Determination of Ideal Factors for Early Adoption and Standardization of
Metagenomic Next-Generation Sequencing for Respiratory System
Infections

Lei      Zhao; Cole   R.   Formslag; Qing      Zhang; Braydon   C.   Cowan; Trenton   G.   Mayberry; Aaron   R.   Barnhill; Yongsheng      Wang; Yujiang      Fang

Abstract

Background: Metagenomic next-generation sequencing (mNGS) demonstrates great promise as a diagnostic tool for determining the cause of pathogenic infections. The standard diagnostic procedures (SDP) include smears and cultures and are typically viewed as less sensitive and more time-consuming when compared to mNGS. There are concerns about the logistics and ease of transition from SDP to mNGS. mNGS lacks standardization of collection processes, databases, and sequencing. Additionally, there is the burden of training clinicians on interpreting mNGS results.

Objective: Until now, few studies have explored factors that could be used as early adoption candidates to ease the transition between SDP and mNGS. This study evaluated 123 patients who had received both SDP and mNGS and compared several variables across a diagnostic test evaluation.

Methods: The diagnostic test evaluation observed metrics such as sensitivity, specificity, positive and negative likelihood ratios (PLR, NLR), positive and negative predictive values (PPV, NPV), and accuracy. Factors included various sample sources such as bronchoalveolar lavage fluid (BALF), lung tissue, and cerebral spinal fluid (CSF). An additional factor observed was the patient's immune status.

Results: Pathogen detection was found to be significantly greater for mNGS for total patients, BALF sample source, CSF sample source, and non-immunocompromised patients (p<0.05). Pathogen detection was found to be insignificant for lung tissue sample sources and immunocompromised patients. Sensitivity, PLR, NLR, PPV, NPV, and accuracy appeared to be higher with mNGS for the total patients, BALF sample source, and non-immunocompromised patients when compared with SDP (p<0.05).

Conclusion: With higher metrics in sensitivity, specificity, PLR, NLR, PPV, NPV, and accuracy for overall patients, mNGS may prove a better diagnostic tool than SDP. When addressing sample sources, mNGS for BALF-collected samples appeared to have higher scores than SDP for the same metrics. When patients were in a non-immunocompromised state, mNGS also demonstrated greater diagnostic benefits to BALF and overall patients compared to SDP. This study demonstrates that using BALF as a sample source and selecting non-immunocompromised patients may prove beneficial as early adoption factors for mNGS standard protocol. Such a study may pave the road for mNGS as a routine clinical method for determining the exact pathogenic etiology of lung infections.

