Optogenetic Strategies for Optimizing the Performance of Phospholipids Biosensors.

High-performance biosensors play a crucial role in elucidating the intricate spatiotemporal regulatory roles and dynamics of membrane phospholipids. However, enhancing the sensitivity and imaging performance remains a significant challenge. Here, optogenetic-based strategies are presented to optimize phospholipid biosensors. These strategies involves presequestering unbound biosensors in the cell nucleus and regulating their cytosolic levels with blue light to minimize background signal interference in phospholipid detection, particularly under conditions of high expression levels of biosensor. Furthermore, optically controlled phase separation and the SunTag system are employed to generate punctate probes for substrate detection, thereby amplifying biosensor signals and enhancing visualization of the detection process. These improved phospholipid biosensors hold great potential for enhancing the understanding of the spatiotemporal dynamics and regulatory roles of membrane lipids in live cells and the methodological insights in this study might be valuable for developing other high-performance biosensors.

Deep learning-enabled fast DNA-PAINT imaging in cells.

DNA-based point accumulation in nanoscale topography (DNA-PAINT) is a well-established technique for single-molecule localization microscopy (SMLM), enabling resolution of up to a few nanometers. Traditionally, DNA-PAINT involves the utilization of tens of thousands of single-molecule fluorescent images to generate a single super-resolution image. This process can be time-consuming, which makes it unfeasible for many researchers. Here, we propose a simplified DNA-PAINT labeling method and a deep learning-enabled fast DNA-PAINT imaging strategy for subcellular structures, such as microtubules. By employing our method, super-resolution reconstruction can be achieved with only one-tenth of the raw data previously needed, along with the option of acquiring the widefield image. As a result, DNA-PAINT imaging is significantly accelerated, making it more accessible to a wider range of biological researchers.

Characterization of PM2.5-bound polycyclic aromatic hydrocarbons and their derivatives (nitro-and oxy-PAHs) emissions from two ship engines under different operating conditions.

Emissions from ship exhaust have been recognized as an important source of air pollution in coastal areas. To investigate the impacts of engine type, fuel and operating conditions on polycyclic aromatic compounds (PACs) emissions, particle matter (PM2.5) samples emitted from an inland-river bulk freighter (BF) using marine diesel oil (MDO) and an ocean-going passenger vessel (PV) using heavy fuel oil (HFO) were collected under five operation conditions (preheating, leaving, cruising, entering and berthing). The concentrations of 17 polycyclic aromatic hydrocarbons (PAHs), 12 nitro-PAHs (NPAHs) and 4 oxygenated-PAHs species were determined. The concentrations of ΣPAHs, ΣNPAHs and ΣOPAHs measured on the BF and PV exhausts ranged from 1.95 to 417 µg/m3, 86.5 to 6.89 × 103 ng/m3 and 2.00-102 µg/m3, respectively. Both ships showed a high proportion of four-ring PAHs, while the BF had more three-ring PAHs (34.00-70.38%) and the PV had more five-ring PAHs (30.02-35.95%). The calculation of indicatory PACs are able to increase the precision of source appointment. The emission factors (EFs) of PACs under maneuvering (including preheating, leaving, entering and berthing) was much higher than those under cruising, which might be due to the engine load, fuel consumption, and secondary reactions. Compared with HFO, combustion with MDO decreased the power-based ΣPAH EFs by 82-99%, power-based ΣNPAH EFs by 86-98%, and power-based ΣOPAHs EFs by 50-82%. These data highlight the importance of quantifying and monitoring ship emissions in close proximity to port area, and are useful for enhancing the relevant databases and improving the accuracy of ship emission inventories.