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Abstract:
Trimeric Autotransporter Adhesins (TAAs) are a widespread family of filamentous outer membrane proteins in Gram-negative bacteria. As mediators of adhesion, they play a crucial role in the colonisation of biotic and abiotic surfaces, offering many attractive targets for medical and biotechnological applications.
Although highly variable, all TAAs arose from the mosaic-like rearrangement of a limited set of domains, whose structure is highly conserved even at low sequence identity. We therefore established a domain dictionary, consisting of bioinformatic sequence descriptors and representative crystal structures, in order to annotate newly sequenced TAAs and reconstruct the full fibres. In 2008, we implemented this approach in the web-based tool daTAA (domain annotation of TAAs).
Here we present daTAA2, a complete reimplementation of the daTAA functionality as a network of hidden Markov states. Its algorithm, which considers both sequence similarity and probabilistic rules of domain arrangement, allows the annotation of a TAA sequence as an array of consecutive states rather than as a collection of individual domains, thereby overcoming the minimum length limitation for recognisable features and yielding a significantly more detailed annotation.
