Identification of five small heat shock protein genes in Spodoptera frugiperda and expression analysis in response to different environmental stressors

Spodoptera frugiperda (J. E. Smith) is a highly adaptable polyphagous migratory pest in tropical and subtropical regions. Small heat shock proteins (sHsps) are molecular chaperones that play important roles in the adaptation to various environment stressors. The present study aimed to clarify the response mechanisms of S. frugiperda to various environmental stressors. We obtained five S. furcifera sHsp genes (SfsHsp21.3, SfsHsp20, SfsHsp20.1, SfsHsp19.3, and SfsHsp29) via cloning. The putative proteins encoded by these genes contained a typical α-crystallin domain. The expression patterns of these genes during different developmental stages, in various tissues of male and female adults, as well as in response to extreme temperatures and UV-A stress were studied via real-time quantitative polymerase chain reaction. The results showed that the expression levels of all five SfsHsp genes differed among the developmental stages as well as among the different tissues of male and female adults. The expression levels of most SfsHsp genes under extreme temperatures and UV-A-induced stress were significantly upregulated in both male and female adults. In contrast, those of SfsHsp20.1 and SfsHsp19.3 were significantly downregulated under cold stress in male adults. Therefore, the different SfsHsp genes of S. frugiperda play unique regulatory roles during development as well as in response to various environmental stressors.     

Overexpression of Kdr in adult endocardium induces endocardial neovascularization and improves heart function after myocardial infarction

Dear Editor, Coronary artery disease is a leading cause of mortality and morbidity worldwide.Blockade of effective blood flow to heart muscles results in cardi...     

Characterization of the SARS‐CoV‐2 E Protein: Sequence,Structure, Viroporin,and Inhibitors

The COVID‐19 epidemic is one of the most influential epidemics in history. Understanding the impact of coronaviruses (CoVs) on host cells is very important for disease treatment. The SARS‐CoV‐2 envelope (E) protein is a small structural protein involved in many aspects of the viral life cycle. The E protein promotes the packaging and reproduction of the virus, and deletion of this protein weakens or even abolishes the virulence. This review aims to establish new knowledge by combining recent advances in the study of the SARS‐CoV‐2 E protein and by comparing it with the SARS‐CoV E protein. The E protein amino acid sequence, structure, self‐assembly characteristics, viroporin mechanisms and inhibitors are summarized and analyzed herein. Although the mechanisms of the SARS‐CoV‐2 and SARS‐CoV E proteins are similar in many respects, specific studies on the SARS‐CoV‐2 E protein, for both monomers and oligomers, are still lacking. A comprehensive understanding of this protein should prompt further studies on the design and characterization of effective targeted therapeutic measures.     

Transport Inhibition of Digoxin Using Several Common P-gp Expressing Cell Lines Is Not Necessarily Reporting Only on Inhibitor Binding to P-gp

We have reported that the P-gp substrate digoxin required basolateral and apical uptake transport in excess of that allowed by digoxin passive permeability (as measured in the presence of GF120918) to achieve the observed efflux kinetics across MDCK-MDR1-NKI (The Netherlands Cancer Institute) confluent cell monolayers. That is, GF120918 inhibitable uptake transport was kinetically required. Therefore, IC₅₀ measurements using digoxin as a probe substrate in this cell line could be due to inhibition of P-gp, of digoxin uptake transport, or both. This kinetic analysis is now extended to include three additional cell lines: MDCK-MDR1-NIH (National Institute of Health), Caco-2 and CPT-B2 (Caco-2 cells with BCRP knockdown). These cells similarly exhibit GF120918 inhibitable uptake transport of digoxin. We demonstrate that inhibition of digoxin transport across these cell lines by GF120918, cyclosporine, ketoconazole and verapamil is greater than can be explained by inhibition of P-gp alone. We examined three hypotheses for this non-P-gp inhibition. The inhibitors can: (1) bind to a basolateral digoxin uptake transporter, thereby inhibiting digoxin''s cellular uptake; (2) partition into the basolateral membrane and directly reduce membrane permeability; (3) aggregate with digoxin in the donor chamber, thereby reducing the free concentration of digoxin, with concomitant reduction in digoxin uptake. Data and simulations show that hypothesis 1 was found to be uniformly acceptable. Hypothesis 2 was found to be uniformly unlikely. Hypothesis 3 was unlikely for GF120918 and cyclosporine, but further studies are needed to completely adjudicate whether hetero-dimerization contributes to the non-P-gp inhibition for ketoconazole and verapamil. We also find that P-gp substrates with relatively low passive permeability such as digoxin, loperamide and vinblastine kinetically require basolateral uptake transport over that allowed by +GF120918 passive permeability, while highly permeable P-gp substrates such as amprenavir, quinidine, ketoconazole and verapamil do not, regardless of whether they actually use the basolateral transporter.     

