Analysis of Complexome Profiles with the Gaussian Interaction Profiler (GIP) Reveals Novel Protein Complexes in Plasmodium falciparum

Complexome profiling is an experimental approach to identify
interactions
by integrating native separation of protein complexes and quantitative
mass spectrometry. In a typical complexome profile, thousands of proteins
are detected across typically ≤100 fractions. This relatively
low resolution leads to similar abundance profiles between proteins
that are not necessarily interaction partners. To address this challenge,
we introduce the Gaussian Interaction Profiler (GIP), a Gaussian mixture
modeling-based clustering workflow that assigns protein clusters by
modeling the migration profile of each cluster. Uniquely, the GIP
offers a way to prioritize actual interactors over spuriously comigrating
proteins. Using previously analyzed human fibroblast complexome profiles,
we show good performance of the GIP compared to other state-of-the-art
tools. We further demonstrate GIP utility by applying it to complexome
profiles from the transmissible lifecycle stage of malaria parasites.
We unveil promising novel associations for future experimental verification,
including an interaction between the vaccine target Pfs47 and the
hypothetical protein PF3D7_0417000. Taken together, the GIP provides
methodological advances that facilitate more accurate and automated
detection of protein complexes, setting the stage for more varied
and nuanced analyses in the field of complexome profiling. The complexome
profiling data have been deposited to the ProteomeXchange Consortium
with the dataset identifier PXD050751.

复合物图谱分析（Complexome profiling）是一种通过整合蛋白质复合物的天然分离与定量质谱法（quantitative mass spectrometry）来鉴定蛋白质相互作用的实验方法。在典型的复合物图谱中，通常可在最多100个组分中检测到数千种蛋白质。这种相对较低的分辨率会导致并非相互作用伙伴的蛋白质呈现相似的丰度图谱。为解决这一难题，我们推出了高斯相互作用分析器（Gaussian Interaction Profiler, GIP）——一种基于高斯混合模型的聚类流程，通过对每个聚类的迁移图谱进行建模来分配蛋白质聚类。其独特之处在于，GIP能够将真实相互作用蛋白与伪共迁移蛋白区分优先级。借助已发表的人类成纤维细胞复合物图谱数据，我们证实GIP相较于其他前沿工具表现优异。我们进一步将GIP应用于疟原虫传播阶段的复合物图谱数据，验证了其实用性。我们揭示了一批可供后续实验验证的新型关联，其中包括疫苗靶点Pfs47与假设蛋白PF3D7_0417000之间的相互作用。综上，GIP实现了方法学上的进步，可实现更精准、自动化的蛋白质复合物检测，为复合物图谱分析领域更多样化、精细化的分析奠定了基础。本研究的复合物图谱分析数据已存入ProteomeXchange联盟，数据集编号为PXD050751。