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Type VI secretion systems (T6SSs) deliver antibacterial effector proteins between neighboring bacteria. Many effectors harbor N-terminal transmembrane domains (TMDs) implicated in effector translocation across target cell membranes. However, the distribution of these TMD-containing effectors remains unknown. Here, we discover prePAAR, a conserved motif found in over 6000 putative TMD-containing effectors encoded predominantly by 15 genera of Proteobacteria. Based on differing numbers of TMDs, effectors group into two distinct classes that both require a member of the Eag family of T6SS chaperones for export. Co-crystal structures of class I and class II effector TMD-chaperone complexes from Salmonella Typhimurium and Pseudomonas aeruginosa, respectively, reveals that Eag chaperones mimic transmembrane helical packing to stabilize effector TMDs. In addition to participating in the chaperone-TMD interface, we find that prePAAR residues mediate effector-VgrG spike interactions. Taken together, our findings reveal mechanisms of chaperone-mediated stabilization and secretion of two distinct families of T6SS membrane protein effectors.
Pubmed ID: 33320089
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Central repository for collection of functional information on proteins, with accurate and consistent annotation. In addition to capturing core data mandatory for each UniProtKB entry (mainly, the amino acid sequence, protein name or description, taxonomic data and citation information), as much annotation information as possible is added. This includes widely accepted biological ontologies, classifications and cross-references, and experimental and computational data. The UniProt Knowledgebase consists of two sections, UniProtKB/Swiss-Prot and UniProtKB/TrEMBL. UniProtKB/Swiss-Prot (reviewed) is a high quality manually annotated and non-redundant protein sequence database which brings together experimental results, computed features, and scientific conclusions. UniProtKB/TrEMBL (unreviewed) contains protein sequences associated with computationally generated annotation and large-scale functional characterization that await full manual annotation. Users may browse by taxonomy, keyword, gene ontology, enzyme class or pathway.
View all literature mentionsA database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software program for clustering biological sequences with many applications in various fields such as making non-redundant databases, finding duplicates, identifying protein families, filtering sequence errors and improving sequence assembly etc. It is very fast and can handle extremely large databases. CD-HIT helps to significantly reduce the computational and manual efforts in many sequence analysis tasks and aids in understanding the data structure and correct the bias within a dataset. The CD-HIT package has CD-HIT, CD-HIT-2D, CD-HIT-EST, CD-HIT-EST-2D, CD-HIT-454, CD-HIT-PARA, PSI-CD-HIT, CD-HIT-OTU and over a dozen scripts. * CD-HIT (CD-HIT-EST) clusters similar proteins (DNAs) into clusters that meet a user-defined similarity threshold. * CD-HIT-2D (CD-HIT-EST-2D) compares 2 datasets and identifies the sequences in db2 that are similar to db1 above a threshold. * CD-HIT-454 identifies natural and artificial duplicates from pyrosequencing reads. * CD-HIT-OTU cluster rRNA tags into OTUs The usage of other programs and scripts can be found in CD-HIT user''s guide. CD-HIT was originally developed by Dr. Weizhong Li at Dr. Adam Godzik''s Lab at the Burnham Institute (now Sanford-Burnham Medical Research Institute).
View all literature mentionsSoftware package as multiple alignment program for amino acid or nucleotide sequences. Can align up to 500 sequences or maximum file size of 1 MB. First version of MAFFT used algorithm based on progressive alignment, in which sequences were clustered with help of Fast Fourier Transform. Subsequent versions have added other algorithms and modes of operation, including options for faster alignment of large numbers of sequences, higher accuracy alignments, alignment of non-coding RNA sequences, and addition of new sequences to existing alignments.
View all literature mentionsSoftware tool for protein coding gene prediction for prokaryotic genomes.
View all literature mentionsSoftware for macromolecular model building, model completion and validation, and protein modelling using X-ray data. Coot displays maps and models and allows model manipulations such as idealization, rigid-body fitting, ligand search, Ramachandran plots, non-crystallographic symmetry and more. Source code is available.
View all literature mentionsA Python-based software suite for the automated determination of molecular structures using X-ray crystallography and other methods. Phenix includes programs for assessing data quality, experimental phasing, molecular replacement, model building, structure refinement, and validation. It also includes tools for reflection data and creating maps and models. Phenix can also be used for neutron crystallography. Tutorials and examples are available in the documentation tab.
View all literature mentionsSource code that infers approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences. It uses the Jukes-Cantor or generalized time-reversible (GTR) models of nucleotide evolution and the JTT, WAG, or LG models of amino acid evolution.
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