Biological characteristics of transcription factor RelB in different immune cell types: implications for the treatment of multiple sclerosis

Yang, Mengjiao; Sun, Li; Han, Jinming; Chen, Zheng; Liang, Hudong; Zhu, Jie

doi:10.1186/s13041-019-0532-6

Cited by 22 publications

(16 citation statements)

References 203 publications

(237 reference statements)

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“…NF-κB is crucial for hematopoiesis and the development of primary and secondary lymphoid tissues, and is activated in thymocytes during positive and negative selection [ 81 , 82 , 83 ]. RelB plays a key role in the development of the thymus as well as the maturation and functioning of dendritic cells, and its deficiency in humans results in dysmaturity of T and B cells, lack of CD27+ memory B cells, reduced T cell output from the thymus, abnormal clonal expansion of T cell subtypes, and severe T and B cell immunodeficiency [ 82 , 84 , 85 , 86 , 87 , 88 ]. NF-κB regulates the early development of B cells and survival of naive B cells.…”

Section: Nf-κb Signaling Pathway In Immune Cellsmentioning

confidence: 99%

NF-κB—An Important Player in Xenoestrogen Signaling in Immune Cells

Nowak

Jabłońska

Ratajczak–Wrona

2021

Cells

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The proper functioning of the immune system is critical for an effective defense against pathogenic factors such as bacteria and viruses. All the cellular processes taking place in an organism are strictly regulated by an intracellular network of signaling pathways. In the case of immune cells, the NF-κB pathway is considered the key signaling pathway as it regulates the expression of more than 200 genes. The transcription factor NF-κB is sensitive to exogenous factors, such as xenoestrogens (XEs), which are compounds mimicking the action of endogenous estrogens and are widely distributed in the environment. Moreover, XE-induced modulation of signaling pathways may be crucial for the proper development of the immune system. In this review, we summarize the effects of XEs on the NF-κB signaling pathway. Based on our analysis, we constructed a model of XE-induced signaling in immune cells and found that in most cases XEs activate NF-κB. Our analysis indicated that the indirect impact of XEs on NF-κB in immune cells is related to the modulation of estrogen signaling and other pathways such as MAPK and JAK/STAT. We also summarize the role of these aspects of signaling in the development and further functioning of the immune system in this paper.

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Section: Nf-κb Signaling Pathway In Immune Cellsmentioning

confidence: 99%

NF-κB—An Important Player in Xenoestrogen Signaling in Immune Cells

Nowak

Jabłońska

Ratajczak–Wrona

2021

Cells

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“…For example, the TRM with the highest influence over TG expression was RELB-STAT1 with the largest Log2NID score of 3.18. Both of these TFs play an important role in immune response and lymphocyte development [38], [39]. Thus, their closely related functions could point to the possibility of their interaction in vivo.…”

Section: Interaction Effects Aided the Detection Of Well-known And Novel Transcription Factor Regulatory Modulesmentioning

confidence: 99%

Detecting global influence of transcription factor interactions on gene expression in lymphoblastoid cells using neural network models

Patel

Bush

2021

Preprint

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Background Transcription factor(TF) interactions are known to regulate target gene(TG) expression in eukaryotes via TF regulatory modules(TRMs). Such interactions can be formed due to co-localizing TFs binding proximally to each other in the DNA sequence or over long distances between distally binding TFs via chromatin looping. While the former type of interaction has been characterized extensively, long distance TF interactions are still largely understudied. Furthermore, most prior approaches have focused on characterizing physical TF interactions without accounting for their effects on TG expression regulation. Understanding TRM based TG expression regulation could aid in understanding diseases caused by disruptions to these mechanisms. In this paper, we present a novel neural network based TRM detection approach that consists of using multi-omics TF based regulatory mechanism information to generate features for building non-linear multilayer perceptron TG expression prediction models in the GM12878 immortalized lymphoblastoid cells.Results We estimated main effects of 149 individual TFs and interaction effects of 48 distinct combinations of TFs forming TRMs based on their influence on TG expression. We identified several well-known and discovered multiple previously uncharacterized TF interactions within our detected set of TRMs. We further characterized the pairwise TRMs using long distance chromatin looping and motif co-occurrence data. We found that nearly all the TFs constituting TRMs detected by our approach interacted via chromatin looping, and that these TFs further interacted with promoters to influence TG expression through one of four possible regulatory configurations. Conclusion Here, we have provided a framework for detecting TRMs using neural network models containing multi-omics TF based regulatory features. We have also described these TRMs based on their regulatory potential along with presenting evidence for the possibility of TF interactions forming the TRMs occurring via chromatin looping.

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“…For example, the TRM with the highest influence over TG expression was RELB-STAT1 with the largest Log2NID score of 3.18. Both of these TFs play an important role in immune response and lymphocyte development [37], [38]. Thus, their closely related functions could point to the possibility of their interaction in vivo.…”

Section: Interaction Effects Aided the Detection Of Well-known And Novel Transcription Factor Regulatory Modulesmentioning

confidence: 99%

Detecting global influence of transcription factor interactions on gene expression in lymphoblastoid cells using neural network models

Patel

Bush

2021

Preprint

View full text Add to dashboard Cite

Background: Transcription factor(TF) interactions are known to regulate target gene(TG) expression in eukaryotes via TF regulatory modules(TRMs). Such interactions can be formed due to co-localizing TFs binding proximally to each other in the DNA sequence or over long distances between distally binding TFs via chromatin looping. While the former type of interaction has been characterized extensively, long distance TF interactions are still largely understudied. Furthermore, most prior approaches have focused on characterizing physical TF interactions without accounting for their effects on TG expression regulation. Understanding TRM based TG expression regulation could aid in understanding diseases caused by disruptions to these mechanisms. In this paper, we present a novel neural network based TRM detection approach that consists of using multi-omics TF based regulatory mechanism information to generate features for building non-linear multilayer perceptron TG expression prediction models in the GM12878 immortalized lymphoblastoid cells. Results: We estimated main effects of 149 individual TFs and interaction effects of 48 distinct combinations of TFs forming TRMs based on their influence on TG expression. We identified several well-known and discovered multiple previously uncharacterized TF interactions within our detected set of TRMs. We further characterized the pairwise TRMs using long distance chromatin looping and motif co-occurrence data. We found that nearly all the TFs constituting TRMs detected by our approach interacted via chromatin looping, and that these TFs further interacted with promoters to influence TG expression through one of four possible regulatory configurations. Conclusion: Here, we have provided a framework for detecting TRMs using neural network models containing multi-omics TF based regulatory features. We have also described these TRMs based on their regulatory potential along with presenting evidence for the possibility of TF interactions forming the TRMs occurring via chromatin looping.

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Biological characteristics of transcription factor RelB in different immune cell types: implications for the treatment of multiple sclerosis

Cited by 22 publications

References 203 publications

NF-κB—An Important Player in Xenoestrogen Signaling in Immune Cells

NF-κB—An Important Player in Xenoestrogen Signaling in Immune Cells

Detecting global influence of transcription factor interactions on gene expression in lymphoblastoid cells using neural network models

Detecting global influence of transcription factor interactions on gene expression in lymphoblastoid cells using neural network models

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