Drug-disease association prediction using semantic graph and function similarity representation learning over heterogeneous information networks.

Discovering new indications for existing drugs is a promising development strategy at various stages of drug research and development. However, most of them complete their tasks by constructing a variety of heterogeneous networks without considering available higher-order connectivity patterns in heterogeneous biological information networks, which are believed to be useful for improving the accuracy of new drug discovering. To this end, we propose a computational-based model, called SFRLDDA, for drug-disease association prediction by using semantic graph and function similarity representation learning. Specifically, SFRLDDA first integrates a heterogeneous information network (HIN) by drug-disease, drug-protein, protein-disease associations, and their biological knowledge. Second, different representation learning strategies are applied to obtain the feature representations of drugs and diseases from different perspectives over semantic graph and function similarity graphs constructed, respectively. At last, a Random Forest classifier is incorporated by SFRLDDA to discover potential drug-disease associations (DDAs). Experimental results demonstrate that SFRLDDA yields a best performance when compared with other state-of-the-art models on three benchmark datasets. Moreover, case studies also indicate that the simultaneous consideration of semantic graph and function similarity of drugs and diseases in the HIN allows SFRLDDA to precisely predict DDAs in a more comprehensive manner.

[Research progress on C_(20)-diterpenoid alkaloids and their bioactivities in Ranunculaceae].

C_(20)-diterpenoid alkaloids are mainly distributed in plants of genus Aconitum, Delphinium, and Consolida in the Ranunculaceae. Their chemical structures are mainly categorized into nine types such as atisines, denudatines, hetidines, and hetisines. Bioactivity studies have shown that C_(20)-diterpenoid alkaloids have exhibited superior anti-tumor, analgesic, antiarrhythmic, and anti-inflammatory effects. In this review, the chemical structures and biological activities of 190 C_(20)-diterpenoid alkaloids reported in the Ranunculaceae from 2002 to the present were summarized, so as to provide a reference for the subsequent research on C_(20)-diterpenoid alkaloids in plants of Ranunculaceae.

Biocaiv: an integrative webserver for motif-based clustering analysis and interactive visualization of biological networks.

BACKGROUND: As an important task in bioinformatics, clustering analysis plays a critical role in understanding the functional mechanisms of many complex biological systems, which can be modeled as biological networks. The purpose of clustering analysis in biological networks is to identify functional modules of interest, but there is a lack of online clustering tools that visualize biological networks and provide in-depth biological analysis for discovered clusters. RESULTS: Here we present BioCAIV, a novel webserver dedicated to maximize its accessibility and applicability on the clustering analysis of biological networks. This, together with its user-friendly interface, assists biological researchers to perform an accurate clustering analysis for biological networks and identify functionally significant modules for further assessment. CONCLUSIONS: BioCAIV is an efficient clustering analysis webserver designed for a variety of biological networks. BioCAIV is freely available without registration requirements at http://bioinformatics.tianshanzw.cn:8888/BioCAIV/ .

Salidroside Regulates Mitochondrial Homeostasis After Polarization of RAW264.7 Macrophages.

ABSTRACT: Salidroside has anti-inflammatory and antiatherosclerotic effects, and mitochondrial homeostasis imbalance is closely related to cardiovascular disease. The aim of this study was to investigate the effect of salidroside on mitochondrial homeostasis after macrophage polarization and elucidate its possible mechanism against atherosclerosis. RAW264.7 cells were stimulated with 1 µg·mL -1 Lipopolysaccharide and 50 ng·mL -1 IFN-γ establish M1 polarization and were also pretreated with 400 µM salidroside. The relative expression of proinflammatory genes was detected by RT-PCR whereas that of mitochondrial homeostasis-related proteins and nuclear factor kappa-B (NF-κB) was detected by WB. Levels of intracellular reactive oxygen species (ROS), mitochondrial membrane potential, and mass were measured by chemifluorescence whereas that of NF-κB nuclear translocation was detected by immunofluorescence. Compared with the Mφ group, the M1 group demonstrated increased mRNA expression of interleukin-1ß , inductible nitric oxide synthase (iNOS), and tumor necrosis factor-α ; increased protein expression of iNOS, NOD-like receptor protein 3, putative kinase 1 , and NF-κB p65 but decreased protein expression of MFN2, Tom20, and PGC-1α; decreased mitochondrial membrane potential and mass; and increased ROS levels and NF-κB p65 nuclear translocation. Salidroside intervention decreased mRNA expression of interleukin-1ß and tumor necrosis factor-α compared with the M1 group but did not affect that of iNOS. Furthermore, salidroside intervention prevented the changes in protein expression, mitochondrial membrane potential and mass, ROS levels, and NF-κB p65 nuclear translocation observed in the M1 group. In summary, salidroside ultimately inhibits M1 macrophage polarization and maintains mitochondrial homeostasis after macrophage polarization by increasing mitochondrial membrane potential, decreasing ROS levels, inhibiting NF-κB activation, and in turn regulating the expression of proinflammatory factors and mitochondrial homeostasis-associated proteins.

