Sophoridine Counteracts Obesity via Src-Mediated Inhibition of VEGFR Expression and PI3K/AKT Phosphorylation.

Sophoridine (SRP) is a natural quinolizidine alkaloid found in many traditional Chinese herbs, though its effect on adipose tissue is unclear. We improved serum lipid levels by administering SRP by gavage in high-fat diet (HFD)-fed C57BL/6 mice. After 11 weeks, SRP supplementation significantly reduced body weight gain and improved glucose homeostasis, while reducing subcutaneous fat and liver weight. SRP also inhibited cell proliferation and differentiation of 3T3-L1 cells. Proteomics analysis revealed that SRP inhibits adipocyte differentiation by interacting with Src, thereby suppressing vascular endothelial growth factor receptor 2 (VEGFR2) expression and PI3K/AKT phosphorylation. This study provides an empirical basis for the treatment of obesity with small molecules.

N, P, O-codoped biochar from phytoremediation residues: a promising cathode material for Li-S batteries.

Environment and energy are two key issues in today's society. In terms of environmental protection, the treatment of phytoremediation residues has become a key problem to be solved urgently, while for energy storage, it tends to utilize low-cost and high specific energy storage materials (i.e. porous carbon). In this study, the phytoremediation residues is applied to the storage materials with low-cost and high specific capacity. Firstly, the phosphorous acid assisted pyrolysis of oilseed rape stems from phytoremediation is effective in the removal of Zn, Cu, Cd and Cr from the derived biochar. Moreover, the derived biochar from phytoremediation residues shows abundant porous structure and polar groups (-O/-P/-N), and it can deliver 650 mAh g-1with 3.0 mg cm-2sulfur, and keeps 80% capacity after 200 cycles when employing it as a sulfur host for lithium-sulfur (Li-S) batteries. Hence, phosphorous acid assisted pyrolysis and application in Li-S battery is a promising approach for the disposal of phytoremediation residues, which is contributed to the environmental protection as well as energy storage.

Screening the bioactive compound from Coptis chinensis inflorescence by immobilized peroxisome proliferator-activated receptor-gamma.

Coptis chinensis inflorescence is a by-product of Coptis chinensis Franch and riches in alkaloids. We screened the bioactive compounds in the by-product through an immobilized peroxisome proliferator-activated receptor gamma. The receptor was covalently immobilized on the macroporous silica gel through amino groups to generate the affinity stationary phase and was applied for screening. Berberine, palmatine, and jatrorrhizine were identified as the retained components of the herb on the affinity column. We evaluated the binding of the three bioactive compounds with the receptor by nonlinear chromatography and molecular docking. The affinities of the compounds to the receptor were (1.42 ± 0.10) ×108 /M, (4.88 ± 0.38) ×107 /M, and (1.65 ± 0.13) ×107 /M for berberine, palmatine, and jatrorrhizine, with dissociation rate constants of (17.70 ± 0.03) ×10-3 /S, (5.18 ± 0.25) ×10-2 /S, and (15.7 ± 0.05) ×10-2 /S, respectively. Cys285, Arg288, Ile326, Leu330, and His449 in the agonist binding pocket of the receptor participated in the formation of bioactive compound-receptor conjugates. These data indicated that the immobilized receptor is a reliable alternative for screening the bioactive compounds. In addition, Coptis chinensis inflorescence has the potential to be a source for drug discovery.

Emerging roles of circRNAs in regulating thermal and hypoxic stresses in Apostichopus japonicus (Echinodermata: Holothuroidea).

