49 research outputs found

    Prediction of Sinorhizobium meliloti sRNA genes and experimental detection in strain 2011

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    Valverde C, Livny J, Schlüter J-P, Reinkensmeier J, Becker A, Parisi G. Prediction of Sinorhizobium meliloti sRNA genes and experimental detection in strain 2011. BMC Genomics. 2008;9(1): 416.Background: Small non-coding RNAs (sRNAs) have emerged as ubiquitous regulatory elements in bacteria and other life domains. However, few sRNAs have been identified outside several well-studied species of gamma-proteobacteria and thus relatively little is known about the role of RNA-mediated regulation in most other bacterial genera. Here we have conducted a computational prediction of putative sRNA genes in intergenic regions (IgRs) of the symbiotic alpha-proteobacterium S. meliloti 1021 and experimentally confirmed the expression of dozens of these candidate loci in the closely related strain S. meliloti 2011. Results: Our first sRNA candidate compilation was based mainly on the output of the sRNAPredictHT algorithm. A thorough manual sequence analysis of the curated list rendered an initial set of 18 IgRs of interest, from which 14 candidates were detected in strain 2011 by Northern blot and/or microarray analysis. Interestingly, the intracellular transcript levels varied in response to various stress conditions. We developed an alternative computational method to more sensitively predict sRNA-encoding genes and score these predicted genes based on several features to allow identification of the strongest candidates. With this novel strategy, we predicted 60 chromosomal independent transcriptional units that, according to our annotation, represent strong candidates for sRNA-encoding genes, including most of the sRNAs experimentally verified in this work and in two other contemporary studies. Additionally, we predicted numerous candidate sRNA genes encoded in megaplasmids pSymA and pSymB. A significant proportion of the chromosomal- and megaplasmid- borne putative sRNA genes were validated by microarray analysis in strain 2011. Conclusion: Our data extend the number of experimentally detected S. meliloti sRNAs and significantly expand the list of putative sRNA-encoding IgRs in this and closely related alpha-proteobacteria. In addition, we have developed a computational method that proved useful to predict sRNA-encoding genes in S. meliloti. We anticipate that this predictive approach can be flexibly implemented in many other bacterial species

    A genome-wide survey of sRNAs in the symbiotic nitrogen-fixing alpha-proteobacterium Sinorhizobium meliloti

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    Schlüter J-P, Reinkensmeier J, Daschkey S, et al. A genome-wide survey of sRNAs in the symbiotic nitrogen-fixing alpha-proteobacterium Sinorhizobium meliloti. BMC Genomics. 2010;11(1): 245.BACKGROUND: Small untranslated RNAs (sRNAs) are widespread regulators of gene expression in bacteria. This study reports on a comprehensive screen for sRNAs in the symbiotic nitrogen-fixing alpha-proteobacterium Sinorhizobium meliloti applying deep sequencing of cDNAs and microarray hybridizations. RESULTS: A total of 1,125 sRNA candidates that were classified as trans-encoded sRNAs (173), cis-encoded antisense sRNAs (117), mRNA leader transcripts (379), and sense sRNAs overlapping coding regions (456) were identified in a size range of 50 to 348 nucleotides. Among these were transcripts corresponding to 82 previously reported sRNA candidates. Enrichment for RNAs with primary 5'-ends prior to sequencing of cDNAs suggested transcriptional start sites corresponding to 466 predicted sRNA regions. The consensus sigma70 promoter motif CTTGAC-N17-CTATAT was found upstream of 101 sRNA candidates. Expression patterns derived from microarray hybridizations provided further information on conditions of expression of a number of sRNA candidates. Furthermore, GenBank, EMBL, DDBJ, PDB, and Rfam databases were searched for homologs of the sRNA candidates identified in this study. Searching Rfam family models with over 1,000 sRNA candidates, re-discovered only those sequences from S. meliloti already known and stored in Rfam, whereas BLAST searches suggested a number of homologs in related alpha-proteobacteria. CONCLUSIONS: The screening data suggests that in S. meliloti about 3% of the genes encode trans-encoded sRNAs and about 2% antisense transcripts. Thus, this first comprehensive screen for sRNAs applying deep sequencing in an alpha-proteobacterium shows that sRNAs also occur in high number in this group of bacteria

    ViCAR: An Adaptive and Landmark-Free Registration of Time Lapse Image Data from Microfluidics Experiments

