的一个独立危险因素,对患者的发病率及死亡率皆有重要的影响。如下呼吸道感染患者在秋冬季节明显高发且容易急性加重,住院次数也往往较夏季有所增多,其原因可能与在寒冷、潮湿环境中呼吸道病毒感染增加有关。

3. NGS在下呼吸道感染诊断中的应用

随着NGS的出现,人们对肺部微生物组及其在肺部疾病中的作用了解的越来越详细,比如当肺部微生物组多样性降低或部分微生物丰度异常增高时可能导致肺炎 [23]。自Wilson等 [24] 利用该技术诊断一例中枢神经系统钩体病后,该技术在感染性疾病诊断中逐渐应用。其中,mNGS对于下呼吸道感染病原体的明确更为有效。mNGS对于病原体鉴定具有独到优势,能够检测出一些传统方法未能检出的微生物,而且相比于传统检测方法,其准确率更高,如Zou等 [25] 在不明原因肺炎患者进行传统病原体检测无效后通过mNGS技术检测出麻疹病毒;Xie等 [26] 对IUC病房178例重症肺炎进行病原体检测,其中48例行宏基因组测序(观察组),其余使用传统检测方法(对照组),根据检测结果调整抗生素方案,结果显示观察组病死率在28 d和90 d均明显低于对照组,分别是16.7% vs 37.7%、16.7% vs 42.3%。

宏基因组检测致病菌阳性率明显高于传统检测方法,有助于更加迅速找到病原体、调整抗生素方案及降低病死率。胡必杰等 [4] 对感染性疾病患者同时进行mNGS与传统培养检测发现,mNGS对于感染性疾病诊断敏感性高于传统检测方法(50.7% vs 35.2%; P< 0.01),此外,mNGS不易受到接触抗生素的影响。对于免疫缺陷儿童的下呼吸道感染,Zinter等 [27] 针对既往传统检测结果阴性患者进行mNGS,结果显示约50%检测出潜在病原体,这说明mNGS相对于传统检测具有更高精准性及敏感性。Leo等 [28] 对一名白血病造血干细胞移植后出现肺部感染的成人患者的肺泡灌洗液进行mNGS,结果显示该技术明显提高了细菌、真菌检出率,甚至检测出病毒、厌氧菌。

mNGS对于目前在全球流行的新型冠状病毒肺炎病毒检测及其他相关研究也起到了重要作用,为全世界人民的生命及财产安全做出了重要贡献。HLA在对病原体的免疫应答中起着关键作用,针对目前在全球流行的新型冠状病毒肺炎(COVID-19),Wei Wang等 [29] 利用mNGS,对82例COVID-19患者进行HLA-A、-B、-C、-DRB1、-DRB3/4/5、-DQA1、-DQB1、-DPA1和-DPB1位点基因分型,结果显示部分HLA等位基因可能与COVID-19的发生有关。NGS作为检测病原体的新型技术,在COVID-19相关检测中起到了重要作用,为全球抗疫做出了重要贡献。

综上所述,mNGS在下呼吸道感染诊断上有着显著的敏感性,更加容易发现罕见菌群,提高人们对新发病、少见病的认识。在原因不明、接触抗生素、免疫功能低下等患者的病原体检测有更高指导价值。在应用NGS的过程中,人们也发现了其许多不足之处,比如:病原体覆盖率仍较低、测序收费偏高、检测回报时间长、外源微生物的污染、采样过程样本可能受到污染、DNA/ RNA流程不能合并检测等问题在一定程度上阻碍了mNGS的临床应用。

4. 未来临床应用及研究热点展望

目前临床感染性疾病使用mNGS确定病因的研究越来越多,与此同时,将该技术应用于呼吸道疾病也逐渐成为热门研究方向。新技术的发展为解决mNGS检测耗时较长的技术难题带来希望,比如:Yatera Kazuhiro等 [30] 利用细菌16S核糖体RNA基因序列,NGS可在很短的时间内快速估算出大量细菌在门、属水平上的序列,甚至部分细菌在种水平上的序列。此外,宏基因组未来发展还需关注如下几个方面:微生物耐药基因检测、DNAseq与RNAseq测序流程合并、利用RNAseq检测宿主转录组评估感染相关性等。相信在不久之后由于相关技术的发展,随着宏基因组技术不断应用于临床感染性疾病诊断中,在形成一系列规范操作流程和评判标准后,mNGS将会成为临床广泛普及的病原体检测方法,帮助临床工作者确定病原体及指导用药,帮助解决抗感染治疗领域的世界性难题。