Some sea cucumbers are economically and ecologically important, but they are threatened by thermal and hypoxic stress in changing oceanographic conditions. We construct circRNAs profiles, reveal circRNAs characters, and illustrate the potential regulatory roles of circRNAs in one commercially important species of sea cucumber, Apostichopus japonicus. Reads are distributed in intergenic (44.14%), exonic (48.26%) and intronic (7.60%) regions of the genome. A total of 1684 circRNAs were identified, and the most common spliced length is 269 nt in the present study. In three treatments (HT [thermal stress], LO [hypoxic stress], and HL [combined thermal and hypoxic stress]), 24, 27 and 27 differentially expressed (DE) circRNAs were identified, respectively. Five novel DE-circRNAs commonly occur in these treatments (novel_circ_0003311, novel_circ_0000229, novel_circ_0003944, novel_circ_0001458 and novel_circ_0000707), and based on them, potential circRNA-miRNA binding pairs were predicted. Sanger sequencing, RNase R treatment experiment and qPCR validation identified the accuracy of the circRNAs. Key circRNAs identified in the present study were covalently closed and were more stable under RNase R treatment than linear RNAs. Based on function analysis, circRNAs could regulate metabolic process, signal transduction, and ion responses in A. japonicus when exposed to thermal and hypoxic stress, and 'regulation of response to stimulus' is a common gene ontology (GO) term that is significantly enriched in each treatment; GO terms for 'DNA' and 'stress' are commonly enriched in heat-related treatments (HT and HL); and GO terms for 'protein' are commonly enriched in hypoxia-related treatments (LO and HL). When environmentally stressed, 'metabolism,' 'transport and catabolism,' 'membrane transport,' and 'signal transduction' were significantly responded in sea cucumber based on KEGG analysis. We provide insights into circRNA functions in stress regulation and lay a foundation for invertebrate circRNA research.

The role of BAMBI in regulating adipogenesis and myogenesis and the association between its polymorphisms and growth traits in cattle.

Bone morphogenic protein and activin membrane-bound inhibitor (BAMBI) is a transmembrane protein that affects the growth, development and muscle regeneration of the body by regulating the TGF-ß, BMP and Wnt signaling pathways. Studies have found that BAMBI has important regulatory functions in skeletal muscle and preadipocytes in vivo and in vitro. However, research on this protein in cattle is lacking. In this study, to determine the role of BAMBI in the growth and development of cattle, we first found that the expression of BAMBI in adipose tissue and longissimus muscle of newborn and adult Qinchuan beef cattle was significantly different. Then we showed that BAMBI knockdown promoted the differentiation of bovine preadipocytes and suppressed myoblast myogenesis, as indicated by the increased lipid droplets and the decreased myotubes, as well as the corresponding significant changes in the expression of PPARγ, C/EBPα, C/EBPß, FABP4, MyoD, MyoG and Myf6. Finally, to further verify the effect of BAMBI on the growth performance of cattle, we identified seven novel SNPs in the BAMBI genomic region, which were significantly correlated with one or more growth traits (p < 0.05). Furthermore, individuals with haplotype H1H4 (TC-GA-CT-CA-AT-AT-AG) had a higher body and carcass quality than those with other haplotypes (p < 0.05). In brief, BAMBI may be a functional gene for the differentiation of bovine preadipocytes and myoblasts, and variations in the BAMBI genomic region, especially the combined haplotype H1H4, may benefit marker-assisted selection in cattle.

Time course analysis of immunity-related gene expression in the sea cucumber Apostichopus japonicus during exposure to thermal and hypoxic stress.

Temperature and dissolved oxygen concentration are important abiotic factors that can limit the growth and survival of sea cucumbers by affecting their immune systems. As global warming intensifies, sea cucumbers are increasingly exposed to adverse environmental conditions, which can cause severe economic losses and limit the sustainable development of sea cucumber aquaculture. It is therefore important to better understand how sea cucumbers respond to environmental stress, especially with regard to its effects on immunity. In the present study, the time series of immunity-related gene expression in sea cucumbers under thermal and hypoxic stresses were analyzed separately. The expression trends of 17 genes related to the nuclear factor κB (NF-κB) pathway, the protease family, the complement system, heat shock proteins (HSPs) and the transferrin family during exposure to two stresses at eight time points were concluded. These genes have interconnected roles in stress defense. The expression levels of genes relating to the NF-κB pathways and HSPs were strongly affected in the sea cucumber thermal stress response, while melanotransferrin (Mtf), ferritin (Ft) and mannan-binding C-type lectin (MBCL) were affected by hypoxia. In contrast, complement factor B (Bf), myosin V (Mys) and serine protease inhibitor (SPI) were not that sensitive during the initial period of environmental stress. Similar expression patterns under both thermal and hypoxic stress for certain genes, including an increase in Hsp90 and decreases in lysozyme (Lys), major yolk protein (MYP) and cathepsin C (CTLC) were observed in sea cucumbers. Conversely, NF-κB and Hsp70 were differentially affected by the two stress treatments. Lysozyme-induced immune defense was inconstant in sea cucumbers coping with stress. A gene ontology (GO) analysis of the selected genes revealed that the most co-involved terms related to immunity and iron ion. Our analysis suggests that sea cucumbers demonstrate complex and varied immune responses to different types of stresses. This dynamic image of the immune responses and stress tolerance of sea cucumbers provides new insights into the adaptive strategies of holothurians in adverse environments.

