Legionella effector LnaB is a phosphoryl AMPylase that impairs phosphosignalling.

AMPylation is a post-translational modification in which AMP is added to the amino acid side chains of proteins1,2. Here we show that, with ATP as the ligand and actin as the host activator, the effector protein LnaB of Legionella pneumophila exhibits AMPylase activity towards the phosphoryl group of phosphoribose on PRR42-Ub that is generated by the SidE family of effectors, and deubiquitinases DupA and DupB in an E1- and E2-independent ubiquitination process3-7. The product of LnaB is further hydrolysed by an ADP-ribosylhydrolase, MavL, to Ub, thereby preventing the accumulation of PRR42-Ub and ADPRR42-Ub and protecting canonical ubiquitination in host cells. LnaB represents a large family of AMPylases that adopt a common structural fold, distinct from those of the previously known AMPylases, and LnaB homologues are found in more than 20 species of bacterial pathogens. Moreover, LnaB also exhibits robust phosphoryl AMPylase activity towards phosphorylated residues and produces unique ADPylation modifications in proteins. During infection, LnaB AMPylates the conserved phosphorylated tyrosine residues in the activation loop of the Src family of kinases8,9, which dampens downstream phosphorylation signalling in the host. Structural studies reveal the actin-dependent activation and catalytic mechanisms of the LnaB family of AMPylases. This study identifies, to our knowledge, an unprecedented molecular regulation mechanism in bacterial pathogenesis and protein phosphorylation.

Efficient design of energy microgrid management system: A promoted Remora optimization algorithm-based approach.

Microgrids are a promising solution for decentralized energy generation and distribution, offering reliability, efficiency, and resilience. These small-scale power systems can operate independently or connect to the main grid, providing greater reliability and resilience. However, integrating renewable energy into microgrids presents challenges due to their unpredictable nature and fluctuating load of electricity. Energy management strategies play a crucial role in optimizing the operation of microgrids, aiming to balance electricity supply and demand, maximize renewable energy utilization, and minimize operational costs. Various approaches have been proposed for energy management in microgrids, including optimization algorithms, machine learning techniques, and intelligent control systems. This study proposes an optimized and efficient strategy for microgrids operating in both independent and grid-connected modes, focusing on microgrids that utilize a combination of solar and green energy sources. The proposed approach, based on the Promoted Remora Optimization (PRO) algorithm, aims to meet load power requirements at the lowest possible cost while ensuring constant DC bus voltage and safeguarding batteries against overcharging and depletion. The CRO method effectively optimized the charging process, maintaining a consistent level of charge and achieving a final SoC of 33.37 %-33.60 %. It also demonstrated high system efficiency, with an average of 87.99 %, and a range of 87.80 %-88.03 %. The optimizer efficiency ranged from 83.12 % to 86.52 %, with an average of 86.46 %. The CRO method also achieved reasonable operating costs, with a cost per power of $0.1687/kW to $0.1699/kW and a daily cost of $1,379,595 to $1,479,998. Overall, the CRO method showed promise in optimizing the charging process in terms of efficiency and cost-effectiveness. Comparative analysis with existing literature is conducted to evaluate the effectiveness of the proposed approach, demonstrating its superior results compared to other energy management strategies for microgrids. This study contributes to the field of microgrid energy management by providing a novel approach based on the PRO algorithm and demonstrating its effectiveness through comparative analysis.