Max-Planck-Institut für Entwicklungsbiologie
Abteilung Proteinevolution
Spemann-Str. 35
72076 Tübingen
Tel.: 07071/601-341 bzw. -458
Fax: 07071/601-352
E-mail: andrei.lupas@tuebingen.mpg.de; birte.hernandezspam prevention@tuebingen.mpg.de
Ph.D. Student:
Anja Heubach Tel: 601-340; anja.heubach@tuebingen.mpg.de
Summary
Prokaryotes display a wide assortment of protein fibers at their cell surface, many of which are highly repetitive in sequence and structure. We have focused so far on one family of such surface fibers, the trimeric autotransporter adhesins, which play a crucial role in pathogen-host interactions. We characterized their domain complement computationally and experimentally and established an on-line domain dictionary. We will extend this approach to other fibrous surface proteins across bacteria by undertaking a census of repeat units and domains in these proteins, deriving a classification and making this available in a web database. We will analyze experimentally repeat units in order to identify the sequence determinants responsible for their structural properties.
Zusammenfassung
Prokaryoten besitzen auf ihrer Zelloberfläche eine große Vielfalt an Proteinfibern mit zum Teil hoch repetitiven Sequenz- bzw. Domänencharakter. Wir haben uns bisher mit Trimeren Autotransporter Adhäsinen (TAA), einer bakteriellen, oberflächenlokalisierten Proteinfamilie mit wichtiger Funktion während des Infektionsprozesses, beschäftigt. Basierend auf der strukturellen und bioinformatischen Analyse ihrer Domänenzusammensetzung haben wir ein Online-Domänen-Wörterbuch erstellt. Zukünftig werden wir diese Methodik auf alle bakteriellen, oberflächenlokalisierten Proteinfibern ausdehnen. Wir möchten repetitive Sequenzelemente und Domänen bakterieller Oberflächenproteinen aus vorhandenen Datenbanken extrahieren, diese klassifizieren und die Ergebnisse in einer Web-Datenbank verfügbar machen. Strukturell bisher nicht charakterisierte bzw. ungewöhnliche Variationen bereits bekannter Strukturen dieser repetitiven Abschnitte sollen experimentell und bioinformatisch analysiert werden.
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