Role of TCF/LEF Transcription Factors in Bone Development and Osteogenesis.

Bone formation occurs by two distinct mechanisms, namely, periosteal ossification and endochondral ossification. In both mechanisms, osteoblasts play an important role in the secretion and mineralization of bone-specific extracellular matrix. Differentiation and maturation of osteoblasts is a prerequisite to bone formation and is regulated by many factors. Recent experiments have shown that transcription factors play an important role in regulating osteoblast differentiation, proliferation, and function. Osteogenesis related transcription factors are the central targets and key mediators of the function of growth factors, such as cytokines. Transcription factors play a key role in the transformation of mesenchymal progenitor cells into functional osteoblasts. These transcription factors are closely linked with each other and in conjunction with bone-related signaling pathways form a complex network that regulates osteoblast differentiation and bone formation. In this paper, we discuss the structure of T-cell factor/lymphoid enhancer factor (TCF/LEF) and its role in embryonic skeletal development and the crosstalk with related signaling pathways and factors.

High-content screening of Aspergillus niger with both increased production and high secretion rate of glucose oxidase.

OBJECTIVES: To develop a rapid, dual-parameter, plate-based screening process to improve production and secretion rate of glucose oxidase simultaneously in Aspergillus niger. RESULTS: A morphology engineering based on CaCO3 was implemented, where the yield of GOD by A. niger was increased by up to 50%. Analysis of extracellular GOD activity was achieved in 96-well plates. There was a close negative correlation between the total GOD activity and its residual glucose of the fermentation broth. Based on this, a rapid, plate-based, qualitative analysis method of the total GOD activity was developed. Compared with the conventional analysis method using o-dianisidine, a correlation coefficient of -0.92 by statistical analysis was obtained. CONCLUSION: Using this dual-parameter screening method, we acquired a strain with GOD activity of 3126 U l-1, which was 146% higher than the original strain. Its secretion rate of GOD was 83, 32% higher than the original strain.

Investigating MicroRNA and transcription factor co-regulatory networks in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is one of the most common malignancies worldwide with poor prognosis. Studies have showed that abnormal microRNA (miRNA) expression can affect CRC pathogenesis and development through targeting critical genes in cellular system. However, it is unclear about which miRNAs play central roles in CRC's pathogenesis and how they interact with transcription factors (TFs) to regulate the cancer-related genes. RESULTS: To address this issue, we systematically explored the major regulation motifs, namely feed-forward loops (FFLs), that consist of miRNAs, TFs and CRC-related genes through the construction of a miRNA-TF regulatory network in CRC. First, we compiled CRC-related miRNAs, CRC-related genes, and human TFs from multiple data sources. Second, we identified 13,123 3-node FFLs including 25 miRNA-FFLs, 13,005 TF-FFLs and 93 composite-FFLs, and merged the 3-node FFLs to construct a CRC-related regulatory network. The network consists of three types of regulatory subnetworks (SNWs): miRNA-SNW, TF-SNW, and composite-SNW. To enhance the accuracy of the network, the results were filtered by using The Cancer Genome Atlas (TCGA) expression data in CRC, whereby we generated a core regulatory network consisting of 58 significant FFLs. We then applied a hub identification strategy to the significant FFLs and found 5 significant components, including two miRNAs (hsa-miR-25 and hsa-miR-31), two genes (ADAMTSL3 and AXIN1) and one TF (BRCA1). The follow up prognosis analysis indicated all of the 5 significant components having good prediction of overall survival of CRC patients. CONCLUSIONS: In summary, we generated a CRC-specific miRNA-TF regulatory network, which is helpful to understand the complex CRC regulatory mechanisms and guide clinical treatment. The discovered 5 regulators might have critical roles in CRC pathogenesis and warrant future investigation.

Disrupted cooperation between transcription factors across diverse cancer types.

