Refka Ben Hamouda, Bertrand Estellon, Khalil Himet, Aimen Cherif, Hugo Marthinet, Jean-Marie Loreau, Gaëtan Texier, Samuel Granjeaud, Lionel Almeras
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引用次数: 0
Abstract
In the early 2000s, matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) emerged as a performant and relevant tool for identifying micro-organisms. Since then, it has become practically essential for identifying bacteria in microbiological diagnostic laboratories. In the last decade, it was successfully applied for arthropod identification, allowing researchers to distinguish vectors from non-vectors of infectious diseases. However, identification failures are not rare, hampering its wide use. Failure is generally attributed either to the absence of respective counter species MS spectra in the database or to the insufficient quality of query MS spectra (i.e., lower intensity and diversity of MS peaks detected). To avoid matching errors due to non-compliant spectra, the development of a strategy for detecting and excluding outlier MS profiles became compulsory. To this end, we created MSProfileR, an R package leading to a bioinformatics tool through a simple installation, integrating a control quality system of MS spectra and an analysis pipeline including peak detection and MS spectra comparisons. MSProfileR can also add metadata concerning the sample that the spectra are derived from. MSProfileR has been developed in the R environment and offers a user-friendly web interface using the R Shiny framework. It is available on Microsoft Windows as a web browser application by simple navigation using the link of the package on Github v.3.10.0. MSProfileR is therefore accessible to non-computer specialists and is freely available to the scientific community. We evaluated MSProfileR using two datasets including exclusively MS spectra from arthropods. In addition to coherent sample classification, outlier MS spectra were detected in each dataset confirming the value of MSProfileR.
本世纪初,基质辅助激光解吸电离飞行时间质谱法(MALDI-TOF MS)作为一种高效、实用的微生物鉴定工具应运而生。从那时起,它实际上已成为微生物诊断实验室鉴定细菌的必备工具。在过去十年中,它被成功地应用于节肢动物的鉴定,使研究人员能够区分传染病的病媒和非病媒。然而,鉴定失败并不罕见,这阻碍了其广泛应用。失败的原因一般是数据库中没有相应的对应物种 MS 图谱,或者查询的 MS 图谱质量不高(即检测到的 MS 峰强度和多样性较低)。为了避免因不符合要求的光谱造成匹配错误,我们必须制定一种策略来检测和排除离群 MS 图谱。为此,我们创建了 MSProfileR,这是一个 R 软件包,只需简单安装即可成为生物信息学工具,其中集成了质谱质量控制系统和分析管道,包括峰值检测和质谱比较。MSProfileR 还能添加与光谱来源样本相关的元数据。MSProfileR 是在 R 环境中开发的,并使用 R Shiny 框架提供了一个用户友好的网络界面。通过使用 Github v.3.10.0 上的软件包链接进行简单导航,它就可以作为网络浏览器应用程序在 Microsoft Windows 上使用。因此,非计算机专业人员也能使用 MSProfileR,而且科学界也能免费使用。我们使用两个数据集对 MSProfileR 进行了评估,这两个数据集仅包括节肢动物的 MS 图谱。除了一致的样本分类外,每个数据集中还检测到了离群质谱,这证实了 MSProfileR 的价值。