文章引用

何承成,何连福,严桥路. NGS对下呼吸道感染诊断价值的探讨
A Review of the Value of Next-Generation Sequencing in the Diagnosis of Lower Respiratory Tract Infection[J]. 临床医学进展, 2021, 11(06): 2521-2525. https://doi.org/10.12677/ACM.2021.116362

参考文献

  1. 1. Zhou, P., Yang, X.L., Wang, X.G., et al. (2020) Apneumonia Outbreak Associated with a New Coronavirus of Probable Bat Origin. Nature, 579, 270-273

  2. 2. Wu, F., Zhao, S., Yu, B., et al. (2020) A New Coronavirus Associated with Human Respiratory Disease in China. Nature, 579, 265-269. https://doi.org/10.1038/s41586-020-2008-3

  3. 3. 田李均, 曹志龙, 黄晓英, 韩旭东. ICU内脓毒症患者应用宏基因组二代测序的临床分析[J]. 中国急救医学, 2019, 39(5): 416-420.

  4. 4. Miao, Q., Ma, Y.Y., Wang, Q.Q., et al. (2018) Microbiological Diagnostic Performance of Metagenomic Next-Generation Sequencing When Applied to Clinical Practice. Clinical Infectious Diseases, 67, S231-S240. https://doi.org/10.1093/cid/ciy693

  5. 5. 王国安, 吴宏成. mNGS在肺部感染患者病原体诊断中的应用[J]. 现代实用医学, 2019, 31(1): 9-10+79.

  6. 6. Lynch, T., Petkau, A., Knox, N., et al. (2016) A Primer on Infectious Disease Bacterial Genomics. Clinical Microbiology Reviews, 29, 881-913. https://doi.org/10.1128/CMR.00001-16

  7. 7. Chen, H. and Jiang, W. (2014) Application of High-Throughput Sequencing in Understanding Human Oral Microbiome Related with Health and Disease. Frontiers in Microbiology, 5, 508. https://doi.org/10.3389/fmicb.2014.00508

  8. 8. Qin, J., Li, R., Raes, J., et al. (2010) A Human Gut Microbial Gene Catalogue Established by Metagenomic Sequencing. Nature, 464, 59-65. https://doi.org/10.1038/nature08821

  9. 9. Sanford, J.A. and Gallo, R.L. (2013) Functions of the Skin Microbiota in Health and Disease. Seminars in Immunology, 25, 370-377. https://doi.org/10.1016/j.smim.2013.09.005

  10. 10. Lopez-Perez, M. and Mirete, S. (2014) Discovery of Novel Antibiotic Resistance Genes through Metagenomics. Recent Advances in DNA & Gene Sequences, 8, 15-19. https://doi.org/10.2174/2352092208666141013231244

  11. 11. Blum, H.E. (2017) The Human Microbiome. Advances in Medical Sciences, 62, 414-420. https://doi.org/10.1016/j.advms.2017.04.005

  12. 12. Rutanga, J.P., Van Puyvelde, S., Heroes, A.S., et al. (2018) 16S Metagenomics for Diagnosis of Bloodstream Infections: Opportunities and Pitfalls. Expert Review of Molecular Diagnostics, 18, 749-759. https://doi.org/10.1080/14737159.2018.1498786

  13. 13. Musher, D.M. and Thorner, A.R. (2014) Community-Acquired Pneumonia. The New England Journal of Medicine, 371, 1619-1628. https://doi.org/10.1056/NEJMra1312885

  14. 14. Maduakor, U., Onyemelukwe, N., Sonny, J.O., et al. (2017) Bacterial Etiology of Lower Respiratory Tract Infections and Their Antimicrobial Susceptibility. The American Journal of the Medical Sciences, 354, 471-475. https://doi.org/10.1016/j.amjms.2017.06.025

  15. 15. Jain, S., Self, W.H., Wunderink, R.G., et al. (2015) Community-Acquired Pneumonia Requiring Hospitalization among U.S. Adults. The New England Journal of Medicine, 373, 415-427. https://doi.org/10.1056/NEJMoa1500245

  16. 16. Shorr, A.F., Fisher, K., Micek, S.T. and Kollef, M.H. (2017) The Burden of Viruses in Pneumonia Associated with Acute Respiratory Failure: An Underappreciated Issue. Chest, 154, 84-90.