[1]
Lozano, R.; Naghavi, M.; Foreman, K.; Lim, S.; Shibuya, K.; Aboyans, V.; Abraham, J.; Adair, T.; Aggarwal, R.; Ahn, S.Y.; AlMazroa, M.A.; Alvarado, M.; Anderson, H.R.; Anderson, L.M.; Andrews, K.G.; Atkinson, C.; Baddour, L.M.; Barker-Collo, S.; Bartels, D.H.; Bell, M.L.; Benjamin, E.J.; Bennett, D.; Bhalla, K.; Bikbov, B.; Abdulhak, A.B.; Birbeck, G.; Blyth, F.; Bolliger, I.; Boufous, S.; Bucello, C.; Burch, M.; Burney, P.; Carapetis, J.; Chen, H.; Chou, D.; Chugh, S.S.; Coffeng, L.E.; Colan, S.D.; Colquhoun, S.; Colson, K.E.; Condon, J.; Connor, M.D.; Cooper, L.T.; Corriere, M.; Cortinovis, M.; de Vaccaro, K.C.; Couser, W.; Cowie, B.C.; Criqui, M.H.; Cross, M.; Dabhadkar, K.C.; Dahodwala, N.; De Leo, D.; Degenhardt, L.; Delossantos, A.; Denenberg, J.; Des Jarlais, D.C.; Dharmaratne, S.D.; Dorsey, E.R.; Driscoll, T.; Duber, H.; Ebel, B.; Erwin, P.J.; Espindola, P.; Ezzati, M.; Feigin, V.; Flaxman, A.D.; Forouzanfar, M.H.; Fowkes, F.G.R.; Franklin, R.; Fransen, M.; Freeman, M.K.; Gabriel, S.E.; Gakidou, E.; Gaspari, F.; Gillum, R.F.; Gonzalez-Medina, D.; Halasa, Y.A.; Haring, D.; Harrison, J.E.; Havmoeller, R.; Hay, R.J.; Hoen, B.; Hotez, P.J.; Hoy, D.; Jacobsen, K.H.; James, S.L.; Jasrasaria, R.; Jayaraman, S.; Johns, N.; Karthikeyan, G.; Kassebaum, N.; Keren, A.; Khoo, J-P.; Knowlton, L.M.; Kobusingye, O.; Koranteng, A.; Krishnamurthi, R.; Lipnick, M.; Lipshultz, S.E.; Ohno, S.L.; Mabweijano, J.; MacIntyre, M.F.; Mallinger, L.; March, L.; Marks, G.B.; Marks, R.; Matsumori, A.; Matzopoulos, R.; Mayosi, B.M.; McAnulty, J.H.; McDermott, M.M.; McGrath, J.; Memish, Z.A.; Mensah, G.A.; Merriman, T.R.; Michaud, C.; Miller, M.; Miller, T.R.; Mock, C.; Mocumbi, A.O.; Mokdad, A.A.; Moran, A.; Mulholland, K.; Nair, M.N.; Naldi, L.; Narayan, K.M.V.; Nasseri, K.; Norman, P.; O’Donnell, M.; Omer, S.B.; Ortblad, K.; Osborne, R.; Ozgediz, D.; Pahari, B.; Pandian, J.D.; Rivero, A.P.; Padilla, R.P.; Perez-Ruiz, F.; Perico, N.; Phillips, D.; Pierce, K.; Pope, C.A., III; Porrini, E.; Pourmalek, F.; Raju, M.; Ranganathan, D.; Rehm, J.T.; Rein, D.B.; Remuzzi, G.; Rivara, F.P.; Roberts, T.; De León, F.R.; Rosenfeld, L.C.; Rushton, L.; Sacco, R.L.; Salomon, J.A.; Sampson, U.; Sanman, E.; Schwebel, D.C.; Segui-Gomez, M.; Shepard, D.S.; Singh, D.; Singleton, J.; Sliwa, K.; Smith, E.; Steer, A.; Taylor, J.A.; Thomas, B.; Tleyjeh, I.M.; Towbin, J.A.; Truelsen, T.; Undurraga, E.A.; Venketasubramanian, N.; Vijayakumar, L.; Vos, T.; Wagner, G.R.; Wang, M.; Wang, W.; Watt, K.; Weinstock, M.A.; Weintraub, R.; Wilkinson, J.D.; Woolf, A.D.; Wulf, S.; Yeh, P-H.; Yip, P.; Zabetian, A.; Zheng, Z-J.; Lopez, A.D.; Murray, C.J.L. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet,  2012, 380(9859), 2095-2128.
 [http://dx.doi.org/10.1016/S0140-6736(12)61728-0] [PMID:  23245604]

[2]
Gu, W.; Deng, X.; Lee, M.; Sucu, Y.D.; Arevalo, S.; Stryke, D.; Federman, S.; Gopez, A.; Reyes, K.; Zorn, K.; Sample, H.; Yu, G.; Ishpuniani, G.; Briggs, B.; Chow, E.D.; Berger, A.; Wilson, M.R.; Wang, C.; Hsu, E.; Miller, S.; DeRisi, J.L.; Chiu, C.Y. Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids. Nat. Med.,  2021, 27(1), 115-124.
 [http://dx.doi.org/10.1038/s41591-020-1105-z] [PMID:  33169017]

[3]
Li, H.; Gao, H.; Meng, H.; Wang, Q.; Li, S.; Chen, H.; Li, Y.; Wang, H. Detection of Pulmonary Infectious Pathogens From Lung Biopsy Tissues by Metagenomic Next-Generation Sequencing. Front. Cell. Infect. Microbiol.,  2018, 8(205), 205.
 [http://dx.doi.org/10.3389/fcimb.2018.00205] [PMID:  29988504]

[4]
Lanks, C.W.; Musani, A.I.; Hsia, D.W. Community-acquired Pneumonia and Hospital-acquired Pneumonia. Med. Clin. North Am.,  2019, 103(3), 487-501.
 [http://dx.doi.org/10.1016/j.mcna.2018.12.008] [PMID:  30955516]

[5]
Bohmwald, K.; Gálvez, N.M.S.; Ríos, M.; Kalergis, A.M. Neurologic Alterations Due to Respiratory Virus Infections. Front. Cell. Neurosci.,  2018, 12, 386.
 [http://dx.doi.org/10.3389/fncel.2018.00386] [PMID:  30416428]

