The preprotachykinin A promoter interacts with a sequence specific single stranded DNA binding protein.

An element within the Preprotachykinin A (PPT) promoter is highly homologous to an element from the rat type II Na channel promoter. This Na Channel element has been previously proposed to be common to a number of neuronal genes. We demonstrate that the PPT element binds a sequence specific DNA binding protein. The protein binds to only one strand of the PPT element and has little or no specificity for the double stranded DNA species. Gel retardation analysis indicates that the protein is found in both rat neuronal tissue and adult dorsal root ganglia neurons in culture but not in established tissue culture cell lines. Using the PPT element linked to magnetic beads we have been able to demonstrate the enrichment of a protein with a molecular weight of 40k with that of the binding activity. A mechanism for protein binding to the DNA is proposed based on the fact that the region binding the protein is the loop of a larger stem-loop structure in the DNA.     

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.     

Mass accuracy and sequence requirements for protein database searching.

To elucidate the role of high mass accuracy in mass spectrometric peptide mapping and database searching, selected proteins were subjected to tryptic digestion and the resulting mixtures were analyzed by electrospray ionization on a 7 Tesla Fourier transform mass spectrometer with a mass accuracy of 1 ppm. Two extreme cases were examined in detail: equine apomyoglobin, which digested easily and gave very few spurious masses, and bovine alpha-lactalbumin, which under the conditions used, gave many spurious masses. The effectiveness of accurate mass measurements in minimizing false protein matches was examined by varying the mass error allowed in the search over a wide range (2-500 ppm). For the "clean" data obtained from apomyoglobin, very few masses were needed to return valid protein matches, and the mass error allowed in the search had little effect up to 500 ppm. However, in the case of alpha-lactalbumin more mass values were needed, and low mass errors increased the search specificity. Mass errors below 30 ppm were particularly useful in eliminating false protein matches when few mass values were used in the search. Collision-induced dissociation of an unassigned peak in the alpha-lactalbumin digest provided sufficient data to unambiguously identify the peak as a fragment from alpha-lactalbumin and eliminate a large number of spurious proteins found in the peptide mass search. The results show that even with a relatively high mass error (0.8 Da for mass differences between singly charged product ions), collision-induced dissociation can help identify proteins in cases where unfavorable digest conditions or modifications render digest peaks unidentifiable by a simple mass mapping search.     

Strong sequence patterns in eukaryotic promoter regions: Potential implications for DNA structure

• 1.1. Analysis of eukaryotic sequences reveals recurring trends in upstream regions. Oligomers composed of (G/C)_n and (A/T)_m blocks are preferentially flanked by (G/C)₂ doublets on their 3' rather than on their 5′ ends, that is (G/C)_nä(A/T)_m(G/C)₂ > (G/C)_n+2(A/T)_m.
• 2.2. These trends are stronger for larger n and smaller m. Additional trends are outlined below.
• 3.3. The trends are correlated with DNA structural parameters, in particular with twist and roll angles.
• 4.4. Generally, the trends hold if the base pair step joining the 5′ (G/C)₂ doublet to the (G/C)_n (A/T)_m oligomer is not undertwisted and is not strongly rolled into the major groove.
• 5.5. Other DNA parameters crucial for DNA-protein interactions are discussed as well.

     

Comparison of methods for searching protein sequence databases.

We have compared commonly used sequence comparison algorithms, scoring matrices, and gap penalties using a method that identifies statistically significant differences in performance. Search sensitivity with either the Smith-Waterman algorithm or FASTA is significantly improved by using modern scoring matrices, such as BLOSUM45-55, and optimized gap penalties instead of the conventional PAM250 matrix. More dramatic improvement can be obtained by scaling similarity scores by the logarithm of the length of the library sequence (In()-scaling). With the best modern scoring matrix (BLOSUM55 or JO93) and optimal gap penalties (-12 for the first residue in the gap and -2 for additional residues), Smith-Waterman and FASTA performed significantly better than BLASTP. With In()-scaling and optimal scoring matrices (BLOSUM45 or Gonnet92) and gap penalties (-12, -1), the rigorous Smith-Waterman algorithm performs better than either BLASTP and FASTA, although with the Gonnet92 matrix the difference with FASTA was not significant. Ln()-scaling performed better than normalization based on other simple functions of library sequence length. Ln()-scaling also performed better than scores based on normalized variance, but the differences were not statistically significant for the BLOSUM50 and Gonnet92 matrices. Optimal scoring matrices and gap penalties are reported for Smith-Waterman and FASTA, using conventional or In()-scaled similarity scores. Searches with no penalty for gap extension, or no penalty for gap opening, or an infinite penalty for gaps performed significantly worse than the best methods. Differences in performance between FASTA and Smith-Waterman were not significant when partial query sequences were used. However, the best performance with complete query sequences was obtained with the Smith-Waterman algorithm and In()-scaling.     

