Abstract:Investigating gene tissue specificity is an important step to understand life process and tissue functions. Despite the long history of research about housekeeping genes and tissue specific genes, their definition and detection methods are various. Housekeeping genes and tissue specific genes can be defined from the aspect of tissue expression number and expression variation across tissues, respectively. In general, housekeeping genes are usually defined as those expressed in most tissues with stable expression levels, while tissue specific or tissue selective genes are defined as those predominantly expressed in one tissue or a few tissues. High-throughput technology, such as microarray, RNA-seq and mass spectrometry have become the main methods to detect the tissue specificity of genes. By comparing the experimental results of some typical researches, we found there are significant differences between different methods in their coverage and sensitivity. In these methods, RNA-seq was the most sensitive, which can detect the most number of housekeeping genes, while mass spectrometry can only detect less tissue specific genes, and the results from different microarray experiments were various. Despite different definition and technology can lead to different housekeeping and tissue specific gene datasets, these datasets have very consistent functions and characters. Housekeeping genes usually implement fundamental functions of tissues or cells, while tissue specific genes perform most specific functions of tissues. Meanwhile, the tissue specificity of genes has close relations with diseases. Compared to other genes, housekeeping genes tend to become cancer genes, while tissue specific genes are more like to become drug targets.

Abstract:Glycosphingolipids are ubiquitous cell membrane and act significantly in many bioprocesses such as cell adhesion, embryonic development, signal transduction and carcinogenesis. The advances of structural analysis of glycosphingolipids using modern analytical instruments, the separation and identification of glycosphingolipids, as well as the biological functions of glycosphingolipids in the progress of diseases were thoroughly discussed in this review. The analysis of glycosphingolipid has made spectacular progress due to the rapid development of modern analytical technology, especially mass spectrometry and the tandem application of chromatography-mass spectrometry. Presently, the use of mass spectrometry in discovering aberrant levels of multiple glycosphingolipids in various malignancies has indicated that the fucosylated glycosphingolipids elevated in the tumor tissues of hepatocellular carcinoma, colorectal cancer, breast cancer and so on. This phenomenon made fucosylated glycosphingolipid a potentially novel cancer marker for early diagnosis. Furthermore, phenotypic and functional research on glycosphingolipids is becoming a popular aspect of glycolipid study, particularly in the relevancy between glycosphingolipids and angiogenesis. For instance, glycosphingolipids shed from the surface of tumor cells act positively on angiogenesis, nevertheless, GM3, a simple ganglioside, acts reversely as a proangiogenesic factor in the tumor microenvironment. This review summarized several cellular hypothesis of the phenomenon above, illustrated the explorations in glycosphingolipid-targeted therapy against malignancies to provide further visions on glycosphingolipid research.

Abstract:Mechanical forces are always involved in a biological process in which intra- and/or inter- biomolecular interactions are essential. Atomic force microscopy (AFM) is an ideal technique that can be used to investigate the mechanical interactions occurred in biological system, due to its high resolution in force measurement and its capability of working in near-physiological conditions. Single-molecule force spectroscopy based on AFM (AFM-SMFS) has an extraordinary ability to interrogate the intra- and/or inter- biomolecular interactions at the single-molecule and/or single-cell level. In this review, the basic principle of AFM-SMFS, and the techniques including AFM tip modifications(silicon/nitride silicon and gold-coated silicon tips), force spectroscopy measurement and data analysis (the worm-like chain model, the freely jointed chain model and the freely rotating chain model) required in AFM-SMFS, are briefly introduced. The emphasis is given on the recent progress made in investigating biomolecules, including proteins (transforming growth factor β1, CD20, Heat Shock Proteins, PTK7, heparin-binding haemagglutinin adhesion and Als5p adhesion proteins) and carbohydrates(glucose, mannose, galactose, group B carbohydrate, capsular polysaccharide, α-mannans, β-mannans, β-glucans and chitin) existing on mammalian, bacterial and fungal cell surfaces. Finally, the limitations of AFM-SMFS and its future applications have been summarized.

Abstract:Filamentous fungi are efficient cell factories in producing industrial enzyme products as the efficiency in extracellular proteins secretion. Most researches on extracellular proteins secretion in new century found that the protein secretion pathway of filamentous fungi had an efficient secretion mechanism compared with other eukaryotes'. In order to explore the efficient mechanism, this paper summarized the latest research progresses of secretory pathway in filamentous fungi. The key proteins in the secretory pathway were selected to perform sequence alignment and structure alignment. And the possible efficient secretion mechanism was put forward.

