Small-Molecule Triggered Cascade Enzymatic Catalysis in Hour-Glass Shaped Nanochannel Reactor for Glucose Monitoring

Construction of an electrical signal-sensitive nanoreactor in response to small molecule remains a challenge in the developing fields of biomimetic device. Solid nanochannels are considered as promising candidates for constructing smart systems, which is highly sensitive to biochemical stimulus. Here, we report an hourglass shaped nanochannel reactor based on cascade enzymatic catalysis and cation-selective nanochannel system. The employed glucose-specific dual-enzyme combination, glucose oxidase (GOx) and horseradish peroxidase (HRP), ensures the glucose catalytic efficiency and selectivity. Presence of glucose immediately induced the bienzymatic sequential reaction. The yielding gluconic acid decreased the microenvironmental pH in the channel gradually. Different concentration of glucose produced different amount of acid and thus altered the negative charge density inside the nanochannel to different extent. Modification convenience and mechanical robustness also ensure the stability of the test platform. Owing to its unique cation-selective property and high sensitivity toward microenvironmental alteration, this nanodevice shows robust glucose-responsive properties through monitoring ionic current signatures

Sensitive and Rapid Screening of T4 Polynucleotide Kinase Activity and Inhibition Based on Coupled Exonuclease Reaction and Graphene Oxide Platform

Phosphorylation of DNA with 5′-hydroxyl termini plays a critical role in a majority of normal cellular events, including DNA recombination, DNA replication, and repair of DNA during strand interruption. Determination of nucleotide kinase activity and inhibition is under intense development due to its importance in regulating nucleic acid metabolism. Here, by using T4 polynucleotide kinase (PNK) as a model, which plays an essential role in cellular nucleic acid metabolism, particularly in the cellular responses to DNA damage, we describe a strategy for simply and accurately determining nucleotide kinase activity and inhibition by means of a coupled λ exonuclease cleavage reaction and graphene oxide (GO) based platform. The dye attached dsDNA preserves most of the fluorescence when mixed with GO. While dsDNA is phosphorylated by PNK and then immediately cleaved by λ exonuclease, fluorescence is greatly quenched. Because of the super quenching ability and the high specific surface area of GO, the as-proposed platform presents an excellent performance with wide linear range and low detection limit in the cell extracts environment. Additionally, inhibition effects of adenosine diphosphate, ammonium sulfate, and sodium hydrogen phosphate have also been investigated. The method not only provides a universal platform for monitoring activity and inhibition of nucleotide kinase but also shows great potential in biological process researches, drug discovery, and clinic diagnostics

Sensitive Nanochannel Biosensor for T4 Polynucleotide Kinase Activity and Inhibition Detection

5′-Polynucleotide kinase is a crucial class of enzyme that catalyzes the phosphorylation of nucleic acids with 5′-hydroxyl termini. This process regulates many important cellular events, especially DNA repair during strand damage and interruption. The activity and inhibition of nucleotide kinase have proven to be an evident effect on cellular nucleic acid regulation and metabolism. Here, we describe a novel nanochannel biosensor for monitoring the activity and inhibition of T4 polynucleotide kinase (PNK), a famous member of the 5′-kinase family playing a major role in the cellular responses to DNA damage. On the basis of the functionalized nanochannel system and coupled λ exonuclease cleavage reaction, the nanochannel-sensing platform exhibits high sensitivity and convenience toward kinase analysis. Biotin-labeled dsDNA effectively blocks the streptavidin-modified nanochannel through forming a closely packed arrangement of DNA structure inside the channel. When dsDNA is phosphorylated by PNK and then immediately cleaved by λ exonuclease, the pore-blocking effect almost disappears. This PNK-induced microstructural distinctness can be directly and accurately monitored by the nanochannel system, which benefits from its high sensitivity to the change of the effective pore size. Furthermore, modification convenience and mechanical robustness also ensure the stability of the test platform. This as-proposed strategy exhibits excellent analytical performance in both PNK activity analysis and inhibition evaluation. The simple and sensitive nanochannel biosensor shows great potential in developing on-chip, high-throughput assays for fundamental biochemical process research, molecular-target therapies, and clinic diagnostics

Abnormal changes in between-group nodal centrality in the MCI and AD groups.

<p>Each of the eight regions belongs to the hub regions in at least one of the three cortical networks and showed a significant difference (p<0.05). The blue spheres indicate significant decreases in between-group nodal centrality. The red spheres indicate significant increases in between-group nodal centrality. <b>A</b> - Abnormal changes shared by the MCI and AD groups. <b>B</b> - Abnormal changes only in the AD group. Note that no abnormal changes occurred only in the MCI group. For the abbreviations of the regions, see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001006#pcbi-1001006-t002" target="_blank">Table 2</a>.</p

Mean clustering coefficients and mean absolute path lengths of the cortical networks in the three subject groups.

