Optimization of Heavy Chain and Light Chain Signal Peptides for High Level Expression of Therapeutic Antibodies in CHO Cells

Translocation of a nascent protein from the cytosol into the ER mediated by its signal peptide is a critical step in protein secretion. The aim of this work was to develop a platform technology to optimize the signal peptides for high level production of therapeutic antibodies in CHO cells. A database of signal peptides from a large number of human immunoglobulin (Ig) heavy chain (HC) and kappa light chain (LC) was generated. Most of the HC signal peptides contain 19 amino acids which can be divided into three domains and the LC signal peptides contain 22 amino acids. The signal peptides were then clustered according to sequence similarity. Based on the clustering, 8 HC and 2 LC signal peptides were analyzed for their impacts on the production of 5-top selling antibody therapeutics, namely, Herceptin, Avastin, Remicade, Rituxan, and Humira. The best HC and LC signal peptides for producing these 5 antibodies were identified. The optimized signal peptides for Rituxan is 2-fold better compared to its native signal peptides which are available in the public database. Substitution of a single amino acid in the optimized HC signal peptide for Avastin reduced its production significantly. Mass spectrometry analyses revealed that all optimized signal peptides are accurately removed in the mature antibodies. The results presented in this report are particularly important for the production of these 5 antibodies as biosimilar drugs. They also have the potential to be the best signal peptides for the production of new antibodies in CHO cells.     

1H-NMR and MS Based Metabolomics Study of the Intervention Effect of Curcumin on Hyperlipidemia Mice Induced by High-Fat Diet

Curcumin, a principle bioactive component of Curcuma longa L, is well known for its anti-hyperlipidemia effect. However, no holistic metabolic information of curcumin on hyperlipidemia models has been revealed, which may provide us an insight into the underlying mechanism. In the present work, NMR and MS based metabolomics was conducted to investigate the intervention effect of curcumin on hyperlipidemia mice induced by high-fat diet (HFD) feeding for 12 weeks. The HFD induced animals were orally administered with curcumin (40, 80 mg/kg) or lovastatin (30 mg/kg, positive control) once a day during the inducing period. Serum biochemistry assay of TC, TG, LDL-c, and HDL-c was conducted and proved that treatment of curcumin or lovastatin can significantly improve the lipid profiles. Subsequently, metabolomics analysis was carried out for urine samples. Orthogonal Partial Least Squares-Discriminant analysis (OPLS-DA) was employed to investigate the anti-hyperlipidemia effect of curcumin and to detect related potential biomarkers. Totally, 35 biomarkers were identified, including 31 by NMR and nine by MS (five by both). It turned out that curcumin treatment can partially recover the metabolism disorders induced by HFD, with the following metabolic pathways involved: TCA cycle, glycolysis and gluconeogenesis, synthesis of ketone bodies and cholesterol, ketogenesis of branched chain amino acid, choline metabolism, and fatty acid metabolism. Besides, NMR and MS based metabolomics proved to be powerful tools in investigating pharmacodynamics effect of natural products and underlying mechanisms.     

MicroRNA Expression Profile during Aphid Feeding in Chrysanthemum (Chrysanthemum morifolium)

MicroRNAs (miRNAs) are important regulators of gene expression, affecting many biological processes. As yet, their roles in the response of chrysanthemum to aphid feeding have not been explored. Here, the identity and abundance of miRNAs induced by aphid infestation have been obtained using high-throughput Illumina sequencing platform. Three leaf small RNA libraries were generated, one from plants infested with the aphid Macrosiphoniella sanbourni (library A), one from plants with mock puncture treatment (library M), and the third from untreated control plants (library CK). A total of 7,944,797, 7,605,251 and 9,244,002 clean unique reads, ranging from 18 to 30 nucleotides (nt) in length, were obtained from library CK, A and M, respectively. As a result, 303 conserved miRNAs belonging to 276 miRNAs families and 234 potential novel miRNAs were detected in chrysanthemum leaf, out of which 80, 100 and 79 significantly differentially expressed miRNAs were identified in the comparison of CK-VS-A, CK-VS-M and M-VS-A, respectively. Several of the differentially abundant miRNAs (in particular miR159a, miR160a, miR393a) may be associated with the plant''s response to aphid infestation.     

Cytokine and Antibody Based Diagnostic Algorithms for Sputum Culture-Positive Pulmonary Tuberculosis

Background

Tuberculosis (TB) is one of the most serious infectious diseases globally and has high mortality rates. A variety of diagnostic tests are available, yet none are wholly reliable. Serum cytokines, although significantly and frequently induced by different diseases and thus good biomarkers for disease diagnosis and prognosis, are not sufficiently disease-specific. TB-specific antibody detection, on the other hand, has been reported to be highly specific but not sufficiently sensitive. In this study, our aim was to improve the sensitivity and specificity of TB diagnosis by combining detection of TB-related cytokines and TB-specific antibodies in peripheral blood samples.

Methods

TB-related serum cytokines were screened using a human cytokine array. TB-related cytokines and TB-specific antibodies were detected in parallel with microarray technology. The diagnostic performance of the new protocol for active TB was systematically compared with other traditional methods.

Results

Here, we show that cytokines I-309, IL-8 and MIG are capable of distinguishing patients with active TB from healthy controls, patients with latent TB infection, and those with a range of other pulmonary diseases, and that these cytokines, and their presence alongside antibodies for TB-specific antigens Ag14-16kDa, Ag32kDa, Ag38kDa and Ag85B, are specific markers for active TB. The diagnostic protocol for active TB developed here, which combines the detection of three TB-related cytokines and TB-specific antibodies, is highly sensitive (91.03%), specific (90.77%) and accurate (90.87%).