BACKGROUND: Transcription Factors (TFs), essential for many cellular processes, generally work coordinately to induce transcriptional change in response to internal and external signals. Disrupted cooperation between TFs, leading to dysregulation of target genes, contributes to the pathogenesis of many diseases, including cancer. Although the aberrant activation of individual TFs and the functional effects have been widely studied, the perturbation of TF cooperativity in cancer has rarely been explored. RESULTS: We used TF co-expression as proxy as cooperativity and performed a large-scale study on disrupted TF cooperation across seven cancer types. While the connectivity of downstream effectors, like metabolic genes and TF targets, were more or similarly disrupted than/with non-TFs, the cooperativity of TFs (upstream regulators) were consistently less disturbed in all studied cancer types. Highly coordinated TFs in normal, however, generally lost that cooperation in cancer. Although different types of cancer shared very few TF pairs with highly disrupted cooperation, the cooperativity of interferon regulatory factors (IRF) was highly disrupted in six cancer types. Specifically, the cooperativity of IRF8 was highly perturbed in lung cancer, which was further validated by two independent lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) datasets. More interestingly, the cooperativity of IRF8 was markedly associated with tumor progression and even contributed to the patient survival independent of tumor stage. CONCLUSIONS: Our findings underscore the far more important role of TF cooperativity in tumorigenesis than previously appreciated. Disrupted cooperation of TFs provides potential clinical utility as prognostic markers for predicting the patient survival.

Reproducible combinatorial regulatory networks elucidate novel oncogenic microRNAs in non-small cell lung cancer.

While previous studies reported aberrant expression of microRNAs (miRNAs) in non-small cell lung cancer (NSCLC), little is known about which miRNAs play central roles in NSCLC's pathogenesis and its regulatory mechanisms. To address this issue, we presented a robust computational framework that integrated matched miRNA and mRNA expression profiles in NSCLC using feed-forward loops. The network consists of miRNAs, transcription factors (TFs), and their common predicted target genes. To discern the biological meaning of their associations, we introduced the direction of regulation. A network edge validation strategy using three independent NSCLC expression profiling data sets pinpointed reproducible biological regulations. Reproducible regulation, which may reflect the true molecular interaction, has not been applied to miRNA-TF co-regulatory network analyses in cancer or other diseases yet. We revealed eight hub miRNAs that connected to a higher proportion of targets validated by independent data sets. Network analyses showed that these miRNAs might have strong oncogenic characteristics. Furthermore, we identified a novel miRNA-TF co-regulatory module that potentially suppresses the tumor suppressor activity of the TGF-ß pathway by targeting a core pathway molecule (TGFBR2). Follow-up experiments showed two miRNAs (miR-9-5p and miR-130b-3p) in this module had increased expression while their target gene TGFBR2 had decreased expression in a cohort of human NSCLC. Moreover, we demonstrated these two miRNAs directly bind to the 3' untranslated region of TGFBR2. This study enhanced our understanding of miRNA-TF co-regulatory mechanisms in NSCLC. The combined bioinformatics and validation approach we described can be applied to study other types of diseases.

Transcriptome sequencing and genome-wide association analyses reveal lysosomal function and actin cytoskeleton remodeling in schizophrenia and bipolar disorder.

Schizophrenia (SCZ) and bipolar disorder (BPD) are severe mental disorders with high heritability. Clinicians have long noticed the similarities of clinic symptoms between these disorders. In recent years, accumulating evidence indicates some shared genetic liabilities. However, what is shared remains elusive. In this study, we conducted whole transcriptome analysis of post-mortem brain tissues (cingulate cortex) from SCZ, BPD and control subjects, and identified differentially expressed genes in these disorders. We found 105 and 153 genes differentially expressed in SCZ and BPD, respectively. By comparing the t-test scores, we found that many of the genes differentially expressed in SCZ and BPD are concordant in their expression level (q⩽0.01, 53 genes; q⩽0.05, 213 genes; q⩽0.1, 885 genes). Using genome-wide association data from the Psychiatric Genomics Consortium, we found that these differentially and concordantly expressed genes were enriched in association signals for both SCZ (P<10(-7)) and BPD (P=0.029). To our knowledge, this is the first time that a substantially large number of genes show concordant expression and association for both SCZ and BPD. Pathway analyses of these genes indicated that they are involved in the lysosome, Fc gamma receptor-mediated phagocytosis, regulation of actin cytoskeleton pathways, along with several cancer pathways. Functional analyses of these genes revealed an interconnected pathway network centered on lysosomal function and the regulation of actin cytoskeleton. These pathways and their interacting network were principally confirmed by an independent transcriptome sequencing data set of the hippocampus. Dysregulation of lysosomal function and cytoskeleton remodeling has direct impacts on endocytosis, phagocytosis, exocytosis, vesicle trafficking, neuronal maturation and migration, neurite outgrowth and synaptic density and plasticity, and different aspects of these processes have been implicated in SCZ and BPD.

Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action.

A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin's antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets.

A comparative study of disease genes and drug targets in the human protein interactome.

BACKGROUND: Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. RESULTS: In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. CONCLUSIONS: The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing.

Oncogenes and tumor suppressor genes: comparative genomics and network perspectives.

BACKGROUND: Defective tumor suppressor genes (TSGs) and hyperactive oncogenes (OCGs) heavily contribute to cell proliferation and apoptosis during cancer development through genetic variations such as somatic mutations and deletions. Moreover, they usually do not perform their cellular functions individually but rather execute jointly. Therefore, a comprehensive comparison of their mutation patterns and network properties may provide a deeper understanding of their roles in the cancer development and provide some clues for identification of novel targets. RESULTS: In this study, we performed a comprehensive survey of TSGs and OCGs from the perspectives of somatic mutations and network properties. For comparative purposes, we choose five gene sets: TSGs, OCGs, cancer drug target genes, essential genes, and other genes. Based on the data from Pan-Cancer project, we found that TSGs had the highest mutation frequency in most tumor types and the OCGs second. The essential genes had the lowest mutation frequency in all tumor types. For the network properties in the human protein-protein interaction (PPI) network, we found that, relative to target proteins, essential proteins, and other proteins, the TSG proteins and OCG proteins both tended to have higher degrees, higher betweenness, lower clustering coefficients, and shorter shortest-path distances. Moreover, the TSG proteins and OCG proteins tended to have direct interactions with cancer drug target proteins. To further explore their relationship, we generated a TSG-OCG network and found that TSGs and OCGs connected strongly with each other. The integration of the mutation frequency with the TSG-OCG network offered a network view of TSGs, OCGs, and their interactions, which may provide new insights into how the TSGs and OCGs jointly contribute to the cancer development. CONCLUSIONS: Our study first discovered that the OCGs and TSGs had different mutation patterns, but had similar and stronger protein-protein characteristics relative to the essential proteins or control proteins in the whole human interactome. We also found that the TSGs and OCGs had the most direct interactions with cancer drug targets. The results will be helpful for cancer drug target identification, and ultimately, understanding the etiology of cancer and treatment at the network level.

Combinatorial therapy discovery using mixed integer linear programming.

MOTIVATION: Combinatorial therapies play increasingly important roles in combating complex diseases. Owing to the huge cost associated with experimental methods in identifying optimal drug combinations, computational approaches can provide a guide to limit the search space and reduce cost. However, few computational approaches have been developed for this purpose, and thus there is a great need of new algorithms for drug combination prediction. RESULTS: Here we proposed to formulate the optimal combinatorial therapy problem into two complementary mathematical algorithms, Balanced Target Set Cover (BTSC) and Minimum Off-Target Set Cover (MOTSC). Given a disease gene set, BTSC seeks a balanced solution that maximizes the coverage on the disease genes and minimizes the off-target hits at the same time. MOTSC seeks a full coverage on the disease gene set while minimizing the off-target set. Through simulation, both BTSC and MOTSC demonstrated a much faster running time over exhaustive search with the same accuracy. When applied to real disease gene sets, our algorithms not only identified known drug combinations, but also predicted novel drug combinations that are worth further testing. In addition, we developed a web-based tool to allow users to iteratively search for optimal drug combinations given a user-defined gene set. AVAILABILITY: Our tool is freely available for noncommercial use at http://www.drug.liuzlab.org/. CONTACT: zhandong.liu@bcm.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

TSGene: a web resource for tumor suppressor genes.