[6]
Gu, X.; Zhou, F.; Wang, Y.; Fan, G.; Cao, B. Respiratory viral sepsis: Epidemiology, pathophysiology, diagnosis and treatment. Eur. Respir. Rev.,  2020, 29(157), 200038.
 [http://dx.doi.org/10.1183/16000617.0038-2020] [PMID:  32699026]

[7]
Berube, B.J.; Rangel, S.M.; Hauser, A.R. Pseudomonas aeruginosa: Breaking down barriers. Curr. Genet.,  2016, 62(1), 109-113.
 [http://dx.doi.org/10.1007/s00294-015-0522-x] [PMID:  26407972]

[8]
McCray, P.B., Jr; Pewe, L.; Wohlford-Lenane, C.; Hickey, M.; Manzel, L.; Shi, L.; Netland, J.; Jia, H.P.; Halabi, C.; Sigmund, C.D.; Meyerholz, D.K.; Kirby, P.; Look, D.C.; Perlman, S. Lethal infection of K18-hACE2 mice infected with severe acute respiratory syndrome coronavirus. J. Virol.,  2007, 81(2), 813-821.
 [http://dx.doi.org/10.1128/JVI.02012-06] [PMID:  17079315]

[9]
Riccobono, E.; Bussini, L.; Giannella, M.; Viale, P.; Rossolini, G.M. Rapid diagnostic tests in the management of pneumonia. Expert Rev. Mol. Diagn.,  2022, 22(1), 49-60.
 [http://dx.doi.org/10.1080/14737159.2022.2018302] [PMID:  34894965]

[10]
Ahmad, F.B.; Anderson, R.N. The Leading Causes of Death in the US for 2020. JAMA,  2021, 325(18), 1829-1830.
 [http://dx.doi.org/10.1001/jama.2021.5469] [PMID:  33787821]

[11]
Lyons, P.G.; Kollef, M.H. Prevention of hospital-acquired pneumonia. Curr. Opin. Crit. Care,  2018, 24(5), 370-378.
 [http://dx.doi.org/10.1097/MCC.0000000000000523] [PMID:  30015635]

[12]
Liu, J.Y.; Dickter, J.K. Nosocomial Infections. Gastrointest. Endosc. Clin. N. Am.,  2020, 30(4), 637-652.
 [http://dx.doi.org/10.1016/j.giec.2020.06.001] [PMID:  32891222]

[13]
Arevalo-Rodriguez, I.; Buitrago-Garcia, D.; Simancas-Racines, D.; Zambrano-Achig, P.; Del Campo, R.; Ciapponi, A.; Sued, O.; Martinez-García, L.; Rutjes, A.W.; Low, N.; Bossuyt, P.M.; Perez-Molina, J.A.; Zamora, J. False-negative results of initial RT-PCR assays for COVID-19: A systematic review. PLoS One,  2020, 15(12), e0242958.
 [http://dx.doi.org/10.1371/journal.pone.0242958] [PMID:  33301459]

[14]
Wormanns, D.; Diederich, S. Characterization of small pulmonary nodules by CT. Eur. Radiol.,  2004, 14(8), 1380-1391.
 [http://dx.doi.org/10.1007/s00330-004-2335-z] [PMID:  15148623]

[15]
Miller, F.G.; Joffe, S.; Kesselheim, A.S. Evidence, errors, and ethics. Perspect. Biol. Med.,  2014, 57(3), 299-307.
 [http://dx.doi.org/10.1353/pbm.2014.0024] [PMID:  25959345]

[16]
Nunn, P. HIV-associated pulmonary tuberculosis. Afr. Health,  1991, 14(1), 10-11.
 [PMID:  12343452]

[17]
Austin, B. The value of cultures to modern microbiology. Antonie van Leeuwenhoek,  2017, 110(10), 1247-1256.
 [http://dx.doi.org/10.1007/s10482-017-0840-8] [PMID:  28168566]

[18]
Moreno, I.; Cicinelli, E.; Garcia-Grau, I.; Gonzalez-Monfort, M.; Bau, D.; Vilella, F.; De Ziegler, D.; Resta, L.; Valbuena, D.; Simon, C. The diagnosis of chronic endometritis in infertile asymptomatic women: A comparative study of histology, microbial cultures, hysteroscopy, and molecular microbiology. Am. J. Obstet. Gynecol.,  2018, 218(6), 602.e1-602.e16.
 [http://dx.doi.org/10.1016/j.ajog.2018.02.012] [PMID:  29477653]

[19]
Wunderink, R.G. Diagnosis of pneumonia. Curr. Opin. Pulm. Med.,  1996, 2(3), 213-217.
 [http://dx.doi.org/10.1097/00063198-199605000-00009] [PMID:  9363142]

