The Experts below are selected from a list of 516 Experts worldwide ranked by ideXlab platform
Soumaya Laalami - One of the best experts on this subject based on the ideXlab platform.
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The Balance between Protein Synthesis and Degradation in Chloroplasts Determines Leaf Variegation in Arabidopsis yellow variegated Mutants.
The Plant cell, 2007Co-Authors: Eiko Miura, Yusuke Kato, Ryo Matsushima, Verónica Albrecht, Soumaya Laalami, Wataru SakamotoAbstract:An Arabidopsis thaliana leaf-variegated mutant yellow variegated2 (var2) results from loss of FtsH2, a major component of the chloroplast FtsH complex. FtsH is an ATP-dependent metalloprotease in thylakoid membranes and degrades several chloroplastic proteins. To understand the role of proteolysis by FtsH and mechanisms leading to leaf variegation, we characterized the second-site recessive mutation fu-gaeri1 (fug1) that suppressed leaf variegation of var2. Map-based cloning and subsequent characterization of the FUG1 locus demonstrated that it encodes a protein homologous to Prokaryotic Translation initiation factor 2 (cpIF2) located in chloroplasts. We show evidence that cpIF2 indeed functions in chloroplast protein synthesis in vivo. Suppression of leaf variegation by fug1 is observed not only in var2 but also in var1 (lacking FtsH5) and var1 var2. Thus, suppression of leaf variegation caused by loss of FtsHs is most likely attributed to reduced protein synthesis in chloroplasts. This hypothesis was further supported by the observation that another viable mutation in chloroplast Translation elongation factor G also suppresses leaf variegation in var2. We propose that the balance between protein synthesis and degradation is one of the determining factors leading to the variegated phenotype in Arabidopsis leaves.
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Initiation Factor 2 of Myxococcus xanthus, a Large Version of Prokaryotic Translation Initiation Factor 2
Journal of bacteriology, 2001Co-Authors: Emmanuelle Tiennault-desbordes, Yves Cenatiempo, Soumaya LaalamiAbstract:We have isolated the structural gene for Translation initiation factor IF2 (infB) from the myxobacterium Myxococcus xanthus. The gene (3.22 kb) encodes a 1,070-residue protein showing extensive homology within its G domain and C terminus to the equivalent regions of IF2 from Escherichia coli. The protein cross-reacts with antibodies raised against E. coli IF2 and was able to complement an E. coli infB mutant. The M. xanthus protein is the largest IF2 known to date. This is essentially due to a longer N-terminal region made up of two characteristic domains. The first comprises a 188-amino-acid sequence consisting essentially of alanine, proline, valine, and glutamic acid residues, similar to the APE domain observed in Stigmatella aurantiaca IF2. The second is unique to M. xanthus IF2, is located between the APE sequence and the GTP binding domain, and consists exclusively of glycine, proline, and arginine residues.
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initiation factor 2 of myxococcus xanthus a large version of Prokaryotic Translation initiation factor 2
Journal of Bacteriology, 2001Co-Authors: Emmanuelle Tiennaultdesbordes, Yves Cenatiempo, Soumaya LaalamiAbstract:We have isolated the structural gene for Translation initiation factor IF2 (infB) from the myxobacterium Myxococcus xanthus. The gene (3.22 kb) encodes a 1,070-residue protein showing extensive homology within its G domain and C terminus to the equivalent regions of IF2 from Escherichia coli. The protein cross-reacts with antibodies raised against E. coli IF2 and was able to complement an E. coli infB mutant. The M. xanthus protein is the largest IF2 known to date. This is essentially due to a longer N-terminal region made up of two characteristic domains. The first comprises a 188-amino-acid sequence consisting essentially of alanine, proline, valine, and glutamic acid residues, similar to the APE domain observed in Stigmatella aurantiaca IF2. The second is unique to M. xanthus IF2, is located between the APE sequence and the GTP binding domain, and consists exclusively of glycine, proline, and arginine residues. Myxococcus xanthus is the best-characterized member of the myxobacteria family. These gram-negative soil bacteria are able to undergo a multicellular developmental program in response to starvation. Hundreds of thousands of bacteria glide to aggregation centers to form complex structures known as fruiting bodies. These specialized structures contain differentiated cells, the myxospores (9). During the developmental cycle of M. xanthus, cellular communication involving at least five different extracellular signals, known as A, B, C, D, and E, is required. The D signal corresponds to Translational initiation factor 3 (IF3) (6, 7, 8), which contains a particular C-terminal extension absent in IF3s from other species. A mutation im
Klaus Zetsche - One of the best experts on this subject based on the ideXlab platform.
