Large-scale Hand, Foot, and Mouth Disease (HFMD) outbreaks have frequently occurred in China since 2008, affecting more than one million children and causing several hundred children deaths every year. The pathogens of HFMD are mainly human enteroviruses (HEVs). Among them, human enterovirus 71 (HEV71) and coxsackievirus A16 (CVA16) are the most common pathogens of HFMD. However, other HEVs could also cause HFMD. To rapidly detect HEV71 and CVA16, and ensure detection of all HEVs causing HFMD, two real-time hybridization probe-based RT-PCR assays were developed in this study. One is a multiplex real-time RT-PCR assay, which was developed to detect and differentiate HEV71 specifically from CVA16 directly from clinical specimens within 1–2 h, and the other is a broad-spectrum real-time RT-PCR assay, which targeted almost all HEVs. The experiments confirmed that the two assays have high sensitivity and specificity, and the sensitivity was up to 0.1 TCID50/ml for detection of HEVs, HEV71, and CVA16, respectively. A total of 213 clinical specimens were simultaneously detected by three kinds of assays, including the two real-time RT-PCR assays, direct conventional RT-PCR assay, and virus isolation assay on human rhabdomyosarcoma cells (RD cells). The total positive rate of both HEV71 and CVA16 was 69.48% with real-time RT-PCR assay, 47.42% with RT-PCR assay, and 34.58% with virus isolation assay. One HFMD clinical specimen was positive for HEV, but negative for HEV71 or CVA16, which was identified as Echovirus 11 (Echo11) by virus isolation, RT-PCR, and sequencing for the VP1 gene. The two real-time RT-PCR assays had been applied in 31 provincial HFMD labs to detect the pathogens of HFMD, which has contributed to the rapid identification of the pathogens in the early stages of HFMD outbreaks, and helped to clarify the etiologic agents of HFMD in China.
West Nile virus (WNV) causes a severe zoonosis, which can lead to a large number of casualties and considerable economic losses. A rapid and accurate identification method for WNV for use in field laboratories is urgently needed. Here, a method utilizing reverse transcription loop-mediated isothermal amplification combined with a vertical flow visualization strip (RT-LAMP-VF) was developed to detect the envelope (E) gene of WNV. The RT-LAMP-VF assay could detect 102 copies/μl of an WNV RNA standard using a 40 min amplification reaction followed by a 2 min incubation of the amplification product on the visualization strip, and no cross-reaction with other closely related members of the Flavivirus genus was observed. The assay was further evaluated using cells and mouse brain tissues infected with a recombinant rabies virus expressing the E protein of WNV. The assay produced sensitivities of 101.5 TCID50/ml and 101.33 TCID50/ml for detection of the recombinant virus in the cells and brain tissues, respectively. Overall, the RT-LAMP-VF assay developed in this study is rapid, simple and effective, and it is therefore suitable for clinical application in the field.
the diversity of pathogens associated with acute respiratory infection (ARi) makes diagnosis challenging. traditional pathogen screening tests have a limited detection range and provide little additional information. We used total RNA sequencing ("meta-transcriptomics") to reveal the full spectrum of microbes associated with paediatric ARI. Throat swabs were collected from 48 paediatric ARI patients and 7 healthy controls. Samples were subjected to meta-transcriptomics to determine the presence and abundance of viral, bacterial, and eukaryotic pathogens, and to reveal mixed infections, pathogen genotypes/subtypes, evolutionary origins, epidemiological history, and antimicrobial resistance. We identified 11 RNA viruses, 4 DNA viruses, 4 species of bacteria, and 1 fungus. While most are known to cause ARIs, others, such as echovirus 6, are rarely associated with respiratory disease. Co-infection of viruses and bacteria and of multiple viruses were commonplace (9/48), with one patient harboring 5 different pathogens, and genome sequence data revealed large intra-species diversity. Expressed resistance against eight classes of antibiotic was detected, with those for MLS, Bla, Tet, Phe at relatively high abundance. In summary, we used a simple total RNA sequencing approach to reveal the complex polymicrobial infectome in ARi. this provided comprehensive and clinically informative information relevant to understanding respiratory disease.Acute respiratory infections (ARI) are a leading cause of morbidity and mortality in newborns and young children, who experience an average of 3 to 6 ARIs annually 1-3 . Identifying the diversity of pathogens responsible for ARIs remains challenging because they involve a diverse set of viruses, bacteria, and fungal pathogens, with co-infection among them commonplace 4,5 . Traditional testing methods such as PCR, serological typing, bacterial culture and antibody detection, are regarded as the "gold standard" and widely used in ARI diagnosis 6,7 . However, despite an ongoing effort to include multiple pathogens in a single assay 8,9 , it remains difficult to simultaneously identify all potential ARI pathogens and capture new or uncommon respiratory pathogens 10 .Metagenomic next-generation sequencing (mNGS) is an unbiased way of discovering a broad range of infectious agents 11-13 , and has been recently introduced into clinical research to investigate the microbial cause of unusual disease cases 14 , perform broad-scale surveys for pathogens in undiagnosed diseases 15,16 , and understand the role of opportunistic infections 17,18 . For example, a study of severe pneumonia revealed that mNGS is both efficient and reliable 19,20 . Importantly, the utility of mNGS goes beyond pathogen identification. In particular, total RNA sequencing ("meta-transcriptomics") has successfully revealed the entire "infectome" (viruses, bacteria and eukaryotes) present within an organism and provided relevant data on genome sequence, gene expression, open Scientific RepoRtS | (2020) 10:3963 | https://doi.o...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.