[20]
Chen, X.; Cao, K.; Wei, Y.; Qian, Y.; Liang, J.; Dong, D.; Tang, J.; Zhu, Z.; Gu, Q.; Yu, W. Metagenomic next-generation sequencing in the diagnosis of severe pneumonias caused by Chlamydia psittaci. Infection,  2020, 48(4), 535-542.
 [http://dx.doi.org/10.1007/s15010-020-01429-0] [PMID:  32314307]

[21]
Keane, O.M.; Budd, K.E.; Flynn, J.; McCoy, F. Increased detection of mastitis pathogens by real‐time PCR compared to bacterial culture. Vet. Rec.,  2013, 173(11), 268-268.
 [http://dx.doi.org/10.1136/vr.101598] [PMID:  23976784]

[22]
Wang, Y.; Salazar, J.K. Culture-Independent Rapid Detection Methods for Bacterial Pathogens and Toxins in Food Matrices. Compr. Rev. Food Sci. Food Saf.,  2016, 15(1), 183-205.
 [http://dx.doi.org/10.1111/1541-4337.12175] [PMID:  33371580]

[23]
Zhang, T.; Lv, C-F.; Wang, J.; Zheng, W-B.; Lu, L-Z.; Liu, S-J.; Bao, J. Direct tuberculosis drug susceptibility testing: Time-saving and cost-effective in detecting MDR-TB. Int. J. Tuberc. Lung Dis.,  2016, 20(3), 323-328.
 [http://dx.doi.org/10.5588/ijtld.15.0637] [PMID:  27046712]

[24]
Diao, Z.; Han, D.; Zhang, R.; Li, J. Metagenomics next-generation sequencing tests take the stage in the diagnosis of lower respiratory tract infections. J. Adv. Res.,  2022, 38, 201-212.
 [http://dx.doi.org/10.1016/j.jare.2021.09.012] [PMID:  35572406]

[25]
Liu, H.; Zhang, Y.; Yang, J.; Liu, Y.; Chen, J. Application of mNGS in the Etiological Analysis of Lower Respiratory Tract Infections and the Prediction of Drug Resistance. Microbiol. Spectr.,  2022, 10(1), e02502-e02521.
 [http://dx.doi.org/10.1128/spectrum.02502-21] [PMID:  35171007]

[26]
Yu, G.; Zhao, W.; Shen, Y.; Zhu, P.; Zheng, H. Metagenomic next generation sequencing for the diagnosis of tuberculosis meningitis: A systematic review and meta-analysis. PLoS One,  2020, 15(12), e0243161.
 [http://dx.doi.org/10.1371/journal.pone.0243161] [PMID:  33259541]

[27]
Liu, J.; Zhang, Q.; Dong, Y.Q.; Yin, J.; Qiu, Y.Q. Diagnostic accuracy of metagenomic next-generation sequencing in diagnosing infectious diseases: A meta-analysis. Sci. Rep.,  2022, 12(1), 21032.
 [http://dx.doi.org/10.1038/s41598-022-25314-y] [PMID:  36470909]

[28]
Françoise, A.; Héry-Arnaud, G. The Microbiome in Cystic Fibrosis Pulmonary Disease. Genes (Basel),  2020, 11(5), 536.
 [http://dx.doi.org/10.3390/genes11050536] [PMID:  32403302]

[29]
Leopold, S.S. When should we adopt new technology into our practices? Arch. Orthop. Trauma Surg.,  2021, 141(12), 2337-2340.
 [http://dx.doi.org/10.1007/s00402-021-04086-6] [PMID:  34402931]

[30]
Gupta, S. Paperless clinical trials: Myth or reality? Indian J. Pharmacol.,  2015, 47(4), 349-353.
 [http://dx.doi.org/10.4103/0253-7613.161247] [PMID:  26288464]

[31]
Jiang, S.; Min, R.; Fang, P. The impact of healthcare reform on the efficiency of public county hospitals in China. BMC Health Serv. Res.,  2017, 17(1), 838.
 [http://dx.doi.org/10.1186/s12913-017-2780-4] [PMID:  29262816]

[32]
James, S.; Rao, S.V.; Granger, C.B. Registry-based randomized clinical trials—a new clinical trial paradigm. Nat. Rev. Cardiol.,  2015, 12(5), 312-316.
 [http://dx.doi.org/10.1038/nrcardio.2015.33] [PMID:  25781411]

