Brainstem Raphe Pallidus and the Adjacent Area Contain a Novel Action Site in the Melanocortin Circuitry Regulating Energy Balance

The central melanocortin system plays a critical role in the regulation of energy balance in rodents and humans. The melanocortin signals in both the hypothalamus and brainstem contribute to this regulation. However, how the melanocortin signals of the hypothalamus interact with those intrinsic to the brainstem in the regulation of energy balance is poorly understood. The brainstem raphe pallidus (RPa) and adjacent areas contain melanocortin 4 receptor (MC4-R)-bearing neurons and sympathetic premotor neurons regulating thermogenesis. Here we report that α-melanocyte-stimulating hormone (α-MSH)-immunoreactive (IR) fibers are in close apposition to MC4-R neurons in the RPa. Retrograde tracing studies revealed a unique direct projection from hypothalamic proopiomelanocortin (POMC) neurons to the RPa and adjacent areas of the brainstem in mice and rats. Furthermore, microinjection of the MC3/4-R agonist MTII into the RPa area dose-dependently stimulated oxygen consumption and inhibited feeding, whereas microinjection of the antagonist, SHU9119, enhanced feeding. These data suggest a novel pathway of hypothalamic POMC neuronal efferents to brainstem RPa area MC4-R neurons in the melanocortin circuitry that contribute to coordinate regulation of energy balance

Transcriptome analysis of hepatopancreas of Eriocheir sinensis with hepatopancreatic necrosis disease (HPND).

Hepatopancreatic necrosis disease (HPND) is a newly emerging disease in the Chinese mitten crab, Eriocheir sinensis, which has resulted in large economic losses. However, the underlying cause of this disease remains unclear. To better understand the pathogenesis and pathogenic mechanism of HPND, we compared the transcriptome differences of the hepatopancreas of E. sinensis with and without HPND. The analysis yielded > 30 million reads for each sample of three test (with HPND) and three control groups (without HPND). We observed 978 downregulated genes and 644 upregulated genes. Among the gene ontology categories "biological process," "cellular component," and "molecular function", the subcategories cellular process, single-organism process, biological regulation, metabolic process, cell part, organelle, organelle part, binding, and catalytic were enriched. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that "metabolism of xenobiotics by cytochrome P450," "drug metabolism-cytochrome P450," "chemical carcinogenesis," and "material metabolism" were the "five" most significantly enriched pathways in the hepatopancreas of E. sinensis with HPND. The results revealed that material metabolic abnormalities and drug effects from the external environment might be associated with HPND in the Chinese mitten crab. Considering the wide use of pyrethroids for pond cleaning in Xinghua city, we speculated that pyrethroids might cause HPND in the Chinese mitten crab. Our study provided useful information about the cause and pathogenetic mechanisms of HPND and could help to prevent this disease in production practice

Table1_Immune landscape in rejection of renal transplantation revealed by high-throughput single-cell RNA sequencing.XLSX

Background: The role of the cellular level in kidney transplant rejection is unclear, and single-cell RNA sequencing (scRNA-seq) can reveal the single-cell landscape behind rejection of human kidney allografts at the single-cell level.Methods: High-quality transcriptomes were generated from scRNA-seq data from five human kidney transplantation biopsy cores. Cluster analysis was performed on the scRNA-seq data by known cell marker genes in order to identify different cell types. In addition, pathways, pseudotime developmental trajectories and transcriptional regulatory networks involved in different cell subpopulations were explored. Next, we systematically analyzed the scoring of gene sets regarding single-cell expression profiles based on biological processes associated with oxidative stress.Results: We obtained 81,139 single cells by scRNA-seq from kidney transplant tissue biopsies of three antibody-mediated rejection (ABMR) patients and two acute kidney injury (AKI) patients with non-rejection causes and identified 11 cell types, including immune cells, renal cells and several stromal cells. Immune cells such as macrophages showed inflammatory activation and antigen presentation and complement signaling, especially in rejection where some subpopulations of cells specifically expressed in rejection showed specific pro-inflammatory responses. In addition, patients with rejection are characterized by an increased number of fibroblasts, and further analysis of subpopulations of fibroblasts revealed their involvement in inflammatory and fibrosis-related pathways leading to increased renal rejection and fibrosis. Notably, the gene set score for response to oxidative stress was higher in patients with rejection.Conclusion: Insight into histological differences in kidney transplant patients with or without rejection was gained by assessing differences in cellular levels at single-cell resolution. In conclusion, we applied scRNA-seq to rejection after renal transplantation to deconstruct its heterogeneity and identify new targets for personalized therapeutic approaches.</p

Image1_Immune landscape in rejection of renal transplantation revealed by high-throughput single-cell RNA sequencing.TIF