A recurrent DNA sequence at sites of protein interaction

Variation in the observed spin letter lattice relaxation rate (R_ob) interpreted as proton exchange dominated in sequences corresponding to part of promoters where RNA polymerase initiates mRNA synthesis has been observed by both Patel et al. (64) and Reid and co-workers (43). A higher R_obs was also seen in the TA pair of the GTG/CAC in the sequence corressponding to the λ phage cro repressor binding site by Kyogoku et al. (44). As we pointed out in the introduction, the one case where a three-dimensional structure for a turn of a helix is known shows clear structural heterogeneity which has led to detailed consideration of geometry of regulatory regions. Nussinov and collaborators have generalized the details of the Dickerson dodecomer to note potential similarities in operators including the lac system (53) and the enhancer sequences described above (65). Like the steric considerations of Calladine (66) and Dickerson (67) and nearest neighbor structure analysis of Bubienko et al. (68), the focus is on the geometry of a sequence leading to base tilt angles and potential overlap since they are measurable parameters.With the observation that the DNA molecule is both structurally (14, 69) and dynamically flexible (70–73), there will no doubt be many new variables that can be made as a function of DNA sequence. Biophysical chemists in some ways are like the intoxicated person searching for a lost key at a site different from where it was lost because that is where the light is best. Thus, each physical method has its most convenient observable. It is hoped that the above discussion illustrates that a very large and diverse set of biochemical results are awaiting detailed explanation in molecular terms using the illumination of high resolution physical techniques.     

DNA-ditercalinium interactions: implications for recognition of damaged DNA.

Ditercalinium is unique among known DNA-binding chemotherapeutic agents. Ditercalinium treatment of Escherichia coli causes cell death by provoking malfunction of the (A)BC exinuclease excision DNA repair system. In this report, we describe the three-dimensional X-ray structure of a ditercalinium-[d(CGCG)]2 complex in detail with an analysis of both the structure and its implications. Ditercalinium bisintercalates in the DNA fragment; the positively-charged linker of the drug interacts with the major groove. The DNA retains an underwound, right-handed, double-helical conformation with a bend of around 15 degrees in the helical axis. One striking feature of the complex is the extensive interaction of ditercalinium with guanines in contrast to the near absence of interaction with cytosines. The terminal cytosines in particular are "unstacked" from the rest of the complex. A systematic comparison of the three-dimensional structure of the DNA-ditercalinium complex with those of triostin A and nogalamycin (chemotherapeutic agents that act by conventional mechanisms) allows us to suggest a general model for recognition by the (A)BC exinuclease excision repair system. It is commonly hypothesized that the same distorted conformation of DNA results from modification by each member of a diverse family of DNA-damaging agents. This specific conformation of DNA would then be recognized by the (A)BC exinuclease excision repair system. Alternatively, we propose that each of these damaging agents causes local instability of DNA (but not necessarily a common conformation) and that the (A)BC exinuclease excision repair system recognizes excessive or unusual deformability of damaged DNA in comparison to normal DNA.     

The amino acid sequence of the CCGG recognizing DNA methyltransferase M.BsuFI: implications for the analysis of sequence recognition by cytosine DNA methyltransferases.

