Biomedical subjects

Yong-Jin Li

Publications and source records attributed to Yong-Jin Li.

4 recordsLinked to original sources

PubMed2006

Reversible immobilization of proteins with streptavidin affinity tags on a surface plasmon resonance biosensor chip.

Dissociation of biotin from streptavidin is very difficult due to their high binding affinity. The re-use of streptavidin-modified surfaces is therefore almost impossible, making devices containing them (e.g. surface plasmon resonance (SPR) sensor chips) expensive. This paper describes a new protocol for reversible and site-directed immobilization of proteins with streptavidin affinity tags on the streptavidin-coated SPR biosensor chip (SA chip). Two streptavidin affinity tags, nano-tag and streptavidin-binding peptide (SBP tag), were applied. They both can specifically interact with streptavidin but have weaker binding force compared to the biotin-streptavidin system, thus allowing association and dissociation under controlled conditions. The SA chip surface could be regenerated repeatedly without loss of activity by injection of 50 mM NaOH solution. The fusion construct of a SBP tag and a single-chain antibody to mature bovine prion protein (scFv-Z186-SBP) interacts with the SA chip, resulting in a single-chain-antibody-modified surface. The chip showed kinetic response to the prion antigen with equilibrium dissociation constant K (D) approximately equal to 4.01 x 10(-7). All results indicated that the capture activity of the SA chip has no irreversible loss after repeated immobilization and regeneration cycles. The method should be of great benefit to various biosensors, biochips and immunoassay applications based on the streptavidin capture surface.

Animals↗

PubMed2006

[Fusion tags technology and their applications].

Fusion tags are originally developed to facilitate the purification of recombinant protein from crude extracts. In recent years, the discovery of different tags and the development of fusion strategy make the function of fusion tags diversified. However, there was no a cure-all fusion tag for different applications. We here give an overview of fusion tag technology and the different applications of fusion tags, including the purification, detection and oriented immobilization of recombinant protein, the visualization of bioevent in vivo, the enhancement of the yield of protein, the improvement of the solubility and stability of the expressed protein.

Recombinant Proteins↗

PubMed2005

[Effects of prenatal methylmercury exposure on learning and memory ability of mice and ultrastructure of hippocampus neurons in mice].

OBJECTIVE: To study the effects of prenatal methylmercury exposure on learning and memory ability of mice and ultrastructure of hippocampus neurons in mice. METHODS: Methylmercury in doses of 0 and 4mg/(kg x d) were fed to pregnant mice at 7th-9th day after conception. Learning and memory ability of the mice offspring was detected. The ultrastructure of hippocampus neurons was observed by electron microscope after the completion of the experiment. RESULTS: The learning and memory ability of the mice offspring of 4 mg/(kg x d) dose group was lower than those of 0 mg/(kg x d) dose group (P < 0.05). Changes in the ultrastructure of hippocampus neurons were obvious in 4 mg/(kg x d) dose group as compared with the 0 mg/(kg x d) dose group. CONCLUSION: Methylmercury could affect the growth and development of central nerve system. The learning and memory ability of mice offspring was greatly damaged and the ultrastructure of hippocampus neurons was changed by methylmercury.

Animals↗

PubMedDate not supplied

Peeling off the hidden genetic heterogeneities of cancers based on disease-relevant functional modules.

Discovering molecular heterogeneities in phenotypically defined disease is of critical importance both for understanding pathogenic mechanisms of complex diseases and for finding efficient treatments. Recently, it has been recognized that cellular phenotypes are determined by the concerted actions of many functionally related genes in modular fashions. The underlying modular mechanisms should help the understanding of hidden genetic heterogeneities of complex diseases. We defined a putative disease module to be the functional gene groups in terms of both biological process and cellular localization, which are significantly enriched with genes highly variably expressed across the disease samples. As a validation, we used two large cancer datasets to evaluate the ability of the modules for correctly partitioning samples. Then, we sought the subtypes of complex diffuse large B-cell lymphoma (DLBCL) using a public dataset. Finally, the clinical significance of the identified subtypes was verified by survival analysis. In two validation datasets, we achieved highly accurate partitions that best fit the clinical cancer phenotypes. Then, for the notoriously heterogeneous DLBCL, we demonstrated that two partitioned subtypes using an identified module ("cellular response to stress") had very different 5-year overall rates (65% vs. 14%) and were highly significantly (P < 0.007) correlated with the clinical survival rate. Finally, we built a multivariate Cox proportional-hazard prediction model that included 4 genes as risk predictors for survival over DLBCL. The proposed modular approach is a promising computational strategy for peeling off genetic heterogeneities and understanding the modular mechanisms of human diseases such as cancers.

Databases, Genetic↗