Anaerobic degradation of papermill sludge in a two-phase digester containing rumen microorganisms and colonized polyurethane foam

Summary The use of reticulated polyurethane foam as a support material for the immobilization of methanogenic associations and its application to the anaerobic treatment of fine particulate solid wastes was investigated. The colonization of polyurethane support particles in a continuous upflow reactor fed on a mixture of acetate, propionate and butyrate, was both rapid and dense. The combination of rumen microorganisms and colonized support particles in a two-phase digester resulted in an efficient anaerobic decomposition of papermill sludge.     

Information content of binding sites on nucleotide sequences

Repressors, polymerases, ribosomes and other macromolecules bind to specific nucleic acid sequences. They can find a binding site only if the sequence has a recognizable pattern. We define a measure of the information (R sequence) in the sequence patterns at binding sites. It allows one to investigate how information is distributed across the sites and to compare one site to another. One can also calculate the amount of information (R frequency) that would be required to locate the sites, given that they occur with some frequency in the genome. Several Escherichia coli binding sites were analyzed using these two independent empirical measurements. The two amounts of information are similar for most of the sites we analyzed. In contrast, bacteriophage T7 RNA polymerase binding sites contain about twice as much information as is necessary for recognition by the T7 polymerase, suggesting that a second protein may bind at T7 promoters. The extra information can be accounted for by a strong symmetry element found at the T7 promoters. This element may be an operator. If this model is correct, these promoters and operators do not share much information. The comparisons between R sequence and R frequency suggest that the information at binding sites is just sufficient for the sites to be distinguished from the rest of the genome.     

Excess information at bacteriophage T7 genomic promoters detected by a random cloning technique.

In our previous analysis of the information at binding sites on nucleic acids, we found that most of the sites examined contain the amount of information expected from their frequency in the genome. The sequences at bacteriophage T7 promoters are an exception, because they are far more conserved (35 bits of information content) than should be necessary to distinguish them from the background of the Escherichia coli genome (17 bits). To determine the information actually used by the T7 RNA polymerase, promoters were chemically synthesized with many variations and those that function well in an in vivo assay were sequenced. Our analysis shows that the polymerase uses 18 bits of information, so the sequences at phage genomic promoters have significantly more information than the polymerase needs. The excess may represent the binding site of another protein.     

Identification of consensus patterns in unaligned DNA sequences known to be functionally related

We have developed a method for identifying consensus patternsin a set of unaligned DNA sequences known to bind a common proteinor to have some other common biochemical function. The methodis based on a tnatrix representation of binding site patterns.Each row of the matrix represents one of the four possible bases,each column represents one of the positions of the binding siteand each element is determined by the frequency the indicatedbase occurs at the indicated position. The goal of the methodis to find the most significant matrix-i.e. the one with thelowest probability of occurring by chance-out of all the matricesthat can be formed from the set of related sequences. The reliabilityof the method improves with the number of sequences, while thetime required increases only linearly with the number of sequences.To test this method, we analysed 11 DNA sequences containingpromoters regulated by the Escherichia coli LexA protein. Thematrices we' found were consistent with the known consensussequence, and could distinguish the generally accepted LexAbinding sites from other DNA sequences. Received on November 6, 1989; accepted on December 20, 1989     

Use of the 'Perceptron' algorithm to distinguish translational initiation sites in E. coli.

We have used a "Perceptron" algorithm to find a weighting function which distinguishes E. coli translational initiation sites from all other sites in a library of over 78,000 nucleotides of mRNA sequence. The "Perceptron" examined sequences as linear representations. The "Perceptron" is more successful at finding gene beginnings than our previous searches using "rules" (see previous paper). We note that the weighting function can find translational initiation sites within sequences that were not included in the training set.     