[33]
Piubello Orsini, L.; Leardini, C.; Vernizzi, S.; Campedelli, B. Inefficiency of public hospitals: A multistage data envelopment analysis in an Italian region. BMC Health Serv. Res.,  2021, 21(1), 1281.
 [http://dx.doi.org/10.1186/s12913-021-07276-5] [PMID:  34838006]

[34]
Flygare, S.; Simmon, K.; Miller, C.; Qiao, Y.; Kennedy, B.; Di Sera, T.; Graf, E.H.; Tardif, K.D.; Kapusta, A.; Rynearson, S.; Stockmann, C.; Queen, K.; Tong, S.; Voelkerding, K.V.; Blaschke, A.; Byington, C.L.; Jain, S.; Pavia, A.; Ampofo, K.; Eilbeck, K.; Marth, G.; Yandell, M.; Schlaberg, R. Taxonomer: An interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling. Genome Biol.,  2016, 17(1), 111.
 [http://dx.doi.org/10.1186/s13059-016-0969-1] [PMID:  27224977]

[35]
Mongkolrattanothai, K.; Naccache, S.N.; Bender, J.M.; Samayoa, E.; Pham, E.; Yu, G.; Dien Bard, J.; Miller, S.; Aldrovandi, G.; Chiu, C.Y. Neurobrucellosis: Unexpected Answer From Metagenomic Next-Generation Sequencing. J. Pediatric Infect. Dis. Soc.,  2017, 6(4), piw066.
 [http://dx.doi.org/10.1093/jpids/piw066] [PMID:  28062553]

[36]
Balloux, F.; Brønstad Brynildsrud, O.; van Dorp, L.; Shaw, L.P.; Chen, H.; Harris, K.A.; Wang, H.; Eldholm, V. From Theory to Practice: Translating Whole-Genome Sequencing (WGS) into the Clinic. Trends Microbiol.,  2018, 26(12), 1035-1048.
 [http://dx.doi.org/10.1016/j.tim.2018.08.004] [PMID:  30193960]

[37]
Han, D.; Li, Z.; Li, R.; Tan, P.; Zhang, R.; Li, J. mNGS in clinical microbiology laboratories: On the road to maturity. Crit. Rev. Microbiol.,  2019, 45(5-6), 668-685.
 [http://dx.doi.org/10.1080/1040841X.2019.1681933] [PMID:  31691607]

[38]
Beck, T.F.; Mullikin, J.C.; Biesecker, L.G. Systematic Evaluation of Sanger Validation of Next-Generation Sequencing Variants. Clin. Chem.,  2016, 62(4), 647-654.
 [http://dx.doi.org/10.1373/clinchem.2015.249623] [PMID:  26847218]

[39]
Kalantar, K.L.; Carvalho, T.; de Bourcy, C.F.A.; Dimitrov, B.; Dingle, G.; Egger, R.; Han, J.; Holmes, O.B.; Juan, Y.F.; King, R.; Kislyuk, A.; Lin, M.F.; Mariano, M.; Morse, T.; Reynoso, L.V.; Cruz, D.R.; Sheu, J.; Tang, J.; Wang, J.; Zhang, M.A.; Zhong, E.; Ahyong, V.; Lay, S.; Chea, S.; Bohl, J.A.; Manning, J.E.; Tato, C.M.; DeRisi, J.L. IDseq—An open source cloud-based pipeline and analysis service for metagenomic pathogen detection and monitoring. Gigascience,  2020, 9(10), giaa111.
 [http://dx.doi.org/10.1093/gigascience/giaa111] [PMID:  33057676]

[40]
Chiu, C.Y.; Miller, S.A. Clinical metagenomics. Nat. Rev. Genet.,  2019, 20(6), 341-355.
 [http://dx.doi.org/10.1038/s41576-019-0113-7] [PMID:  30918369]

[41]
Simner, P.J.; Miller, S.; Carroll, K.C. Understanding the Promises and Hurdles of Metagenomic Next-Generation Sequencing as a Diagnostic Tool for Infectious Diseases. Clin. Infect. Dis.,  2018, 66(5), 778-788.
 [http://dx.doi.org/10.1093/cid/cix881] [PMID:  29040428]

[42]
van Dijk, E.L.; Jaszczyszyn, Y.; Thermes, C. Library preparation methods for next-generation sequencing: Tone down the bias. Exp. Cell Res.,  2014, 322(1), 12-20.
 [http://dx.doi.org/10.1016/j.yexcr.2014.01.008] [PMID:  24440557]