<p>Mean clustering coefficient (C_p) and mean absolute path length (L_p) over a wide range of sparsity values () and the error bars were obtained using bootstrap method. <b>A</b> - The red stars represent the mean clustering coefficient in the AD group. The blue circles represent the mean clustering coefficient in the MCI group. The black squares represent the mean clustering coefficient in the NC group. <b>B</b> - The red stars represent the mean absolute path length in the AD group. The blue circles represent the mean absolute path length in the MCI group. The black squares represent the mean absolute path length in the NC group. The mean clustering coefficient was the greatest for the AD group and the absolute path length was shortest for the NC group. The measurements of the MCI group were intermediate between the NCs and ADs.</p

The interregional correlations matrix in the AD, MCI and NC groups.

<p>The color bar indicates the value of the correlation coefficient r (ranging from −0.8 to 1). <b>A</b>. The correlations matrices obtained by calculating the correlations between pairs of AAL areas within each group (left - the AD group, middle - the MCI group and right - the NC group). <b>B</b>. The binarized matrices obtained by thresholding the above correlations matrices of <b>A</b> with a sparsity threshold (15%). The sparsity threshold sets the same number of nodes and edges in each of the three cortical networks.</p

Hub regions in cortical networks of the three populations listed in descending order of their normalized betweenness in the NCs.

<p>Hub regions in cortical networks of the three populations listed in descending order of their normalized betweenness in the NCs.</p

Abnormal interregional correlations in the MCI and AD subjects.

<p>The red and blue lines indicate significant between-group differences in interregional correlations between pairs of regions (p<0.01, FDR-corrected); the yellow dots represent those AAL regions with significantly abnormal correlations. The red and blue lines indicate the significantly increased and decreased interregional correlations between the corresponding regions, respectively. <b>A</b> - Significant changes in interregional correlations between the NC and AD groups. <b>B</b> - Significant changes in interregional correlations between the NC and MCI groups. <b>C</b> - Significant changes in interregional correlations between the MCI and AD groups. For the abbreviations of the regions, see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001006#pcbi-1001006-t002" target="_blank">Table 2</a>.</p

Between-group differences in the clustering coefficient (C_p) and the absolute path length (L_p) over a range of sparsity values.

<p>The left shows the between-group differences in clustering coefficients (ΔCp) and the right shows the between-group differences in absolute path lengths (ΔLp) over a wide range of sparsity values (). The black open circles represent the mean values and the black lines represent the 95% confidence intervals of the between-group differences obtained from 1000 permutation tests at each sparsity value. <b>A</b> - Differences between the NC and AD groups (ΔCp = Cp_NC−Cp_AD, ΔLp = Lp_NC−Lp_AD). <b>B</b> - Differences between the NC and MCI groups (ΔCp = Cp_NC−Cp_MCI, ΔLp = Lp_NC−Lp_MCI). <b>C</b> - Differences between the MCI and AD groups (ΔCp = Cp_MCI−Cp_AD, ΔLp = Lp_MCI−Lp_AD). The arrows indicate the significant (p<0.05) between-group differences in the clustering coefficients and absolute path lengths.</p

Image_1_Effect of wind on summer chlorophyll-a variability in the Yellow Sea.pdf

Winds potentially affect primary production in shelf seas during the stratified season by enhancing upwelling and mixing. However, the exact extent and modalities of this effect in the Yellow Sea remain unclear. Here, based on the satellite and in situ observation data, statistical method, and wind-driven upwelling theory, we examined the wind effect on the chlorophyll-a (Chl-a) variability in the summer of 2002-2020 and the effect mechanism. The satellite data revealed a significantly positive correlation between anomalies of the monthly mean of the summer sea surface Chl-a and wind speed at the continental slope region (water depth of 20-60 m) in the southwestern Yellow Sea where strong wind-driven upwelling has been indicated by previous studies. The wind-driven upwelling along the continental slope was further verified using two summer in-situ observations. After a fortnight of southeasterly wind, the upwelling patterns of high salinity and rich nutrients from the Yellow Sea cold water mass were observed, and consequently, high Chl-a concentrations occurred in the upper layer of the slope region. The wind-driven upwelling occurred in the region at water depth of ~20-60 m, which is consistent with the result of the wind-driven coastal upwelling theory (0.5D 2/d, 81 ± 45 μmol/m2/d and 1460 ± 899 μmol/m2/d, respectively, accounting for 30%-40% of total nutrient supply, and were several times larger than that contributed by the turbulent mixing, which can explain why the strong wind-Chl-a correlation only occurred at the upwelling region rather than the entire sea. In addition, in this region, the interannual variability of the summer mean Chl-a was negatively correlated to both the Pacific Decadal Oscillation (PDO) and El Niño-Southern Oscillation (ENSO) indexes, due to the opposite phase of the summer wind anomaly and the PDO/ENSO. This study revealed the wind effect on the shelf phytoplankton is regional and highlighted that wind could be a pivotal factor driving the climate variability of shelf primary production in the stratified season.</p