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Organization of plastid-encoded ATPase genes and flanking regions including homologues of infB and tsf in the thermophilic red alga Galdieria sulphuraria
Plant Molecular Biology, 1993Co-Authors: Markus Kostrzewa, Klaus ZetscheAbstract:We have cloned and sequenced the plastid ATPase operons ( atp1 and atp2 ) and flanking regions from the unicellular red alga Galdieria sulphuraria (Cyanidium caldarium) . Six genes (5 atpI, H, G, F, D and A 3) are linked in atp1 encoding ATPase subunits a, c, b, b, δ and α, respectively. The atpF gene does not contain an intron and overlaps atpD by 1 bp. As in the genome of chloroplasts from land plants, the cluster is located downstream of rps2 , but between this gene and atp1 we found the gene for the Prokaryotic Translation elongation factor TS. Downstream of atpA , we detected two open reading frames, one encoding a putative transport protein. The genes atpB and atpE , encoding ATPase subunits β and ε, respectively, are linked in atp2 , seperated by a 2 bp spacer. Upstream of atpB , an uninterrupted orf167 was detected which is homologous to an intron-containing open reading frame in land plant chloroplasts. This orf167 is preceded on the opposite DNA strand by a homologue to initiation factor 2 in prokaryotes. The arrangement of atp1 and atp2 is the same as observed in the multicellular red alga Antithamnion sp. indicatiing a conserved genome arrangement in the red algal plastid genome. Differences compared to green chloroplast genomes suggest a large phylogenetic distance between red algae and green plants, while similarities in arrangement and sequence to chromophytic ATPase operons support a red algal origin of chlorophyll a/c -containing plastids or alternatively point to a common Prokaryotic endosymbiont.
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Organization of plastid-encoded ATPase genes and flanking regions including homologues of infB and tsf in the thermophilic red alga Galdieria sulphuraria.
Plant molecular biology, 1993Co-Authors: Markus Kostrzewa, Klaus ZetscheAbstract:We have cloned and sequenced the plastid ATPase operons (atp1 and atp2) and flanking regions from the unicellular red alga Galdieria sulphuraria (Cyanidium caldarium). Six genes (5 atpI, H, G, F, D and A 3) are linked in atp1 encoding ATPase subunits a, c, b, b, delta and alpha, respectively. The atpF gene does not contain an intron and overlaps atpD by 1 bp. As in the genome of chloroplasts from land plants, the cluster is located downstream of rps2, but between this gene and atp1 we found the gene for the Prokaryotic Translation elongation factor TS. Downstream of atpA, we detected two open reading frames, one encoding a putative transport protein. The genes atpB and atpE, encoding ATPase subunits beta and epsilon, respectively, are linked in atp2, separated by a 2 bp spacer. Upstream of atpB, an uninterrupted orf167 was detected which is homologous to an intron-containing open reading frame in land plant chloroplasts. This orf167 is preceded on the opposite DNA strand by a homologue to initiation factor 2 in prokaryotes. The arrangement of atp1 and atp2 is the same as observed in the multicellular red alga Antithamnion sp., indicating a conserved genome arrangement in the red algal plastid genome. Differences compared to green chloroplast genomes suggest a large phylogenetic distance between red algae and green plants, while similarities in arrangement and sequence to chromophytic ATPase operons support a red algal origin of chlorophyll a/c-containing plastids or alternatively point to a common Prokaryotic endosymbiont.
