Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, United States.
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, United States; Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, 21205, United States; Institute of NanoBioTechnology, Johns Hopkins University, Baltimore, MD, 21218, United States.
Anal Chim Acta. 2024 Apr 8;1297:342371. doi: 10.1016/j.aca.2024.342371. Epub 2024 Feb 17.
Bacterial infections, especially polymicrobial infections, remain a threat to global health and require advances in diagnostic technologies for timely and accurate identification of all causative species. Digital melt - microfluidic chip-based digital PCR combined with high resolution melt (HRM) - is an emerging method for identification and quantification of polymicrobial bacterial infections. Despite advances in recent years, existing digital melt instrumentation often delivers nonuniform temperatures across digital chips, resulting in nonuniform digital melt curves for individual bacterial species. This nonuniformity can lead to inaccurate species identification and reduce the capacity for differentiating bacterial species with similar digital melt curves.
We introduce herein a new temperature calibration method for digital melt by incorporating an unamplified, synthetic DNA fragment with a known melting temperature as a calibrator. When added at a tuned concentration to an established digital melt assay amplifying the commonly targeted 16S V1 - V6 region, this calibrator produced visible low temperature calibrator melt curves across-chip along with the target bacterial melt curves. This enables alignment of the bacterial melt curves and correction of heating-induced nonuniformities. Using this calibration method, we were able to improve the uniformity of digital melt curves from three causative species of bacteria. Additionally, we assessed calibration's effects on identification accuracy by performing machine learning identification of three polymicrobial mixtures comprised of two bacteria with similar digital melt curves in different ratios. Calibration greatly improved mixture composition prediction.
To the best of our knowledge, this work represents the first DNA calibrator-supplemented assay and calibration method for nanoarray digital melt. Our results suggest that this calibration method can be flexibly used to improve identification accuracy and reduce melt curve variabilities across a variety of pathogens and assays. Therefore, this calibration method has the potential to elevate the diagnostic capabilities of digital melt toward polymicrobial bacterial infections and other infectious diseases.
细菌感染，特别是混合感染，仍然对全球健康构成威胁，需要在诊断技术方面取得进展，以便及时、准确地识别所有病原体。基于数字熔解微流控芯片的数字 PCR 与高分辨率熔解（HRM）相结合，是一种用于鉴定和定量混合细菌感染的新兴方法。尽管近年来取得了进展，但现有的数字熔解仪器通常在数字芯片上提供不均匀的温度，导致单个细菌物种的数字熔解曲线不均匀。这种不均匀性可能导致物种鉴定不准确，并降低区分具有相似数字熔解曲线的细菌物种的能力。
我们在此引入了一种新的数字熔解温度校准方法，即将具有已知熔解温度的未扩增合成 DNA 片段用作校准物。当以调谐浓度添加到扩增常见靶向 16S V1-V6 区域的既定数字熔解测定中时，该校准物会在芯片上产生可见的低温校准物熔解曲线，以及目标细菌熔解曲线。这使得细菌熔解曲线能够对齐，并校正加热引起的不均匀性。使用这种校准方法，我们能够改善三种病原体细菌的数字熔解曲线的均匀性。此外，我们通过对由两种具有相似数字熔解曲线的细菌以不同比例组成的三种混合细菌进行机器学习鉴定，评估了校准对鉴定准确性的影响。校准大大提高了混合物组成的预测。
据我们所知，这项工作代表了第一个 DNA 校准物补充测定和校准方法用于纳米阵列数字熔解。我们的结果表明，这种校准方法可以灵活用于提高鉴定准确性，并减少各种病原体和测定中熔解曲线的变异性。因此，这种校准方法有可能提高数字熔解对混合细菌感染和其他传染病的诊断能力。
