Fibrillar adhesins are long multidomain proteins that form filamentous structures at the cell surface of bacteria. They are an important yet understudied class of proteins composed of adhesive and ...stalk domains that mediate interactions of bacteria with their environment. This study aims to characterize fibrillar adhesins in a wide range of bacterial phyla and to identify new fibrillar adhesin-like proteins to improve our understanding of host-bacteria interactions.
Through careful literature and computational searches, we identified 82 stalk and 27 adhesive domain families in fibrillar adhesins. Based on the presence of these domains in the UniProt Reference Proteomes database, we identified and analysed 3,542 fibrillar adhesin-like proteins across species of the most common bacterial phyla. We further enumerate the adhesive and stalk domain combinations found in nature and demonstrate that fibrillar adhesins have complex and variable domain architectures, which differ across species. By analysing the domain architecture of fibrillar adhesins, we show that in Gram positive bacteria, adhesive domains are mostly positioned at the N-terminus and cell surface anchors at the C-terminus of the protein, while their positions are more variable in Gram negative bacteria. We provide an open repository of fibrillar adhesin-like proteins and domains to enable further studies of this class of bacterial surface proteins.
This study provides a domain-based characterization of fibrillar adhesins and demonstrates that they are widely found in species across the main bacterial phyla. We have discovered numerous novel fibrillar adhesins and improved our understanding of pathogenic adhesion and invasion mechanisms.
Protein domains are the common currency of protein structure and function. Over 10,000 such protein families have now been collected in the Pfam database. Using these data along with animal gene ...phylogenies from TreeFam allowed us to investigate the gain and loss of protein domains. Most gains and losses of domains occur at protein termini. We show that the nature of changes is similar after speciation or duplication events. However, changes in domain architecture happen at a higher frequency after gene duplication. We suggest that the bias towards protein termini is largely because insertion and deletion of domains at most positions in a protein are likely to disrupt the structure of existing domains. We can also use Pfam to trace the evolution of specific families. For example, the immunoglobulin superfamily can be traced over 500 million years during its expansion into one of the largest families in the human genome. It can be shown that this protein family has its origins in basic animals such as the poriferan sponges where it is found in cell-surface-receptor proteins. We can trace how the structure and sequence of this family diverged during vertebrate evolution into constant and variable domains that are found in the antibodies of our immune system as well as in neural and muscle proteins.
Abstract
RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of ...organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world’s largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.
Approximately 5% of Pfam families are enzymatic, but only a small fraction of the sequences within these families (<0.5%) have had the residues responsible for catalysis determined. To increase the ...active site annotations in the Pfam database, we have developed a strict set of rules, chosen to reduce the rate of false positives, which enable the transfer of experimentally determined active site residue data to other sequences within the same Pfam family.
We have created a large database of predicted active site residues. On comparing our active site predictions to those found in UniProtKB, Catalytic Site Atlas, PROSITE and MEROPS we find that we make many novel predictions. On investigating the small subset of predictions made by these databases that are not predicted by us, we found these sequences did not meet our strict criteria for prediction. We assessed the sensitivity and specificity of our methodology and estimate that only 3% of our predicted sequences are false positives.
We have predicted 606110 active site residues, of which 94% are not found in UniProtKB, and have increased the active site annotations in Pfam by more than 200 fold. Although implemented for Pfam, the tool we have developed for transferring the data can be applied to any alignment with associated experimental active site data and is available for download. Our active site predictions are re-calculated at each Pfam release to ensure they are comprehensive and up to date. They provide one of the largest available databases of active site annotation.
Abstract
RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences, collating information on ncRNA sequences of all types from a broad range of organisms. We have recently added a ...new genome mapping pipeline that identifies genomic locations for ncRNA sequences in 296 species. We have also added several new types of functional annotations, such as tRNA secondary structures, Gene Ontology annotations, and miRNA-target interactions. A new quality control mechanism based on Rfam family assignments identifies potential contamination, incomplete sequences, and more. The RNAcentral database has become a vital component of many workflows in the RNA community, serving as both the primary source of sequence data for academic and commercial groups, as well as a source of stable accessions for the annotation of genomic and functional features. These examples are facilitated by an improved RNAcentral web interface, which features an updated genome browser, a new sequence feature viewer, and improved text search functionality. RNAcentral is freely available at https://rnacentral.org.
Transposons are mobile genetic elements that drive evolution and adaptation throughout the tree of life. In bacteria, they often transfer antibiotic resistance genes and contribute to the emergence ...of multidrug‐resistant pathogens.
In this talk, I will present our recent discoveries on a group of transposons that efficiently propagate antibiotic resistance genes across diverse microbial communities. Using a dedicated computational pipeline, we mapped the most wide‐spread transposons in bacterial genomes and characterized their diversity, genetic cargo, and transfer dynamics. Selected elements were experimentally reconstituted to describe their molecular mechanisms and biochemical pathways. We determined numerous high‐resolution crystal and cryo‐EM structures of the protein‐DNA assemblies involved in transposon movement. The structures capture various stages of transposition and reveal an intricate interplay between the core transposition machinery and host‐encoded proteins. Protein interactions shape transposon and genomic DNA in unique ways to cut, exchange and re‐join strands in a tightly regulated manner. Importantly, our data also explain how specific DNA distortion and cleavage mechanisms enable the transposons to move between diverse genomic sites, expanding gene transfer across many species.
These results shed new light onto the molecular strategies of antibiotic resistance carrying transposons and show how they evolved to effectively spread key genetic traits. Our insights also open new opportunities to develop strategies for blocking transposition and thereby help control resistance spreading.
Although eukaryotic protein kinases (ePKs) contribute to many cellular processes, only three Plasmodium falciparum ePKs have thus far been identified as essential for parasite asexual blood stage ...development. To identify pathways essential for parasite transmission between their mammalian host and mosquito vector, we undertook a systematic functional analysis of ePKs in the genetically tractable rodent parasite Plasmodium berghei. Modeling domain signatures of conventional ePKs identified 66 putative Plasmodium ePKs. Kinomes are highly conserved between Plasmodium species. Using reverse genetics, we show that 23 ePKs are redundant for asexual erythrocytic parasite development in mice. Phenotyping mutants at four life cycle stages in Anopheles stephensi mosquitoes revealed functional clusters of kinases required for sexual development and sporogony. Roles for a putative SR protein kinase (SRPK) in microgamete formation, a conserved regulator of clathrin uncoating (GAK) in ookinete formation, and a likely regulator of energy metabolism (SNF1/KIN) in sporozoite development were identified.
Proteins that are known only at a sequence level outnumber those with an experimental characterization by orders of magnitude. Classifying protein regions (domains) into homologous families can ...generate testable functional hypotheses for yet unannotated sequences. Existing domain family resources typically use at least some degree of manual curation: they grow slowly over time and leave a large fraction of the protein sequence space unclassified. We here describe automatic clustering by Density Peak Clustering of UniRef50 v. 2017_07, a protein sequence database including approximately 23M sequences. We performed a radical re-implementation of a pipeline we previously developed in order to allow handling millions of sequences and data volumes of the order of 3 TeraBytes. The modified pipeline, which we call DPCfam, finds ∼ 45,000 protein clusters in UniRef50. Our automatic classification is in close correspondence to the ones of the Pfam and ECOD resources: in particular, about 81% of medium-large Pfam families and 72% of ECOD families can be mapped to clusters generated by DPCfam. In addition, our protocol finds more than 14,000 clusters constituted of protein regions with no Pfam annotation, which are therefore candidates for representing novel protein families. These results are made available to the scientific community through a dedicated repository.
PDF