Background: The role of the cellular level in kidney transplant rejection is unclear, and single-cell RNA sequencing (scRNA-seq) can reveal the single-cell landscape behind rejection of human kidney allografts at the single-cell level.Methods: High-quality transcriptomes were generated from scRNA-seq data from five human kidney transplantation biopsy cores. Cluster analysis was performed on the scRNA-seq data by known cell marker genes in order to identify different cell types. In addition, pathways, pseudotime developmental trajectories and transcriptional regulatory networks involved in different cell subpopulations were explored. Next, we systematically analyzed the scoring of gene sets regarding single-cell expression profiles based on biological processes associated with oxidative stress.Results: We obtained 81,139 single cells by scRNA-seq from kidney transplant tissue biopsies of three antibody-mediated rejection (ABMR) patients and two acute kidney injury (AKI) patients with non-rejection causes and identified 11 cell types, including immune cells, renal cells and several stromal cells. Immune cells such as macrophages showed inflammatory activation and antigen presentation and complement signaling, especially in rejection where some subpopulations of cells specifically expressed in rejection showed specific pro-inflammatory responses. In addition, patients with rejection are characterized by an increased number of fibroblasts, and further analysis of subpopulations of fibroblasts revealed their involvement in inflammatory and fibrosis-related pathways leading to increased renal rejection and fibrosis. Notably, the gene set score for response to oxidative stress was higher in patients with rejection.Conclusion: Insight into histological differences in kidney transplant patients with or without rejection was gained by assessing differences in cellular levels at single-cell resolution. In conclusion, we applied scRNA-seq to rejection after renal transplantation to deconstruct its heterogeneity and identify new targets for personalized therapeutic approaches.</p

Table2_Immune landscape in rejection of renal transplantation revealed by high-throughput single-cell RNA sequencing.xlsx

Background: The role of the cellular level in kidney transplant rejection is unclear, and single-cell RNA sequencing (scRNA-seq) can reveal the single-cell landscape behind rejection of human kidney allografts at the single-cell level.Methods: High-quality transcriptomes were generated from scRNA-seq data from five human kidney transplantation biopsy cores. Cluster analysis was performed on the scRNA-seq data by known cell marker genes in order to identify different cell types. In addition, pathways, pseudotime developmental trajectories and transcriptional regulatory networks involved in different cell subpopulations were explored. Next, we systematically analyzed the scoring of gene sets regarding single-cell expression profiles based on biological processes associated with oxidative stress.Results: We obtained 81,139 single cells by scRNA-seq from kidney transplant tissue biopsies of three antibody-mediated rejection (ABMR) patients and two acute kidney injury (AKI) patients with non-rejection causes and identified 11 cell types, including immune cells, renal cells and several stromal cells. Immune cells such as macrophages showed inflammatory activation and antigen presentation and complement signaling, especially in rejection where some subpopulations of cells specifically expressed in rejection showed specific pro-inflammatory responses. In addition, patients with rejection are characterized by an increased number of fibroblasts, and further analysis of subpopulations of fibroblasts revealed their involvement in inflammatory and fibrosis-related pathways leading to increased renal rejection and fibrosis. Notably, the gene set score for response to oxidative stress was higher in patients with rejection.Conclusion: Insight into histological differences in kidney transplant patients with or without rejection was gained by assessing differences in cellular levels at single-cell resolution. In conclusion, we applied scRNA-seq to rejection after renal transplantation to deconstruct its heterogeneity and identify new targets for personalized therapeutic approaches.</p

Effects of deltamethrin treatment on the gene expression profile of <i>E</i>. <i>sinensis</i>.

<p>Volcanic plot of the degree of differences in the expression profile of <i>E</i>. <i>sinensis</i>. X-axis, log₂ (fold change); Y-axis, -log₂ (p-value). Red, significantly upregulated genes; green, significantly downregulated genes. Each dot represents one gene.</p

Transcriptional responses in the hepatopancreas of <i>Eriocheir sinensis</i> exposed to deltamethrin

<div><p>Deltamethrin is an important pesticide widely used against ectoparasites. Deltamethrin contamination has resulted in a threat to the healthy breeding of the Chinese mitten crab, <i>Eriocheir sinensis</i>. In this study, we investigated transcriptional responses in the hepatopancreas of <i>E</i>. <i>sinensis</i> exposed to deltamethrin. We obtained 99,087,448, 89,086,478, and 100,117,958 raw sequence reads from control 1, control 2, and control 3 groups, and 92,094,972, 92,883,894, and 92,500,828 raw sequence reads from test 1, test 2, and test 3 groups, respectively. After filtering and quality checking of the raw sequence reads, our analysis yielded 79,228,354, 72,336,470, 81,859,826, 77,649,400, 77,194,276, and 75,697,016 clean reads with a mean length of 150 bp from the control and test groups. After deltamethrin treatment, a total of 160 and 167 genes were significantly upregulated and downregulated, respectively. Gene ontology terms “biological process,” “cellular component,” and “molecular function” were enriched with respect to cell killing, cellular process, other organism part, cell part, binding, and catalytic. Pathway analysis using the Kyoto Encyclopedia of Genes and Genomes showed that the metabolic pathways were significantly enriched. We found that the CYP450 enzyme system, carboxylesterase, glutathione-<i>S</i>-transferase, and material (including carbohydrate, lipid, protein, and other substances) metabolism played important roles in the metabolism of deltamethrin in the hepatopancreas of <i>E</i>. <i>sinensis</i>. This study revealed differentially expressed genes related to insecticide metabolism and detoxification in <i>E</i>. <i>sinensis</i> for the first time and will help in understanding the toxicity and molecular metabolic mechanisms of deltamethrin in <i>E</i>. <i>sinensis</i>.</p></div

Statistical results for mapping the trimmed reads with the reference genome.

<p>Statistical results for mapping the trimmed reads with the reference genome.</p

Effects of deltamethrin treatment on the gene expression profile using pattern clustering.

<p>Red, upregulated genes; green, downregulated genes. Each line represents one gene.</p