Establishment of an A/T-Rich Specifically MGB Probe digital droplet PCR Assays Based on SNP for Brucella wild strains and vaccine strains

Li, Wanyang; Zhang, Shuai; Dang, Sheng; Gao, Lanzhu; Li, Guangchen; Cheng, Dawei; Jiang, Longguang; Huang, Tianpeng; Zhai, Jingbo

doi:10.1016/j.diagmicrobio.2024.116432

Cited by 2 publications

References 37 publications

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VaxLLM: Leveraging Fine-tuned Large Language Model for automated annotation ofBrucellaVaccines

Li,

Zheng,

et al. 2024

Preprint

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BackgroundVaccines play a vital role in enhancing immune defense and preventing the hosts against a wide range of diseases. However, research relating to vaccine annotation remains a labor-intensive task due to the ever-increasing volume of scientific literature. This study explores the application of Large Language Models (LLMs) to automate the classification and annotation of scientific literature on vaccines as exemplified onBrucellavaccines.ResultsWe developed an automatic pipeline to automatically perform the classification and annotation ofBrucellavaccine-related articles, using abstract and title. The pipeline includes VaxLLM (Vaccine Large Language Model), which is a fine-tuned Llama 3 model. VaxLLM systematically classifies articles by identifying the presence of vaccine formulations and extracts the key information about vaccines, including vaccine antigen, vaccine formulation, vaccine platform, host species used as animal models, and experiments used to investigate the vaccine. The model demonstrated high performance in classification (Precision: 0.90, Recall: 1.0, F1-Score: 0.95) and annotation accuracy (97.9%), significantly outperforming a corresponding non-fine-tuned Llama 3 model. The outputs from VaxLLM are presented in a structured format to facilitate the integration into databases such as the VIOLIN vaccine knowledgebase. To further enhance the accuracy and depth of theBrucellavaccine data annotations, the pipeline also incorporates PubTator, enabling cross comparison with VaxLLM annotations and supporting downstream analyses like gene enrichment.ConclusionVaxLLM rapidly and accurately extracted detailed itemized vaccine information from publications, significantly outperforming traditional annotation methods in both speed and precision. VaxLLM also shows great potential in automating knowledge extraction in the domain of vaccine research.AvailabilityAll data is available athttps://github.com/xingxianli/VaxLLM, and the model was also uploaded to HuggingFace (https://huggingface.co/Xingxian123/VaxLLM).

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VaxLLM: Leveraging Fine-tuned Large Language Model for automated annotation ofBrucellaVaccines

Li,

Zheng,

et al. 2024

Preprint

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Development and application of a quadruplex TaqMan real-time fluorescence quantitative PCR assay for four porcine digestive pathogens

Wang,

Sun,

Chen

et al. 2024

Front. Cell. Infect. Microbiol.

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IntroductionSalmonella, Escherichia coli, Lawsonella intracellularis, and Brachyspira hyodysenteriae are the primary pathogens responsible for gastrointestinal diseases in pigs, posing a significant threat to the health and productivity of pig production systems. Pathogen detection is a crucial tool for monitoring and managing these infections.MethodsWe designed primers and probes targeting the invA gene of Salmonella, the 23S rRNA gene of Escherichia coli, the aspA gene of Lawsonella intracellularis, and the nox gene of Brachyspira hyodysenteriae. We developed a quadruplex TaqMan real-time quantitative PCR assay capable of simultaneously detecting these four pathogens.ResultsThis assay demonstrated high sensitivity, with detection limits of 100 copies/μL for the recombinant plasmid standards pEASY-23S rRNA, pEASY-aspA, and pEASY-nox, and 10 copies/μL for pEASY-invA. The standard curves exhibited excellent linearity (R2 values of 0.999, 0.999, 1, and 0.998, respectively) and high amplification efficiencies (93.57%, 94.84%, 85.15%, and 81.81%, respectively). The assay showed high specificity, with no cross-reactivity detected against nucleic acids from Streptococcus suis, porcine epidemic diarrhoea virus (PEDV), porcine transmissible gastroenteritis virus (TGEV), Pasteurella multocida, Clostridium perfringens, Gracilaria parapsilosis, porcine delta coronavirus (PDCoV), porcine group A rotavirus (GARV), and porcine teschovirus (PTV). The assay also exhibited excellent repeatability, with inter- and intra-assay coefficient of variation (CV) ranging from 0.15% to 1.12%. High concentrations of nucleic acids did not interfere with the detection of low concentrations, ensuring robust performance in complex samples. Among 263 diarrhoeic samples, the assay detected Salmonella in 23.95%, Escherichia coli in 26.24%, Lawsonella intracellularis in 33.84%, and Brachyspira hyodysenteriae in 22.43%.DiscussionThis quadruplex TaqMan qPCR assay offers a rapid, sensitive, and specific tool for the simultaneous detection of Salmonella, Escherichia coli, Lawsonella intracellularis, and Brachyspira hyodysenteriae in pigs.

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Establishment of an A/T-Rich Specifically MGB Probe digital droplet PCR Assays Based on SNP for Brucella wild strains and vaccine strains

Cited by 2 publications

References 37 publications

VaxLLM: Leveraging Fine-tuned Large Language Model for automated annotation ofBrucellaVaccines

VaxLLM: Leveraging Fine-tuned Large Language Model for automated annotation ofBrucellaVaccines

Development and application of a quadruplex TaqMan real-time fluorescence quantitative PCR assay for four porcine digestive pathogens

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