The Bacillus subtilis FI DNA methyltransferase (M.BsuFI) modifies the outer cytosine of the DNA sequence CCGG, causing resistance against R.BsuFI and R.MspI restriction. The M.BsuFI gene was cloned and expressed in B.subtilis and Escherichia coli. As derived from the nucleotide sequence, the M.BsuFI protein has 409 amino acids, corresponding to a molecular mass of 46,918 daltons. Including these data we have compared the nucleotide and amino acid sequences of different CCGG recognizing enzymes. These analyses showed that M.BsuFI is highly related to two other CCGG specific methyltransferases, M.MspI and M.HpaII, which were isolated from Gram-negative bacteria. Between M.BsuFI and M.MspI the sequence similarity is particularly significant in a region, which has been postulated to contain the target recognition domains (TRDs) of cytosine-specific DNA methyltransferases. Apparently M.BsuFI and M.MspI, derived from phylogenetic distant organisms, use highly conserved structural elements for the recognition of the CCGG target sequence. In contrast the very same region of M.HpaII is quite different from those of M.BsuFI and M.MspI. We attribute this difference to the different targeting of methylation within the sequence CCGG, where M.HpaII methylates the inner, M.BsuFI/M.MspI the outer cytosine. Also the CCGG recognizing TRD of the multispecific B.subtilis phage SPR Mtase is distinct from that of the host enzyme, possibly indicating different requirements for TRDs operative in mono- and multispecific enzymes.     

A large database DNA sequence handling program with generalized searching specifications.

The program described allows for the creation and manipulation of files of DNA sequence data up to very great lengths. The program uses its own paging system to load segments of the sequence into a small internal buffer so that the program does not have excessive memory requirements. The program offers a menu of functions to the user, and has been written to be forgiving of user errors. A code for the generalised specification of bases as a series of groups (i.e. A or T, Purine, etc.) has been devised and can be used in search specifications or in sequence files. Versions of the program have been developed to run with special efficiency under DIGITAL's RT11 operating system or to run under systems with a suitable implementation of FORTRAN VI.     

An efficient code searching for sequence homology and DNA duplication

This paper presents a very simple and efficient algorithm that searches for sequence homology and gene duplication. The code finds the best alignment of two, short or long, sequences without having to specify how many unmatched bases are allowed to be looped out. Following Needleman & Wunsch (1970), Sellers (1974), Sankoff (1972) and Smith, Waterman & Fitch (1981) gap constraints are incorporated into the program and may be employed. The availability of such a fast computer code enables detection of homologous genes which may fulfill a different function at present, but have arisen from a common gene-ancestor. The code is extremely fast and runs in O(n3/2) units of time. It was applied to the phi X174 sequence.     

Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition

We present an approach to integrate physical properties of DNA, such as DNA bendability or GC content, into our probabilistic promoter recognition system McPROMOTER. In the new model, a promoter is represented as a sequence of consecutive segments represented by joint likelihoods for DNA sequence and profiles of physical properties. Sequence likelihoods are modeled with interpolated Markov chains, physical properties with Gaussian distributions. The background uses two joint sequence/profile models for coding and non-coding sequences, each consisting of a mixture of a sense and an anti-sense submodel. On a large Drosophila test set, we achieved a reduction of about 30% of false positives when compared with a model solely based on sequence likelihoods.     

DNA sequence recognition by under-methylated analogues of triostin A.

Two new analogues of TANDEM (des-N-tetramethyl triostin A) have been synthesised in an effort to elucidate the molecular basis of DNA nucleotide sequence recognition in this series of compounds. Their binding preferences have been investigated by DNAase I footprinting and differential inhibition of restriction nuclease attack. The presence of a single N-methyl group on only one valine residue (in [N-MeVal4] TANDEM) abolishes the ability to recognise DNA, presumably because this antibiotic analogue has suffered an unfavourable conformational change in the depsipeptide ring. A bis-methylated analogue, [N-MeCys3, N-MeCys7]TANDEM, was found to interact quite strongly with DNA and afforded binding sites, rich in AT residues, identical to those of TANDEM. Footprinting with various DNA fragments of known sequence showed that this analogue recognises sequences containing the dinucleotide TpA, although we cannot exclude the possibility that it binds to ApT as well. [N-MeCys3, N-MeCys7]TANDEM inhibits cutting by RsaI, a restriction enzyme that recognises GTAC but not by Sau3AI which recognises GATC. This provides further supportive evidence that the ligand (and, by extension, TANDEM itself) prefers binding to sequences containing the dinucleotide step TpA.