[43]
van Griethuysen, J.J.M.; Fedorov, A.; Parmar, C.; Hosny, A.; Aucoin, N.; Narayan, V.; Beets-Tan, R.G.H.; Fillion-Robin, J.C.; Pieper, S.; Aerts, H.J.W.L. Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Res.,  2017, 77(21), e104-e107.
 [http://dx.doi.org/10.1158/0008-5472.CAN-17-0339] [PMID:  29092951]

[44]
Greathouse, K.L.; Sinha, R.; Vogtmann, E. DNA extraction for human microbiome studies: The issue of standardization. Genome Biol.,  2019, 20(1), 212.
 [http://dx.doi.org/10.1186/s13059-019-1843-8] [PMID:  31639026]

[45]
Roy, S.; Coldren, C.; Karunamurthy, A.; Kip, N.S.; Klee, E.W.; Lincoln, S.E.; Leon, A.; Pullambhatla, M.; Temple-Smolkin, R.L.; Voelkerding, K.V.; Wang, C.; Carter, A.B. Standards and Guidelines for Validating Next-Generation Sequencing Bioinformatics Pipelines. J. Mol. Diagn.,  2018, 20(1), 4-27.
 [http://dx.doi.org/10.1016/j.jmoldx.2017.11.003] [PMID:  29154853]

[46]
Duan, H.; Li, X.; Mei, A.; Li, P.; Liu, Y.; Li, X.; Li, W.; Wang, C.; Xie, S. The diagnostic value of metagenomic next-generation sequencing in infectious diseases. BMC Infect. Dis.,  2021, 21(1), 62.
 [http://dx.doi.org/10.1186/s12879-020-05746-5] [PMID:  33435894]

[47]
Wang, J.; Han, Y.; Feng, J. Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis. BMC Pulm. Med.,  2019, 19(1), 252.
 [http://dx.doi.org/10.1186/s12890-019-1022-4] [PMID:  31856779]

[48]
Zheng, Y.; Qiu, X.; Wang, T.; Zhang, J. The Diagnostic Value of Metagenomic Next–Generation Sequencing in Lower Respiratory Tract Infection. Front. Cell. Infect. Microbiol.,  2021, 11, 694756.
 [http://dx.doi.org/10.3389/fcimb.2021.694756] [PMID:  34568089]

[49]
Su, S.; Chen, X.; Zhou, L.; Lin, P.; Chen, J.; Chen, C.; Wu, Q.; Ye, J.; Li, Y. Diagnostic performance of the metagenomic next-generation sequencing in lung biopsy tissues in patients suspected of having a local pulmonary infection. BMC Pulm. Med.,  2022, 22(1), 112.
 [http://dx.doi.org/10.1186/s12890-022-01912-4] [PMID:  35351079]

[50]
Miao, Q.; Ma, Y.; Wang, Q.; Pan, J.; Zhang, Y.; Jin, W.; Yao, Y.; Su, Y.; Huang, Y.; Wang, M.; Li, B.; Li, H.; Zhou, C.; Li, C.; Ye, M.; Xu, X.; Li, Y.; Hu, B. Microbiological Diagnostic Performance of Metagenomic Next-generation Sequencing When Applied to Clinical Practice. Clin. Infect. Dis.,  2018, 67(Suppl. 2), S231-S240.
 [http://dx.doi.org/10.1093/cid/ciy693] [PMID:  30423048]

[51]
Shi, C.L.; Han, P.; Tang, P.J.; Chen, M.M.; Ye, Z.J.; Wu, M.Y.; Shen, J.; Wu, H.Y.; Tan, Z.Q.; Yu, X.; Rao, G.H.; Zhang, J.P. Clinical metagenomic sequencing for diagnosis of pulmonary tuberculosis. J. Infect.,  2020, 81(4), 567-574.
 [http://dx.doi.org/10.1016/j.jinf.2020.08.004] [PMID:  32768450]

[52]
Husain, U.; Tilak, R.; Aggarwal, S.K.; Priyadarshi, K.; Dhameja, N. Time to speed up the diagnostic evaluation in clinically suspected rhinosinusitis patients: A debate on the conventional versus molecular workup to establish fungal infective etiology for prompt management. Curr. Med. Mycol.,  2022, 8(1), 1-6.
 [http://dx.doi.org/10.18502/cmm.8.1.9207] [PMID:  36340434]

