In vitro and in vivo evaluation of adenovirus combined silk fibroin scaffolds for BMP-7 gene delivery

Introduction and aims: For a scaffold material to be considered effective and efficient for tissue engineering it must be biocompatible as well as bioinductive. Silk fiber is a natural biocompatible material suitable for scaffold fabrication; however, silk is tissue-conductive and lacks tissue-inductive properties. One proposed method to make the scaffold tissue-inductive is to introduce plasmids or viruses encoding a specific growth factor into the scaffold. In this study, we constructed adenoviruses encoding bone morphogenetic protein-7 (BMP-7) and incorporated these into silk scaffolds. The osteo-inductive and new bone formation properties of these constructs were assessed in vivo in a critical-sized skull defect animal model. Materials and methods: Silk fibroin scaffolds containing adenovirus particles coding BMP-7 were prepared. The release of the adenovirus particles from the scaffolds was quantified by tissue-culture infective dose (TCID50) and the bioactivity of the released viruses was evaluated on human bone marrow mesenchymal stromal cells (BMSCs). To demonstrate the in vivo bone forming ability of the virus-carrying silk fibroin scaffold, the scaffold constructs were implanted into calvarial defects in SCID mice. Results: In vitro studies demonstrated that the virus-carrying silk fibroin scaffold released virus particles over a 3 week period while preserving their bioactivity. In vivo test of the scaffold constructs in critical-sized skull defect areas revealed that silk scaffolds were capable of delivering the adenovirus encoding BMP-7, resulting significantly enhanced new bone formation. Conclusions: Silk scaffolds carrying BMP-7 encoding adenoviruses can effectively transfect cells and enhance both in vitro and in vivo osteogenesis. The findings of this study indicate silk fibroin is a promising biomaterial for gene delivery to repair critical-sized bone defects.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

The expanding roles of the ghrelin-gene derived peptide obestatin in health and disease

Obestatin is a 23 amino acid, ghrelin gene-derived peptide hormone produced in the stomach and a range of other tissues throughout the body. While it was initially reported that obestatin opposed the actions of ghrelin with regards to appetite and food intake, it is now clear that obestatin is not an endogenous ghrelin antagonist of ghrelin, but it is a multi-functional peptide hormone in its own right. In this review we will discuss the controversies associated with the discovery of obestatin and explore emerging central and peripheral roles of obestatin, roles in adipogenesis, pancreatic homeostasis and cancer.

A variant of the KLK4 gene is expressed as a cis sense-antisense chimeric transcript in prostate cancer cells

In humans, more than 30,000 chimeric transcripts originating from 23,686 genes have been identified. The mechanisms and association of chimeric transcripts arising from chromosomal rearrangements with cancer are well established, but much remains unknown regarding the biogenesis and importance of other chimeric transcripts that arise from nongenomic alterations. Recently, a SLC45A3–ELK4 chimera has been shown to be androgen-regulated, and is overexpressed in metastatic or high-grade prostate tumors relative to local prostate cancers. Here, we characterize the expression of a KLK4 cis sense–antisense chimeric transcript, and show other examples in prostate cancer. Using non-protein-coding microarray analyses, we initially identified an androgen-regulated antisense transcript within the 3′ untranslated region of the KLK4 gene in LNCaP cells. The KLK4 cis-NAT was validated by strand-specific linker-mediated RT-PCR and Northern blotting. Characterization of the KLK4 cis-NAT by 5′ and 3′ rapid amplification of cDNA ends (RACE) revealed that this transcript forms multiple fusions with the KLK4 sense transcript. Lack of KLK4 antisense promoter activity using reporter assays suggests that these transcripts are unlikely to arise from a trans-splicing mechanism. 5′ RACE and analyses of deep sequencing data from LNCaP cells treated ±androgens revealed six high-confidence sense–antisense chimeras of which three were supported by the cDNA databases. In this study, we have shown complex gene expression at the KLK4 locus that might be a hallmark of cis sense–antisense chimeric transcription.

