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Zhou Y, Yu H, Zhao X, Ni J, Gan S, Dong W, Du J, Zhou X, Wang X, Song H. Detection and differentiation of seven porcine respiratory pathogens using a multiplex ligation-dependent probe amplification assay. Vet J 2024; 305:106124. [PMID: 38653339 DOI: 10.1016/j.tvjl.2024.106124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 03/27/2024] [Accepted: 04/18/2024] [Indexed: 04/25/2024]
Abstract
Respiratory diseases due to viral or bacterial agents, either alone or in combination, cause substantial economic burdens to the swine industry worldwide. Rapid and reliable detection of causal pathogens is crucial for effective epidemiological surveillance and disease management. This research aimed to employ the multiplex ligation-dependent probe amplification (MLPA) assay for simultaneous detection of seven distinct pathogens causing respiratory problems in swine, porcine reproductive and respiratory syndrome virus (PRRSV), swine influenza virus (SIV), porcine respiratory coronavirus (PRCV), porcine circovirus type 2 (PCV2), Pasteurella multocida, Actinobacillus pleuropneumoniae, and Glässerella parasuis. The results indicated no probe cross-reactivity among the seven target agents with other swine pathogens. The detection limits ranged from 5 to 34 copies per assay for the target organisms. The MLPA assay was evaluated with 88 samples and compared to real-time or multiplex PCR for the target pathogens. The MLPA assay demonstrated high relative test sensitivities (100 %) and reasonable to good relative specificities at 62.5 %, 95.1 %, 86.8 %, and 97.6 % for PRRSV, P. multocida, G. parasuis, and PCV2, respectively, relative to comparator PCR assays. In 71 samples where MLPA and comparator PCR assays matched exactly, infections were detected in 64 samples (90.1 %), with PRRSV being the most commonly found virus and 50.7 % of the samples showing co-infection with two to five of the pathogens. This approach serves as a valuable tool for conducting differential diagnoses and epidemiological investigations of pathogen prevalence within swine populations.
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Affiliation(s)
- Yingshan Zhou
- Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics and Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology and College of Veterinary Medicine of Zhejiang A and F University, 666 Wusu St., Lin'an District, Hangzhou, Zhejiang Province 311300, China
| | - Haoran Yu
- Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics and Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology and College of Veterinary Medicine of Zhejiang A and F University, 666 Wusu St., Lin'an District, Hangzhou, Zhejiang Province 311300, China
| | - Xiuling Zhao
- Ningbo Key Laboratory of Port Biological and Food Safety Testing, Technical Center of Ningbo Customs, Ningbo, Zhejiang Province 315000, China
| | - Jianbo Ni
- Ningbo Key Laboratory of Port Biological and Food Safety Testing, Technical Center of Ningbo Customs, Ningbo, Zhejiang Province 315000, China
| | - Shiqi Gan
- Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics and Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology and College of Veterinary Medicine of Zhejiang A and F University, 666 Wusu St., Lin'an District, Hangzhou, Zhejiang Province 311300, China
| | - Wanyu Dong
- Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics and Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology and College of Veterinary Medicine of Zhejiang A and F University, 666 Wusu St., Lin'an District, Hangzhou, Zhejiang Province 311300, China
| | - Jing Du
- Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics and Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology and College of Veterinary Medicine of Zhejiang A and F University, 666 Wusu St., Lin'an District, Hangzhou, Zhejiang Province 311300, China
| | - Xingdong Zhou
- Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics and Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology and College of Veterinary Medicine of Zhejiang A and F University, 666 Wusu St., Lin'an District, Hangzhou, Zhejiang Province 311300, China
| | - Xiaodu Wang
- Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics and Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology and College of Veterinary Medicine of Zhejiang A and F University, 666 Wusu St., Lin'an District, Hangzhou, Zhejiang Province 311300, China.
| | - Houhui Song
- Key Laboratory of Applied Technology on Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Zhejiang Provincial Engineering Research Center for Animal Health Diagnostics and Advanced Technology, Zhejiang International Science and Technology Cooperation Base for Veterinary Medicine and Health Management, China-Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology and College of Veterinary Medicine of Zhejiang A and F University, 666 Wusu St., Lin'an District, Hangzhou, Zhejiang Province 311300, China.