[53]
Sun, T.; Wu, X.; Cai, Y.; Zhai, T.; Huang, L.; Zhang, Y.; Zhan, Q. Metagenomic Next-Generation Sequencing for Pathogenic Diagnosis and Antibiotic Management of Severe Community-Acquired Pneumonia in Immunocompromised Adults. Front. Cell. Infect. Microbiol.,  2021, 11, 661589.
 [http://dx.doi.org/10.3389/fcimb.2021.661589] [PMID:  34141628]

[54]
Nwadike, V.U.; Onwah, A.L.; Owolabi, T.A.; Ogunnaike-Quaye, T. Candidaemia in the immunocompromised; a case for early diagnosis/detection and treatment. Jos J Med,  2013, 7(2)

[55]
Arp, M.; Larsen, S.O. Comparison of detection speed and yield in agitated and non‐agitated aerobic blood culture bottles. Acta Pathol. Microbiol. Scand. Suppl.,  1992, 100(7-12), 1061-1065.
 [http://dx.doi.org/10.1111/j.1699-0463.1992.tb04041.x] [PMID:  1492974]

[56]
Sacco, O.; Battistini, E.; Oddera, S.; Silvestri, M.; Pallecchi, A.; Gandolpo, A.; Rossi, G.A. Clinical application of bronchoscopy and bronchoalveolar lavage in the immunocompromised host. Monaldi Arch. Chest Dis.,  1994, 49(3), 217-220.
 [PMID:  8087118]

[57]
Fekkar, A.; Pionneau, C.; Brossas, J.Y.; Marinach-Patrice, C.; Snounou, G.; Brock, M.; Ibrahim-Granet, O.; Mazier, D. DIGE enables the detection of a putative serum biomarker of fungal origin in a mouse model of invasive aspergillosis. J. Proteomics,  2012, 75(9), 2536-2549.
 [http://dx.doi.org/10.1016/j.jprot.2012.01.040] [PMID:  22370163]

[58]
Millon, L.; Larosa, F.; Lepiller, Q.; Legrand, F.; Rocchi, S.; Daguindau, E.; Scherer, E.; Bellanger, A.P.; Leroy, J.; Grenouillet, F. Quantitative polymerase chain reaction detection of circulating DNA in serum for early diagnosis of mucormycosis in immunocompromised patients. Clin. Infect. Dis.,  2013, 56(10), e95-e101.
 [http://dx.doi.org/10.1093/cid/cit094] [PMID:  23420816]

[59]
Barnes, R.A. Early diagnosis of fungal infection in immunocompromised patients. J. Antimicrob. Chemother.,  2008, 61(Suppl. 1), i3-i6.
 [http://dx.doi.org/10.1093/jac/dkm424] [PMID:  18063601]

[60]
Guo, Y.; Li, H.; Chen, H.; Li, Z.; Ding, W.; Wang, J.; Yin, Y.; Jin, L.; Sun, S.; Jing, C.; Wang, H. Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue. EBioMedicine,  2021, 73, 103639.
 [http://dx.doi.org/10.1016/j.ebiom.2021.103639] [PMID:  34700283]

[61]
Fu, M.; Cao, L.J.; Xia, H.L.; Ji, Z.M.; Hu, N.N.; Leng, Z.J.; Xie, W.; Fang, Y.; Zhang, J.Q.; Xia, D.Q. The performance of detecting Mycobacterium tuberculosis complex in lung biopsy tissue by metagenomic next-generation sequencing. BMC Pulm. Med.,  2022, 22(1), 288.
 [http://dx.doi.org/10.1186/s12890-022-02079-8] [PMID:  35902819]

[62]
Wu, X.; Li, Y.; Zhang, M.; Li, M.; Zhang, R.; Lu, X.; Gao, W.; Li, Q.; Xia, Y.; Pan, P.; Li, Q. Etiology of Severe Community-Acquired Pneumonia in Adults Based on Metagenomic Next-Generation Sequencing: A Prospective Multicenter Study. Infect. Dis. Ther.,  2020, 9(4), 1003-1015.
 [http://dx.doi.org/10.1007/s40121-020-00353-y] [PMID:  33170499]

[63]
Peng, J.M.; Du, B.; Qin, H.Y.; Wang, Q.; Shi, Y. Metagenomic next-generation sequencing for the diagnosis of suspected pneumonia in immunocompromised patients. J. Infect.,  2021, 82(4), 22-27.
 [http://dx.doi.org/10.1016/j.jinf.2021.01.029] [PMID:  33609588]

