Distinguishing Glioblastoma Subtypes by Methylation Signatures.

Glioblastoma, also called glioblastoma multiform (GBM), is the most aggressive cancer that initiates within the brain. GBM is produced in the central nervous system. Cancer cells in GBM are similar to stem cells. Several different schemes for GBM stratification exist. These schemes are based on intertumoral molecular heterogeneity, preoperative images, and integrated tumor characteristics. Although the formation of glioblastoma is remarkably related to gene methylation, GBM has been poorly classified by epigenetics. To classify glioblastoma subtypes on the basis of different degrees of genes' methylation, we adopted several powerful machine learning algorithms to identify numerous methylation features (sites) associated with the classification of GBM. The features were first analyzed by an excellent feature selection method, Monte Carlo feature selection (MCFS), resulting in a feature list. Then, such list was fed into the incremental feature selection (IFS), incorporating one classification algorithm, to extract essential sites. These sites can be annotated onto coding genes, such as CXCR4, TBX18, SP5, and TMEM22, and enriched in relevant biological functions related to GBM classification (e.g., subtype-specific functions). Representative functions, such as nervous system development, intrinsic plasma membrane component, calcium ion binding, systemic lupus erythematosus, and alcoholism, are potential pathogenic functions that participate in the initiation and progression of glioblastoma and its subtypes. With these sites, an efficient model can be built to classify the subtypes of glioblastoma.

Identifying Robust Microbiota Signatures and Interpretable Rules to Distinguish Cancer Subtypes.

Cancer can be generally defined as a cluster of systematic diseases triggered by abnormal cell proliferation and growth. With the development of biological sciences and biotechnologies, the etiology of cancer is partially revealed, including some of the most substantial pathogenic factors [either endogenous (genetics) or exogenous (environmental)]. However, some remaining factors that contribute to the tumorigenesis but have not been analyzed and discussed in detail remain. For instance, some typical correlations between microorganisms and tumorigenesis have been reported already, but previous studies are just sporadic studies on single microorganism-cancer subtype pairs and do not explain and validate the specific contribution of microbiome on tumorigenesis. On the basis of the systematic microbiome analyses of blood and cancer-associated tissues in cancer patients/controls in public domain, we performed interpretable analyses. We identified several core regulatory microorganisms that contribute to the classification of multiple tumor subtypes and established quantitative predictive models for interpretable prediction by using multiple machine learning methods. We also compared the optimal features (microorganisms) and rules identified from microbiome profiles processed using the Kraken and the SHOGUN. Collectively, our study identified new microbiome signatures and their interpretable classification rules for cancer discrimination and carried out reliable methodological comparison for robust cancer microbiome analyses, thereby promoting the development of tumor etiology at the microbiome level.

Isolation ssDNA aptamers specific for both live and viable but nonculturable state Vibrio vulnificus using whole bacteria-SEILEX technology.

Vibrio vulnificus is a ubiquitous marine bacterium that may cause rapid and deadly infection, threatening lives of people living around natural bodies of water, especially in coastal regions. However, traditional culture-based methods are time-consuming and unable to detect Viable But Non-Culturable (VBNC) V. vulnificus cells. In this work, we isolated a batch of detection aptamers specifically binding to V. vulnificus in all culture status. With traditional whole bacteria-SELEX (Systematic Evolution of Ligands by EXponential enrichment), flow cytometer analysis and imaging, we identify 18 candidates and validated two of them (V8 and V13) as applicable aptamers. Their truncated sequences also showed comparable performance. The dissociation constant (KD) value of V8 is shown to be as low as 11.22 ± 1.32 nM. Optimal aptamers V8 and V13 are also validated to be effective to detect different Vibrio vulnificus strains under different binding environments using flow cytometry. As for detection parameters, the LOD of the V8 from cytometry is 29.96 CFU mL-1, and the linear range is 102-5 × 105 CFU mL-1. This is the first case demonstrating that aptamers can detect the existence of VBNC bacteria as well as live bacteria.

Rapid and sensitive detection of nodularin-R in water by a label-free BLI aptasensor.

Contamination of freshwater with nodularin-R (NOD-R) represents a significant global environmental and public health concern. However, ethical problems and technical difficulties surrounding the current detection methods for NOD-R necessitate further studies to devise appropriate alternatives within a regulatory monitoring regime. In this work, we employed an aptamer as a specific recognition element and developed a biolayer interferometry (BLI) biosensor platform for NOD-R detection. The aptasensor we propose displayed a broad detection range from 40 to 600 nM NOD-R (and a linear response range from 40 to 200 nM), and achieved a detection limit as low as 167 pM. In addition, the aptamer-based biosensor was shown to possess high selectivity, as well as good reproducibility and stability. We believe that this novel aptamer-based biosensor provides a potential alternative for the sensitive and rapid detection of NOD-R.

Study of the binding mechanism between aptamer GO18-T-d and gonyautoxin 1/4 by molecular simulation.

GTX1/4 can induce the formation of an antiparallel G-quadruplex structure in aptamer GO18-T-d and combine steadily in the groove at the top of the G-quadruplex structure. The complex structures and special induced fit mechanism between aptamer and small molecules provide a reference for aptamer development in molecular diagnostics and therapeutic application.

The Annexin a2 Promotes Development in Arthritis through Neovascularization by Amplification Hedgehog Pathway.