Conclusions

Our results show that combining detection of TB-related cytokines and TB-specific antibodies significantly enhances diagnostic accuracy for active TB, providing greater accuracy than conventional diagnostic methods such as interferon gamma release assays (IGRAs), TB antibody Colloidal Gold Assays and microbiological culture, and suggest that this diagnostic protocol has potential for clinical application.     

An Effective Method to Identify Heritable Components from Multivariate Phenotypes

Multivariate phenotypes may be characterized collectively by a variety of low level traits, such as in the diagnosis of a disease that relies on multiple disease indicators. Such multivariate phenotypes are often used in genetic association studies. If highly heritable components of a multivariate phenotype can be identified, it can maximize the likelihood of finding genetic associations. Existing methods for phenotype refinement perform unsupervised cluster analysis on low-level traits and hence do not assess heritability. Existing heritable component analytics either cannot utilize general pedigrees or have to estimate the entire covariance matrix of low-level traits from limited samples, which leads to inaccurate estimates and is often computationally prohibitive. It is also difficult for these methods to exclude fixed effects from other covariates such as age, sex and race, in order to identify truly heritable components. We propose to search for a combination of low-level traits and directly maximize the heritability of this combined trait. A quadratic optimization problem is thus derived where the objective function is formulated by decomposing the traditional maximum likelihood method for estimating the heritability of a quantitative trait. The proposed approach can generate linearly-combined traits of high heritability that has been corrected for the fixed effects of covariates. The effectiveness of the proposed approach is demonstrated in simulations and by a case study of cocaine dependence. Our approach was computationally efficient and derived traits of higher heritability than those by other methods. Additional association analysis with the derived cocaine-use trait identified genetic markers that were replicated in an independent sample, further confirming the utility and advantage of the proposed approach.     

人脐带和骨髓间充质干细胞体外分离培养及生物学特性比较

目的体外分离培养、扩增人脐带间充质干细胞(h UC-MSC)和人骨髓间充质干细胞(h BM-MSC),并对其生物学特性进行比较。方法采用组织块贴壁法从足月胎儿脐带分离、纯化和培养h UC-MSC,健康成人骨髓肝素抗凝后,采用密度梯度离心法分离、纯化和培养h BM-MSC;用倒置显微镜观察两种细胞的形态及细胞生长增殖情况,流式细胞仪分析检测第3代细胞表面标志的表达,Von?Kossa染色及油红O染色检测分化潜能。结果镜下两种细胞均为贴壁生长,形态为均一的成纤维细胞样,取相同数量的细胞传代接种后,h UC-MSC的增殖速率快于h BM-MSC,两种细胞具有均一的细胞表型,均表达CD29、CD44、CD105,不表达CD45、CD34、HLA-DR、HLA-G、CD80、CD86,两种细胞都有成骨、成脂分化潜能,但h UC-MSC的分化潜能更强。结论 h UC-MSC与h BM-MSC具有相似的生物学特性,且前者具有更强的增殖能力和分化潜能,h UC-MSC有望成为h BMMSC理想的替代来源。     

Thrombotic Role of Blood and Endothelial Cells in Uremia through Phosphatidylserine Exposure and Microparticle Release

The mechanisms contributing to an increased risk of thrombosis in uremia are complex and require clarification. There is scant morphological evidence of membrane-dependent binding of factor Xa (FXa) and factor Va (FVa) on endothelial cells (EC) in vitro. Our objectives were to confirm that exposed phosphatidylserine (PS) on microparticle (MP), EC, and peripheral blood cell (PBC) has a prothrombotic role in uremic patients and to provide visible and morphological evidence of PS-dependent prothrombinase assembly in vitro. We found that uremic patients had more circulating MP (derived from PBC and EC) than controls. Additionally, patients had more exposed PS on their MPs and PBCs, especially in the hemodialysis group. In vitro, EC exposed more PS in uremic toxins or serum. Moreover, reconstitution experiments showed that at the early stages, PS exposure was partially reversible. Using confocal microscopy, we observed that PS-rich membranes of EC and MP provided binding sites for FVa and FXa. Further, exposure of PS in uremia resulted in increased generation of FXa, thrombin, and fibrin and significantly shortened coagulation time. Lactadherin, a protein that blocks PS, reduced 80% of procoagulant activity on PBC, EC, and MP. Our results suggest that PBC and EC in uremic milieu are easily injured or activated, which exposes PS and causes a release of MP, providing abundant procoagulant membrane surfaces and thus facilitating thrombus formation. Blocking PS binding sites could become a new therapeutic target for preventing thrombosis.     

Graphite Carbon-Supported Mo2C Nanocomposites by a Single-Step Solid State Reaction for Electrochemical Oxygen Reduction

Novel graphite-molybdenum carbide nanocomposites (G-Mo₂C) are synthesized by a typical solid state reaction with melamine and MoO₃ as precursors under inert atmosphere. The characterization results indicate that G-Mo₂C composites are composed of high crystallization and purity of Mo₂C and few layers of graphite carbon. Mo₂C nanoparticles with sizes ranging from 5 to 50 nm are uniformly supported by surrounding graphite layers. It is believed that Mo atom resulting from the reduction of MoO₃ is beneficial to the immobilization of graphite carbon. Moreover, the electrocatalytic performances of G-Mo₂C for ORR in alkaline medium are investigated by cyclic voltammetry (CV), rotating disk electrode (RDE) and chronoamperometry test with 3M methanol. The results show that G-Mo₂C has a considerable catalytic activity and superior methanol tolerance performance for the oxygen reduction reaction (ORR) benefiting from the chemical interaction between the carbide nanoparticles and graphite carbon.     

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells.