Molecular coevolution of mammalian ribosomal gene terminator sequences and the transcription termination factor TTF-I.

Both the DNA elements and the nuclear factors that direct termination of ribosomal gene transcription exhibit species-specific differences. Even between mammals--e.g., human and mouse--the termination signals are not identical and the respective transcription termination factors (TTFs) which bind to the terminator sequence are not fully interchangeable. To elucidate the molecular basis for this species-specificity, we have cloned TTF-I from human and mouse cells and compared their structural and functional properties. Recombinant TTF-I exhibits species-specific DNA binding and terminates transcription both in cell-free transcription assays and in transfection experiments. Chimeric constructs of mouse TTF-I and human TTF-I reveal that the major determinant for species-specific DNA binding resides within the C terminus of TTF-I. Replacing 31 C-terminal amino acids of mouse TTF-I with the homologous human sequences relaxes the DNA-binding specificity and, as a consequence, allows the chimeric factor to bind the human terminator sequence and to specifically stop rDNA transcription.

Sets of EcoRI fragments containing ribosomal RNA sequences are conserved among different strains of Listeria monocytogenes.

To classify Listeria monocytogenes using taxonomic characters derived from the rRNA operons and their flanking sequences, we studied a sample of 1346 strains within the taxon. DNA from each strain was digested with a restriction endonuclease, EcoRI. The fragments were separated by gel electrophoresis, immobilized on a membrane, and hybridized with a labeled rRNA operon from Escherichia coli. The pattern of bands, positions, and intensities of hybridized fragments were electronically captured. Software was used to normalize the band positions relative to standards, scale the signal intensity, and reduce the background so that each strain was reproducibly represented in a data base as a pattern. With these methods, L. monocytogenes was resolved into 50 pattern types differing in the length of at least one polymorphic fragment. Pattern types representing multiple strains were recorded as the mathematical average of the strain patterns. Pattern types were arranged by size polymorphisms of assigned rRNA regions into subsets, which revealed the branching genetic structure of the species. Subtracting the polymorphic variants of a specific assigned region from the pattern types and averaging the types within each subset resulted in reduced sets of conserved fragments that could be used to recognize strains of the species. Pattern types and reduced sets of conserved fragments were conserved among different strains of L. monocytogenes but were not observed in total among strains of other species.

Types of Listeria monocytogenes predicted by the positions of EcoRI cleavage sites relative to ribosomal RNA sequences.

By using taxonomic characters derived from EcoRI restriction endonuclease digestion of genomic DNA and hybridization with a labeled rRNA operon from Escherichia coli, a polymorphic structure of Listeria monocytogenes, characterized by fragments with different frequencies of occurrence, was observed. This structure was expanded by creating predicted patterns through a recursive process of observation, expectation, prediction, and assessment of completeness. This process was applied, in turn, to normalized strain patterns, fragment bands, and positions of EcoRI recognition sites relative to rRNA regions. Analysis of 1346 strains provided observed patterns, fragment sizes, and their frequencies of occurrence in the patterns. Fragment size statistics led to the creation of unobserved combinations of bands, predicted pattern types. The observed fragment bands revealed positions of EcoRI sites relative to rRNA sequences. Each EcoRI site had a frequency of occurrence, and unobserved fragment sizes were postulated on the basis of knowing the restriction site locations. The result of the recursion process applied to the components of the strain data was an extended classification with observed and predicted members.