Phylogeographic reconstruction of a bacterial species with high levels of lateral gene transfer

Background Phylogeographic reconstruction of some bacterial populations is hindered by low diversity coupled with high levels of lateral gene transfer. A comparison of recombination levels and diversity at seven housekeeping genes for eleven bacterial species, most of which are commonly cited as having high levels of lateral gene transfer shows that the relative contributions of homologous recombination versus mutation for Burkholderia pseudomallei is over two times higher than for Streptococcus pneumoniae and is thus the highest value yet reported in bacteria. Despite the potential for homologous recombination to increase diversity, B. pseudomallei exhibits a relative lack of diversity at these loci. In these situations, whole genome genotyping of orthologous shared single nucleotide polymorphism loci, discovered using next generation sequencing technologies, can provide very large data sets capable of estimating core phylogenetic relationships. We compared and searched 43 whole genome sequences of B. pseudomallei and its closest relatives for single nucleotide polymorphisms in orthologous shared regions to use in phylogenetic reconstruction. Results Bayesian phylogenetic analyses of >14,000 single nucleotide polymorphisms yielded completely resolved trees for these 43 strains with high levels of statistical support. These results enable a better understanding of a separate analysis of population differentiation among >1,700 B. pseudomallei isolates as defined by sequence data from seven housekeeping genes. We analyzed this larger data set for population structure and allele sharing that can be attributed to lateral gene transfer. Our results suggest that despite an almost panmictic population, we can detect two distinct populations of B. pseudomallei that conform to biogeographic patterns found in many plant and animal species. That is, separation along Wallace's Line, a biogeographic boundary between Southeast Asia and Australia. Conclusion We describe an Australian origin for B. pseudomallei, characterized by a single introduction event into Southeast Asia during a recent glacial period, and variable levels of lateral gene transfer within populations. These patterns provide insights into mechanisms of genetic diversification in B. pseudomallei and its closest relatives, and provide a framework for integrating the traditionally separate fields of population genetics and phylogenetics for other bacterial species with high levels of lateral gene transfer.

Expression of PSA-RP2, an alternatively spliced variant from the PSA gene, is increased in prostate cancer tissues but the protein is not secreted from prostate cancer cells

PSA-RP2 is a variant transcript expressed from the PSA gene that is conserved in gorillas, chimpanzees and humans suggesting a particular relevance for this transcript in these primates. We demonstrated by qRT-PCR that PSA-RP2 is upregulated in prostate cancer compared with benign prostatic hyperplasia tissues. The PSA-RP2 protein was not detected in seminal fluid and was cytoplasmically localised but not secreted from LNCaP or transfected PC3 prostate cells, despite secretion from transfected Cos-7 and HEK293 kidney cell lines. PSA-RP2-transfected PC3 cells showed slightly decreased proliferation and increased migration towards PC3-conditioned medium that could suggest a functional role in prostate cancer.

Common variation in the fibroblast growth factor receptor 2 gene is not associated with endometriosis risk

BACKGROUND Endometriosis is a polygenic disease with a complex and multifactorial aetiology that affects 8-10% of women of reproductive age. Epidemiological data support a link between endometriosis and cancers of the reproductive tract. Fibroblast growth factor receptor 2 (FGFR2) has recently been implicated in both endometrial and breast cancer. Our previous studies on endometriosis identified significant linkage to a novel susceptibility locus on chromosome 10q26 and the FGFR2 gene maps within this linkage region. We therefore hypothesized that variation in FGFR2 may contribute to the risk of endometriosis. METHODS We genotyped 13 single nucleotide polymorphisms (SNPs) densely covering a 27 kb region within intron 2 of FGFR2 including two SNPs (rs2981582 and rs1219648) significantly associated with breast cancer and a total 40 tagSNPs across 150 kb of the FGFR2 gene. SNPs were genotyped in 958 endometriosis cases and 959 unrelated controls. RESULTS We found no evidence for association between endometriosis and FGFR2 intron 2 SNPs or SNP haplotypes and no evidence for association between endometriosis and variation across the FGFR2 gene. CONCLUSIONS Common variation in the breast-cancer implicated intron 2 and other highly plausible causative candidate regions of FGFR2 do not appear to be a major contributor to endometriosis susceptibility in our large Australian sample.