Identification of Binding Proteins for TSC22D1 Family Proteins Using Mass Spectrometry

Kamimura, Ryouta; Uchida, Daisuke; Kanno, Shin Ichiro; Shiraishi, Ryo; Hyodo, Toshiki; Sawatani, Yuta; Shimura, Michiko; Hasegawa, Tomonori; Tsubura-Okubo, Maki; Yaguchi, Erika; Komiyama, Yuske; Fukumoto, Chonji; Izumi, Sayaka; Fujita, Atsushi; Wakui, Takahiro; Kawamata, Hitoshi

doi:10.3390/ijms222010913

Cited by 7 publications

(4 citation statements)

References 50 publications

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“…The TSC-22 domain family includes four members: TSC22D1/TSC-22, TSC22D2/KIAA0669, TSC22D3/GILZ, and TSC22D4/THG-1. The best-characterized member of this protein family is TSC22D1, which possesses a tumor-suppressor function, and TGF-β1-stimulated clone 22 (TSC-22/TSC22D1) was first identified as a target gene of TGF-β1 in mouse osteosarcoma cells [32,33]. In addition, our studies indicated a low frequency of TSC-22 SNP alleles in the population [34].…”

Section: Discussionmentioning

confidence: 61%

The Association between the rs3747406 Polymorphism in the Glucocorticoid-Induced Leucine Zipper Gene and Sepsis Survivals Depends on the SOFA Score

Rusev,

Thon,

Rahmel

et al. 2024

IJMS

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The variability in mortality in sepsis could be a consequence of genetic variability. The glucocorticoid system and the intermediate TSC22D3 gene product—glucocorticoid-induced leucine zipper—are clinically relevant in sepsis, which is why this study aimed to clarify whether TSC22D3 gene polymorphisms contribute to the variance in sepsis mortality. Blood samples for DNA extraction were obtained from 455 patients with a sepsis diagnosis according to the Sepsis-III criteria and from 73 control subjects. A SNP TaqMan assay was used to detect single-nucleotide polymorphisms (SNPs) in the TSC22D3 gene. Statistical and graphical analyses were performed using the SPSS Statistics and GraphPad Prism software. C-allele carriers of rs3747406 have a 2.07-fold higher mortality rate when the sequential organ failure assessment (SOFA) score is higher than eight. In a multivariate COX regression model, the SNP rs3747406 with a SOFA score ≥ 8 was found to be an independent risk factor for 30-day survival in sepsis. The HR was calculated to be 2.12, with a p-value of 0.011. The wild-type allele was present in four out of six SNPs in our cohort. The promoter of TSC22D3 was found to be highly conserved. However, we discovered that the C-allele of rs3747406 poses a risk for sepsis mortality for SOFA Scores higher than 6.

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Section: Discussionmentioning

confidence: 61%

The Association between the rs3747406 Polymorphism in the Glucocorticoid-Induced Leucine Zipper Gene and Sepsis Survivals Depends on the SOFA Score

Rusev,

Thon,

Rahmel

et al. 2024

IJMS

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“…A previous study has attributed the effect of glucocorticoid on the activity of adenylate cyclase 50 . Specifically, the TSC22 protein family showed direct binding with this enzyme 51 . Moreover, the fact that TSC22D3 is in WGNCA|HepG2:235 annotated for ‘adenylate cyclase-inhibiting activity’ suggested the connection between activity of this enzyme with proliferation 52 .…”

Section: Discussionmentioning

confidence: 99%

A Network-based Transcriptomic Landscape of HepG2 cells to Uncover Causal Gene Cytotoxicity Interactions Underlying Drug-Induced Liver Injury

