Metagenomic analysis for the microbial consortium of anaerobic CO oxidizers

Metagenomics analysis has been applied to identify the dominant anaerobic microbial consortium of the carbon monoxide (CO) oxidizers in anaerobic sludge. Reads from the hypervariable V6 region in the bacterial 16s rDNA were aligned and finally clustered into operational taxonomic units (OTUs). The OTUs from different stages in anaerobic CO condition were classified. Alphaproteobacteria, clostridia, betaproteobacteria and actinobacteria were the most abundant groups, while alphaproteobacteria, betaproteobacteria and actinobacteria were variable groups. CO consumption and production efficiency of the microbial consortium were studied. Semi-continuous trials showed that these anaerobic CO oxidizers formed a stable microbial community, and the CO conversion rate was at over 84%, with the highest CO consumption activity of 28.9 mmol CO/g VSS●day and methane production activity at 7.6 mmol CH₄/g VSS●day during six cycles.     

Noninvasive Evaluation of Metabolic Tumor Volume in Lewis Lung Carcinoma Tumor-Bearing C57BL/6 Mice with Micro-PET and the Radiotracers 18F-Alfatide and 18F-FDG: A Comparative Analysis

Purpose

To explore the value of a new simple lyophilized kit for labeling PRGD₂ peptide (¹⁸F-ALF-NOTA-PRGD₂, denoted as ¹⁸F-alfatide) in the determination of metabolic tumor volume (MTV) with micro-PET in lewis lung carcinoma (LLC) tumor-bearing C57BL/6 mice verified by pathologic examination and compared with those using ¹⁸F-fluorodeoxyglucose (FDG) PET.

Methods

All LLC tumor-bearing C57BL/6 mice underwent two attenuation-corrected whole-body micro-PET scans with the radiotracers ¹⁸F-alfatide and ¹⁸F-FDG within two days. ¹⁸F-alfatide metabolic tumor volume (V_RGD) and ¹⁸F-FDG metabolic tumor volume (V_FDG) were manually delineated slice by slice on PET images. Pathologic tumor volume (V_Path) was measured in vitro after the xenografts were removed.

Results

A total of 37 mice with NSCLC xenografts were enrolled and 33 of them underwent ¹⁸F-alfatide PET, and 35 of them underwent ¹⁸F-FDG PET and all underwent pathological examination. The mean ± standard deviation of V_Path, V_RGD, and V_FDG were 0.59±0.32 cm³ (range,0.13~1.64 cm³), 0.61±0.37 cm³ (range,0.15~1.86 cm³), and 1.24±0.53 cm³ (range,0.17~2.20 cm³), respectively. V_Path vs. V_RGD, V_Path vs. V_FDG, and V_RGD vs. V_FDG comparisons were t = -0.145, P = 0.885, t = -6.239, P<0.001, and t = -5.661, P<0.001, respectively. No significant difference was found between V_Path and V_RGD. V_FDG was much larger than V_RGD and V_Path. V_RGD seemed more approximate to the pathologic gross tumor volume. Furthermore, V_Path was more strongly correlated with V_RGD (R = 0.964,P<0.001) than with V_FDG (R = 0.584,P<0.001).

Conclusions

¹⁸F-alfatide PET provided a better estimation of gross tumor volume than ¹⁸F-FDG PET in LLC tumor-bearing C57BL/6 mice.     

A cold-adapted and glucose-stimulated type II α-glucosidase from a deep-sea bacterium <Emphasis Type="Italic">Pseudoalteromonas</Emphasis> sp. K8

Objectives

To express and characterize a putative α-glucosidase, Pagl, from Pseudoalteromonas sp. K8 obtained via genome mining approach.

Results

Pagl was expressed and purified to homogeneity, with a molecular mass of 60 kDa. It was optimally active at pH 8.5 and 30 °C, and showed cold-adapted activity. Pagl exhibited specific activity towards substrates with α-1,4-linkage, with the highest specific activity of 19.4 U/mg for maltose, followed by pNPαG and maltodextrins, suggesting that Pagl belongs to the type II α-glucosidase. Interestingly, the activity of Pagl is significantly enhanced (2.7 times) in the presence of 200 mM glucose.

Conclusion

The unique catalytic properties of Pagl make it an attractive candidate for several industrial applications.

