The Mode of Action of Maleic Hydrazide: Inhibition of Growth

Maleic hydrazide (MH) inhibits corn root elongation through an effect on cell division apparently without inhibiting cell enlargement. The decrease in the rate of elongation was apparent only after a considerable lag, over 14 hours, even with a concentration as high as 5 mM. MH (1 mM) did not inhibit His growth of roots from corn seeds given very large doses of Γ-irradiation or excised corn root segments including the elongation Zone or the cell enlargement induced by IAA in corn coleoptile sections. Many compounds including purines, pyrimidines, nucleosides. cysteine, pyridoxal, pyruvate. kinetin and CoCl 2 , many of which had previously been reported to alleviate MH inhibition in other tissues, were tested for their ability to prevent the inhibition of corn root elongation by MH, but none were effective. These data do not support the theory that MH acts by inhibiting the synthesis of or competing with some simple metabolite or hormone. Whatever its mechanism of action the failure of MH to inhibit cell enlargement in most systems indicates that it is fairly selective.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74891/1/j.1399-3054.1969.tb07375.x.pd

Predicting RNA secondary structure by the comparative approach: how to select the homologous sequences

<p>Abstract</p> <p>Background</p> <p>The secondary structure of an RNA must be known before the relationship between its structure and function can be determined. One way to predict the secondary structure of an RNA is to identify covarying residues that maintain the pairings (Watson-Crick, Wobble and non-canonical pairings). This "comparative approach" consists of identifying mutations from homologous sequence alignments. The sequences must covary enough for compensatory mutations to be revealed, but comparison is difficult if they are too different. Thus the choice of homologous sequences is critical. While many possible combinations of homologous sequences may be used for prediction, only a few will give good structure predictions. This can be due to poor quality alignment in stems or to the variability of certain sequences. This problem of sequence selection is currently unsolved.</p> <p>Results</p> <p>This paper describes an algorithm, <it>SSCA</it>, which measures the suitability of sequences for the comparative approach. It is based on evolutionary models with structure constraints, particularly those on sequence variations and stem alignment. We propose three models, based on different constraints on sequence alignments. We show the results of the <it>SSCA </it>algorithm for predicting the secondary structure of several RNAs. <it>SSCA </it>enabled us to choose sets of homologous sequences that gave better predictions than arbitrarily chosen sets of homologous sequences.</p> <p>Conclusion</p> <p><it>SSCA </it>is an algorithm for selecting combinations of RNA homologous sequences suitable for secondary structure predictions with the comparative approach.</p

High incidence of Epstein-Barr virus, cytomegalovirus and human herpesvirus 6 infections in children with cancer

BACKGROUND: A prospective single-center study was performed to study infection with lymphotropic herpesviruses (LH) Epstein-Barr virus (EBV), cytomegalovirus (CMV) and human herpesvirus 6 (HHV-6) in children with cancer. METHODS: The group of 186 children was examined for the presence of LH before, during and 2 months after the end of anticancer treatment. Serology of EBV and CMV was monitored in all children, serology of HHV-6 and DNA analysis of all three LH was monitored in 70 children. RESULTS: At the time of cancer diagnosis (pre-treatment), there was no difference between cancer patients and age-matched healthy controls in overall IgG seropositivity for EBV (68.8% vs. 72.0%; p = 0.47) and CMV (37.6% vs. 41.7%; p = 0.36). During anticancer therapy, primary or reactivated EBV and CMV infection was present in 65 (34.9%) and 66 (35.4%) of 186 patients, respectively, leading to increased overall post-treatment IgG seropositivity that was significantly different from controls for EBV (86.6% vs. 72.0%; p = 0.0004) and CMV (67.7% vs. 41.7%; p < 0.0001). Overall pre-treatment IgG seropositivity for HHV-6 was significantly lower in patients than in controls (80.6% vs. 91.3%; p = 0.0231) which may be in agreement with Greaves hypothesis of protective effect of common infections in infancy to cancer development. Primary or reactivated HHV-6 infection was present in 23 (32.9%) of 70 patients during anticancer therapy leading to post-treatment IgG seropositivity that was not significantly different from controls (94.3% vs. 91.3%; p = 0.58). The LH infection occurred independently from leukodepleted blood transfusions given. Combination of serology and DNA analysis in detection of symptomatic EBV or CMV infection was superior to serology alone. CONCLUSION: EBV, CMV and HHV-6 infections are frequently present during therapy of pediatric malignancy

Structural Constraints Identified with Covariation Analysis in Ribosomal RNA

Covariation analysis is used to identify those positions with similar patterns of sequence variation in an alignment of RNA sequences. These constraints on the evolution of two positions are usually associated with a base pair in a helix. While mutual information (MI) has been used to accurately predict an RNA secondary structure and a few of its tertiary interactions, early studies revealed that phylogenetic event counting methods are more sensitive and provide extra confidence in the prediction of base pairs. We developed a novel and powerful phylogenetic events counting method (PEC) for quantifying positional covariation with the Gutell lab’s new RNA Comparative Analysis Database (rCAD). The PEC and MI-based methods each identify unique base pairs, and jointly identify many other base pairs. In total, both methods in combination with an N-best and helix-extension strategy identify the maximal number of base pairs. While covariation methods have effectively and accurately predicted RNAs secondary structure, only a few tertiary structure base pairs have been identified. Analysis presented herein and at the Gutell lab’s Comparative RNA Web (CRW) Site reveal that the majority of these latter base pairs do not covary with one another. However, covariation analysis does reveal a weaker although significant covariation between sets of nucleotides that are in proximity in the three-dimensional RNA structure. This reveals that covariation analysis identifies other types of structural constraints beyond the two nucleotides that form a base pair