Tumor suppressor genes (TSGs) are guardian genes that play important roles in controlling cell proliferation processes such as cell-cycle checkpoints and inducing apoptosis. Identification of these genes and understanding their functions are critical for further investigation of tumorigenesis. So far, many studies have identified numerous TSGs and illustrated their functions in various types of tumors or normal samples. Furthermore, accumulating evidence has shown that non-coding RNAs can act as TSGs to prevent the tumorigenesis processes. Therefore, there is a growing demand to integrate TSGs with large-scale experimental evidence (e.g. gene expression and epigenetic signatures) to provide a comprehensive resource for further investigation of TSGs and their molecular mechanisms in cancer. To achieve this goal, we first developed a comprehensive literature-based database called TSGene (tumor suppressor gene database), freely available at http://bioinfo.mc.vanderbilt.edu/TSGene/. In the current release, TSGene contains 716 human (637 protein-coding and 79 non-coding genes), 628 mouse and 567 rat TSGs curated from UniProtKB, the Tumor Associated Gene database and 5795 PubMed abstracts. Additionally, the TSGene provides detailed annotations for each TSG, such as cancer mutations, gene expressions, methylation sites, TF regulations and protein-protein interactions.

Ganoderma spore lipid ameliorates docetaxel, cisplatin, and 5-fluorouracil chemotherapy-induced damage to bone marrow mesenchymal stem cells and hematopoiesis.

BACKGROUND: A triplet chemotherapy regimen of docetaxel, cisplatin, and 5-fluorouracil (TPF) is used to treat head and neck squamous cell carcinoma; however, it is toxic to bone marrow mesenchymal stem cells (BMSCs). We previously demonstrated that Ganoderma spore lipid (GSL) protect BMSCs against cyclophosphamide toxicity. In this study, we investigated the protective effects of GSL against TPF-induced BMSCs and hematopoietic damage. METHODS: BMSCs and C57BL/6 mice were divided into control, TPF, co-treatment (simultaneously treated with GSL and TPF for 2 days), and pre-treatment (treated with GSL for 7 days before 2 days of TPF treatment) groups. In vitro, morphology, phenotype, proliferation, senescence, apoptosis, reactive oxygen species (ROS), and differentiation of BMSCs were evaluated. In vivo, peripheral platelets (PLTs) and white blood cells (WBCs) from mouse venous blood were quantified. Bone marrow cells were isolated for hematopoietic colony-forming examination. RESULTS: In vitro, GSL significantly alleviated TPF-induced damage to BMSCs compared with the TPF group, recovering their morphology, phenotype, proliferation, and differentiation capacity (p < 0.05). Annexin V/PI and senescence-associated ß-galactosidase staining showed that GSL inhibited apoptosis and delayed senescence in TPF-treated BMSCs (p < 0.05). GSL downregulated the expression of caspase-3 and reduced ROS formation (p < 0.05). In vivo, GSL restored the number of peripheral PLTs and WBCs and protected the colony-forming capacity of bone marrow cells (p < 0.05). CONCLUSIONS: GSL efficiently protected BMSCs from damage caused by TPF and recovered hematopoiesis.

Integrating Single-Cell and Spatial Transcriptomics Reveals Heterogeneity of Early Pig Skin Development and a Subpopulation with Hair Placode Formation.

The dermis and epidermis, crucial structural layers of the skin, encompass appendages, hair follicles (HFs), and intricate cellular heterogeneity. However, an integrated spatiotemporal transcriptomic atlas of embryonic skin has not yet been described and would be invaluable for studying skin-related diseases in humans. Here, single-cell and spatial transcriptomic analyses are performed on skin samples of normal and hairless fetal pigs across four developmental periods. The cross-species comparison of skin cells illustrated that the pig epidermis is more representative of the human epidermis than mice epidermis. Moreover, Phenome-wide association study analysis revealed that the conserved genes between pigs and humans are strongly associated with human skin-related diseases. In the epidermis, two lineage differentiation trajectories describe hair follicle (HF) morphogenesis and epidermal development. By comparing normal and hairless fetal pigs, it is found that the hair placode (Pc), the most characteristic initial structure in HFs, arises from progenitor-like OGN+/UCHL1+ cells. These progenitors appear earlier in development than the previously described early Pc cells and exhibit abnormal proliferation and migration during differentiation in hairless pigs. The study provides a valuable resource for in-depth insights into HF development, which may serve as a key reference atlas for studying human skin disease etiology using porcine models.

Exploring drug-target interaction networks of illicit drugs.

BACKGROUND: Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. RESULTS: In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. CONCLUSIONS: This study presents the first systematic review of the network characteristics of illicit drugs, their targets, and other drugs that share the targets of these illicit drugs. The results, though preliminary, provide some novel insights into the molecular mechanisms of drug addiction. The observation of illicit-related drugs, with partial verification from previous studies, demonstrated that the network-assisted approach is promising for the identification of drug repositioning.