V. Ramakrishnan - One of the best experts on this subject based on the ideXlab platform.
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Prokaryotic Translation INITIATION FACTOR IF3 IS AN ELONGATED PROTEIN CONSISTING OF TWO CRYSTALLIZABLE DOMAINS
Biochemistry, 1995Co-Authors: Jadwiga H. Kycia, Valérie Biou, Fong Shu, Sue Ellen Gerchman, Vito Graziano, V. RamakrishnanAbstract:We show that Translation initiation factor IF3 can be split into two fragments of nearly equal size by the Escherichia coli outer membrane protease omptin. Circular dichroism and small-angle neutron scattering show that the two fragments are structured as domains. Each domain is relatively compact, and they are separated by about 45 {Angstrom} in intact IF3. Thus IF3 is an elongated protein that consists of two well-separated domains. We suggest that these two domains are involved in ribosome binding across the cleft of the 30S ribosome. We also report the crystallization of each domain of IF3. 26 refs., 3 figs., 1 tab.
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Prokaryotic Translation INITIATION FACTOR IF3 IS AN ELONGATED PROTEIN CONSISTING OF TWO CRYSTALLIZABLE DOMAINS
Biochemistry, 1995Co-Authors: Jadwiga H. Kycia, Valérie Biou, Fong Shu, Sue Ellen Gerchman, Vito Graziano, V. RamakrishnanAbstract:We show that Translation initiation factor IF3 can be split into two fragments of nearly equal size by the Escherichia coli outer membrane protease omptin. Circular dichroism and small-angle neutron scattering show that the two fragments are structured as domains. Each domain is relatively compact, and they are separated by about 45 A in intact IF3. Thus IF3 is an elongated protein that consists of two well-separated domains. We suggest that these two domains are involved in ribosome binding across the cleft of the 30S ribosome. We also report the crystallization of each domain of IF3.
David M. Kehoe - One of the best experts on this subject based on the ideXlab platform.
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Translation initiation factor 3 families: what are their roles in regulating cyanobacterial and chloroplast gene expression?
Photosynthesis Research, 2015Co-Authors: April D. Nesbit, Craig Whippo, Roger P. Hangarter, David M. KehoeAbstract:Initiation is a key control point for the regulation of Translation in prokaryotes and Prokaryotic-like Translation systems such as those in plant chloroplasts. Genome sequencing and biochemical studies are increasingly demonstrating differences in many aspects of Translation between well-studied microbes such as Escherichia coli and lesser studied groups such as cyanobacteria. Analyses of chloroplast Translation have revealed its Prokaryotic origin but also uncovered many unique aspects that do not exist in E. coli . Recently, a novel form of posttranscriptional regulation by light color was discovered in the filamentous cyanobacterium Fremyella diplosiphon that requires a putative stem-loop and involves the use of two different Prokaryotic Translation initiation factor 3s (IF3s). Multiple (up to five) putative IF3s have now been found to be encoded in 22 % of sequenced cyanobacterial genomes and 26 % of plant nuclear genomes. The lack of similar light-color regulation of gene expression in most of these species suggests that IF3s play roles in regulating gene expression in response to other environmental and developmental cues. In the plant Arabidopsis , two nuclear-encoded IF3s have been shown to localize to the chloroplasts, and the mRNA levels encoding these vary significantly in certain organ and tissue types and during several phases of development. Collectively, the accumulated data suggest that in about one quarter of photosynthetic prokaryotes and eukaryotes, IF3 gene families are used to regulate gene expression in addition to their traditional roles in Translation initiation. Models for how this might be accomplished in prokaryotes versus eukaryotic plastids are presented.
