MEKK3 is required for lysophosphatidic acid-induced NF-κB activation

Lysophosphatidic acid (LPA) is a potent agonist that exerts various cellular functions on many cell types through binding to its cognate G protein-coupled receptors (GPCRs). Although LPA induces NF-κB activation by acting on its GPCR receptor, the molecular mechanism of LPA receptor-mediated NF-κB activation remains to be well defined. In the present study, by using MEKK3-, TAK1-, and IKKβ-deficient murine embryonic fibroblasts (MEFs), we found that MEKK3 but not TAK1 deficiency impairs LPA and protein kinase C (PKC)-induced IκB kinase (IKK)-NF-κB activation, and IKKβ is required for PKC-induced NF-κB activation. In addition, we demonstrate that LPA and PKC-induced IL-6 and MIP-2 production are abolished in the absence of MEKK3 but not TAK1. Together, our results provide the genetic evidence that MEKK3 but not TAK1 is required for LPA receptor-mediated IKK-NF-κB activation.     

Detection and Isolation of Preformed Antifungal Compounds from the Peel of Pyrus bretschneideri Rehd. cv. Pingguoli at Different Stages of Maturity

Ethanol‐dichloromethane crude extract from peel of pear (Pyrus bretschneideri Rehd. cv. Pingguoli) was separated by thin layer chromatographic plates and bioassayed with conidia of Alternaria alternata. The inhibition zones differed significantly in retention factor (R_f) at expanding stage, harvest time and after 100 days of cold storage. The compounds in the inhibition zones were isolated and identified with gas chromatography and mass spectroscopy. Palmitate methyl, oleic acid methyl, linolenic acid methyl and squalene were present at all stages. The concentration of these chemicals was the highest in expanding stage fruit peel and decreased rapidly with fruit development. It is suggested that these compounds may be the main antifungal compounds in the growing fruit. The phthalate alkyl esters occurred at relatively higher concentrations in pear peel at harvest and after 100 days of cold storage. Six phthalate alkyl esters were identified from peel of pear fruit after 100 days of cold storage. It is also supposed that these esters may be the antifungal compounds in postharvest pear.     

Lanthionine Synthetase C-like Protein 1 Interacts with and Inhibits Cystathionine β-Synthase: A TARGET FOR NEURONAL ANTIOXIDANT DEFENSE*

The finding that eukaryotic lanthionine synthetase C-like protein 1 (LanCL1) is a glutathione-binding protein prompted us to investigate the potential relationship between LanCL1 and cystathionine β-synthase (CBS). CBS is a trans-sulfuration enzyme critical for the reduced glutathione (GSH) synthesis and GSH-dependent defense against oxidative stress. In this study we found that LanCL1 bound to CBS in mouse cortex and HEK293 cells. Mapping studies revealed that the binding region in LanCL1 spans amino acids 158–169, and that in CBS contains N-terminal and C-terminal regulatory domains. Recombinant His-LanCL1 directly bound endogenous CBS from mouse cortical lysates and inhibited its activity. Overexpression of LanCL1 inhibited CBS activity in HEK293 cells. CBS activity is reported to be regulated by oxidative stress. Here we found that oxidative stress induced by H₂O₂ or glutamate lowered the GSH/GSSG ratio, dissociated LanCL1 from CBS, and elevated CBS activity in primary rat cortical neurons. Decreasing the GSH/GSSG ratio by adding GSSG to cellular extracts also dissociated LanCL1 from CBS. Either lentiviral knockdown of LanCL1 or specific disruption of the LanCL1-CBS interaction using the peptide Tat-LanCL1_153–173 released CBS activity in neurons but occluded CBS activation in response to oxidative stress, indicating the major contribution of the LanCL1-CBS interaction to the regulation of CBS activity. Furthermore, LanCL1 knockdown or Tat-LanCL1_153–173 treatment reduced H₂O₂ or glutamate-induced neuronal damage. This study implies potential therapeutic value in targeting the LanCL1-CBS interaction for neuronal oxidative stress-related diseases.     

重组鼠疫菌F1抗原的纯化及其在ELISA检测鼠疫免疫中的应用

从表达rF1抗原的大肠杆菌中以Superdex-200凝胶过滤层析纯化rF1抗原,电泳扫描显示纯化率>90%。SDS-PAGE及琼脂免疫双扩散结果显示纯化的rF1抗原具天然F1抗原的活性。将此纯化的rF1抗原用于间接ELISA分析免疫动物血清中抗F1抗体的水平,并与天然F1抗原相比较,证明rF1抗原优于天然F1抗原分析结果,可用于鼠疫的血清学检测。     

Overexpression of SmLEA enhances salt and drought tolerance in Escherichia coli and Salvia miltiorrhiza

Salinity and drought are important abiotic stresses limiting plant growth and development. Late embryogenesis abundant (LEA) proteins are a group of proteins associated with tolerance to water-related stress. We previously cloned an LEA gene, SmLEA, from Salvia miltiorrhiza Bunge. Phylogenetic analysis indicated that SmLEA belongs to Group LEA14, which is involved in the dehydration response. To determine its function in detail, we have now overexpressed SmLEA in Escherichia coli and S. miltiorrhiza. The logarithmic increase in accumulations of SmLEA proteins in E. coli occurred earlier under salinity than under standard conditions. SmLEA-transformed S. miltiorrhiza plants also showed faster root elongation and a lower malondialdehyde concentration than the empty vector control plants did when cultured on MS media supplemented with 60 mM NaCl or 150 mM mannitol. Moreover, SmLEA-overexpressing transgenics experienced a less rapid rate of water loss. Under either salinity or drought, overexpressing plants had greater superoxide dismutase activity and a higher glutathione concentration. These results suggest that SmLEA may be useful in efforts to improve drought and salinity tolerance in S. miltiorrhiza. Our data also provide a good foundation for further studies into the stress resistance mechanism and molecular breeding of this valuable medicinal plant.     

