Flagging False Positives Following Untargeted LC–MS Characterization of Histone Post-Translational Modification Combinations

Epigenetic changes
can be studied with an untargeted characterization
of histone post-translational modifications (PTMs) by liquid chromatography–mass
spectrometry (LC–MS).
While prior information about more than 20 types of histone PTMs exists,
little is known about histone PTM combinations (PTMCs). Because of
the combinatorial explosion it is intrinsically impossible to consider
all potential PTMCs in a database search. Consequentially, high-scoring
false positives with unconsidered but correct alternative isobaric
PTMCs can occur. Current quality controls can neither estimate the
amount of unconsidered alternatives nor flag potential false positives.
Here, we propose a conceptual workflow that provides such options.
In this workflow, an in silico modeling of all candidate isoforms
with known-to-exist PTMs is made. The most frequently occurring PTM
sets of these candidate isoforms are determined and used in several
database searches. This suppresses the combinatorial explosion while
considering as many candidate isoforms as possible. Finally, annotations
can be classified as unique or ambiguous, the latter implying false
positives. This workflow was evaluated on an LC–MS data set
containing 44 histone extracts. We were able to consider 60% of all
candidate isoforms. Importantly, 40% of all annotations were classified
as ambiguous. This highlights the need for a more thorough evaluation
of modified peptide annotations.

表观遗传学变化可通过液相色谱-质谱联用（LC-MS）对组蛋白翻译后修饰（PTMs）进行非靶向表征进行研究。尽管关于超过20种组蛋白PTMs的先验信息已存在，但对于组蛋白PTM组合（PTMCs）的了解却甚少。由于组合爆炸的存在，在数据库搜索中考虑所有潜在的PTMCs在本质上是不可能的。因此，可能出现高得分但未被考虑的正确同位素PTMCs的假阳性。当前的质量控制无法估计未考虑的替代方案的数量，也无法标记潜在的假阳性。在此，我们提出了一种概念性工作流程，提供了此类选项。在此工作流程中，对已知存在的PTMs的所有候选异构体进行计算机模拟。确定了这些候选异构体中最常见的PTM集，并将其用于多次数据库搜索。这抑制了组合爆炸，同时尽可能考虑所有候选异构体。最终，可以将注释分类为独特或模糊，后者意味着假阳性。该工作流程在包含44个组蛋白提取物的LC-MS数据集上进行了评估。我们能够考虑所有候选异构体的60%。重要的是，所有注释中有40%被分类为模糊。这突出了对修饰肽注释进行更彻底评估的必要性。