Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling
Abstract Background Microbial infections, particularly in children, require rapid and accurate diagnostics. It is difficult to differentiate pathogens from commensal organisms, and it is impossible to identify antibiotic resistance genes that belong to pathogens with current methods. Third‐generatio...
Saved in:
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-12-01
|
| Series: | iLabmed |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ila2.64 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849239023367749632 |
|---|---|
| author | Yunke Sun Xiaonan Li Jiale He Lingguo Zhao Qingliang Chen Lei Lei Jun Chen Lin Zhong Guobao Li Yu Xia Yanmin Bao Yingdan Zhang Liang Yang |
| author_facet | Yunke Sun Xiaonan Li Jiale He Lingguo Zhao Qingliang Chen Lei Lei Jun Chen Lin Zhong Guobao Li Yu Xia Yanmin Bao Yingdan Zhang Liang Yang |
| author_sort | Yunke Sun |
| collection | DOAJ |
| description | Abstract Background Microbial infections, particularly in children, require rapid and accurate diagnostics. It is difficult to differentiate pathogens from commensal organisms, and it is impossible to identify antibiotic resistance genes that belong to pathogens with current methods. Third‐generation sequencing provides rapid library preparation and real‐time data acquisition. Nanopore normal sampling (NNS) enables unbiased sequencing of clinical samples without amplification, aiding pathogen identification and antimicrobial resistance gene prediction. However, clinical samples often contain a considerable amount of human DNA, potentially masking pathogen data. Nanopore adaptive sampling (NAS) aims to selectively enrich pathogens, promising improved diagnostics for acute infections and better treatment decisions in clinical practice. This study aimed to determine the utility of NAS in enhancing the real‐time detection of pathogens and predicting AMR in infectious disease outbreaks. Methods This study used NAS technology to rapidly and directly detect Mycoplasma pneumoniae infection in bronchoalveolar lavage fluid samples from 28 pediatric patients at Shenzhen Children's Hospital. We assessed the efficacy of NAS compared with that of NNS by evaluating the number of microbial reads and the amount of microbial DNA data. We then compared the accuracy of detecting pathogens between NNS and NAS and between NAS and real‐time polymerase chain reaction assays. Furthermore, we predicted antimicrobial resistance (AMR) and examined AMR genes associated with pathogens. Results NAS showed up to a 14.67‐fold increase in the amount of microbial DNA data from patients' samples compared with NNS within the initial 2.5 h of sequencing. Additionally, NAS reduced the amount of host DNA data by up to 6.67‐fold compared with NNS. Unlike TaqMan real‐time polymerase chain reaction assays, NAS technology identified dominant pathogens and provided detailed insight into the abundance of the microbial community. Furthermore, NAS was able to predict AMR profiles of microbial communities and attribute specific AMR traits to individual microbes within the samples. Conclusion This study shows that NAS advances the clinical diagnosis because it can rapidly detect pathogens directly from patients' samples and provides antimicrobial resistance information for clinical guidance. These abilities further facilitate the application of NAS in personalized treatment, reduce the misuse of broad‐spectrum antibiotics, and promote patients' recovery. |
| format | Article |
| id | doaj-art-5446da82f1b641babe53c4c8bacedf1e |
| institution | Kabale University |
| issn | 2834-443X 2834-4448 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | iLabmed |
| spelling | doaj-art-5446da82f1b641babe53c4c8bacedf1e2025-08-20T04:01:16ZengWileyiLabmed2834-443X2834-44482024-12-012426627610.1002/ila2.64Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive samplingYunke Sun0Xiaonan Li1Jiale He2Lingguo Zhao3Qingliang Chen4Lei Lei5Jun Chen6Lin Zhong7Guobao Li8Yu Xia9Yanmin Bao10Yingdan Zhang11Liang Yang12Joint Laboratory of Guangdong‐Hong Kong Universities for Vascular Homeostasis and Diseases School of Medicine Southern University of Science and Technology Shenzhen Guangdong ChinaDepartment of Respiratory Diseases Shenzhen Children's Hospital Shenzhen Guangdong ChinaJoint Laboratory of Guangdong‐Hong Kong Universities for Vascular Homeostasis and Diseases School of Medicine Southern University of Science and Technology Shenzhen Guangdong ChinaBao'an District Center for Disease Control and Prevention of Shenzhen City Shenzhen Guangdong ChinaBao'an District Center for Disease Control and Prevention of Shenzhen City Shenzhen Guangdong ChinaBao'an District Center for Disease Control and Prevention of Shenzhen City Shenzhen Guangdong ChinaShenzhen Third People's Hospital The Second Affiliated Hospital of Southern University of Science and Technology Shenzhen Guangdong ChinaShenzhen Third People's Hospital The Second Affiliated Hospital of Southern University of Science and Technology Shenzhen Guangdong ChinaShenzhen Third People's Hospital The Second