Metabolic Engineering of the Isopentenol Utilization Pathway Enhanced the Production of Terpenoids in Chlamydomonas reinhardtii.

Eukaryotic green microalgae show considerable promise for the sustainable light-driven biosynthesis of high-value fine chemicals, especially terpenoids because of their fast and inexpensive phototrophic growth. Here, the novel isopentenol utilization pathway (IUP) was introduced into Chlamydomonas reinhardtii to enhance the hemiterpene (isopentenyl pyrophosphate, IPP) titers. Then, diphosphate isomerase (IDI) and limonene synthase (MsLS) were further inserted for limonene production. Transgenic algae showed 8.6-fold increase in IPP compared with the wild type, and 23-fold increase in limonene production compared with a single MsLS expressing strain. Following the culture optimization, the highest limonene production reached 117 µg/L, when the strain was cultured in a opt2 medium supplemented with 10 mM isoprenol under a light: dark regimen. This demonstrates that transgenic algae expressing the IUP represent an ideal chassis for the high-value terpenoid production. The IUP will facilitate further the metabolic and enzyme engineering to enhance the terpenoid titers by significantly reducing the number of enzyme steps required for an optimal biosynthesis.

[Quantitative Analysis of Heave Mental Ion Based on Portable NIR Spectrometer].

By virtue of the characters of rapid analysis and simple pretreatment, near infrared reflectance spectroscopy technique is widely used in agriculture, medicine, environment, petrochemical and other fields. To satisfy the rapid on-site identification and analysis, portable near-infrared spectrometers have gained more and more attention. Because near infrared reflectance spectroscopy technique also is a green tool for multi-component analysis, the paper aims at investigating the feasibility for simultaneous quantitative analysis of various heavy metal ions in dilute solution using portable near infrared spectrometer. First, amino modified polymerized starch was used as adsorbent to enrich nickel ions and copper ions in diluted solution. Then, the diffuse reflectance spectra of amino modified polymerized starch samples were measured directly by portable near-infrared spectrometer. Furthermore, with the help of spectral preprocessing methods and partial least-squares regression, quantitative models were built from the near infrared diffuse reflectance spectra of amino modified polymerized starch enriched with heavy metal ions and reference concentrations. At last, the stability of the models was proved through cross validation and external validation. The results show that nickel ions and copper ions in diluted solution can be efficiently enriched by amino modified polymerized starch in the presence of other interfering ions. The adsorption rates for nickel ions and copper ions are 99.5% and 99.8%, respectively. Two robust models can be achieved after spectra processing and partial least squares regression. The spectra processing methods contains Continuous wavelet transform and multiplicative scatter correction combined with Savitzky-Golay. The obtained corresponding correlation coefficients of the two robust models are 0.981 9 and 0.965 4, respectively. Thus, simultaneous quantitative analysis of nickel ions and copper ions in the mixed diluted solution was achieved, and the detectable concentrations of nickel ions and copper ions are both as low as 3.0 mg·L(-1). The method not only improves the sensitivity of near infrared reflectance spectroscopy technique, but also demonstrates the feasibility for simultaneous quantitative determination of various heavy metal ions by using portable near infrared spectrometer. Moreover, the method may be a useful exploration to further broaden the application of near infrared reflectance spectroscopy technique.

[Near infrared spectroscopy and multivariate statistical process analysis for real-time monitoring of production process].

Near infrared diffusive reflectance spectroscopy has been applied in on-site or on-line analysis due to its characteristics of fastness, non-destruction and the feasibility for real complex sample analysis. The present work reported a real-time monitoring method for industrial production by using near infrared spectroscopic technique and multivariate statistical process analysis. In the method, the real-time near infrared spectra of the materials are collected on the production line, and then the evaluation of the production process can be achieved by a statistic Hotelling T2 calculated with the established model. In this work, principal component analysis (PCA) is adopted for building the model, and the statistic is calculated by projecting the real-time spectra onto the PCA model. With an application of the method in a practical production, it was demonstrated that a real-time evaluation of the variations in the production can be realized by investigating the changes in the statistic, and the comparison of the products in different batches can be achieved by further statistics of the statistic. Therefore, the proposed method may provide a practical way for quality insurance of production processes.

Unlabeled multi tumor marker detection system based on bioinitiated light addressable potentiometric sensor.

Multi biomarkers' assays are of great significance in clinical diagnosis. A label-free multi tumor markers' parallel detection system was proposed based on a light addressable potentiometric sensor (LAPS). Arrayed LAPS chips with basic structure of Si(3)N(4)-SiO(2)-Si were prepared on silicon wafers, and the label-free parallel detection system for this component was developed with user friendly controlling interfaces. Then the l-3,4-dihydroxyphenyl-alanine (L-Dopa) hydrochloric solution was used to initiate the surface of LAPS. The L-Dopa immobilization state was investigated by the theoretical calculation. L-Dopa initiated LAPS' chip was biofunctionalized respectively by the antigens and antibodies of four tumor markers, α-fetoprotein (AFP), carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9) and Ferritin. Then unlabeled antibodies and antigens of these four biomarkers were detected by the proposed detection systems. Furthermore physical and measuring principles in this system were described, and qualitative understanding for experimental data were given. The measured response ranges were compared with their clinical cutoff values, and sensitivities were calculated by OriginLab. The results indicate that this bioinitiated LAPS based label-free detection system may offer a new choice for the realization of unlabeled multi tumor markers' clinical assay.

