Dataset Information

The SOXE transcription factors-SOX8, SOX9 and SOX10-share a bi-partite transactivation mechanism.

ABSTRACT: SOX8, SOX9 and SOX10 compose the SOXE transcription factor group. They govern cell fate and differentiation in many lineages, and mutations impairing their activity cause severe diseases, including campomelic dysplasia (SOX9), sex determination disorders (SOX8 and SOX9) and Waardenburg-Shah syndrome (SOX10). However, incomplete knowledge of their modes of action limits disease understanding. We here uncover that the proteins share a bipartite transactivation mechanism, whereby a transactivation domain in the middle of the proteins (TAM) synergizes with a C-terminal one (TAC). TAM comprises amphipathic ?-helices predicted to form a protein-binding pocket and overlapping with minimal transactivation motifs (9-aa-TAD) described in many transcription factors. One 9-aa-TAD sequence includes an evolutionarily conserved and functionally required E?[D/E]QY? motif. SOXF proteins (SOX7, SOX17 and SOX18) contain an identical motif, suggesting evolution from a common ancestor already harboring this motif, whereas TAC and other transactivating SOX proteins feature only remotely related motifs. Missense variants in this SOXE/SOXF-specific motif are rare in control individuals, but have been detected in cancers, supporting its importance in development and physiology. By deepening understanding of mechanisms underlying the central transactivation function of SOXE proteins, these findings should help further decipher molecular networks essential for development and health and dysregulated in diseases.

SUBMITTER: Haseeb A

PROVIDER: S-EPMC6649842 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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The SOXE transcription factors-SOX8, SOX9 and SOX10-share a bi-partite transactivation mechanism.

Haseeb Abdul A Lefebvre Véronique V

Nucleic acids research 20190701 13

SOX8, SOX9 and SOX10 compose the SOXE transcription factor group. They govern cell fate and differentiation in many lineages, and mutations impairing their activity cause severe diseases, including campomelic dysplasia (SOX9), sex determination disorders (SOX8 and SOX9) and Waardenburg-Shah syndrome (SOX10). However, incomplete knowledge of their modes of action limits disease understanding. We here uncover that the proteins share a bipartite transactivation mechanism, whereby a transactivation ...[more]

PMID: 31194875

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Project description:Abstract The brain consists of three major cell types: neurons and two glial cell types (astrocytes and oligodendrocytes). Although they are generated from common multipotent neural stem/precursor cells (NS/PCs), embryonic NS/PCs cannot generate all of the cell types at the beginning of brain development. NS/PCs first undergo extensive self‐renewal to expand their pools, and then acquire the potential to produce neurons, followed by glial cells. Astrocytes are the most frequently found cell type in the central nervous system (CNS), and play important roles in brain development and functions. Although it has been shown that nuclear factor IA (Nfia) is a pivotal transcription factor for conferring gliogenic potential on neurogenic NS/PCs by sequestering DNA methyltransferase 1 (Dnmt1) from astrocyte‐specific genes, direct targets of Nfia that participate in astrocytic differentiation have yet to be completely identified. Here we show that SRY‐box transcription factor 8 (Sox8) is a direct target gene of Nfia at the initiation of the gliogenic phase. We found that expression of Sox8 augmented leukemia inhibitory factor (LIF)‐induced astrocytic differentiation, while Sox8 knockdown inhibited Nfia‐enhanced astrocytic differentiation of NS/PCs. In contrast to Nfia, Sox8 did not induce DNA demethylation of an astrocyte‐specific marker gene, glial fibrillary acidic protein (Gfap), but instead associated with LIF downstream transcription factor STAT3 through transcriptional coactivator p300, explaining how Sox8 expression further facilitated LIF‐induced Gfap expression. Taken together, these results suggest that Sox8 is a crucial Nfia downstream transcription factor for the astrocytic differentiation of NS/PCs in the developing brain. Dnmt1 maintains DNA methylation on the promoter of astrocytic genes such as Gfap in mid‐gestational NS/PCs, precluding their differentiation into astrocytes even if STAT3 is activated by the astrocyte‐inducing cytokine LIF (left). In late‐gestation, Nfia induces Sox8 expression, and sequesters Dnmt1 from astrocytic gene promoters, leading to their demethylation. As a result, NS/PCs now acquire the potential of astrocyte differentiation: upon LIF stimulation, STAT3 can associates with the astrocytic gene promoter together with p300 and Sox8 to efficiently activate the target gene.

Project description:BackgroundMetabolic reconstructions contain detailed information about metabolic enzymes and their reactants and products. These networks can be used to infer functional associations between metabolic enzymes. Many methods are based on the number of metabolites shared by two enzymes, or the shortest path between two enzymes. Metabolite sharing can miss associations between non-consecutive enzymes in a serial pathway, and shortest-path algorithms are sensitive to high-degree metabolites such as water and ATP that create connections between enzymes with little functional similarity.ResultsWe present new, fast methods to infer functional associations in metabolic networks. A local method, the degree-corrected Poisson score, is based only on the metabolites shared by two enzymes, but uses the known metabolite degree distribution. A global method, based on graph diffusion kernels, predicts associations between enzymes that do not share metabolites. Both methods are robust to high-degree metabolites. They out-perform previous methods in predicting shared Gene Ontology (GO) annotations and in predicting experimentally observed synthetic lethal genetic interactions. Including cellular compartment information improves GO annotation predictions but degrades synthetic lethal interaction prediction. These new methods perform nearly as well as computationally demanding methods based on flux balance analysis.ConclusionsWe present fast, accurate methods to predict functional associations from metabolic networks. Biological significance is demonstrated by identifying enzymes whose strong metabolic correlations are missed by conventional annotations in GO, most often enzymes involved in transport vs. synthesis of the same metabolite or other enzyme pairs that share a metabolite but are separated by conventional pathway boundaries. More generally, the methods described here may be valuable for analyzing other types of networks with long-tailed degree distributions and high-degree hubs.

Dataset Information

The SOXE transcription factors-SOX8, SOX9 and SOX10-share a bi-partite transactivation mechanism.

Publications

The SOXE transcription factors-SOX8, SOX9 and SOX10-share a bi-partite transactivation mechanism.

Similar Datasets

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