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Zhenyu Cheng

Publications and source records attributed to Zhenyu Cheng.

2 recordsLinked to original sources

Alternative quadruplex real-time PCR reactions for detection and discrimination of Streptococcus pneumoniae serotypes within serogroup 6.

UNLABELLED: Streptococcus pneumoniae causes significant morbidity and mortality worldwide, and serotyping is important to assess the burden of disease that is vaccine preventable. For serotyping, the Centers for Disease Control and Prevention (CDC) use a series of 12 real-time multiplex PCRs (rmPCRs) performed in quadruplex reactions; however, rmPCR reaction 5 (rmPCR-5) for serotypes 6A, 6B, 6C, and 6D often failed at low DNA concentrations. This study investigated the cause of rmPCR-5 failure and provided alternative rmPCRs to resolve this issue. Quadruplex rmPCR target sequences were compared to S. pneumoniae reference genomes. Reactions rmPCR-5 [6ABCD, 6AB, 6BD, and 6CD] and rm-PCR-11 [37, 10F, 11BC, and 18CFBA] were compared to alternative reactions rmPCR-A1 [6ABCD, 10F, 11BC, and 18CFBA] and rmPCR-A2 [37, 6AB, 6BD, and 6CD]. All rmPCRs were tested using 10-fold serial dilutions of DNA from representative serotypes, and analytical specificity was assessed using DNA from other S. pneumoniae serotypes or various streptococci and Gram-positive cocci. Failure of rmPCR-5 was associated with overlapping 6ABCD and 6BD targets. Separation of these targets in the alternative rmPCRs-A1 and rmPCR-A2 allowed sensitive and specific detection and discrimination of serotypes 6A, 6B, 6C, and 6D, without impacting the detection of serotypes 10F, 11BC, 18CFBA, and 37. This study highlights the importance of rigorous author and peer-review to avoid manuscript errors and unintended consequences. By explaining what caused rmPCR-5 failure and proposing alternative reactions rmPCRs-A1 and rmPCR-A2, this study demonstrates the value of scientific collaboration to ensure molecular assays best serve the scientific community. IMPORTANCE: Streptococcus pneumoniae is a bacterium that can cause life-threatening infections like pneumonia and meningitis, leading to millions of deaths worldwide each year. A key feature enabling S. pneumoniae to cause disease is its sugar coating, allowing it to avoid the immune system. These surface sugars are the target of S. pneumoniae vaccines. However, vaccines only protect against some sugars and understanding which ones are on the surface of S. pneumoniae is called "serotyping." The Centers for Disease Control and Prevention (CDC) have protocols that allow us to predict S. pneumoniae serotypes by looking at its DNA. We found errors in the CDC protocols and provided a simple solution to fix them. Ultimately, having accurate serotyping protocols allows us to know how much disease is preventable by vaccine, allows us to monitor how well vaccine are working, and helps develop new vaccines if needed.

Streptococcus pneumoniae

HSDSnake: a user-friendly SnakeMake pipeline for analysis of duplicate genes in eukaryotic genomes.

SUMMARY: Gene duplication is a well-known driver of molecular evolution-it acts as a source of genetic novelty, thereby providing the raw substrate for organismal adaption. However, detecting different types of gene duplicates and comparing them in sequence datasets can be difficult. Existing tools can identify and classify gene duplicates that have arisen by various processes, but have limitations; for example, some do not have a user-friendly workflow and can include many intermediate steps requiring manual adjustments of parameters and/or are not maintained for the benefit of research community members. Here, we have developed HSDSnake, a user-friendly SnakeMake pipeline that can detect and classify gene duplications into five categories: dispersed, proximal, tandem, transposed, and whole genome. It also curates and evaluates the highly similar gene duplicates (HSDs) in each gene duplication category with reliance on both sequence similarity and conserved domains. Lastly, the detected gene duplicates can be visualized within a KEGG functional pathway framework and the substitution rates (Ka, Ks, and their Ka/Ks ratio) can be analyzed for all the duplicate gene pairs. We demonstrate HSDSnake's capabilities by analyzing two reference genomes directly downloaded from NCBI and provide detailed instructions for each step. AVAILABILITY AND IMPLEMENTATION: The HSDSnake pipeline uses SnakeMake and Conda to run and install dependencies. The distribution version is available online at GitHub: https://github.com/zx0223winner/HSDSnake and the archived version at Zenodo is https://doi.org/10.5281/zenodo.15521945.

Software