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There are currently no multi-transgenic minipig models of diabetes for the regulation of multiple genes involved in its pathogenesis. The foot and mouth disease virus 2A (F2A)-mediated polycistronic system possesses several advantages, and the present study developed a novel multi-transgenic minipig model associated with diabetes using this system. The tissue-specific polycistronic system used in the present study consisted of two expression cassettes, separated by an insulator: (i) 11-β-hydroxysteroid dehydrogenase 1 (11β-HSD1), driven by the porcine liver-specific apolipoprotein E promoter; (ii) human islet amyloid polypeptide (hIAPP) and C/EBP homologous protein (CHOP), linked to the furin digested site and F-2A, driven by the porcine pancreas-specific insulin promoter. In the present study, porcine fetal fibroblasts were transfected with this vector. Following somatic cell nuclear transfer using 10 cell clones and the transplantation of 1,459 embryos in total, three Landrace x Yorkshire surrogates became pregnant and delivered three Wuzhishan piglets. Genomic polymerase chain reaction (PCR) demonstrated that the piglets were multi-transgenic. Reverse transcription-quantitative PCR confirmed that 11β-HSD1 transcription was upregulated in the targeted liver. Similarly, hIAPP and CHOP were expressed at high levels, compared with the control (P<0.05 and P<0.01) in the pancreas, consistent with the western blotting and immunohistochemistry results. The primary results also showed that overexpression of 11β-HSD1 in the liver increased the liver fat lipid parameters; and the levels of hIAPP and CHOP in the pancreatic islet cells, leading to delayed β-cell development and apoptosis. This novel tissue-specific polycistronic system offers a promising starting point for efficiently mimicking multigenic metabolic disease.

Long-term adherence to a high-fat, high-calorie diet influences human health and causes obesity, metabolic syndrome and nonalcoholic steatohepatitis (NASH). Inflammation plays a key role in the development of NASH; however, the mechanism of inflammation induced by over-nutrition remains largely unknown. In this study, we fed Bama minipigs a high-fat, high-sucrose diet (HFHSD) for 23 months. The pigs exhibited characteristics of metabolic syndrome and developed steatohepatitis with greatly increased numbers of inflammatory cells, such as lymphocytes (2.27-fold, P<0.05), Kupffer cells (2.59-fold, P<0.05), eosinophils (1.42-fold, P<0.05) and neutrophils (2.77-fold, P<0.05). High-throughput RNA sequencing (RNA-seq) was performed to explore the systemic transcriptome of the pig liver during inflammation. Approximately 18.2 gigabases of raw sequence data were generated, and over 303 million high-quality reads were assembled into 21,126 unigenes. RNA-seq data analysis showed that 822 genes were differentially expressed in liver (P<0.05) between the HFHSD and control groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the process of inflammation involved the inflammatory signal transduction-related toll-like receptor, MAPK, and PPAR signaling pathways; the cytokine-related chemokine signaling, cytokine-cytokine receptor interaction, and IL2, IL4, IL6, and IL12 signaling pathways; the leukocyte receptor signaling-related T cell, B cell, and natural killer cell signaling pathways; inflammatory cell migration and invasion- related pathways; and other pathways. Moreover, we identified several differentially expressed inflammation-related genes between the two groups, including FOS, JUN, TLR7, MYC, PIK3CD, VAV3, IL2RB and IL4R, that could be potential targets for further investigation. Our study suggested that long-term HFHSD induced obesity and liver inflammation, providing basic insight into the molecular mechanism of this condition and laying the groundwork for further studies on obesity and steatohepatitis.

A long-term high-energy diet affects human health and leads to obesity and metabolic syndrome in addition to cardiac steatosis and hypertrophy. Ectopic fat accumulation in the heart has been demonstrated to be a risk factor for heart disorders, but the molecular mechanism of heart disease remains largely unknown. Bama miniature pigs were fed a high-fat, high-sucrose diet (HFHSD) for 23 months. These pigs developed symptoms of metabolic syndrome and showed cardiac steatosis and hypertrophy with a greatly increased body weight (2.73-fold, P<0.01), insulin level (4.60-fold, P<0.01), heart weight (1.82-fold, P<0.05) and heart volume (1.60-fold, P<0.05) compared with the control pigs. To understand the molecular mechanisms of cardiac steatosis and hypertrophy, nine pig heart cRNA samples were hybridized to porcine GeneChips. Microarray analyses revealed that 1,022 genes were significantly differentially expressed (P<0.05, ≥1.5-fold change), including 591 up-regulated and 431 down-regulated genes in the HFHSD group relative to the control group. KEGG analysis indicated that the observed heart disorder involved the signal transduction-related MAPK, cytokine, and PPAR signaling pathways, energy metabolism-related fatty acid and oxidative phosphorylation signaling pathways, heart function signaling-related focal adhesion, axon guidance, hypertrophic cardiomyopathy and actin cytoskeleton signaling pathways, inflammation and apoptosis pathways, and others. Quantitative RT-PCR assays identified several important differentially expressed heart-related genes, including STAT3, ACSL4, ATF4, FADD, PPP3CA, CD74, SLA-8, VCL, ACTN2 and FGFR1, which may be targets of further research. This study shows that a long-term, high-energy diet induces obesity, cardiac steatosis, and hypertrophy and provides insights into the molecular mechanisms of hypertrophy and fatty heart to facilitate further research.

