A Call to Action: the Need for Standardization in Developing Open-Source Mass Spectrometry-Based Methods for Microbial Subspecies Discrimination
A Call to Action: the Need for Standardization in Developing Open-Source Mass Spectrometry-Based Methods for Microbial Subspecies Discrimination
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行动呼吁：开发基于开源质谱的微生物亚种歧视方法标准化的必要性
DOI：
10.1128/msystems.00813-19
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发表时间：
2020
期刊：
影响因子：
6.4
通讯作者：
Sanchez, Laura M.
中科院分区：
文献类型：
--
作者：
Clark, Chase M.;Murphy, Brian T.;Sanchez, Laura M.
在过去的十年中，学术研究人员重新推动创建快速、准确的技术来区分、识别和优先考虑可培养的微生物分离株。基质辅助激光解吸电离飞行时间质谱 (MALDI-TOF MS) 是一种持续受到微生物学家青睐的技术。它是一种成熟的、廉价的技术，通常用于快速识别微生物分类群和区分可培养的微生物。这项技术在临床和兽医实验室中已变得司空见惯，其中经过严格验证的方法与市售参考数据库结合使用来识别病原微生物。然而，更广泛的社区，尤其是研究环境微生物的实验室，通常无法访问昂贵的软件和数据库。我们认为，这个依赖免费和开源软件的社区目前缺乏一套一致的公认实验实践，包括内部标准菌株的使用、生物和技术复制的统计驱动确定以及将 MS 数据存储到开放获取存储库中。制定指南将使研究人员能够更好地比较微生物分型方法，并提高我们以有效的方式对环境分离株进行分组和描述的能力，特别是在亚种水平上。为此，我们建议未来的研究至少应采用以下指南。(i) 在创建/验证方法时，应使用新的生物重复或密切相关的菌株（“测试数据”）的光谱来获得报告的准确性/精度，这些光谱未用于确定方法的参数（“训练和验证”）数据”）。尽管通常是一个挑战，但应使用与获取训练光谱不同的仪器/实验室来获取测试光谱。(ii) 除了报告培养持续时间、MALDI 矩阵类型和其他类似变量之外，已发表的研究还应报告收集数据的实验设计，包括生物和技术复制、随机化和分组（旨在考虑变异和混杂的来源，例如 MALDI 目标板上的样品位置、数据收集日期、化学/介质成分批次等）(1).(iii)已发表的研究应在质谱交互式虚拟环境数据存储库（MassIVE；https://massive.ucsd.edu）（3）等存储库中以原始和标准开放格式（例如 mzML）（2）提供数据供公众使用。
In the last decade, there has been a renewed push by academic researchers to create rapid and accurate techniques to differentiate, identify, and prioritize culturable microbial isolates. One such technique that continues to gain momentum among microbiologists is matrix-assisted laser desorption–ionization time of flight mass spectrometry (MALDI-TOF MS). It is an established, inexpensive technique commonly used to rapidly identify microbial taxa and differentiate culturable microbes. This technology has become commonplace in clinical and veterinary laboratories where rigorously validated methods are used in conjunction with commercially available reference databases to identify pathogenic microorganisms. However, the broader community, especially laboratories working with environmental microbes, typically cannot access the expensive software and databases. It is our opinion that this community, which relies on free and open-source software, currently lacks a coherent set of accepted experimental practices, including employment of internal standard strains, statistically driven determination of biological and technical replicates, and deposition of MS data into open-access repositories. Establishing guidelines would enable researchers to better compare microbial typing methods and advance our ability to group and delineate environmental isolates in an effective manner, particularly at the subspecies level.Toward this end, we recommend that future studies should, at a minimum, employ the following guidelines.(i) When creating/validating methods, the reported accuracy/precision should be obtained using spectra from new biological replicates or closely related strains (“test data”) that were not used to determine the parameters of the method (“training and validation data”). Though often a challenge, test spectra should be acquired using a different instrument/laboratory than was used to acquire training spectra.(ii) In addition to reporting culture duration, MALDI matrix type, and other similar variables, published studies should report the experimental design of collected data, including biological and technical replication, randomization, and blocking (designed to account for sources of variation and confounding, such as sample location on the MALDI target plate, day of data collection, chemical/medium ingredient batches, etc.)(1).(iii) Published studies should make data available for public use in both raw and standard open format (eg mzML)(2) in a repository such as the Mass Spectrometry Interactive Virtual Environment data repository (MassIVE; https://massive. ucsd. edu)(3).
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影响因子：
6.4
作者：
Dumolin, Charles;Aerts, Maarten;Carlier, Aurelien
通讯作者：
Carlier, Aurelien
DOI：
10.1073/pnas.1801247115
发表时间：
2018-05-08
影响因子：
11.1
作者：
Clark CM;Costa MS;Sanchez LM;Murphy BT
通讯作者：
Murphy BT
从质谱数据识别微生物的结构化机器学习方法的基准
DOI：
--
发表时间：
2015
期刊：
arXiv.org
影响因子：
--
作者：
K. Vervier;P. Mahé;Jean;Jean
通讯作者：
Jean
影响因子：
48
作者：
Sczyrba A;Hofmann P;Belmann P;Koslicki D;Janssen S;Dröge J;Gregor I;Majda S;Fiedler J;Dahms E;Bremges A;Fritz A;Garrido-Oter R;Jørgensen TS;Shapiro N;Blood PD;Gurevich A;Bai Y;Turaev D;DeMaere MZ;Chikhi R;Nagarajan N;Quince C;Meyer F;Balvočiūtė M;Hansen LH;Sørensen SJ;Chia BKH;Denis B;Froula JL;Wang Z;Egan R;Don Kang D;Cook JJ;Deltel C;Beckstette M;Lemaitre C;Peterlongo P;Rizk G;Lavenier D;Wu YW;Singer SW;Jain C;Strous M;Klingenberg H;Meinicke P;Barton MD;Lingner T;Lin HH;Liao YC;Silva GGZ;Cuevas DA;Edwards RA;Saha S;Piro VC;Renard BY;Pop M;Klenk HP;Göker M;Kyrpides NC;Woyke T;Vorholt JA;Schulze-Lefert P;Rubin EM;Darling AE;Rattei T;McHardy AC
通讯作者：
McHardy AC