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Unique role for Translation initiation factor 3 in the light color regulation of photosynthetic gene expression
Proceedings of the National Academy of Sciences of the United States of America, 2013Co-Authors: Andrian Gutu, April D. Nesbit, Andrew J. Alverson, Jeffrey D. Palmer, David M. KehoeAbstract:Light-harvesting antennae are critical for collecting energy from sunlight and providing it to photosynthetic reaction centers. Their abundance and composition are tightly regulated to maintain efficient photosynthesis in changing light conditions. Many cyanobacteria alter their light-harvesting antennae in response to changes in ambient light-color conditions through the process of chromatic acclimation. The control of green light induction (Cgi) pathway is a light-color-sensing system that controls the expression of photosynthetic genes during chromatic acclimation, and while some evidence suggests that it operates via transcription attenuation, the components of this pathway have not been identified. We provide evidence that Translation initiation factor 3 (IF3), an essential component of the Prokaryotic Translation initiation machinery that binds the 30S subunit and blocks premature association with the 50S subunit, is part of the control of green light induction pathway. Light regulation of gene expression has not been previously described for any Translation initiation factor. Surprisingly, deletion of the IF3-encoding gene infCa was not lethal in the filamentous cyanobacterium Fremyella diplosiphon, and its genome was found to contain a second, redundant, highly divergent infC gene which, when deleted, had no effect on photosynthetic gene expression. Either gene could complement an Escherichia coli infC mutant and thus both encode bona fide IF3s. Analysis of Prokaryotic and eukaryotic genome databases established that multiple infC genes are present in the genomes of diverse groups of bacteria and land plants, most of which do not undergo chromatic acclimation. This suggests that IF3 may have repeatedly evolved important roles in the regulation of gene expression in both prokaryotes and eukaryotes.
Peter Meinicke - One of the best experts on this subject based on the ideXlab platform.
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TICO: a tool for postprocessing the predictions of Prokaryotic Translation initiation sites.
Nucleic acids research, 2006Co-Authors: Maike Tech, Burkhard Morgenstern, Peter MeinickeAbstract:Exact localization of the Translation initiation sites (TIS) in Prokaryotic genomes is difficult to achieve using conventional gene finders. We recently introduced the program TICO for postprocessing TIS predictions based on a completely unsupervised learning algorithm. The program can be utilized through our web interface at http://tico.gobics.de/ and it is also freely available as a commandline version for Linux and Windows. The latest version of our program provides a tool for visualization of the resulting TIS model. Although the underlying method is not based on any specific assumptions about characteristic sequence features of Prokaryotic TIS the prediction rates of our tool are competitive on experimentally verified test data.
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Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts
Lecture Notes in Computer Science, 2006Co-Authors: Britta Mersch, Peter Meinicke, Tobias Glasmachers, Christian IgelAbstract:Oligo kernels for biological sequence classification have a high discriminative power. A new parameterization for the K-mer oligo kernel is presented, where all oligomers of length K are weighted individually. The task specific choice of these parameters increases the classification performance and reveals information about discriminative features. For adapting the multiple kernel parameters based on cross-validation the covariance matrix adaptation evolution strategy is proposed. It is applied to optimize the trimer oligo kernel for the detection of Prokaryotic Translation initiation sites. The resulting kernel leads to higher classification rates, and the adapted parameters reveal the importance for classification of particular triplets, for example of those occurring in the Shine-Dalgarno sequence.