Integrating 'omic' information: a bridge between genomics and systems biology

The availability of genome sequences for several organisms, including humans, and the resulting first-approximation lists of genes, have allowed a transition from molecular biology to 'modular biology'. In modular biology, biological processes of interest, or modules, are studied as complex systems of functionally interacting macromolecules. Functional genomic and proteomic ('omic') approaches can be helpful to accelerate the identification of the genes and gene products involved in particular modules, and to describe the functional relationships between them. However, the data emerging from individual omic approaches should be viewed with caution because of the occurrence of false-negative and false-positive results and because single annotations are not sufficient for an understanding of gene function. To increase the reliability of gene function annotation, multiple independent datasets need to be integrated. Here, we review the recent development of strategies for such integration and we argue that these will be important for a systems approach to modular biology.     

An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era

Background

Gene expression microarray has been the primary biomarker platform ubiquitously applied in biomedical research, resulting in enormous data, predictive models, and biomarkers accrued. Recently, RNA-seq has looked likely to replace microarrays, but there will be a period where both technologies co-exist. This raises two important questions: Can microarray-based models and biomarkers be directly applied to RNA-seq data? Can future RNA-seq-based predictive models and biomarkers be applied to microarray data to leverage past investment?

Results

We systematically evaluated the transferability of predictive models and signature genes between microarray and RNA-seq using two large clinical data sets. The complexity of cross-platform sequence correspondence was considered in the analysis and examined using three human and two rat data sets, and three levels of mapping complexity were revealed. Three algorithms representing different modeling complexity were applied to the three levels of mappings for each of the eight binary endpoints and Cox regression was used to model survival times with expression data. In total, 240,096 predictive models were examined.

Conclusions

Signature genes of predictive models are reciprocally transferable between microarray and RNA-seq data for model development, and microarray-based models can accurately predict RNA-seq-profiled samples; while RNA-seq-based models are less accurate in predicting microarray-profiled samples and are affected both by the choice of modeling algorithm and the gene mapping complexity. The results suggest continued usefulness of legacy microarray data and established microarray biomarkers and predictive models in the forthcoming RNA-seq era.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0523-y) contains supplementary material, which is available to authorized users.     

Models and Algorithms for Hub and Spoke Locations for Emergency Service Facilities in Response to Serious Emergency Incidents

This article examines the location-allocation of emergency service facilities as a research subject. The research presents the setup of the single allocation set covering location-allocation models for emergency service facilities under strong time constraints, in view of the shortage of hub & spoke network bypass. The article also presents an extension to the single allocation set covering location-allocation model (SASCP) and the SASCP model with bypass constraints (γ-SASCP) for emergency service facilities under large-scale emergency requirements. For the two models, an improved genetic algorithm was designed and the two models were respectively solved, with the effectiveness of the algorithm verified by a specific example. The impacts of change of parameters such as time discount rate, maximum time constraints, and bypass ratio on the model's results are compared and analyzed, based on solved results by the specific example.     

Patterns of Adaptive and Neutral Diversity Identify the Xiaoxiangling Mountains as a Refuge for the Giant Panda

Genetic variation plays a significant role in maintaining the evolutionary potential of a species. Comparing the patterns of adaptive and neutral diversity in extant populations is useful for understanding the local adaptations of a species. In this study, we determined the fine-scale genetic structure of 6 extant populations of the giant panda (Ailuropoda melanoleuca) using mtDNA and DNA fingerprints, and then overlaid adaptive variations in 6 functional Aime-MHC class II genes (DRA, DRB3, DQA1, DQA2, DQB1, and DQB2) on this framework. We found that: (1) analysis of the mtDNA and DNA fingerprint-based networks of the 6 populations identified the independent evolutionary histories of the 2 panda subspecies; (2) the basal (ancestral) branches of the fingerprint-based Sichuan-derived network all originated from the smallest Xiaoxiangling (XXL) population, suggesting the status of a glacial refuge in XXL; (3) the MHC variations among the tested populations showed that the XXL population exhibited extraordinary high levels of MHC diversity in allelic richness, which is consistent with the diversity characteristics of a glacial refuge; (4) the phylogenetic tree showed that the basal clades of giant panda DQB sequences were all occupied by XXL-specific sequences, providing evidence for the ancestor-resembling traits of XXL. Finally, we found that the giant panda had many more DQ alleles than DR alleles (33∶13), contrary to other mammals, and that the XXL refuge showed special characteristics in the DQB loci, with 7 DQB members of 9 XXL-unique alleles. Thus, this study identified XXL as a glacial refuge, specifically harboring the most number of primitive DQB alleles.