Abstract:Sialyltransferase (ST) and sialidase (SA) are the main enzymes responsible for the addition or removal of sialic acids to the terminal of glycan on glycoprotein or glycolipids. In our study, the expression of sialic acids, sialidases and sialyltransferases in normal bladder epithelial cell line HCV29, and two bladder cancer cell lines KK47 and YTS-1 were detected. Our results showed YTS-1 cells, the highly invasive cell line, expressed higher level of sialic acids than other two cell lines. However, the level of Neu1 in YTS-1 cells was the lowest among all the cell lines. The expression of Toll like receptors TLR1,2,3,4 was consistent with neu1 expression in these three cell lines. When normal bladder cell HCV29 underwent TGF-β induced epithelial to mesenchymal transition (EMT) process, expression of Neu1 and TLR3 were significantly decreased. When Neu1 expression was inhibited in HCV29 cell line, the level of TLR3 was also reduced. Overexpression of Neu1 in YTS-1cells resulted in TLR3 increase accompanied with the activation of NF-κB signaling pathway. Our results indicated that Neu1 shared closed relationship with the expression of TLRs in bladder cancer cells, which may potentially provide therapeutic candidates in treating bladder cancer.

Abstract:To identify signature genes for the tumor progression of lung squamous cell carcinoma, which provides a deeper theoretical basis for further explanation of its inherent mechanism, new targeted drugs and treatments development. The pattern recognition method was used to analysis the genome-wide mRNA gene expression (GE) values, methylation values (ME), and copy number variation (CNV) data. To overcome the disadvantages inherent in the genome-wide data such as ultrahigh-dimensional-small-size, high-noise and multi-correlation among genes, and to overcome the predominate influence of the whole genome to the dozens of signature genes, a new iterative multiple variable selection strategy was used to identify signature genes step by step. The importance of genes was comprehensively evaluated by their significant difference with SAM (significant analysis of microarray), statistical analysis using PLS (partial least squares), known biological functions and contributions to the classification model. 67 GE signature genes, 70 ME signature genes and 31 CNV signature genes were identified from the LUSC stageⅠ～Ⅲ patient samples in TCGA (The Cancer Genome Atlas project) database. The corresponding accuracies from 5 fold cross-validation are: 86.29%, 90.92 % and 69.16% respectively. The genetic network analysis and pathway analysis using KEGG (Kyoto Encyclopedia of Genes and Genomes) and IPA (Ingenuity Pathway Analysis) indicated the highly related relationship among these three kinds of genes. They also indicated the immediate relationship between our signature genes and the progression of LUSC which is very important to the understanding of its mechanism and to the development of new targeted therapy.

Abstract:Cell penetrating peptides (CPPs) are kinds of small molecular peptides, which can penetrate cell membrane easily. Their discovery sheds light on delivering drugs into target efficiently. Therefore, the investigation of CPPs has crucial significance in biomedicine field. In this work we intended to find factors which have influence on CPPs penetrating activity and introduce a new method called physico-chemical mass center of bio-sequence. This method was enlightened by particle mechanics. We used it to analyze bio-sequence. In addition, the differences between all kinds of CPPs with different penetrating activities were also investigated. The CPPs and Non-cell penetrating peptides (NonCPPs) were obtained based on CPPsite database version 1.0 (http://crdd.osdd.net/raghava/cppsite1/) and references, respectively. After that we extracted CPPs with high, medium, and low penetrating activities (HCPPs, MCPPs, LCPPs), respectively. Firstly, the amino acids composition was calculated for every peptide in HCPPs, MCPPs, LCPPs datasets, individually. We used ANOVA to analyze the amino acids composition in HCPPs, MCPPs, LCPPs datasets. From the results we noticed that there has a significant difference for amino acids with electric charge and hydrophobic properties. These results revealed that electrostatic and hydrophobic interactions may play a key role in CPPs' penetrating activities. ANOVA analysis also revealed that helix and coil structure may also have influence on CPPs' activities. Secondly, CPPs and NonCPPs can yield a clustering phenomenon under some physicochemical features such as pK values, and their corresponding lengths. HCPPs, MCPPs, LCPPs, and NonCPPs can be divided into three groups. The differences between CPPs and NonCPPs can be reflected by the above phenomena. Lastly, as a case study we used the new concept named physico-chemical mass center of bio-sequence method encouraged by particle mechanics to study CPPs. The sequences can be represented by a series of points in the above method. Combining with principal component analysis (PCA), we found that the distribution of CPPs under their first, second and third scores can generate a cluster for CPPs. The differences between HCPPs, MCPPs, LCPPs and NonCPPs were also demonstrated by the above phenomenon. From this study, we can conclude that this work can help us to further understand the differences between them in terms of their primary structures and the factors affecting on their activities. Most important, the physico-chemical mass center can be used to analyze other biological issues as well as input features for biological pattern recognitions.

Abstract:Female fig wasps differ phenotypically from conspecific males to the extent that often they cannot be associated with one another. Weighted gene co-expression network analysis (WGCNA) of the genome and transcriptomes of one such fig wasp, Ceratosolensolmsi, generated five expression modules, which were flagged as blue, turquoise, brown, green and yellow. These involved two female-biased expression modules and three pupa-biased expression modules, respectively. Gene ontologies indicated three functional enrichment gene sets in modules turquoise and yellow. Two functional enrichment gene sets that participate in cell cycle or have nucleotide binding activityclustered in turquoise module. The functionally enriched gene set in yellow module played roles in cell differentiation, especially in neuron morphogenesis.