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TICO: a tool for improving predictions of Prokaryotic Translation initiation sites
Bioinformatics (Oxford England), 2005Co-Authors: Maike Tech, Nico Pfeifer, Burkhard Morgenstern, Peter MeinickeAbstract:We provide the tool 'TICO' (Translation Initiation site COrrection) for improving the results of conventional gene finders for Prokaryotic genomes with regard to exact localization of the Translation initiation site (TIS). At the current state TICO provides an interface for direct post processing of the predictions obtained from the widely used program GLIMMER. Our program is based on a clustering algorithm for completely unsupervised scoring of potential TIS locations. Our tool can be freely accessed through a web interface at http://tico.gobics.de/ maike@gobics.de
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Oligo kernels for datamining on biological sequences: a case study on Prokaryotic Translation initiation sites
BMC bioinformatics, 2004Co-Authors: Peter Meinicke, Maike Tech, Burkhard Morgenstern, Rainer MerklAbstract:Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals. We propose a kernel-based approach to datamining on biological sequences. With our method it is possible to model and analyze positional variability of oligomers of any length in a natural way. On one hand this is achieved by mapping the sequences to an intuitive but high-dimensional feature space, well-suited for interpretation of the learnt models. On the other hand, by means of the kernel trick we can provide a general learning algorithm for that high-dimensional representation because all required statistics can be computed without performing an explicit feature space mapping of the sequences. By introducing a kernel parameter that controls the degree of position-dependency, our feature space representation can be tailored to the characteristics of the biological problem at hand. A regularized learning scheme enables application even to biological problems for which only small sets of example sequences are available. Our approach includes a visualization method for transparent representation of characteristic sequence features. Thereby importance of features can be measured in terms of discriminative strength with respect to classification of the underlying sequences. To demonstrate and validate our concept on a biochemically well-defined case, we analyze E. coli Translation initiation sites in order to show that we can find biologically relevant signals. For that case, our results clearly show that the Shine-Dalgarno sequence is the most important signal upstream a start codon. The variability in position and composition we found for that signal is in accordance with previous biological knowledge. We also find evidence for signals downstream of the start codon, previously introduced as transcriptional enhancers. These signals are mainly characterized by occurrences of adenine in a region of about 4 nucleotides next to the start codon. We showed that the oligo kernel can provide a valuable tool for the analysis of relevant signals in biological sequences. In the case of Translation initiation sites we could clearly deduce the most discriminative motifs and their positional variation from example sequences. Attractive features of our approach are its flexibility with respect to oligomer length and position conservation. By means of these two parameters oligo kernels can easily be adapted to different biological problems.
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oligo kernels for datamining on biological sequences a case study on Prokaryotic Translation initiation sites
BMC Bioinformatics, 2004Co-Authors: Peter Meinicke, Maike Tech, Burkhard Morgenstern, Rainer MerklAbstract:Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals. Results: We propose a kernel-based approach to datamining on biological sequences. With our method it is possible to model and analyze positional variability of oligomers of any length in a natural way. On one hand this is achieved by mapping the sequences to an intuitive but high-dimensional feature space, wellsuited for interpretation of the learnt models. On the other hand, by means of the kernel trick we can provide a general learning algorithm for that high-dimensional representation because all required statistics can be computed without performing an explicit feature space mapping of the sequences. By introducing a kernel parameter that controls the degree of position-dependency, our feature space representation can be tailored to the characteristics of the biological problem at hand. A regularized learning scheme enables application even to biological problems for which only small sets of example sequences are available. Our approach includes a visualization method for transparent representation of characteristic sequence features. Thereby importance of features can be measured in terms of discriminative strength with respect to classification of the underlying sequences. To demonstrate and validate our concept on a biochemically well-defined case, we analyze E. coli Translation initiation sites in order to show that we can find biologically relevant signals. For that case, our results clearly show that the Shine-Dalgarno sequence is the most important signal upstream a start codon. The variability in position and composition we found for that signal is in accordance with previous biological knowledge. We also find evidence for signals downstream of the start codon, previously introduced as transcriptional enhancers. These signals are mainly characterized by occurrences of adenine in a region of about 4 nucleotides next to the start codon. Conclusions: We showed that the oligo kernel can provide a valuable tool for the analysis of relevant signals in biological sequences. In the case of Translation initiation sites we could clearly deduce the most discriminative motifs and their positional variation from example sequences. Attractive features of our approach are its flexibility with respect to oligomer length and position conservation. By means of these two parameters oligo kernels can easily be adapted to different biological problems.