Effects of Restrained Sampling Space and Nonplanar Amino Groups on Free-Energy Predictions for RNA with Imino and Sheared Tandem GA Base Pairs Flanked by GC, CG, iGiC or iCiG Base Pairs

Guanine-adenine (GA) base pairs play important roles in determining the structure, dynamics, and stability of RNA. In RNA internal loops, GA base pairs often occur in tandem arrangements and their structure is context and sequence dependent. Calculations reported here test the thermodynamic integration (TI) approach with the amber99 force field by comparing computational predictions of free energy differences with the free energy differences expected on the basis of NMR determined structures of the RNA motifs (5′-GCGGACGC-3′)2, (5′-GCiGGAiCGC-3′)2, (5′-GGCGAGCC-3′)2, and (5′-GGiCGAiGCC-3′)2. Here, iG and iC denote isoguanosine and isocytidine, which have amino and carbonyl groups transposed relative to guanosine and cytidine. The NMR structures show that the GA base pairs adopt either imino (cis Watson−Crick/Watson−Crick A-G) or sheared (trans Hoogsteen/Sugar edge A-G) conformations depending on the identity and orientation of the adjacent base pair. A new mixing function for the TI method is developed that allows alchemical transitions in which atoms can disappear in both the initial and final states. Unrestrained calculations gave ΔG° values 2−4 kcal/mol different from expectations based on NMR data. Restraining the structures with hydrogen bond restraints did not improve the predictions. Agreement with NMR data was improved by 0.7 to 1.5 kcal/mol, however, when structures were restrained with weak positional restraints to sample around the experimentally determined NMR structures. The amber99 force field was modified to partially include pyramidalization effects of the unpaired amino group of guanosine in imino GA base pairs. This provided little or no improvement in comparisons with experiment. The marginal improvement is observed when the structure has potential cross-strand out-of-plane hydrogen bonding with the G amino group. The calculations using positional restraints and a nonplanar amino group reproduce the signs of ΔG° from the experimental results and are, thus, capable of providing useful qualitative insights complementing the NMR experiments. Decomposition of the terms in the calculations reveals that the dominant terms are from electrostatic and interstrand interactions other than hydrogen bonds in the base pairs. The results suggest that a better description of the backbone is key to reproducing the experimental free energy results with computational free energy predictions

Species diversity of Trichoderma in Poland

In the present study, we reinvestigate the diversity of Trichoderma in Poland utilizing a combination of morphological and molecular/phylogenetic methods. A total of 170 isolates were collected from six different substrata at 49 sites in Poland. These were divided among 14 taxa as follows: 110 of 170 Trichoderma isolates were identified to the species level by the analysis of their ITS1, ITS2 rDNA sequences as: T. harzianum (43 isolates), T. aggressivum (35), T. citrinoviride (11), T. hamatum (9), T. virens (6), T. longibrachiatum (4), T. polysporum (1), and T. tomentosum (1); 60 isolates belonging to the Viride clade were identified based on a fragment of the translation-elongation factor 1-alpha (tef1) gene as: T. atroviride (20 isolates), T. gamsii (2), T. koningii (17), T. viridescens (13), T. viride (7), and T. koningiopsis (1). Identifications were made using the BLAST interface in TrichOKEY and TrichoBLAST (http://www.isth.info). The most diverse substrata were soil (nine species per 22 isolates) and decaying wood (nine species per 75 isolates). The most abundant species (25%) isolated from all substrata was T. harzianum

nocoRNAc: Characterization of non-coding RNAs in prokaryotes

<p>Abstract</p> <p>Background</p> <p>The interest in non-coding RNAs (ncRNAs) constantly rose during the past few years because of the wide spectrum of biological processes in which they are involved. This led to the discovery of numerous ncRNA genes across many species. However, for most organisms the non-coding transcriptome still remains unexplored to a great extent. Various experimental techniques for the identification of ncRNA transcripts are available, but as these methods are costly and time-consuming, there is a need for computational methods that allow the detection of functional RNAs in complete genomes in order to suggest elements for further experiments. Several programs for the genome-wide prediction of functional RNAs have been developed but most of them predict a genomic locus with no indication whether the element is transcribed or not.</p> <p>Results</p> <p>We present <smcaps>NOCO</smcaps>RNAc, a program for the genome-wide prediction of ncRNA transcripts in bacteria. <smcaps>NOCO</smcaps>RNAc incorporates various procedures for the detection of transcriptional features which are then integrated with functional ncRNA loci to determine the transcript coordinates. We applied RNAz and <smcaps>NOCO</smcaps>RNAc to the genome of <it>Streptomyces coelicolor </it>and detected more than 800 putative ncRNA transcripts most of them located antisense to protein-coding regions. Using a custom design microarray we profiled the expression of about 400 of these elements and found more than 300 to be transcribed, 38 of them are predicted novel ncRNA genes in intergenic regions. The expression patterns of many ncRNAs are similarly complex as those of the protein-coding genes, in particular many antisense ncRNAs show a high expression correlation with their protein-coding partner.</p> <p>Conclusions</p> <p>We have developed <smcaps>NOCO</smcaps>RNAc, a framework that facilitates the automated characterization of functional ncRNAs. <smcaps>NOCO</smcaps>RNAc increases the confidence of predicted ncRNA loci, especially if they contain transcribed ncRNAs. <smcaps>NOCO</smcaps>RNAc is not restricted to intergenic regions, but it is applicable to the prediction of ncRNA transcripts in whole microbial genomes. The software as well as a user guide and example data is available at <url>http://www.zbit.uni-tuebingen.de/pas/nocornac.htm</url>.</p