     

Magnetic-Based Fano Resonance by a Trimer with Y-shaped Gap

We introduce a Y-shaped gap into a silver disk to break the structure symmetry which can be looked as a loop-linked structure. Magnetic resonances are excited by incident light when incident electric field is parallel to the trimer plane. Fano resonance is generated by the coupling between bright electric mode and dark magnetic mode. These resonances can be adjusted by tuning the gap size, the radius of trimer, and the position of Y-shaped gap. The extinction cross section of the structure is calculated with the finite element method (FEM). The maximum figure of merit (FOM) is 37.8. Both the magnetic and electric field are greatly enhanced at the Fano dip and the magnetic resonance peak.     

Mutation mechanism of chlorophyll-less barley mutant <Emphasis Type="Italic">NYB</Emphasis>

NYB is chlorophyll-less barley mutant, which is controlled by a recessive nuclear gene. The mutation mechanism is revealed. The activities of enzymes transforming 5-aminolevulinic acid into protochlorophyllide were the same in both NYB and the wild type (WT), but the activity of the protochlorophyllide oxidoreductase (POR) in WT was much higher than that of NYB. Most of the photosystem 2 apoproteins were present in both WT and NYB, suggesting that the capability of protein synthesis was probably fully preserved in the mutant. Thus chlorophyll (Chl) biosynthesis in NYB was hampered at conversion form protochlorophyllide (Pchlide) into chlorophyllide. The open reading frame of porB gene in NYB was inserted with a 95 bp fragment, which included a stop codon. The NYB mutant is a very useful material for studies of Chl biosynthesis, chloroplast signalling, and structure of light-harvesting POR-Pchlide complex (LHPP).     

Characterization of the spontaneous murine B cell leukemia (BCL1). III. Evidence for monoclonality by using an anti-idiotype antibody.

We have raised an anti-idiotypic antibody against the cell surface IgM of the murine BCL1 tumor cells. This antiserum reacts exclusively with the IgM expressed on the tumor cells and detects a unique population of cells in the spleen and blood of the tumor-bearing mice. When these cells are stimulated in vitro with LPS, they secrete an IgM bearing the same idiotype as the cell surface Ig. These results are discussed in terms of a model for the immunotherapy of a chronic lymphocytic leukemia-like syndrome in mice.     

microRNA-95 knockdown inhibits epithelial–mesenchymal transition and cancer stem cell phenotype in gastric cancer cells through MAPK pathway by upregulating DUSP5

This study investigated the role of microRNA-95 (miR-95) in gastric cancer (GC) and to elucidate the underlying mechanism. Initially, bioinformatic prediction was used to predict the differentially expressed genes and related miRNAs in GC. miR-95 and DUSP5 expression was altered in GC cell line (MGC803) to evaluate their respective effects on the epithelial–mesenchymal transition (EMT) process, cellular processes (cell proliferation, migration, invasion, cell cycle, and apoptosis), cancer stem cell (CSC) phenotype, as well as tumor growth ability. It was further predicted in bioinformatic prediction and verified in GC tissue and cell line experiments that miR-95 was highly expressed in GC. miR-95 negatively regulated DUSP5, which resulted in the MAPK pathway activation. Inhibited miR-95 or overexpressed DUSP5 was observed to inhibit the levels of CSC markers (CD133, CD44, ALDH1, and Lgr5), highlighting the inhibitory role in the CSC phenotype. More important, evidence was obtained demonstrating that miR-95 knockdown or DUSP5 upregulation exerted an inhibitory effect on the EMT process, cellular processes, and tumor growth. Together these results, miR-95 knockdown inhibited GC development via DUSP5-dependent MAPK pathway.     

ProDCoNN: Protein design using a convolutional neural network

Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this problem as predicting the residue type given the 3D structural environment around the C _α atom of a residue, which is repeated for each residue of a protein. We designed a nine-layer 3D deep convolutional neural network (CNN) that takes as input a gridded box with the atomic coordinates and types around a residue. Several CNN layers were designed to capture structure information at different scales, such as bond lengths, bond angles, torsion angles, and secondary structures. Trained on a very large number of protein structures, the method, called ProDCoNN (protein design with CNN), achieved state-of-the-art performance when tested on large numbers of test proteins and benchmark datasets.