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. 2023 Dec 14;25(1):378–403. doi: 10.1038/s44319-023-00012-6

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the data associated with this article, unless otherwise stated in a credit line to the data, but does not extend to the graphical or creative elements of illustrations, charts, or figures. This waiver removes legal barriers to the re-use and mining of research data. According to standard scholarly practice, it is recommended to provide appropriate citation and attribution whenever technically possible.

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(A) Schematic of the integrated proteomics workflow for establishing the NME4 protein interaction network using tandem affinity purification coupled to mass spectrometry (TAP-MS) or TurboID-MS. (B,C) General (B) and specific (C) diseases were enriched using the high-confidence candidate interacting proteins (HCIPs) that were identified by TAP-MS and performed in IPA software (Ingenuity Pathway Analysis). P values ≤ 0.05 was presented. (D) Pathway network enrichment of HCIPs that were identified by TAP-MS. (E) The top four pathways enriched in (D) with related genes are shown. (F) A Venn diagram showing the overlap between the NME4 interaction networks established by TAP-MS and TurboID-MS. (G,H) Gene Ontology analysis in Cellular Components (CC) (G) and KEGG analysis in diseases (H) was carried out using TurboID-MS HCIPs and performed by Hitplot. P.adjust ≤ 0.05 was significant, P values was adjusted by Benjamini and Hochberg FDR (BH).