  17. 17. Tramuto, F., Maida, C.M., Napoli, G., et al. (2016) Burden and Viral Aetiology of Influenza-Like Illness and Acute Respiratory Infection in Intensive Care Units. Microbes and Infection, 18, 270-276. https://doi.org/10.1016/j.micinf.2015.11.008

  18. 18. van Someren Greve, F., Juffermans, N.P., Bos, L.D., et al. (2018) Respiratory Viruses in Invasively Ventilated Critically Ill Patients—A Prospective Multicenter Observational Study. Critical Care Medicine, 46, 29-36. https://doi.org/10.1097/CCM.0000000000002752

  19. 19. Peng, D., Zhao, D., Liu, J., et al. (2009) Multipathogen Infections in Hospitalized Children with Acute Respiratory Infections. Virology Journal, 6, 155. https://doi.org/10.1186/1743-422X-6-155

  20. 20. File, T.M. and Marrie, T.J. (2010) Burden of Community-Acquired Pneumonia in North American Adults. Postgraduate Medicine, 122, 130-141. https://doi.org/10.3810/pgm.2010.03.2130

  21. 21. Hayes, B.H., Haberling, D.L., Kennedy, J.L., Varma, J.K., Fry, A.M. and Vora, N.M. (2018) Burden of Pneumonia-Associated Hospitalizations: United States, 2001-2014. Chest, 153, 427-437. https://doi.org/10.1016/j.chest.2017.09.041

  22. 22. Burton, D.C., Flannery, B., Bennett, N.M., Farley, M.M., Gershman, K., Harrison, L.H., Lynfield, R., Petit, S., Reingold, A.L., Schaffner, W., Thomas, A., Plikaytis, B.D., Rose, C.E., Whitney, C.G., Schuchat, A., Active Bacterial Core Surveillance/Emerging Infections Program Network (2010) Socioeconomic and Racial/Ethnic Disparities in the Incidence of Bacteremic Pneumonia among US Adults. American Journal of Public Health, 100, 1904-1911. https://doi.org/10.2105/AJPH.2009.181313

  23. 23. Dickson, R.P., Erb, J.R. and Huffnagle, G.B. (2014) Towards an Ecology of the Lung: New Conceptual Models of Pulmonary Microbiology and Pneumonia Pathogenesis. The Lancet Respiratory Medicine, 2, 238-246. https://doi.org/10.1016/S2213-2600(14)70028-1

  24. 24. Wilson, M.R., Naccache, S.N., Samayoa, E., et al. (2014) Actionable Diagnosis of Neuroleptospirosis by Next-Generation Sequencing. The New England Journal of Medicine, 370, 2408-2417. https://doi.org/10.1056/NEJMoa1401268

  25. 25. Zou, X., Tang, G., Zhao, X., et al. (2017) Simultaneous Virus Identification and Characterization of Severe Unexplained Pneumonia Cases Using a Metagenomics Sequencing Technique. Science China Life Sciences, 60, 279-286. https://doi.org/10.1007/s11427-016-0244-8

  26. 26. Xie, Y., Du, J., Jin, W., et al. (2019) Next Generation Sequencing for Diagnosis of Severe Pneumonia: China, 2010-2018. Journal of Infection, 78, 158-169. https://doi.org/10.1016/j.jinf.2018.09.004

  27. 27. Zinter, M.S., Dvorak, C.C., Mayday, M.Y., et al. (2019) Pulmonary Metagenomic Sequencing Suggests Missed Infections in Immunocompromised Children. Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America, 68, 1847-1855. https://doi.org/10.1093/cid/ciy802

  28. 28. Leo, S., Gaïa, N., Ruppe, E., et al. (2017) Detection of Bacterial Pathogens from Broncho-Alveolar Lavage by Next-Generation Sequencing. International Journal of Molecular Sciences, 18, 1-13. https://doi.org/10.3390/ijms18092011

  29. 29. Wang, W., Zhang, W., Zhang, J.J., et al. (2020) Distribution of HLA Allele Frequencies in 82 Chinese Individuals with Coronavirus Disease-2019 (COVID-19). HLA, 96, 194-196. https://doi.org/10.1111/tan.13941

  30. 30. Kazuhiro, Y., Shingo, N. and Hiroshi, M. (2018) The Microbiome in the Lower Respiratory Tract. Respiratory Investigation, 56, 432-439. https://doi.org/10.1016/j.resinv.2018.08.003

  31. NOTES

    *通讯作者。

期刊菜单