[64]
Lin, M.; Wang, K.; Qiu, L.; Liang, Y.; Tu, C.; Chen, M.; Wang, Z.; Wu, J.; Huang, Y.; Tan, C.; Chen, Q.; Zheng, X.; Liu, J. Tropheryma whipplei detection by metagenomic next-generation sequencing in bronchoalveolar lavage fluid: A cross-sectional study. Front. Cell. Infect. Microbiol.,  2022, 12, 961297.
 [http://dx.doi.org/10.3389/fcimb.2022.961297] [PMID:  36061864]

[65]
Yan, L.; Sun, W.; Lu, Z.; Fan, L. Metagenomic Next-Generation Sequencing (mNGS) in cerebrospinal fluid for rapid diagnosis of Tuberculosis meningitis in HIV-negative population. Int. J. Infect. Dis.,  2020, 96, 270-275.
 [http://dx.doi.org/10.1016/j.ijid.2020.04.048] [PMID:  32339718]

[66]
Buurma, H.A.; Buurma, B.J. The effect of smear layer on bacterial penetration through roots obturated using zinc oxide eugenol-based sealer. BMC Oral Health,  2020, 20(1), 88.
 [http://dx.doi.org/10.1186/s12903-020-01069-8] [PMID:  32216774]

[67]
Zhang, Y.; Cui, P.; Zhang, H.C.; Wu, H.L.; Ye, M.Z.; Zhu, Y.M.; Ai, J.W.; Zhang, W.H. Clinical application and evaluation of metagenomic next-generation sequencing in suspected adult central nervous system infection. J. Transl. Med.,  2020, 18(1), 199.
 [http://dx.doi.org/10.1186/s12967-020-02360-6] [PMID:  32404108]

[68]
Alvarez-Payares, J.C.; Bello-Simanca, J.D.; De La Peña-Arrieta, E.D.J.; Agamez-Gomez, J.E.; Garcia-Rueda, J.E.; Rodriguez-Arrieta, A.; Rodriguez-Arrieta, L.A. Common Pitfalls in the Interpretation of Endocrine Tests. Front. Endocrinol. (Lausanne),  2021, 12, 727628.
 [http://dx.doi.org/10.3389/fendo.2021.727628] [PMID:  34557164]

[69]
Malvagia, S.; Forni, G.; Ombrone, D.; la Marca, G. Development of Strategies to Decrease False Positive Results in Newborn Screening. Int. J. Neonatal Screen.,  2020, 6(4), 84.
 [http://dx.doi.org/10.3390/ijns6040084] [PMID:  33147868]

[70]
Geisler, B.P.; Jilg, N.; Patton, R.G.; Pietzsch, J.B. Model to evaluate the impact of hospital-based interventions targeting false-positive blood cultures on economic and clinical outcomes. J. Hosp. Infect.,  2019, 102(4), 438-444.
 [http://dx.doi.org/10.1016/j.jhin.2019.03.012] [PMID:  30928573]

[71]
Healy, B.; Khan, A.; Metezai, H.; Blyth, I.; Asad, H. The impact of false positive COVID-19 results in an area of low prevalence. Clin. Med. (Lond.),  2021, 21(1), e54-e56.
 [http://dx.doi.org/10.7861/clinmed.2020-0839] [PMID:  33243836]

[72]
Kumar, P.; Gill, R.M.; Phelps, A.; Tulpule, A.; Matthay, K.; Nicolaides, T. Surveillance Screening in Li-Fraumeni Syndrome: Raising Awareness of False Positives. Cureus,  2018, 10(4), e2527.
 [http://dx.doi.org/10.7759/cureus.2527] [PMID:  29946497]

[73]
Dong, B.; He, Z.; Li, Y.; Xu, X.; Wang, C.; Zeng, J. Improved Conventional and New Approaches in the Diagnosis of Tuberculosis. Front. Microbiol.,  2022, 13, 924410.
 [http://dx.doi.org/10.3389/fmicb.2022.924410] [PMID:  35711765]

[74]
Teixeira, H.C.; Abramo, C.; Munk, M.E. Diagnóstico imunológico da tuberculose: Problemas e estratégias para o sucesso. J. Bras. Pneumol.,  2007, 33(3), 323-334.
 [http://dx.doi.org/10.1590/S1806-37132007000300015] [PMID:  17906795]

[75]
Aliannejad, R.; Bahrmand, A. Accuracy of a New Rapid Antigen Detection Test for Pulmonary Tuberculosis. PubMed,  2016, 8(4), 238-242.

Cite As

Current Pharmaceutical Biotechnology

Determination of Ideal Factors for Early Adoption and Standardization of Metagenomic Next-Generation Sequencing for Respiratory System Infections

Abstract