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Abstract Background Different iron transport systems evolved in Gram-negative bacteria during evolution. Most of the transport systems depend on outer membrane localized TonB-dependent transporters (TBDTs), a periplasma-facing TonB protein and a plasma membrane localized machinery (ExbBD). So far, iron chelators (siderophores), oligosaccharides and polypeptides have been identified as substrates of TBDTs. For iron transport, three uptake systems are defined: the lactoferrin/transferrin binding proteins, the porphyrin-dependent transporters and the siderophore-dependent transporters. However, for cyanobacteria almost nothing is known about possible TonB-dependent uptake systems for iron or other substrates. Results We have screened all publicly available eubacterial genomes for sequences representing (putative) TBDTs. Based on sequence similarity, we identified 195 clusters, where elements of one cluster may possibly recognize similar substrates. For Anabaena sp. PCC 7120 we identified 22 genes as putative TBDTs covering almost all known TBDT subclasses. This is a high number of TBDTs compared to other cyanobacteria. The expression of the 22 putative TBDTs individually depends on the presence of iron, copper or nitrogen. Conclusion We exemplified on TBDTs the power of CLANS-based classification, which demonstrates its importance for future application in systems biology. In addition, the tentative substrate assignment based on characterized proteins will stimulate the research of TBDTs in different species. For cyanobacteria, the atypical dependence of TBDT gene expression on different nutrition points to a yet unknown regulatory mechanism. In addition, we were able to clarify a hypothesis of the absence of TonB in cyanobacteria by the identification of according sequences.

Abstract Background The identification of β-barrel membrane proteins out of a genomic/proteomic background is one of the rapidly developing fields in bioinformatics. Our main goal is the prediction of such proteins in genome/proteome wide analyses. Results For the prediction of β-barrel membrane proteins within prokaryotic proteomes a set of parameters was developed. We have focused on a procedure with a low false positive rate beside a procedure with lowest false prediction rate to obtain a high certainty for the predicted sequences. We demonstrate that the discrimination between β-barrel membrane proteins and other proteins is improved by analyzing a length limited region. The developed set of parameters is applied to the proteome of E. coli and the results are compared to four other described procedures. Conclusion Analyzing the β-barrel membrane proteins revealed the presence of a defined membrane inserted β-barrel region. This information can now be used to refine other prediction programs as well. So far, all tested programs fail to predict outer membrane proteins in the proteome of the prokaryote E. coli with high reliability. However, the reliability of the prediction is improved significantly by a combinatory approach of several programs. The consequences and usability of the developed scores are discussed.