Publikation:

Mono- and Intralink Filter (Mi-Filter) To Reduce False Identifications in Cross-Linking Mass Spectrometry Data

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2022

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Eisele, Markus R.
Sakata, Eri
Pellarin, Riccardo

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http://nbn-resolving.de/urn:nbn:de:bsz:352-2-181jilox555hd3
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https://doi.org/10.1021/acs.analchem.2c00494
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CC BY 4.0

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Published

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Analytical Chemistry. American Chemical Society (ACS). 2022, 94(51), pp. 17751-17756. ISSN 0096-4484. eISSN 1520-6882. Available under: doi: 10.1021/acs.analchem.2c00494

Zusammenfassung

Cross-linking mass spectrometry (XL-MS) has become an indispensable tool for the emerging field of systems structural biology over the recent years. However, the confidence in individual protein–protein interactions (PPIs) depends on the correct assessment of individual inter-protein cross-links. In this article, we describe a mono- and intralink filter (mi-filter) that is applicable to any kind of cross-linking data and workflow. It stipulates that only proteins for which at least one monolink or intra-protein cross-link has been identified within a given data set are considered for an inter-protein cross-link and therefore participate in a PPI. We show that this simple and intuitive filter has a dramatic effect on different types of cross-linking data ranging from individual protein complexes over medium-complexity affinity enrichments to proteome-wide cell lysates and significantly reduces the number of false-positive identifications for inter-protein links in all these types of XL-MS data.

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570 Biowissenschaften, Biologie

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ISO 690CHEN, Xingyu, Carolin SAILER, Kai-Michael KAMMER, Julius FÜRSCH, Markus R. EISELE, Eri SAKATA, Riccardo PELLARIN, Florian STENGEL, 2022. Mono- and Intralink Filter (Mi-Filter) To Reduce False Identifications in Cross-Linking Mass Spectrometry Data. In: Analytical Chemistry. American Chemical Society (ACS). 2022, 94(51), pp. 17751-17756. ISSN 0096-4484. eISSN 1520-6882. Available under: doi: 10.1021/acs.analchem.2c00494
BibTex
@article{Chen2022-12-27Intra-59702,
  year={2022},
  doi={10.1021/acs.analchem.2c00494},
  title={Mono- and Intralink Filter (Mi-Filter) To Reduce False Identifications in Cross-Linking Mass Spectrometry Data},
  number={51},
  volume={94},
  issn={0096-4484},
  journal={Analytical Chemistry},
  pages={17751--17756},
  author={Chen, Xingyu and Sailer, Carolin and Kammer, Kai-Michael and Fürsch, Julius and Eisele, Markus R. and Sakata, Eri and Pellarin, Riccardo and Stengel, Florian}
}
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