[Classification of oils by attenuated total reflectance-Fourier transform infrared spectrometry combined with pattern recognition techniques].

In the present work, the combination of attenuated total reflectance-Fourier transform infrared spectrometry (ATR-FTIR) and pattern recognition, including principal components analysis (PCA) and hierarchical cluster analysis (HCA), is used as a fast and convenient analytical tool to classify oil samples. Twenty five samples including crude oils and fuel oils with different total contents of n-alkanes were analyzed. It was found that multiplicative scatter correction (MSC) and continuous wavelet transform (CWT) as a pretreatment method could improve the classification results of pattern recognition. The classification results were proved to be in agreement with the origin of the oil samples. The oils with high content of n-alkanes and those with low content were classified clearly by this developed method, but it still had some constraint to differentiating oils with little difference. The present work provides a feasible method for quick classification of oils, which can be used for the initial identification of spill oils and afford useful information for the further identification of the oils.

[A local regression method for near-infrared spectral quantitative analysis of tobacco samples].

A local regression method based on distance criterion in principal component (PC) space for near-infrared (NIR) spectral quantitative analysis was proposed. In this method, principal component analysis (PCA) is firstly utilized to extract the information of the NIR spectra, and then, the calibration subsets are individually selected for each prediction sample according to the distance between the sample and calibration samples in the PCs space. Finally, the PLS local model for every prediction sample is established individually and the prediction of the sample is done with the local model. It was found that the Euclidean distance can more effectively measure the similarity of the samples than Mahalanobis distance. With an application of the local regression method to the quantitative determination of chlorine and nicotine in tobacco samples, it is proved that the prediction precision of local regression method is better than that of global regression methods, especially in the situation of predicting the low concentration components.

Molecular dynamics simulation reveals how phosphorylation of tyrosine 26 of phosphoglycerate mutase 1 upregulates glycolysis and promotes tumor growth.

Phosphoglycerate mutase 1 (PGAM1) catalyzes the eighth step of glycolysis and is often found upregulated in cancer cells. To test the hypothesis that the phosphorylation of tyrosine 26 residue of PGAM1 greatly enhances its activity, we performed both conventional and steered molecular dynamics simulations on the binding and unbinding of PGAM1 to its substrates, with tyrosine 26 either phosphorylated or not. We analyzed the simulated data in terms of structural stability, hydrogen bond formation, binding free energy, etc. We found that tyrosine 26 phosphorylation enhances the binding of PGAM1 to its substrates through generating electrostatic environment and structural features that are advantageous to the binding. Our results may provide valuable insights into computer-aided design of drugs that specifically target cancer cells with PGAM1 tyrosine 26 phosphorylated.

Development of functional biointerfaces by surface modification of polydimethylsiloxane with bioactive chlorogenic acid.

The effect of physicochemical surface properties and chemical structure on the attachment and viability of bacteria and mammalian cells has been extensively studied for the development of biologically relevant applications. In this study, we report a new approach that uses chlorogenic acid (CA) to modify the surface wettability, anti-bacterial activity and cell adhesion properties of polydimethylsiloxane (PDMS). The chemical structure of the surface was obtained by X-ray photoelectron spectroscopy (XPS), the roughness was measured by atomic force microscopy (AFM), and the water contact angle was evaluated for PDMS substrates both before and after CA modification. Molecular modelling showed that the modification was predominately driven by van der Waals and electrostatic interactions. The exposed quinic-acid moiety improved the hydrophilicity of CA-modified PDMS substrates. The adhesion and viability of E. coli and HeLa cells were investigated using fluorescence and phase contrast microscopy. Few viable bacterial cells were found on CA-coated PDMS surfaces compared with unmodified PDMS surfaces. Moreover, HeLa cells exhibited enhanced adhesion and increased spreading on the modified PDMS surface. Thus, CA-coated PDMS surfaces reduced the ratio of viable bacterial cells and increased the adhesion of HeLa cells. These results contribute to the purposeful design of anti-bacterial surfaces for medical device use.

Molecular dynamics simulation of polyethylene on single wall carbon nanotube.

Molecular dynamics simulations are carried out on the isothermal crystallization process of single polyethylene chains with different chain lengths on the single wall carbon nanotube. This process is summarized as two steps, i.e., adsorption and orientation, and the bond-orientational order parameter is used to show the details of this process. The results show that the attractive van der Waals interactions control the adsorption and orientation of polyethylene on single wall carbon nanotube, and as the chain length increases, more microstructures appear in the last ordered structure. The stems of the ordered structure align parallel to the single wall carbon nanotube axis.