Association between MMP1 -1607 1G>2G Polymorphism and Head and Neck Cancer Risk: A Meta-Analysis

Background

MMP1 is an important member of the MMP endopeptidase family that plays a critical role in the development of head and neck cancer (HNC). Several studies have investigated the association between the MMP1 -1607 1G>2G polymorphism and risk of HNC, but their results have been inconsistent. Here, we conducted a meta-analysis to further explore the role of the MMP1 -1607 1G>2G polymorphism in HNC development.

Methods

We identified all eligible studies in the electronic databases of PubMed, ISI Web of Knowledge, MEDLINE, Embase, and Google Scholar (from January 2000 to June 2012). A meta-analysis was performed to evaluate the association between the MMP1 -1607 1G>2G polymorphism and risk of HNC by calculating odds ratios (OR) and 95% confidence interval (CIs).

Results

Twelve studies were included in this meta-analysis. In overall comparison, significant associations were found using the recessive and allelic contrast models (OR, 1.38; 95% CI, 1.07–1.79 and OR, 1.27; 95% CI, 1.05–1.53, respectively), but no association was detected using the dominant model. In the stratified analyses by several variables, significant associations were observed using the recessive, dominant, and allelic contrast models in the Asian population (OR, 1.64; 95% CI, 1.29–2.08; OR, 1.39; 95% CI, 1.06–1.82; and OR, 1.41; 95% CI, 1.21–1.65, respectively), European population (OR, 0.58; 95% CI, 0.40–0.84; OR, 0.64; 95% CI, 0.44–0.92; and OR, 0.68; 95% CI, 0.54–0.85, respectively), and population-based subgroup (OR, 1.24; 95% CI,1.05–1.47; OR,1.48; 95% CI,1.04–2.12; and OR, 1.22; 95% CI, 1.07–1.38, respectively). Furthermore, significant associations were detected in oral cavity cancer and nasopharyngeal cancer under the recessive model.

Conclusion

Our results suggest that the MMP1 -1607 1G>2G polymorphism is associated with risk of HNC and that it plays different roles in Asian and European populations. Further studies with large sample size are needed to validate our findings.     

Measuring disease similarity and predicting disease-related ncRNAs by a novel method

Background

Similar diseases are always caused by similar molecular origins, such as diasease-related protein-coding genes (PCGs). And the molecular associations reflect their similarity. Therefore, current methods for calculating disease similarity often utilized functional interactions of PCGs. Besides, the existing methods have neglected a fact that genes could also be associated in the gene functional network (GFN) based on intermediate nodes.

Methods

Here we presented a novel method, InfDisSim, to deduce the similarity of diseases. InfDisSim utilized the whole network based on random walk with damping to model the information flow. A benchmark set of similar disease pairs was employed to evaluate the performance of InfDisSim.

Results

The region beneath the receiver operating characteristic curve (AUC) was calculated to assess the performance. As a result, InfDisSim reaches a high AUC (0.9786) which indicates a very good performance. Furthermore, after calculating the disease similarity by the InfDisSim, we reconfirmed that similar diseases tend to have common therapeutic drugs (Pearson correlation γ²?=?0.1315, p?=?2.2e-16). Finally, the disease similarity computed by infDisSim was employed to construct a miRNA similarity network (MSN) and lncRNA similarity network (LSN), which were further exploited to predict potential associations of lncRNA-disease pairs and miRNA-disease pairs, respectively. High AUC (0.9893, 0.9007) based on leave-one-out cross validation shows that the LSN and MSN is very appropriate for predicting novel disease-related lncRNAs and miRNAs, respectively.

Conclusions

The high AUC based on benchmark data indicates the method performs well. The method is valuable in the prediction of disease-related lncRNAs and miRNAs.

     

Identification and characterization of a chondroitin synthase from Avibacterium paragallinarum

Applied Microbiology and Biotechnology - Avibacterium paragallinarum is a Gram-negative bacterium that causes infectious coryza in chicken. It was reported that the capsule polysaccharides...