Increased EEG gamma power under exposure to drug-related cues: a translational index for cue-elicited craving in METH-dependent individuals.

BACKGROUND: This study explored the feasibility of using EEG gamma-band (30-49 Hz) power as an index of cue-elicited craving in METH-dependent individuals. METHODS: Twenty-nine participants dependent on methamphetamine (METH) and 30 healthy participants were instructed to experience a METH-related virtual reality (VR) social environment. RESULTS: Individuals with METH dependence showed significantly stronger self-reported craving and higher gamma power in a VR environment than healthy individuals. In the METH group, the VR environment elicited a significant increase in gamma power compared with the resting state. The METH group then received a VR counterconditioning procedure (VRCP), which was deemed useful in suppressing cue-induced reactivity. After VRCP, participants showed significantly lower self-reported craving scores and gamma power when exposed to drug-related cues than the first time. CONCLUSIONS: These findings suggest that the EEG gamma-band power may be a marker of cue-induced reactivity in patients with METH dependence.

GPS2 promotes erythroid differentiation by control of the stability of EKLF protein.

Erythropoiesis is a complex multistage process that involves differentiation of early erythroid progenitors to enucleated mature red blood cells, in which lineage-specific transcription factors play essential roles. Erythroid Krüppel-like factor (EKLF/KLF1) is a pleiotropic erythroid transcription factor that is required for the proper maturation of the erythroid cells, whose expression and activation are tightly controlled in a temporal and differentiation stage-specific manner. Here, we uncover a novel role of G-protein pathway suppressor 2 (GPS2), a subunit of the nuclear receptor corepressor/silencing mediator of retinoic acid and thyroid hormone receptor corepressor complex, in erythrocyte differentiation. Our study demonstrates that knockdown of GPS2 significantly suppresses erythroid differentiation of human CD34+ cells cultured in vitro and xenotransplanted in nonobese diabetic/severe combined immunodeficiency/interleukin-2 receptor γ-chain null mice. Moreover, global deletion of GPS2 in mice causes impaired erythropoiesis in the fetal liver and leads to severe anemia. Flow cytometric analysis and Wright-Giemsa staining show a defective differentiation at late stages of erythropoiesis in Gps2-/- embryos. Mechanistically, GPS2 interacts with EKLF and prevents proteasome-mediated degradation of EKLF, thereby increasing EKLF stability and transcriptional activity. Moreover, we identify the amino acids 191-230 region in EKLF protein, responsible for GPS2 binding, that is highly conserved in mammals and essential for EKLF protein stability. Collectively, our study uncovers a previously unknown role of GPS2 as a posttranslational regulator that enhances the stability of EKLF protein and thereby promotes erythroid differentiation.

Metabolic Adaptation of a Globally Important Diatom following 700 Generations of Selection under a Warmer Temperature.

Diatoms, accounting for 40% of the marine primary production and 20% of global carbon dioxide fixation, are threatened by the ongoing ocean warming (OW). However, whether and how these ecologically important phytoplankton adapt to OW remains poorly unknown. Here, we experimentally examined the metabolic adaptation of a globally important diatom species Skeletonema dohrnii (S. dohrnii) to OW at two elevated temperatures (24 and 28 °C compared with 20 °C) under short-term (∼300 generations) and long-term (∼700 generations) selection. Both warming levels significantly increased the cell growth rate but decreased the chlorophyll a content. The contents of particulate organic carbon (POC) and particulate organic nitrogen (PON) decreased significantly initially (i.e., until 300 generations) at two temperature treatments but completely recovered after 700 generations of selection, suggesting that S. dohrnii ultimately developed thermal adaptation. Proteomic analysis demonstrated that elevated temperatures upregulated energy metabolism via glycolysis, tricarboxylic acid cycle, and fatty acid oxidation as well as nitrogen acquisition and utilization, which in turn reduced substance storage because of trade-off in the 300th generation, thus decreasing POC and PON. Interestingly, populations at both elevated temperatures exhibited significant proteome plasticity in the 700th generation, as primarily demonstrated by the increased lipid catabolism and glucose accumulation, accounting for the recovery of POC and PON. Changes occurring in cells at the 300th and 700th generations demonstrate that S. dohrnii can adapt to the projected OW, and readjusting the energy metabolism is an important adaptive strategy.