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Shin J, Shin S, Jung SH, Park C, Cho SY, Lee DG, Chung YJ. Duplex dPCR System for Rapid Identification of Gram-Negative Pathogens in the Blood of Patients with Bloodstream Infection: A Culture-Independent Approach. J Microbiol Biotechnol 2021; 31:1481-1489. [PMID: 34528911 PMCID: PMC9705831 DOI: 10.4014/jmb.2103.03044] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 08/17/2021] [Accepted: 09/09/2021] [Indexed: 12/15/2022]
Abstract
Early and accurate detection of pathogens is important to improve clinical outcomes of bloodstream infections (BSI), especially in the case of drug-resistant pathogens. In this study, we aimed to develop a culture-independent digital PCR (dPCR) system for multiplex detection of major sepsiscausing gram-negative pathogens and antimicrobial resistance genes using plasma DNA from BSI patients. Our duplex dPCR system successfully detected nine targets (five bacteria-specific targets and four antimicrobial resistance genes) through five reactions within 3 hours. The minimum detection limit was 50 ag of bacterial DNA, suggesting that 1 CFU/ml of bacteria in the blood can be detected. To validate the clinical applicability, cell-free DNA samples from febrile patients were tested with our system and confirmed high consistency with conventional blood culture. This system can support early identification of some drug-resistant gram-negative pathogens, which can help improving treatment outcomes of BSI.
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Affiliation(s)
- Juyoun Shin
- Department of Microbiology, The Catholic University of Korea, College of Medicine, Seoul 06591, Republic of Korea
| | - Sun Shin
- Precision Medicine Research Center, Integrated Research Center for Genome Polymorphism, The Catholic University of Korea, College of Medicine, Seoul 06591, Republic of Korea
| | - Seung-Hyun Jung
- Department of Biochemistry, The Catholic University of Korea, College of Medicine, Seoul 06591, Republic of Korea
| | - Chulmin Park
- Vaccine Bio Research Institute, The Catholic University of Korea, College of Medicine, Seoul St. Mary’s Hospital, Seoul 06591, Republic of Korea
| | - Sung-Yeon Cho
- Vaccine Bio Research Institute, The Catholic University of Korea, College of Medicine, Seoul St. Mary’s Hospital, Seoul 06591, Republic of Korea,Department of Internal Medicine, The Catholic University of Korea, College of Medicine, Seoul St. Mary’s Hospital, Seoul 06591, Republic of Korea
| | - Dong-Gun Lee
- Vaccine Bio Research Institute, The Catholic University of Korea, College of Medicine, Seoul St. Mary’s Hospital, Seoul 06591, Republic of Korea,Department of Internal Medicine, The Catholic University of Korea, College of Medicine, Seoul St. Mary’s Hospital, Seoul 06591, Republic of Korea
| | - Yeun-Jun Chung
- Department of Microbiology, The Catholic University of Korea, College of Medicine, Seoul 06591, Republic of Korea,Precision Medicine Research Center, Integrated Research Center for Genome Polymorphism, The Catholic University of Korea, College of Medicine, Seoul 06591, Republic of Korea,Corresponding author Phone: +82-2-2258-7343 Fax: +82-2-537-0572 E-mail:
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Dong XM, Xu NN, Yao YY, Guan YY, Li QY, Zheng F, Chen FZ, Wang G. The Efficacy and Safety of High-dose Daptomycin in the Treatment of Complicated Skin and Soft Tissue Infections in Asians. Int J Infect Dis 2020; 95:38-43. [PMID: 32251792 DOI: 10.1016/j.ijid.2020.03.060] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 03/18/2020] [Accepted: 03/24/2020] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE To compare the efficacy and safety of standard-dose (SD) daptomycin with those of high-dose (HD) daptomycin in complicated skin and soft tissue infections (cSSTIs) in an Asian population. MATERIALS AND METHODS Patients from three medical centers diagnosed with cSSTIs were screened in the clinical information system. Patients included in the analysis were divided into two groups: those who received daptomycin at doses ≥ 6 mg/kg (HD group) and those receiving 4 mg/kg (SD group). The demographics and clinical treatment information were analyzed. RESULTS Overall, 155 patients were recruited, including 108 patients in the SD group and 47 patients in the HD group. The rate of healthcare-associated infections was higher in the HD group (61.70% vs. 37.04%), demonstrating a statistically significant difference (P = 0.005). Compared with the SD group, the HD group had statistically significant early clinical stabilization (72.34% vs 52.78%, P = 0.023). The results of the multivariate analysis indicated that HD daptomycin was an independent effector for early clinical stabilization (HR=0.394, P < 0.001). The rate of drug-related adverse events was equally distributed in the HD and SD groups (36.17% vs. 26.85%, P = 0.243). CONCLUSION Compared with SD daptomycin, HD daptomycin increased the rate of early clinical stabilization in Asian patients with cSSTIs, whereas the incidence of adverse events did not increase.