Wijaya

Gábor

Pot

et al. 2023

Preprint

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Drug-induced liver injury (DILI) remains the main reason of drug development attritions largely due to poor mechanistic understanding. Toxicogenomics to interrogate the mechanism of DILI has been broadly performed. Gene network-based transcriptome analysis is a bioinformatics approach that potentially contributes to improving mechanistic interpretation of toxicogenomics data. In this current study, we performed an extensive concentration time course response-toxicogenomics study in the HepG2 cell line exposed to various DILI compounds, reference compounds for stress response pathways, cytokine receptors, and growth factor receptors. We established > 500 conditions subjected to whole transcriptome targeted RNA sequences and applied weighted gene co-regulated network analysis (WGCNA) to the transcriptomics data followed by identification of gene networks (modules) that were strongly modulated upon the exposure of DILI compounds. Preservation analysis on the module responses of HepG2 and PHH demonstrated highly preserved adaptive stress responses gene networks. We correlated gene network with cell death as the progressive cellular outcomes. Causality of the target genes of these modules was evaluated using RNA interference validation experiments. We identified that GTPBP2, HSPA1B, IRF1, SIRT1 and TSC22D3 exhibited strong causality towards cell death. Altogether, we demonstrate the application of large transcriptome datasets combined with network-based analysis and biological validation to uncover the candidate determinants of DILI.

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“…A previous study has attributed the effect of glucocorticoid on the activity of adenylate cyclase ( Aksoy et al , 2002 ). Specifically, the TSC22 protein family showed direct binding with this enzyme ( Kamimura et al , 2021 ). Moreover, the fact that TSC22D3 is in WGNCA|HepG2:235 annotated for “adenylate cyclase-inhibiting activity” suggested the connection between activity of this enzyme with proliferation.…”

Section: Discussionmentioning

confidence: 99%

A network-based transcriptomic landscape of HepG2 cells uncovering causal gene-cytotoxicity interactions underlying drug-induced liver injury

Wijaya,

Gabor,

Pot

et al. 2023

Toxicological Sciences

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Drug-induced liver injury (DILI) remains the main reason for drug development attritions largely due to poor mechanistic understanding. Toxicogenomic to interrogate the mechanism of DILI has been broadly performed. Gene coregulation network-based transcriptome analysis is a bioinformatics approach that potentially contributes to improve mechanistic interpretation of toxicogenomic data. Here we performed an extensive concentration time course response-toxicogenomic study in the HepG2 cell line exposed to 20 DILI compounds, 7 reference compounds for stress response pathways, and 10 agonists for cytokines and growth factor receptors. We performed whole transcriptome targeted RNA sequencing to more than 500 conditions and applied weighted gene coregulated network analysis to the transcriptomics data followed by the identification of gene coregulated networks (modules) that were strongly modulated upon the exposure of DILI compounds. Preservation analysis on the module responses of HepG2 and PHH demonstrated highly preserved adaptive stress response gene coregulated networks. We correlated gene coregulated networks with cell death onset and causal relationships of 67 critical target genes of these modules with the onset of cell death was evaluated using RNA interference screening. We identified GTPBP2, HSPA1B, IRF1, SIRT1, and TSC22D3 as essential modulators of DILI compound-induced cell death. These genes were also induced by DILI compounds in PHH. Altogether, we demonstrate the application of large transcriptome datasets combined with network-based analysis and biological validation to uncover the candidate determinants of DILI.

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Identification of Binding Proteins for TSC22D1 Family Proteins Using Mass Spectrometry

Cited by 7 publications

References 50 publications

The Association between the rs3747406 Polymorphism in the Glucocorticoid-Induced Leucine Zipper Gene and Sepsis Survivals Depends on the SOFA Score

The Association between the rs3747406 Polymorphism in the Glucocorticoid-Induced Leucine Zipper Gene and Sepsis Survivals Depends on the SOFA Score

A Network-based Transcriptomic Landscape of HepG2 cells to Uncover Causal Gene Cytotoxicity Interactions Underlying Drug-Induced Liver Injury

A network-based transcriptomic landscape of HepG2 cells uncovering causal gene-cytotoxicity interactions underlying drug-induced liver injury

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