The neovascularization network of pannus formation plays a crucial role in the development of rheumatoid arthritis (RA). Annexin a2 (Axna2) is an important mediating agent that induces angiogenesis in vascular diseases. The correlation between Axna2 and pannus formation has not been studied. Here, we provided evidence that compared to osteoarthritis (OA) patients and healthy people, the expression of Axna2 and Axna2 receptor (Axna2R) were up-regulated in patients with RA. Joint swelling, inflammation and neovascularization were increased significantly in mice with collagen-induced arthritis (CIA) that were exogenously added Axna2. Cell experiments showed that Axna2 promoted HUVEC proliferation by binding Axna2R, and could activate Hedgehog (HH) signaling and up-regulate the expression of Ihh and Gli. Besides, expression of Ihh, Patched (Ptc), Smoothened (Smo) and Gli and matrix metalloproteinase-2 (MMP-2), vascular endothelial growth factor (VEGF) and angiopoietin-2 (Ang-2), angiogenic growth factor of HH signaling downstream, were down-regulated after inhibition of expression Axna2R on HUVEC. Together, our research definitely observed that over-expression of Axna2 could promote the development of CIA, especially during the process of pannus formation for the first time. Meanwhile, Axna2 depended on combining Axna2R to activate and enlarge HH signaling and the expression of its downstream VEGF, Ang-2 and MMP-2 to promote HUVEC proliferation, and eventually caused to angiogenesis. Therefore, the role of Axna2 is instructive for understanding the development of RA, suppress the effect of Axna2 might provide a new potential measure for treatment of RA.

Gonyautoxin 1/4 aptamers with high-affinity and high-specificity: From efficient selection to aptasensor application.

Gonyautoxin 1/4 (GTX1/4) are potent marine neurotoxins with significant public health impact. However, the ethical issues and technical defects associated with the currently applied detection methods for paralytic shellfish toxin GTX1/4 are pressing further studies to develop suitable alternatives in a regulatory monitoring system. This work describes the first successful selection, optimization, and characterization of an aptamer that bind with high affinity and specificity to GTX1/4. Compared to the typical MB-SELEX, GO-SELEX, an advanced screening technology, has significant advantages for small molecular aptamer development. Furthermore, we truncated GTX1/4 aptamer and obtained the aptamer core sequence with a higher Kd of 17.7 nM. The aptamer GO18-T-d was then used to construct a label-free and real-time optical BLI aptasensor for the detection of GTX1/4. The aptasensor showed a broad detection range from 0.2 to 200 ng/mL GTX1/4 (linear range from 0.2 to 90 ng/mL), with a low detection limit of 50 pg/mL. Moreover, the aptasensor exhibited a high degree of specificity for GTX1/4 and no cross reactivity to other marine toxins. The aptasensor was then applied to the detection of GTX1/4 in spiked shellfish samples and showed a good reproducibility and stability. We believe that this novel aptasensor offers a promising alternative to traditional analytical methods for the rapid detection of the marine biotoxin GTX1/4.

Core-shell molecularly imprinted polymer nanoparticles with assistant recognition polymer chains for effective recognition and enrichment of natural low-abundance protein.

Core-shell molecular imprinting of nanomaterials overcomes difficulties with template transfer and achieves higher binding capacities for macromolecular imprinting, which are more important to the imprinting of natural low-abundance proteins from cell extracts. In the present study, a novel strategy of preparing core-shell nanostructured molecularly imprinted polymers (MIPs) was developed that combined the core-shell approach with assistant recognition polymer chains (ARPCs). Vinyl-modified silica nanoparticles were used as support and ARPCs were used as additional functional monomers. Immunoglobulin heavy chain binding protein (BiP) from the endoplasmic reticulum (ER) was chosen as the model protein. The cloned template protein BiP was selectively assembled with ARPCs from their library, which contained numerous limited-length polymer chains with randomly distributed recognition and immobilization sites. The resulting complex was copolymerized onto the surface of vinyl-modified silica nanoparticles under low concentrations of the monomers. After template removal, core-shell-structured nanoparticles with a thin imprinted polymer layer were produced. The particles demonstrated considerably high adsorption capacity, fast adsorption kinetics and selective binding affinities toward the template BiP. Furthermore, the synthesized MIP nanoparticles successfully isolated cloned protein BiP from protein mixtures and highly enriched BiP from an ER extract containing thousands of kinds of proteins. The enrichment reached 115-fold and the binding capacity was 5.4 µg g(-1), which were higher than those achieved by using traditional MIP microspheres. The advantageous properties of MIP nanoparticles hold promise for further practical applications in biology, such as protein analysis and purification.

The design of protein-imprinted polymers as antibody substitutes for investigating protein-protein interactions.

Co-immunoprecipitation is a very effective method for studying protein-protein interactions. However, the preparation of antibodies in this method involves the injection of antigen into mammals, and requires the use of the expensive protein A-Sepharose 4B. Molecular imprinting polymer can compensate for these deficiencies. In this paper, a new strategy for studying protein interactions is reported; this method is based on the use of protein-imprinted polymers (PIPs). PIP is a proper substitute for antibody. We designed and synthesized assistant recognition polymer chains (ARPCs), which were limited length polymer chains with randomly distributed recognition and immobilizing sites. The template protein was selectively assembled with ARPCs. The assemblies were adsorbed by macroporous microspheres, and were immobilized by cross-linking polymerization. After removing the templates, the two kinds of synthesized PIPs were used to adsorb natural BiP or FKBP23 from ER extract; both showed high selectivity. Furthermore, we investigated the binding specificity of BiP to FKBP23, using synthesized PIPs. The results showed that FKBP23 could bind to BiP in ER in a process regulated by the concentration of Ca(2+), which was consistent with the immunoprecipitation results. This strategy may provide a general solution for investigating protein interactions.