The Pathogen Spectra of Infections with Hematological Diseaes Detected Using Metagenomic Next Generation Sequencing
Background As infection is a common complication and cause of death in hematological disease, early detection of microorganisms causing infections is particularly important for the improvement of prognosis. The newly emerged metagenomic next-generation sequencing (mNGS) technology has the advantages...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Chinese General Practice Publishing House Co., Ltd
2022-08-01
|
| Series: | Zhongguo quanke yixue |
| Subjects: | |
| Online Access: | https://www.chinagp.net/fileup/1007-9572/PDF/zx20220007.pdf |
| _version_ | 1797217194047700992 |
|---|---|
| author | Ruli PANG, Meiqing WU, Zeyan SHI, Yu LIN, Yanyun SU, Baowen ZHOU, Ziwen BAI, Weihua ZHAO |
| author_facet | Ruli PANG, Meiqing WU, Zeyan SHI, Yu LIN, Yanyun SU, Baowen ZHOU, Ziwen BAI, Weihua ZHAO |
| author_sort | Ruli PANG, Meiqing WU, Zeyan SHI, Yu LIN, Yanyun SU, Baowen ZHOU, Ziwen BAI, Weihua ZHAO |
| collection | DOAJ |
| description | Background As infection is a common complication and cause of death in hematological disease, early detection of microorganisms causing infections is particularly important for the improvement of prognosis. The newly emerged metagenomic next-generation sequencing (mNGS) technology has the advantages of simple operation, small sample size required, fast detection, unsusceptible to contamination. Moreover, it has better performance than culture methods in detecting marginal microorganisms. Objective To determine the causes of infections in patients with hematological diseases via analyzing the bacterial and viral pathogen spectra of infections in such patients detected using mNGS, to inform relevant clinical treatment. Methods Participants (n=53) were hematological disease patients who had clinical infections or suspected infections symptoms during the hospitalization in Department of Hematology, the First Affiliated Hospital of Guangxi Medical University from August 2018 to December 2020. Samples collected from them included whole blood, cerebrospinal fluid, pleural effusion, tissue, abdominal drainage fluid, joint fluid, sputum, fluid aspirated by puncture of the right lower extremity. For detecting microorganisms causing infections, mNGS technology was used for all patients (58 samples) , culture was used for 52 patients (55 samples) , G/GM test was used for 46 patients (50 samples) , and PCR test was used for 44 patients (48 samples) as well. Results The bacterial and viral pathogen spectra of infections detected by mNGS technology showed that the most common Gram-positive bacteria were Propionibacterium acnes (42 times) , Staphylococcus epidermidis (33 times) , and Staphylococcus hominis (32 times) , the most common Gram-negative bacteria were Acinetobacter johnsonii (26 times) , Burkholderia vietnamiensis (20 times) , and Burkholderia ubonensis (19 times) , the most common fungus was Malassezia restricta (28 times) , and the most common viruses were Cytomegalovirus (26 times) , Epstein-Barr virus (14 times) and Torque teno virus (19 times) . Toxoplasma gondii was detected in the blood and cerebrospinal fluid of a patient with severe thalassemia after hematopoietic stem cell transplantation. Compared to culture method, G/GM test, and PCR test, mNGS technology had a higher detection rate (P<0.05) . The medication of 6 patients were adjusted according to the detection results of mNGS, and 4 of them were much improved, but the other 2 cases were still poorly treated. Conclusion This study indicates that mNGS technology is contributive to the determination of causes of clinical infections and guidance on treatment in patients with hematological diseases. However, due to possible false positive and false negative rates in the detection by mNGS, mNGS technology is recommended to be used in combination with other detection methods, which could reduce the possibility of misdiagnosis. |
| first_indexed | 2024-04-24T11:57:58Z |
| format | Article |
| id | doaj.art-c0bb152603aa460d9ddb49ba1a398244 |
| institution | Directory Open Access Journal |
| issn | 1007-9572 |
| language | zho |
| last_indexed | 2024-04-24T11:57:58Z |
| publishDate | 2022-08-01 |
| publisher | Chinese General Practice Publishing House Co., Ltd |
| record_format | Article |
| series | Zhongguo quanke yixue |