Affiliated Hospital of Southern University of Science and Technology Shenzhen Guangdong ChinaSchool of Environmental Science & Engineering Southern University of Science and Technology Shenzhen Guangdong ChinaDepartment of Respiratory Diseases Shenzhen Children's Hospital Shenzhen Guangdong ChinaJoint Laboratory of Guangdong‐Hong Kong Universities for Vascular Homeostasis and Diseases School of Medicine Southern University of Science and Technology Shenzhen Guangdong ChinaJoint Laboratory of Guangdong‐Hong Kong Universities for Vascular Homeostasis and Diseases School of Medicine Southern University of Science and Technology Shenzhen Guangdong ChinaAbstract Background Microbial infections, particularly in children, require rapid and accurate diagnostics. It is difficult to differentiate pathogens from commensal organisms, and it is impossible to identify antibiotic resistance genes that belong to pathogens with current methods. Third‐generation sequencing provides rapid library preparation and real‐time data acquisition. Nanopore normal sampling (NNS) enables unbiased sequencing of clinical samples without amplification, aiding pathogen identification and antimicrobial resistance gene prediction. However, clinical samples often contain a considerable amount of human DNA, potentially masking pathogen data. Nanopore adaptive sampling (NAS) aims to selectively enrich pathogens, promising improved diagnostics for acute infections and better treatment decisions in clinical practice. This study aimed to determine the utility of NAS in enhancing the real‐time detection of pathogens and predicting AMR in infectious disease outbreaks. Methods This study used NAS technology to rapidly and directly detect Mycoplasma pneumoniae infection in bronchoalveolar lavage fluid samples from 28 pediatric patients at Shenzhen Children's Hospital. We assessed the efficacy of NAS compared with that of NNS by evaluating the number of microbial reads and the amount of microbial DNA data. We then compared the accuracy of detecting pathogens between NNS and NAS and between NAS and real‐time polymerase chain reaction assays. Furthermore, we predicted antimicrobial resistance (AMR) and examined AMR genes associated with pathogens. Results NAS showed up to a 14.67‐fold increase in the amount of microbial DNA data from patients' samples compared with NNS within the initial 2.5 h of sequencing. Additionally, NAS reduced the amount of host DNA data by up to 6.67‐fold compared with NNS. Unlike TaqMan real‐time polymerase chain reaction assays, NAS technology identified dominant pathogens and provided detailed insight into the abundance of the microbial community. Furthermore, NAS was able to predict AMR profiles of microbial communities and attribute specific AMR traits to individual microbes within the samples. Conclusion This study shows that NAS advances the clinical diagnosis because it can rapidly detect pathogens directly from patients' samples and provides antimicrobial resistance information for clinical guidance. These abilities further facilitate the application of NAS in personalized treatment, reduce the misuse of broad‐spectrum antibiotics, and promote patients' recovery.https://doi.org/10.1002/ila2.64antimicrobial resistanceMycoplasma pneumoniananopore adaptive sampling |
| spellingShingle | Yunke Sun Xiaonan Li Jiale He Lingguo Zhao Qingliang Chen Lei Lei Jun Chen Lin Zhong Guobao Li Yu Xia Yanmin Bao Yingdan Zhang Liang Yang Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling iLabmed antimicrobial resistance Mycoplasma pneumonia nanopore adaptive sampling |
| title | Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling |
| title_full | Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling |
| title_fullStr | Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling |
| title_full_unstemmed | Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling |
| title_short | Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling |
| title_sort | rapid diagnosis of mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling |
| topic | antimicrobial resistance Mycoplasma pneumonia nanopore adaptive sampling |
| url | https://doi.org/10.1002/ila2.64 |
| work_keys_str_mv | AT yunkesun rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT xiaonanli rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT jialehe rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT lingguozhao rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT qingliangchen rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT leilei rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT junchen rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT linzhong rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT guobaoli rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT yuxia rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT yanminbao rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT yingdanzhang rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling AT liangyang rapiddiagnosisofmycoplasmapneumoniaeandpredictionofantibioticresistancebynanoporeadaptivesampling |