Lapp Zena, Abel Lucy, Mangeni Judith, Obala Andrew A, O'Meara Wendy P, Taylor Steve M, Markwalter Christine F
Duke Global Health Institute, Duke University, Durham, NC, USA.
Academic Model Providing Access to Healthcare (AMPATH), Eldoret, Kenya.
Methods Ecol Evol. 2024 Feb;15(2):308-316. doi: 10.1111/2041-210x.14277. Epub 2023 Dec 30.
Measuring vector-human contact in a natural setting can inform precise targeting of interventions to interrupt transmission of vector-borne diseases. One approach is to directly match human DNA in vector bloodmeals to the individuals who were bitten using genotype panels of discriminative short tandem repeats (STRs). Existing methods for matching STR profiles in bloodmeals to the people bitten preclude the ability to match most incomplete profiles and multi-source bloodmeals to bitten individuals.We developed bistro, an R package that implements 3 preexisting STR matching methods as well as the package's namesake, bistro, a new algorithm described here. bistro employs forensic analysis methods to calculate likelihood ratios and match human STR profiles in bloodmeals to people using a dynamic threshold. We evaluated the algorithm's accuracy and compared it to existing matching approaches using a publicly-available panel of 188 single-source and 100 multi-source samples containing DNA from 50 known human sources. Then we applied it to match 777 newly field-collected mosquito bloodmeals to a database of 645 people.The R package implements four STR matching algorithms in user-friendly functions with clear documentation. bistro correctly matched 99% (187/188) of profiles in single-source samples, and 62% (224/359) of profiles from multi-source samples, resulting in a sensitivity of 0.75 (vs < 0.51 for other algorithms). The specificity of bistro was 0.9998 (vs. 1 for other algorithms). Furthermore, bistro identified 79% (720/906) of all possible matches for field-derived mosquitoes, yielding 1.4x more matches than existing algorithms.bistro identifies more correct bloodmeal-human matches than existing approaches, enabling more accurate and robust analyses of vector-human contact in natural settings. The bistro R package and corresponding documentation allow for straightforward uptake of this algorithm by others.
在自然环境中测量媒介与人类的接触情况,可为精准实施干预措施以阻断媒介传播疾病的传播提供依据。一种方法是利用具有鉴别能力的短串联重复序列(STR)基因型面板,将媒介血餐中的人类DNA与被叮咬个体直接匹配。现有的将血餐中的STR图谱与被叮咬者进行匹配的方法,无法将大多数不完整图谱以及多源血餐与被叮咬个体进行匹配。我们开发了Bistro,这是一个R软件包,它实现了3种现有的STR匹配方法以及该软件包的同名新算法Bistro(本文所描述的一种新算法)。Bistro采用法医分析方法来计算似然比,并使用动态阈值将血餐中的人类STR图谱与个体进行匹配。我们评估了该算法的准确性,并使用一个公开可用的包含来自50个已知人类来源DNA的188个单源样本和100个多源样本面板,将其与现有的匹配方法进行比较。然后,我们将其应用于将777份新采集的野外蚊子血餐与一个645人的数据库进行匹配。该R软件包通过具有清晰文档的用户友好型函数实现了四种STR匹配算法。Bistro正确匹配了单源样本中99%(187/188)的图谱,以及多源样本中62%(224/359)的图谱,灵敏度为0.75(其他算法<0.51)。Bistro的特异性为0.9998(其他算法为1)。此外,Bistro识别出了野外采集蚊子所有可能匹配中的79%(720/906),比现有算法多产生了1.4倍的匹配结果。Bistro比现有方法能识别出更多正确的血餐 - 人类匹配,从而能够在自然环境中对媒介与人类的接触进行更准确、更可靠的分析。Bistro R软件包及相应文档使其他人能够直接采用该算法。