Using defined finger–finger interfaces as units of assembly for constructing zinc-finger nucleases

Zinc-finger nucleases (ZFNs) have been used for genome engineering in a wide variety of organisms; however, it remains challenging to design effective ZFNs for many genomic sequences using publicly available zinc-finger modules. This limitation is in part because of potential finger–finger incompatibility generated on assembly of modules into zinc-finger arrays (ZFAs). Herein, we describe the validation of a new set of two-finger modules that can be used for building ZFAs via conventional assembly methods or a new strategy—finger stitching—that increases the diversity of genomic sequences targetable by ZFNs. Instead of assembling ZFAs based on units of the zinc-finger structural domain, our finger stitching method uses units that span the finger–finger interface to ensure compatibility of neighbouring recognition helices. We tested this approach by generating and characterizing eight ZFAs, and we found their DNA-binding specificities reflected the specificities of the component modules used in their construction. Four pairs of ZFNs incorporating these ZFAs generated targeted lesions in vivo, demonstrating that stitching yields ZFAs with robust recognition properties.     

Comparative genomics identifies a flagellar and basal body proteome that includes the BBS5 human disease gene

Cilia and flagella are microtubule-based structures nucleated by modified centrioles termed basal bodies. These biochemically complex organelles have more than 250 and 150 polypeptides, respectively. To identify the proteins involved in ciliary and basal body biogenesis and function, we undertook a comparative genomics approach that subtracted the nonflagellated proteome of Arabidopsis from the shared proteome of the ciliated/flagellated organisms Chlamydomonas and human. We identified 688 genes that are present exclusively in organisms with flagella and basal bodies and validated these data through a series of in silico, in vitro, and in vivo studies. We then applied this resource to the study of human ciliation disorders and have identified BBS5, a novel gene for Bardet-Biedl syndrome. We show that this novel protein localizes to basal bodies in mouse and C. elegans, is under the regulatory control of daf-19, and is necessary for the generation of both cilia and flagella.     

A graph theoretical approach for predicting common RNA secondary structure motifs including pseudoknots in unaligned sequences

MOTIVATION: RNA structure motifs contained in mRNAs have been found to play important roles in regulating gene expression. However, identification of novel RNA regulatory motifs using computational methods has not been widely explored. Effective tools for predicting novel RNA regulatory motifs based on genomic sequences are needed. RESULTS: We present a new method for predicting common RNA secondary structure motifs in a set of functionally or evolutionarily related RNA sequences. This method is based on comparison of stems (palindromic helices) between sequences and is implemented by applying graph-theoretical approaches. It first finds all possible stable stems in each sequence and compares stems pairwise between sequences by some defined features to find stems conserved across any two sequences. Then by applying a maximum clique finding algorithm, it finds all significant stems conserved across at least k sequences. Finally, it assembles in topological order all possible compatible conserved stems shared by at least k sequences and reports a number of the best assembled stem sets as the best candidate common structure motifs. This method does not require prior structural alignment of the sequences and is able to detect pseudoknot structures. We have tested this approach on some RNA sequences with known secondary structures, in which it is capable of detecting the real structures completely or partially correctly and outperforms other existing programs for similar purposes. AVAILABILITY: The algorithm has been implemented in C++ in a program called comRNA, which is available at http://ural.wustl.edu/softwares.html     

Additivity in protein-DNA interactions: how good an approximation is it?

Man and Stormo and Bulyk et al. recently presented their results on the study of the DNA binding affinity of proteins. In both of these studies the main conclusion is that the additivity assumption, usually applied in methods to search for binding sites, is not true. In the first study, the analysis of binding affinity data from the Mnt repressor protein bound to all possible DNA (sub)targets at positions 16 and 17 of the binding site, showed that those positions are not independent. In the second study, the authors analysed DNA binding affinity data of the wild-type mouse EGR1 protein and four variants differing on the middle finger. The binding affinity of these proteins was measured to all 64 possible trinucleotide (sub)targets of the middle finger using microarray technology. The analysis of the measurements also showed interdependence among the positions in the DNA target. In the present report, we review the data of both studies and we re- analyse them using various statistical methods, including a comparison with a multiple regression approach. We conclude that despite the fact that the additivity assumption does not fit the data perfectly, in most cases it provides a very good approximation of the true nature of the specific protein–DNA interactions. Therefore, additive models can be very useful for the discovery and prediction of binding sites in genomic DNA.