| spelling | doaj.art-c0bb152603aa460d9ddb49ba1a3982442024-04-09T03:55:13ZzhoChinese General Practice Publishing House Co., LtdZhongguo quanke yixue1007-95722022-08-0125243022302810.12114/j.issn.1007-9572.2022.0007The Pathogen Spectra of Infections with Hematological Diseaes Detected Using Metagenomic Next Generation SequencingRuli PANG, Meiqing WU, Zeyan SHI, Yu LIN, Yanyun SU, Baowen ZHOU, Ziwen BAI, Weihua ZHAO0Hematology Department, the First Affiliated Hospital of Guangxi Medical University, Nanning 530000, ChinaBackground As infection is a common complication and cause of death in hematological disease, early detection of microorganisms causing infections is particularly important for the improvement of prognosis. The newly emerged metagenomic next-generation sequencing (mNGS) technology has the advantages of simple operation, small sample size required, fast detection, unsusceptible to contamination. Moreover, it has better performance than culture methods in detecting marginal microorganisms. Objective To determine the causes of infections in patients with hematological diseases via analyzing the bacterial and viral pathogen spectra of infections in such patients detected using mNGS, to inform relevant clinical treatment. Methods Participants (n=53) were hematological disease patients who had clinical infections or suspected infections symptoms during the hospitalization in Department of Hematology, the First Affiliated Hospital of Guangxi Medical University from August 2018 to December 2020. Samples collected from them included whole blood, cerebrospinal fluid, pleural effusion, tissue, abdominal drainage fluid, joint fluid, sputum, fluid aspirated by puncture of the right lower extremity. For detecting microorganisms causing infections, mNGS technology was used for all patients (58 samples) , culture was used for 52 patients (55 samples) , G/GM test was used for 46 patients (50 samples) , and PCR test was used for 44 patients (48 samples) as well. Results The bacterial and viral pathogen spectra of infections detected by mNGS technology showed that the most common Gram-positive bacteria were Propionibacterium acnes (42 times) , Staphylococcus epidermidis (33 times) , and Staphylococcus hominis (32 times) , the most common Gram-negative bacteria were Acinetobacter johnsonii (26 times) , Burkholderia vietnamiensis (20 times) , and Burkholderia ubonensis (19 times) , the most common fungus was Malassezia restricta (28 times) , and the most common viruses were Cytomegalovirus (26 times) , Epstein-Barr virus (14 times) and Torque teno virus (19 times) . Toxoplasma gondii was detected in the blood and cerebrospinal fluid of a patient with severe thalassemia after hematopoietic stem cell transplantation. Compared to culture method, G/GM test, and PCR test, mNGS technology had a higher detection rate (P<0.05) . The medication of 6 patients were adjusted according to the detection results of mNGS, and 4 of them were much improved, but the other 2 cases were still poorly treated. Conclusion This study indicates that mNGS technology is contributive to the determination of causes of clinical infections and guidance on treatment in patients with hematological diseases. However, due to possible false positive and false negative rates in the detection by mNGS, mNGS technology is recommended to be used in combination with other detection methods, which could reduce the possibility of misdiagnosis.https://www.chinagp.net/fileup/1007-9572/PDF/zx20220007.pdfhematologic diseases|infections|metagenomic next-generation sequencing|noxae|gram-positive bacteria|gram-negative bacteria|fungi|viruses |
| spellingShingle | Ruli PANG, Meiqing WU, Zeyan SHI, Yu LIN, Yanyun SU, Baowen ZHOU, Ziwen BAI, Weihua ZHAO The Pathogen Spectra of Infections with Hematological Diseaes Detected Using Metagenomic Next Generation Sequencing Zhongguo quanke yixue hematologic diseases|infections|metagenomic next-generation sequencing|noxae|gram-positive bacteria|gram-negative bacteria|fungi|viruses |
| title | The Pathogen Spectra of Infections with Hematological Diseaes Detected Using Metagenomic Next Generation Sequencing |
| title_full | The Pathogen Spectra of Infections with Hematological Diseaes Detected Using Metagenomic Next Generation Sequencing |
| title_fullStr | The Pathogen Spectra of Infections with Hematological Diseaes Detected Using Metagenomic Next Generation Sequencing |
| title_full_unstemmed | The Pathogen Spectra of Infections with Hematological Diseaes Detected Using Metagenomic Next Generation Sequencing |
| title_short | The Pathogen Spectra of Infections with Hematological Diseaes Detected Using Metagenomic Next Generation Sequencing |
| title_sort | pathogen spectra of infections with hematological diseaes detected using metagenomic next generation sequencing |
| topic | hematologic diseases|infections|metagenomic next-generation sequencing|noxae|gram-positive bacteria|gram-negative bacteria|fungi|viruses |
| url | https://www.chinagp.net/fileup/1007-9572/PDF/zx20220007.pdf |
| work_keys_str_mv | AT rulipangmeiqingwuzeyanshiyulinyanyunsubaowenzhouziwenbaiweihuazhao thepathogenspectraofinfectionswithhematologicaldiseaesdetectedusingmetagenomicnextgenerationsequencing AT rulipangmeiqingwuzeyanshiyulinyanyunsubaowenzhouziwenbaiweihuazhao pathogenspectraofinfectionswithhematologicaldiseaesdetectedusingmetagenomicnextgenerationsequencing |