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Mapping adipocyte interactome networks by HaloTag-enrichment–mass spectrometry

ABSTRACT: Mapping protein interaction complexes in their natural state in a cell in vivo is a holy grail of protein network analysis. We here describe the development of HaloMS, a high-throughput HaloTag-based affinity purification–mass spectrometry assay for protein interaction discovery. The approach enabled quick capture of newly expressed protein and eliminated the tedious conventional one-by-one assay. As a proof-of-principle, we used HaloMS to evaluate protein complex interactions of 17 regulatory proteins in human adipocyte. The adipocyte interactome network was validated using an in vitro pull-down assay and artificial intelligence-based prediction tools. The application of HaloMS to probe adipocyte differentiation signaling pathways allowed the identification of previously unknown transcription factor–protein complexes and revealed proteome-wide human adipocyte transcription factor networks. This study using new technology reveals hidden networks of adipocyte signaling pathways, shedding light on how signals from different pathways are integrated.

ORGANISM(S): Homo Sapiens (human) Arabidopsis Thaliana (mouse-ear Cress)

SUBMITTER: Junshi Yazaki

PROVIDER: PXD041085 | JPOST Repository | Wed May 22 00:00:00 BST 2024

REPOSITORIES: jPOST

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Project description:Adipocytes are functionally the most important cell type in adipose tissue, which play a key role in systemic metabolism and inflammation. Toll-like receptors (TLRs) are important innate immune receptors involve in the early recognition of infection flowed by inflammatory responses. We recently reported that nine members of TLR (1-9) are expressed in the porcine adipocyte. To further development of our in vitro adipocyte model for evaluating potential immunobiotics, herein we characterized the global transcriptome alterations in porcine mature adipocytes (PMA) following stimulation with Pam3csk4, Poly(I:C) and LPS for 12 h, as a specific ligand for TLR2, TLR3 and TLR4, respectively. Analysis of microarray data revealed that 530 (218 up, 312 down), 520 (245 up, 275 down) and 525 (239 up, 286 down) genes were differentially expressed in PMA following stimulation with Pam3csk4, poly (I:C) and LPS stimulation, respectively. Gene ontology classification revealed that differentially expressed genes (DEGs) are involved in several biological process including immune response, inflammatory responses, cytokine-mediated signaling, chemokine-mediated signaling. The accurately annotated genes were organized into two: immune response related genes (cytokine, chemokine, complement factors, adhesion molecules and signal transduction), and genes involved with metabolic and endocrine function (hormones and receptors, growth factors and lipogenic). We inferred protein interaction networks from common DEGs and found that EGR1, NOTCH, NOS2, TNFAIP3, TRAF3IP1, INSR, CXCR4, PPARA, MAPK10 and C3 are the major hub genes of TLR induced transcriptional network of porcine adipocyte. Potential hubs of protein interaction network also exhibited higher centrality estimates in the Gene-Transcription factor interaction network. Expressions of the important genes were also measured by qRT-PCR, confirming the microarray results. Our results provide new insights of transcriptome modifications of adipocytes association with immune response, metabolic and endocrine function.

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Mapping adipocyte interactome networks by HaloTag-enrichment–mass spectrometry

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