Assessment of splice variant-specific functions of desmocollin 1 in the skin

Desmocollin 1 (Dsc1) is part of a desmosomal cell adhesion receptor formed in terminally differentiating keratinocytes of stratified epithelia. The dsc1 gene encodes two proteins (Dsc1a and Dsc1b) that differ only with respect to their COOH-terminal cytoplasmic amino acid sequences. On the basis of in vitro experiments, it is thought that the Dsc1a variant is essential for assembly of the desmosomal plaque, a structure that connects desmosomes to the intermediate filament cytoskeleton of epithelial cells. We have generated mice that synthesize a truncated Dsc1 receptor that lacks both the Dsc1a- and Dsc1b-specific COOH-terminal domains. This mutant transmembrane receptor, which does not bind the common desmosomal plaque proteins plakoglobin and plakophilin 1, is integrated into functional desmosomes. Interestingly, our mutant mice did not show the epidermal fragility previously observed in dsc1-null mice. This suggests that neither the Dsc1a- nor the Dsc1b-specific COOH-terminal cytoplasmic domain is required for establishing and maintaining desmosomal adhesion. However, a comparison of our mutants with dsc1-null mice suggests that the Dsc1 extracellular domain is necessary to maintain structural integrity of the skin.     

Comment on “Is Yuan in China’s Three Gorges a Gibbon or a Langur?”

International Journal of Primatology -     

Genome-wide association study combined with biological context can reveal more disease-related SNPs altering microRNA target seed sites

Background

Emerging studies demonstrate that single nucleotide polymorphisms (SNPs) resided in the microRNA recognition element seed sites (MRESSs) in 3′UTR of mRNAs are putative biomarkers for human diseases and cancers. However, exhaustively experimental validation for the causality of MRESS SNPs is impractical. Therefore bioinformatics have been introduced to predict causal MRESS SNPs. Genome-wide association study (GWAS) provides a way to detect susceptibility of millions of SNPs simultaneously by taking linkage disequilibrium (LD) into account, but the multiple-testing corrections implemented to suppress false positive rate always sacrificed the sensitivity. In our study, we proposed a method to identify candidate causal MRESS SNPs from 12 GWAS datasets without performing multiple-testing corrections. Alternatively, we used biological context to ensure credibility of the selected SNPs.

Results

In 11 out of the 12 GWAS datasets, MRESS SNPs were over-represented in SNPs with p-value ≤ 0.05 (odds ratio (OR) ranged from 1.1 to 2.4). Moreover, host genes of susceptible MRESS SNPs in each of the 11 GWAS dataset shared biological context with reported causal genes. There were 286 MRESS SNPs identified by our method, while only 13 SNPs were identified by multiple-testing corrections with a given threshold of 1 × 10⁻⁵, which is a common cutoff used in GWAS. 27 out of the 286 candidate SNPs have been reported to be deleterious while only 2 out of 13 multiple-testing corrected SNPs were documented in PubMed. MicroRNA-mRNA interactions affected by the 286 candidate SNPs were likely to present negatively correlated expression. These SNPs introduced greater alternation of binding free energy than other MRESS SNPs, especially when grouping by haplotypes (4210 vs. 4105 cal/mol by mean, 9781 vs. 8521 cal/mol by mean, respectively).

Conclusions

MRESS SNPs are promising disease biomarkers in multiple GWAS datasets. The method of integrating GWAS p-value and biological context is stable and effective for selecting candidate causal MRESS SNPs, it reduces the loss of sensitivity compared to multiple-testing corrections. The 286 candidate causal MRESS SNPs provide researchers a credible source to initialize their design of experimental validations in the future.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-669) contains supplementary material, which is available to authorized users.     

Predicting disease-associated substitution of a single amino acid by analyzing residue interactions

Background  

The rapid accumulation of data on non-synonymous single nucleotide polymorphisms (nsSNPs, also called SAPs) should allow us to further our understanding of the underlying disease-associated mechanisms. Here, we use complex networks to study the role of an amino acid in both local and global structures and determine the extent to which disease-associated and polymorphic SAPs differ in terms of their interactions to other residues.     

Environmental risk assessment of manganese and its associated heavy metals in a stream impacted by manganese mining in South China

In South China, high manganese content in the drinking water source influenced by upstream manganese mine drainage has become a major concern. To investigate the extent of metal pollution and environmental risk in upstream sediments and native aquatic macrophytes, a study was conducted on a manganese mining-impacted river named the Heishui River. The results indicated that streambed sediments collected were polluted by Mn and other metals with the highest contents of Mn 43349.4 mg kg^?1, Pb 128.6 mg kg^?1, Zn 502.9 mg kg^?1, and Cu 107.2 mg kg^?1. The level of Mn in all sediments was higher than the consensus-based Probable Effect Concentration, indicating that adverse effects on sediment-dwelling organisms were likely to occur frequently. Among the studied metals, Mn had the highest bioavailability and ecological risk, followed by Zn. Native aquatic macrophytes accumulate large amounts of the studied metals. A significantly positive correlation was found between exchangeable fractions of the studied metals in sediments and in aquatic macrophytes. The risk assessment code showed the following risk levels of metals in sediments in descending order: Mn > Zn > Cu > Pb. In conclusion, the river impacted by manganese mining drainage poses a high risk to both the local ecosystem and downstream drinking water.     

Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences

Compared to the available protein sequences of different organisms, the number of revealed protein-protein interactions (PPIs) is still very limited. So many computational methods have been developed to facilitate the identification of novel PPIs. However, the methods only using the information of protein sequences are more universal than those that depend on some additional information or predictions about the proteins. In this article, a sequence-based method is proposed by combining a new feature representation using auto covariance (AC) and support vector machine (SVM). AC accounts for the interactions between residues a certain distance apart in the sequence, so this method adequately takes the neighbouring effect into account. When performed on the PPI data of yeast Saccharomyces cerevisiae, the method achieved a very promising prediction result. An independent data set of 11,474 yeast PPIs was used to evaluate this prediction model and the prediction accuracy is 88.09%. The performance of this method is superior to those of the existing sequence-based methods, so it can be a useful supplementary tool for future proteomics studies. The prediction software and all data sets used in this article are freely available at http://www.scucic.cn/Predict_PPI/index.htm.     

Comparison of Endoscopic Submuscosal Implantation vs. Surgical Intramuscular Implantation of VX2 Fragments for Establishing a Rabbit Esophageal Tumor Model for Mimicking Human Esophageal Squamous Carcinoma

Purpose

This study was undertaken to establish a rabbit esophageal tumor model for mimicking human esophageal squamous carcinoma (ESC) by endoscopic and surgical implantation of VX2 tumors.

Methods

Fragments of a VX2 tumour were endoscopically implanted in the submucosal layer of the thoracic esophagus of 32 New Zealand white rabbits, while 34 animals received surgical implantation into the muscular layer. Then, the animals were studied endoscopically and pathologically. The safety and efficiency of the two methods and the pathological features of the animal models were analyzed.

Results

Both the endoscopic and the surgical method had a relatively high success rate of tumor implantation [93.7% (30/32) vs. 97.1% (33/34)] and tumor growth [86.7% (26/30) vs. 81.8% (27/33)], and the variation in the results was not statistically significant (P>0.05). Compared with those produced by the surgical method, the models produced by the endoscopic method had a higher rate of severe esophageal stricture [61.5% (16/26) vs. 29.6% (8/27)] and of intra-luminal tumor growth [73.1% (19/26) vs. 37.0% (10/27)], and had a lower rate of tumor invasion of adjacent organs [53.8% (14/26) vs. 81.5% (22/27)]; all of these results were statistically significant (P<0.05). However, the difference in the survival time and the rates of tumor regional/distant metastasis [38.5% (10/26) vs. 51.8% (14/27)] between the two methods were not statistically significant (P>0.05).

Conclusion

The endoscopic and surgical methods are both safe and effective for establishment of VX2 tumors in the rabbit esophagus. The models produced by the two methods have different pathologic features mimicking that of human ESC. We recommend the models for studies on surgical procedures and minimally invasive treatments.     

Comparative sequence analysis of imprinted genes between human and mouse to reveal imprinting signatures

We performed a comparative genomic sequence analysis between human and mouse for 24 imprinted genes on human chromosomes 1, 6, 7, 11, 13, 14, 15, 18, 19, and 20. The MEME program was used to search for motifs within conserved sequences among the imprinted genes and we then used the MAST program to analyze for the presence or absence of motifs in the imprinted genes and 128 nonimprinted genes. Our analysis identified 15 motifs that were significantly enriched in the imprinted genes. We generated a logistic regression model by combining multiple motifs as input variables and the 24 imprinted genes and the 128 nonimprinted genes as a training set. The accuracy, sensitivity, and specificity of our model were 98, 92, and 99%, respectively. The model was further validated by an open test on 12 additional imprinted genes. The motifs identified in this study are novel imprinting signatures, which should improve our understanding of genomic imprinting and the role of genomic imprinting in human diseases.     

Promoter hypermethylation of tumor suppressor genes in serum as potential biomarker for the diagnosis of nasopharyngeal carcinoma

Purpose: Promoter hypermethylation of tumor suppressor genes may serve as a promising biomarker for the diagnosis of cancer. Cell-free circulating DNA (cf-DNA) shares hypermethylation status with primary tumors. This study investigated promoter hypermethylation of five tumor suppressor genes as markers in the detection of nasopharyngeal carcinoma (NPC) in serum samples. Methods: cf-DNA was extracted from serum collected from 40 NPC patients and 41 age- and sex-matched healthy subjects. The promoter hypermethylation status of the five genes (RASSF1, CDKN2A, DLEC1, DAPK1 and UCHL1) was assessed by methylation-specific PCR after sodium bisulfite conversion. Differences in the methylation status of these five genes between NPC patients and healthy subjects were compared. Results: The concentration of cf-DNA in the serum of NPC patients was significantly higher than that in normal controls. The five tumor suppressor genes – RASSF1, CDKN2A, DLEC1, DAPK1 and UCHL1 – were found to be methylated in 17.5%, 22.5%, 25.0%, 51.4% and 64.9% of patients, respectively. The combination of four-gene marker – CDKN2A, DLEC1, DAPK1 and UCHL1 – had the highest sensitivity and specificity in predicting NPC. Conclusion: Screening DNA hypermethylation of tumor suppressor genes in serum was a promising approach for the diagnosis of NPC.