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Affiliation(s)
- Xiao-Meng Dong
- Department of Infectious Diseases, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Nan-Nan Xu
- Department of Infectious Diseases, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Yong-Yuan Yao
- Department of Intensive Care Medicine, Rizhao People's Hospital, Rizhao 276800, China
| | - Yan-Yan Guan
- Department of Infectious Diseases, Rizhao People's Hospital, Rizhao 276800, China
| | - Qing-Yan Li
- Department of Infectious Diseases, Liaocheng People's Hospital, Liaocheng 252000, China
| | - Feng Zheng
- Department of Infectious Diseases, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Feng-Zhe Chen
- Department of Infectious Diseases, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Gang Wang
- Department of Infectious Diseases, Qilu Hospital of Shandong University, Jinan 250012, China.
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Chung B, Park C, Cho SY, Shin J, Shin S, Yim SH, Lee DG, Chung YJ. Multiplex identification of sepsis-causing Gram-negative pathogens from the plasma of infected blood. Electrophoresis 2017; 39:645-652. [PMID: 29193166 DOI: 10.1002/elps.201700405] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Accepted: 11/16/2017] [Indexed: 11/09/2022]
Abstract
Early and accurate detection of bacterial pathogens in the blood is the most crucial step for sepsis management. Gram-negative bacteria are the most common organisms causing severe sepsis and responsible for high morbidity and mortality. We aimed to develop a method for rapid multiplex identification of clinically important Gram-negative pathogens and also validated whether our system can identify Gram-negative pathogens with the cell-free plasm DNA from infected blood. We designed five MLPA probe sets targeting the genes specific to major Gram-negative pathogens (uidA and lacY for E. coli, ompA for A. baumannii, phoE for K. pneumoniae, and ecfX for P. aeruginosa) and one set targeting the CTX-M group 1 to identify the ESBL producing Gram-negative pathogens. All six target-specific peaks were clearly separated without any non-specific peaks in a multiplex reaction condition. The minimum detection limit was 100 fg of pathogen DNA. When we tested 28 Gram-negative clinical isolates, all of them were successfully identified without any non-specific peaks. To evaluate the clinical applicability, we tested seven blood samples from febrile patients. Three blood culture positive cases showed E. coli specific peaks, while no peak was detected in the other four culture negative samples. This technology can be useful for detection of major sepsis-causing, drug-resistant Gram-negative pathogens and also the major ESBL producing Gram-negatives from the blood of sepsis patients in a clinical setting. This system can help early initiation of effective antimicrobial treatment against Gram-negative pathogens for sepsis patients, which is very crucial for better treatment outcomes.
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Affiliation(s)
- Boram Chung
- Department of Microbiology, The Catholic University of Korea, College of Medicine, Seoul, Republic of Korea.,Precision Medicine Research Center, Integrated Research Center for Genome Polymorphism, The Catholic University of Korea, College of Medicine, Seoul, Republic of Korea
| | - Chulmin Park
- Vaccine Bio Research Institute, The Catholic University of Korea, College of Medicine, Seoul St. Mary's Hospital, Seoul, Republic of Korea
| | - Sung-Yeon Cho
- Vaccine Bio Research Institute, The Catholic University of Korea, College of Medicine, Seoul St. Mary's Hospital, Seoul, Republic of Korea.,Department of Internal Medicine, The Catholic University of Korea, College of Medicine, Seoul St. Mary's Hospital, Seoul, Republic of Korea
| | - Juyoun Shin
- Department of Microbiology, The Catholic University of Korea, College of Medicine, Seoul, Republic of Korea
| | - Sun Shin
- Department of Microbiology, The Catholic University of Korea, College of Medicine, Seoul, Republic of Korea.,Precision Medicine Research Center, Integrated Research Center for Genome Polymorphism, The Catholic University of Korea, College of Medicine, Seoul, Republic of Korea
| | - Seon-Hee Yim
- Precision Medicine Research Center, Integrated Research Center for Genome Polymorphism, The Catholic University of Korea, College of Medicine, Seoul, Republic of Korea
| | - Dong-Gun Lee
- Vaccine Bio Research Institute, The Catholic University of Korea, College of Medicine, Seoul St. Mary's Hospital, Seoul, Republic of Korea.,Department of Internal Medicine, The Catholic University of Korea, College of Medicine, Seoul St. Mary's Hospital, Seoul, Republic of Korea
| | - Yeun-Jung Chung
- Department of Microbiology, The Catholic University of Korea, College of Medicine, Seoul, Republic of Korea.,Precision Medicine Research Center, Integrated Research Center for Genome Polymorphism, The Catholic University of Korea, College of Medicine, Seoul, Republic of Korea
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