DNA sequence and structure: direct and indirect recognition in protein-DNA binding.

MOTIVATION: Direct recognition, or direct readout, of DNA bases by a DNA-binding protein involves amino acids that interact directly with features specific to each base. Experimental evidence also shows that in many cases the protein achieves partial sequence specificity by indirect recognition, i.e., by recognizing structural properties of the DNA. (1) Could threading a DNA sequence onto a crystal structure of bound DNA help explain the indirect recognition component of sequence specificity? (2) Might the resulting pure-structure computational motif manifest itself in familiar sequence-based computational motifs? RESULTS: The starting structure motif was a crystal structure of DNA bound to the integration host factor protein (IHF) of E. coli. IHF is known to exhibit both direct and indirect recognition of its binding sites. (1) Threading DNA sequences onto the crystal structure showed statistically significant partial separation of 60 IHF binding sites from random and intragenic sequences and was positively correlated with binding affinity. (2) The crystal structure was shown to be equivalent to a linear Markov network, and so, to a joint probability distribution over sequences, computable in linear time. It was transformed algorithmically into several common pure-sequence representations, including (a) small sets of short exact strings, (b) weight matrices, (c) consensus regular patterns, (d) multiple sequence alignments, and (e) phylogenetic trees. In all cases the pure-sequence motifs retained statistically significant partial separation of the IHF binding sites from random and intragenic sequences. Most exhibited positive correlation with binding affinity. The multiple alignment showed some conserved columns, and the phylogenetic tree partially mixed low-energy sequences with IHF binding sites but separated high-energy sequences. The conclusion is that deformation energy explains part of indirect recognition, which explains part of IHF sequence-specific binding.

Improved statistical inference from DNA microarray data using analysis of variance and a Bayesian statistical framework. Analysis of global gene expression in Escherichia coli K12.

We describe statistical methods based on the t test that can be conveniently used on high density array data to test for statistically significant differences between treatments. These t tests employ either the observed variance among replicates within treatments or a Bayesian estimate of the variance among replicates within treatments based on a prior estimate obtained from a local estimate of the standard deviation. The Bayesian prior allows statistical inference to be made from microarray data even when experiments are only replicated at nominal levels. We apply these new statistical tests to a data set that examined differential gene expression patterns in IHF(+) and IHF(-) Escherichia coli cells (Arfin, S. M., Long, A. D., Ito, E. T., Tolleri, L., Riehle, M. M., Paegle, E. S., and Hatfield, G. W. (2000) J. Biol. Chem. 275, 29672-29684). These analyses identify a more biologically reasonable set of candidate genes than those identified using statistical tests not incorporating a Bayesian prior. We also show that statistical tests based on analysis of variance and a Bayesian prior identify genes that are up- or down-regulated following an experimental manipulation more reliably than approaches based only on a t test or fold change. All the described tests are implemented in a simple-to-use web interface called Cyber-T that is located on the University of California at Irvine genomics web site.

Global gene expression profiling in Escherichia coli K12. The effects of integration host factor.

We have used nylon membranes spotted in duplicate with full-length polymerase chain reaction-generated products of each of the 4,290 predicted Escherichia coli K12 open reading frames (ORFs) to measure the gene expression profiles in otherwise isogenic integration host factor IHF(+) and IHF(-) strains. Our results demonstrate that random hexamer rather than 3' ORF-specific priming of cDNA probe synthesis is required for accurate measurement of gene expression levels in bacteria. This is explained by the fact that the currently available set of 4,290 unique 3' ORF-specific primers do not hybridize to each ORF with equal efficiency and by the fact that widely differing degradation rates (steady-state levels) are observed for the 25-base pair region of each message complementary to each ORF-specific primer. To evaluate the DNA microarray data reported here, we used a linear analysis of variance (ANOVA) model appropriate for our experimental design. These statistical methods allowed us to identify and appropriately correct for experimental variables that affect the reproducibility and accuracy of DNA microarray measurements and allowed us to determine the statistical significance of gene expression differences between our IHF(+) and IHF(-) strains. Our results demonstrate that small differences in gene expression levels can be accurately measured and that the significance of differential gene expression measurements cannot be assessed simply by the magnitude of the fold difference. Our statistical criteria, supported by excellent agreement between previously determined effects of IHF on gene expression and the results reported here, have allowed us to identify new genes regulated by IHF with a high degree of confidence.