Automated Phosphopeptide Identification Using Multiple MS/MS Fragmentation Modes

Phosphopeptide identification is still a challenging
task because fragmentation spectra obtained by mass spectrometry do
not necessarily contain sufficient fragment ions to establish with
certainty the underlying amino acid sequence and the precise phosphosite.
To improve upon this, it has been suggested to acquire pairs of spectra
from every phosphorylated precursor ion using different fragmentation
modes, for example CID, ETD, and/or HCD. The development of automated
tools for the interpretation of these paired spectra has however,
until now, lagged behind. Using phosphopeptide samples analyzed by
an LTQ-Orbitrap instrument, we here assess an approach in which, on
each selected precursor, a pair of CID spectra, with or without multistage
activation (MSA or MS2, respectively), are acquired in the linear
ion trap. We applied this approach on phosphopeptide samples of variable
proteomic complexity obtained from Arabidopsis
thaliana. We present a straightforward computational
approach to reconcile sequence and phosphosite identifications provided
by the database search engine Mascot on the spectrum pairs, using
two simple filtering rules, at the amino acid sequence and phosphosite
localization levels. If multiple sequences and/or phosphosites are
likely, they are reported in the consensus sequence. Using our program
FragMixer, we could assess that on samples of moderate complexity,
it was worth combining the two fragmentation schemes on every precursor
ion to help efficiently identify amino acid sequences and precisely
localize phosphosites. FragMixer can be flexibly configured, independently
of the Mascot search parameters, and can be applied to various spectrum
pairs, such as MSA/ETD and ETD/HCD, to automatically compare and combine
the information provided by these more differing fragmentation modes.
The software is openly accessible and can be downloaded from our Web
site at http://proteomics.fr/FragMixer.

磷酸肽（Phosphopeptide）的鉴定仍是一项极具挑战性的任务，因为质谱（mass spectrometry）获取的碎裂谱图未必含有足够的碎片离子，无法确切判定其对应的氨基酸序列以及精确的磷酸化位点（phosphosite）。为改善这一现状，已有研究提出对每个磷酸化前体离子（precursor ion）采用不同碎裂模式获取谱图对，例如碰撞诱导解离（CID）、电子转移解离（ETD）和/或高能碰撞解离（HCD）。不过迄今为止，用于解析这类谱图对的自动化工具开发仍相对滞后。本研究借助LTQ-Orbitrap质谱仪分析的磷酸肽样品，评估了如下策略：在每个选定的前体离子上，在线性离子阱（linear ion trap）中获取两组碰撞诱导解离（CID）谱图，分别带有多级激活（multistage activation, MSA）与不带有多级激活（即二级质谱MS2）。我们将该策略应用于从拟南芥（Arabidopsis thaliana）中获取的、蛋白质组复杂度各异的磷酸肽样品。我们提出了一种简便的计算方法，可通过两条简单的过滤规则，在氨基酸序列与磷酸化位点定位层面，整合数据库搜索引擎Mascot针对谱图对给出的序列与磷酸化位点鉴定结果。若存在多个可能的序列和/或磷酸化位点，这些结果将被汇总至一致性序列（consensus sequence）中。借助我们开发的FragMixer程序，我们可证实：针对中等复杂度的样品，对每个前体离子联合采用两种碎裂模式进行分析，能够高效辅助氨基酸序列鉴定与磷酸化位点的精确定位。FragMixer可独立于Mascot搜索参数进行灵活配置，还可应用于各类谱图对（如MSA/ETD与ETD/HCD），自动对比并整合来自这些差异更大的碎裂模式所提供的信息。该软件为开源免费获取，可从我们的网站http://proteomics.fr/FragMixer下载。