Over the past decade, with the development of high-throughput single-cell sequencing technology, single-cell omics has been emerged as a powerful tool to understand the molecular basis of cellular mechanisms and refine our knowledge of diverse cell states. They can reveal the heterogeneity at different genetic layers and elucidate their associations by multiple omics analysis, providing a more comprehensive genetic map of biological regulatory networks. In the post-GWAS era, the molecular biological mechanisms influencing human diseases will be further elucidated by single-cell omics. This review mainly summarizes the development and trend of single-cell omics. This involves single-cell omics technologies, single-cell multi-omics technologies, multiple omics data integration methods, applications in various human organs and diseases, classic laboratory cell lines, and animal disease models. The review will reveal some perspectives for elucidating human diseases and constructing animal models.

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BackgroundType 2 diabetes is characterized by insulin resistance accompanied by defective insulin secretion. Transgenic mouse models play an important role in medical research. However, single transgenic mouse models may not mimic the complex phenotypes of most cases of type 2 diabetes.MethodsFocusing on genes related to pancreatic islet damage, peripheral insulin resistance and related environmental inducing factors, we generated single-transgenic (C/EBP homology protein, CHOP) mice (CHOP mice), dual-transgenic (human islet amyloid polypeptide, hIAPP; CHOP) mice (hIAPP-CHOP mice) and triple-transgenic (11β-hydroxysteroid dehydrogenase type 1, 11β-HSD1; hIAPP; CHOP) mice (11β-HSD1-hIAPP- CHOP mice). The latter two types of transgenic (Tg) animals were induced with high-fat high-sucrose diets (HFHSD). We analyzed the diabetes-related symptoms and histology features of the transgenic animals.ResultsComparing symptoms on the spot-checked points, we determined that the triple-transgene mice were more suitable for systematic study. The results of intraperitoneal glucose tolerance tests (IPGTT) of triple-transgene animals began to change 60 days after induction (p < 0.001). After 190 days of induction, the body weights (p < 0.01) and plasma glucose of the animals in Tg were higher than those of the animals in Negative Control (Nc). After sacrificed, large amounts of lipid were found deposited in adipose (p < 0.01) and ectopically deposited in the non-adipose tissues (p < 0.05 or 0.01) of the animals in the Tg HFHSD group. The weights of kidneys and hearts of Tg animals were significantly increased (p < 0.01). Serum C peptide (C-P) was decreased due to Tg effects, and insulin levels were increased due to the effects of the HFHSD in the Tg HFHSD group, indicating that damaged insulin secretion and insulin resistance hyperinsulinemia existed simultaneously in these animals. The serum corticosterone of Tg was slightly higher than those of Nc due to the effects of the 11βHSD-1 transgene and obesity. In Tg HFHSD, hepatic adipose deposition was more severe and the pancreatic islet area was enlarged under compensation, accompanying apoptosis. In the transgenic control diet (Tg ControlD) group, hepatic adipose deposition was also severe, pancreatic islets were damaged, and their areas were decreased (p < 0.05), and apoptosis of pancreatic cells occurred. Taken together, these data show the transgenes led to early-stage pathological changes characteristic of type 2 diabetes in the triple-transgene HFHSD group. The disease of triple-transgenic mice was more severe than that of dual or single-transgenic mice.ConclusionThe use of multi-transgenes involved in insulin resistance and pancreatic apoptosis is a better way to generate polygene-related early-stage diabetes models.

Chromosome conformation-capture technologies are widely used in 3D genomics; however, experimentally, such methods have high-noise limitations and, therefore, require significant bioinformatics efforts to extract reliable distal interactions. Miscellaneous undesired linear DNAs, present during proximity-ligation, represent a main noise source, which needs to be minimized or eliminated. In this study, different exonuclease combinations were tested to remove linear DNA fragments from a circularized DNA preparation. This method efficiently removed linear DNAs, raised the proportion of annulation and increased the valid-pairs ratio from ∼40% to ∼80% for enhanced interaction detection in standard Hi-C. This strategy is applicable for development of various 3D genomics technologies, or optimization of Hi-C sequencing efficiency.