Histone Deacetylase HDA19 Affects Root Cortical Cell Fate by Interacting with SCARECROW.

The Arabidopsis (Arabidopsis thaliana) root epidermis is a simple model for investigating cell fate specification and pattern formation. In addition to regulatory networks consisting of transcription factors, histone deacetylases are also involved in the formation of cellular patterns. Here, we report thatHistone Deacetylase19 (HDA19) affects the root epidermal cellular pattern through regulation of cortical cell fate by interacting with SCARECROW (SCR). HDA19 binds to the DNA sequence upstream of SCR, as well as to those of several of SCR's target genes, and regulates their expression. Mutant lines of several SCR target genes show impaired patterns of epidermal differentiation and cortical cell division, similar to that of hda19 This work presents HDA19 and SCR as two further players in the regulation of cortical and epidermal cell specification and describes an additional function for SCR.

Functional Differences in the Blooming Phytoplankton Heterosigma akashiwo and Prorocentrum donghaiense Revealed by Comparative Metaproteomics.

Phytoplankton blooms are natural phenomena in the ocean, which are the results of rapid cell growth of some phytoplankton species in a unique environment. However, little is known about the molecular events occurring during the bloom. Here, we compared metaproteomes of two phytoplankton Heterosigma akashiwo and Prorocentrum donghaiense in the coastal East China Sea. H. akashiwo and P. donghaiense accounted for 7.82% and 4.74% of the phytoplankton community protein abundances in the nonbloom sample, whereas they contributed to 60.13% and 78.09%, respectively, in their individual blooming samples. Compared with P. donghaiense, H. akashiwo possessed a significantly higher abundance of light-harvesting complex proteins, carbonic anhydrasem and RuBisCO. The blooming H. akashiwo cells expressed more proteins related to external nutrient acquisition, such as bicarbonate transporter SLC4, ammonium transporter, nitrite transporter, and alkaline phosphatase, while the blooming P. donghaiense cells highly expressed proteins related to extra- and intracellular organic nutrient utilization, such as amino acid transporter, 5'-nucleotidase, acid phosphatase, and tripeptidyl-peptidase. The strong capabilities of light harvesting, as well as acquisition and assimilation of inorganic carbon, nitrogen, and phosphorus, facilitated the formation of the H. akashiwo bloom under the high turbidity and inorganic nutrient-sufficient condition, whereas the competitive advantages in organic nutrient acquisition and reallocation guaranteed the occurrence of the P. donghaiense bloom under the inorganic nutrient-insufficient condition. This study highlights the power of metaproteomics for revealing the underlying molecular behaviors of different coexisting phytoplankton species and advances our knowledge on the formation of phytoplankton blooms.IMPORTANCE A deep understanding of the mechanisms driving bloom formation is a prerequisite for effective bloom management. Metaproteomics was applied in this study to reveal the adaptive and responsive strategies of two coexisting phytoplankton species, H. akashiwo and P. donghaiense, during their bloom periods. Metabolic features and niche divergence in light harvesting, as well as carbon, nitrogen, and phosphorus acquisition and assimilation likely promoted the bloom occurrence under different environments. The molecular behaviors of coexisting bloom-causing species will give clues for bloom monitoring and management in the oceans.

Metaproteomics reveals major microbial players and their metabolic activities during the blooming period of a marine dinoflagellate Prorocentrum donghaiense.

Interactions between bacteria and phytoplankton during bloom events are essential for both partners, which impacts their physiology, alters ambient chemistry and shapes ecosystem diversity. Here, we investigated the community structure and metabolic activities of free-living bacterioplankton in different blooming phases of a dinoflagellate Prorocentrum donghaiense using a metaproteomic approach. The Fibrobacteres-Chlorobi-Bacteroidetes group, Rhodobacteraceae, SAR11 and SAR86 clades contributed largely to the bacterial community in the middle-blooming phase while the Pseudoalteromonadaceae exclusively dominated in the late-blooming phase. Transporters and membrane proteins, especially TonB-dependent receptors were highly abundant in both blooming phases. Proteins involved in carbon metabolism, energy metabolism and stress response were frequently detected in the middle-blooming phase while proteins participating in proteolysis and central carbon metabolism were abundant in the late-blooming phase. Beta-glucosidase with putative algicidal capability was identified from the Pseudoalteromonadaceae only in the late-blooming phase, suggesting an active role of this group in lysing P. donghaiense cells. Our results indicated that diverse substrate utilization strategies and different capabilities for environmental adaptation among bacteria shaped their distinct niches in different bloom phases, and certain bacterial species from the Pseudoalteromonadaceae might be crucial for the termination of a dinoflagellate bloom.