The Type VI secretion system (T6SS) is a macromolecular system distributed in Gram-negative bacteria, responsible for the secretion of effector proteins into target cells. The T6SS has a broad versatility as it can target both eukaryotic and prokaryotic cells. It is therefore involved in host pathogenesis or killing neighboring bacterial cells to colonize a new niche. At the architecture level, the T6SS core apparatus is composed of 13 proteins, which assemble in two subcomplexes. One of these subcomplexes, composed of subunits that share structural similarities with bacteriophage tail and baseplate components, is anchored to the cell envelope by the membrane subcomplex. This latter is constituted of at least three proteins, TssL, TssM, and TssJ. The crystal structure of the TssJ outer membrane lipoprotein and its interaction with the inner membrane TssM protein have been recently reported. TssL and TssM share sequence homology and characteristics with two components of the Type IVb secretion system (T4bSS), IcmH/DotU and IcmF, respectively. In this study, we report the crystal structure of the cytoplasmic domain of the TssL inner membrane protein from the enteroaggregative Escherichia coli Sci-1 T6SS. It folds as a hook-like structure composed of two three-helix bundles. Two TssL molecules associate to form a functional complex. Although the TssL trans-membrane segment is the main determinant of self-interaction, contacts between the cytoplasmic domains are required for TssL function. Based on sequence homology and secondary structure prediction, we propose that the TssL structure is the prototype for the members of the TssL and IcmH/DotU families.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3340138 | PMC |
http://dx.doi.org/10.1074/jbc.M111.338731 | DOI Listing |
Zhonghua Yu Fang Yi Xue Za Zhi
May 2024
State Key Laboratory of Pathogen and Biosecurity, State Key Laboratory of Pathogen and Biosecurity, Beijing 100071, China.
Int J Hyg Environ Health
May 2024
Institute for Water and Wastewater Technology, Durban University of Technology, Durban, 4001, Kwa-Zulu Natal, South Africa. Electronic address:
Free living amoeba (FLA) are among the organisms commonly found in wastewater and are well-established hosts for diverse microbial communities. Despite its clinical significance, there is little knowledge on the FLA microbiome and resistome, with previous studies relying mostly on conventional approaches. In this study we comprehensively analyzed the microbiome, antibiotic resistome and virulence factors (VFs) within FLA isolated from final treated effluents of two wastewater treatment plants (WWTPs) using shotgun metagenomics.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2024
Department of Mechanical Engineering, Keio University, Yokohama 223-8522, Japan.
Classification of molecular structures is a crucial step in molecular dynamics (MD) simulations to detect various structures and phases within systems. Molecular structures, which are commonly identified using order parameters, were recently identified using machine learning (ML), that is, the ML models acquire structural features using labeled crystals or phases via supervised learning. However, these approaches may not identify unlabeled or unknown structures, such as the imperfect crystal structures observed in nonequilibrium systems and interfaces.
View Article and Find Full Text PDFMicromachines (Basel)
June 2023
Electrical and Computer Engineering, Inha University, 100 Inharo, Nam-gu, Incheon 22212, Republic of Korea.
This paper investigates the performance of deep convolutional spiking neural networks (DCSNNs) trained using spike-based backpropagation techniques. Specifically, the study examined temporal spike sequence learning via backpropagation (TSSL-BP) and surrogate gradient descent via backpropagation (SGD-BP) as effective techniques for training DCSNNs on the field programmable gate array (FPGA) platform for object classification tasks. The primary objective of this experimental study was twofold: (i) to determine the most effective backpropagation technique, TSSL-BP or SGD-BP, for deeper spiking neural networks (SNNs) with convolution filters across various datasets; and (ii) to assess the feasibility of deploying DCSNNs trained using backpropagation techniques on low-power FPGA for inference, considering potential configuration adjustments and power requirements.
View Article and Find Full Text PDFData Brief
June 2023
University of Science, Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Viet Nam.
is one of the major plant pathogens causing bacterial wilt disease in a variety of plant species. In Vietnam, according to our knowledge, we first discovered which is one of four phylotypes of as a causal agent wilting in cucumber (). Due to the latent infection of and its heterogenous species complex, controlling the disease becomes difficult.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!