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Transcriptional study reveals a potential leptin-dependent gene regulatory network in zebrafish brain.

ABSTRACT: The signal mediated by leptin hormone and its receptor is a major regulator of body weight, food intake and metabolism. In mammals and many teleost fish species, leptin has an anorexigenic role and inhibits food intake by influencing the appetite centres in the hypothalamus. However, the regulatory connections between leptin and downstream genes mediating its appetite-regulating effects are still not fully explored in teleost fish. In this study, we used a loss of function leptin receptor zebrafish mutant and real-time quantitative PCR to assess brain expression patterns of several previously identified anorexigenic genes downstream of leptin signal under different feeding conditions (normal feeding, 7-day fasting, 2 and 6-h refeeding). These downstream factors include members of cart genes, crhb and gnrh2, as well as selected genes co-expressed with them based on a zebrafish co-expression database. Here, we found a potential gene expression network (GRN) comprising the abovementioned genes by a stepwise approach of identifying co-expression modules and predicting their upstream regulators. Among the transcription factors (TFs) predicted as potential upstream regulators of this GRN, we found expression pattern of sp3a to be correlated with transcriptional changes of the downstream gene network. Interestingly, the expression and transcriptional activity of Sp3 orthologous gene in mammals have already been implicated to be under the influence of leptin signal. These findings suggest a potentially conserved regulatory connection between leptin and sp3a, which is predicted to act as a transcriptional driver of a downstream gene network in the zebrafish brain.

SUBMITTER: Ahi EP

PROVIDER: S-EPMC8302498 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The hormone leptin is a key regulator of body weight, food intake and metabolism. In mammals, leptin acts as an anorexigen and inhibits food intake centrally by affecting the appetite centres in the hypothalamus. In teleost fish, the regulatory connections between leptin and other appetite-regulating genes are largely unknown. In the present study, we used a zebrafish mutant with a loss of function leptin receptor to investigate brain expression patterns of 12 orexigenic and 24 anorexigenic genes under different feeding conditions (normal feeding, 7-day fasting, 2 and 6-hours refeeding). Expression patterns were compared to wild-type zebrafish, in order to identify leptin-dependent differentially expressed genes under different feeding conditions. We provide evidence that the transcription of certain orexigenic and anorexigenic genes is influenced by leptin signalling in the zebrafish brain. We found that the expression of orexigenic genes was not affected by impaired leptin signalling under normal feeding conditions; however, several orexigenic genes showed increased transcription during fasting and refeeding, including agrp, apln, galr1a and cnr1. This suggests an inhibitory effect of leptin signal on the transcription of these orexigenic genes during short-term fasting and refeeding in functional zebrafish. Most pronounced effects were observed in the group of anorexigenic genes, where the impairment of leptin signalling resulted in reduced gene expression in several genes, including cart family, crhb, gnrh2, mc4r, pomc and spx, in the control group. This suggests a stimulatory effect of leptin signal on the transcription of these anorexigenic genes under normal feeding condition. In addition, we found multiple gain and loss in expression correlations between the appetite-regulating genes, in zebrafish with impaired leptin signal, suggesting the presence of gene regulatory networks downstream of leptin signal in zebrafish brain. The results provide the first evidence for the effects of leptin signal on the transcription of various appetite-regulating genes in zebrafish brain, under different feeding conditions. Altogether, these transcriptional changes suggest an anorexigenic role for leptin signal, which is likely to be mediated through distinct set of appetite-regulating genes under different feeding conditions.

Project description:Transcription factors (TFs) regulate the expression of target genes, inducing changes in cell morphology or activities needed for cell fate determination and differentiation. The BMP signaling pathway is widely regarded as one of the most important pathways in vertebrate skeletal biology, of which BMP2 is a potent inducer, governing the osteoblast differentiation of bone marrow stromal cells (BMSCs). However, the mechanism by which BMP2 initiates its downstream transcription factor cascade and determines the direction of differentiation remains largely unknown. In this study, we used RNA-seq, ATAC-seq, and animal models to characterize the BMP2-dependent gene regulatory network governing osteoblast lineage commitment. Sp7-Cre; Bmp2fx/fx mice (BMP2-cKO) were generated and exhibited decreased bone density and lower osteoblast number (n > 6). In vitro experiments showed that BMP2-cKO mouse bone marrow stromal cells (mBMSCs) had an impact on osteoblast differentiation and deficient cell proliferation. Osteogenic medium induced mBMSCs from BMP2-cKO mice and control were subjected to RNA-seq and ATAC-seq analysis to reveal differentially expressed TFs, along with their target open chromatin regions. Combined with H3K27Ac CUT&Tag during osteoblast differentiation, we identified 2338 BMP2-dependent osteoblast-specific active enhancers. Motif enrichment assay revealed that over 80% of these elements were directly targeted by RUNX2, DLX5, MEF2C, OASIS, and KLF4. We deactivated Klf4 in the Sp7 + lineage to validate the role of KLF4 in osteoblast differentiation of mBMSCs. Compared to the wild-type, Sp7-Cre; Klf4fx/+ mice (KLF4-Het) were smaller in size and had abnormal incisors resembling BMP2-cKO mice. Additionally, KLF4-Het mice had fewer osteoblasts and decreased osteogenic ability. RNA-seq and ATAC-seq revealed that KLF4 mainly "co-bound" with RUNX2 to regulate downstream genes. Given the significant overlap between KLF4- and BMP2-dependent NFRs and enriched motifs, our findings outline a comprehensive BMP2-dependent gene regulatory network specifically governing osteoblast differentiation of the Sp7 + lineage, in which Klf4 is a novel transcription factor.

Project description:Recent analysis of single-cell transcriptomic data has revealed a surprising organization of the transcriptional variability pervasive across individual neurons. In response to distinct combinations of synaptic input-type, a new organization of neuronal subtypes emerged based on transcriptional states that were aligned along a gradient of correlated gene expression. Individual neurons traverse across these transcriptional states in response to cellular inputs. However, the regulatory network interactions driving these changes remain unclear. Here we present a novel fuzzy logic-based approach to infer quantitative gene regulatory network models from highly variable single-cell gene expression data. Our approach involves developing an a priori regulatory network that is then trained against in vivo single-cell gene expression data in order to identify causal gene interactions and corresponding quantitative model parameters. Simulations of the inferred gene regulatory network response to experimentally observed stimuli levels mirrored the pattern and quantitative range of gene expression across individual neurons remarkably well. In addition, the network identification results revealed that distinct regulatory interactions, coupled with differences in the regulatory network stimuli, drive the variable gene expression patterns observed across the neuronal subtypes. We also identified a key difference between the neuronal subtype-specific networks with respect to negative feedback regulation, with the catecholaminergic subtype network lacking such interactions. Furthermore, by varying regulatory network stimuli over a wide range, we identified several cases in which divergent neuronal subtypes could be driven towards similar transcriptional states by distinct stimuli operating on subtype-specific regulatory networks. Based on these results, we conclude that heterogenous single-cell gene expression profiles should be interpreted through a regulatory network modeling perspective in order to separate the contributions of network interactions from those of cellular inputs.

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Transcriptional study reveals a potential leptin-dependent gene regulatory network in zebrafish brain.

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