American journal of clinical pathology · 2022
Tandem Mass Spectrometry-Based Amyloid Typing Using Manual Microdissection and Open-Source Data Processing.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Phipps William S, Smith Kelly D, Yang Han-Yin, Henderson Clark M, Pflaum Hannah, Lerch Melissa L, Fondrie William E, Emrick Michelle A, Wu Christine C, MacCoss Michael J, Noble William S, Hoofnagle Andrew N
Аннотация
OBJECTIVES: Standard implementations of amyloid typing by liquid chromatography-tandem mass spectrometry use capabilities unavailable to most clinical laboratories. To improve accessibility of this testing, we explored easier approaches to tissue sampling and data processing.
METHODS: We validated a typing method using manual sampling in place of laser microdissection, pairing the technique with a semiquantitative measure of sampling adequacy. In addition, we created an open-source data processing workflow (Crux Pipeline) for clinical users.
RESULTS: Cases of amyloidosis spanning the major types were distinguishable with 100% specificity using measurements of individual amyloidogenic proteins or in combination with the ratio of λ and κ constant regions. Crux Pipeline allowed for rapid, batched data processing, integrating the steps of peptide identification, statistical confidence estimation, and label-free protein quantification.
CONCLUSIONS: Accurate mass spectrometry-based amyloid typing is possible without laser microdissection. To facilitate entry into solid tissue proteomics, newcomers can leverage manual sampling approaches in combination with Crux Pipeline and related tools.
METHODS: We validated a typing method using manual sampling in place of laser microdissection, pairing the technique with a semiquantitative measure of sampling adequacy. In addition, we created an open-source data processing workflow (Crux Pipeline) for clinical users.
RESULTS: Cases of amyloidosis spanning the major types were distinguishable with 100% specificity using measurements of individual amyloidogenic proteins or in combination with the ratio of λ and κ constant regions. Crux Pipeline allowed for rapid, batched data processing, integrating the steps of peptide identification, statistical confidence estimation, and label-free protein quantification.
CONCLUSIONS: Accurate mass spectrometry-based amyloid typing is possible without laser microdissection. To facilitate entry into solid tissue proteomics, newcomers can leverage manual sampling approaches in combination with Crux Pipeline and related tools.