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    Hattab G, Schlüter J-P, Becker A, Nattkemper TW. ViCAR: An Adaptive and Landmark-Free Registration of Time Lapse Image Data from Microfluidics Experiments. Frontiers in Genetics. 2017;8: 69.In order to understand gene function in bacterial life cycles, time lapse bioimaging is applied in combination with different marker protocols in so called microfluidics chambers (i.e., a multi-well plate). In one experiment, a series of T images is recorded for one visual field, with a pixel resolution of 60 nm/px. Any (semi-)automatic analysis of the data is hampered by a strong image noise, low contrast and, last but not least, considerable irregular shifts during the acquisition. Image registration corrects such shifts enabling next steps of the analysis (e.g., feature extraction or tracking). Image alignment faces two obstacles in this microscopic context: (a) highly dynamic structural changes in the sample (i.e., colony growth) and (b) an individual data set-specific sample environment which makes the application of landmarks-based alignments almost impossible. We present a computational image registration solution, we refer to as ViCAR: (Vi)sual (C)ues based (A)daptive (R)egistration, for such microfluidics experiments, consisting of (1) the detection of particular polygons (outlined and segmented ones, referred to as visual cues), (2) the adaptive retrieval of three coordinates throughout different sets of frames, and finally (3) an image registration based on the relation of these points correcting both rotation and translation. We tested ViCAR with different data sets and have found that it provides an effective spatial alignment thereby paving the way to extract temporal features pertinent to each resulting bacterial colony. By using ViCAR, we achieved an image registration with 99.9% of image closeness, based on the average rmsd of 4.10−2 pixels, and superior results compared to a state of the art algorithm

    The relevance of oral exposure in the workplace: a systematic review and meta-analysis

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    IntroductionThe inclusion of all relevant exposure routes in the exposure assessment is essential for the protection of workers. However, under European chemical regulations but also for workplace risk assessments according to occupational safety and health (OSH) requirements, the quantitative assessment of oral exposure is usually neglected assuming good occupational hygiene. In contrast, several studies point to the importance of unintentional ingestion in the workplace. To our knowledge, there is no systematic analysis of the extent of this exposure route.MethodsTherefore, the aim of this study was to assess systematically the current knowledge on the relevance of occupational oral exposure using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method. Five electronic databases and nine institutional websites were searched for all publications on the relevance. The data were extracted into a concept matrix. In the subsequent meta-analysis, the identified conclusions on the relevance were analyzed. In addition, the measurement methods or modeling approaches that were described for occupational oral exposure were determined as well as the potentially relevant workplaces and substances.ResultsIn total, 147 studies were included in this analysis that contain a general or several, differentiated assessments of the relevance of occupational oral exposure. Nine of these studies assessed this exposure route as irrelevant. However, 123 studies considered oral exposure as potentially contributing and 80 studies explicitly identified it as relevant. 78 and 94 of the publications described modeling and measurement approaches, respectively. The workplaces frequently identified as potentially or explicitly relevant were other indoor, other industrial or recycling workplaces. Analogously, metals, dust and powders or pesticides were the most frequently investigated substance groups.DiscussionAs several studies assessed occupational oral exposure as relevant in the context of different workplaces and substances, further investigation of this exposure route is needed. This systematic review and meta-analysis serve as a basis for further development of feasible assessment methods for this route of exposure

    Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence

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    Ampattu BJ, Hagmann L, Liang C, et al. Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence. BMC Genomics. 2017;18(1): 282.Background: Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain alpha 522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence. Results: Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p) ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region. Conclusions: Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis

    Diversification in evolutionary arenas : Assessment and synthesis

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    Understanding how and why rates of evolutionary diversification vary is a central issue in evolutionary biology and ecology. The concept of adaptive radiation has attracted much interest, but is metaphorical and verbal in nature, making it difficult to quantitatively compare different evolutionary lineages or geographic regions. In addition, the causes of evolutionary stasis are relatively neglected. Here we review the central concepts in the evolutionary diversification literature and bring these together by proposing a general framework for estimating rates of diversification and quantifying their underlying dynamics, which can be applied across clades and regions and across spatial and temporal scales. Our framework describes the diversification rate (d) as a function of the abiotic environment (a), the biotic environment (b) and clade-specific phenotypes or traits (c); thus d~a,b,c. We refer to the four components (a-d) and their interactions collectively as the 'Evolutionary Arena'. We outline analytical approaches to this conceptual model that open up new avenues for research, and present a case study on conifers, for which we parameterise the general model. We also discuss three conceptual examples based on existing literature: the Lupinus radiation in the Andes in the context of emerging ecological opportunity and fluctuating fragmentation due to climatic oscillation; oceanic island radiations in the context of archipelago isolation and island formation and erosion; and biotically driven radiations of the Mediterranean orchid genus Ophrys. The results of the conifer case study are consistent with the long-standing scenario that large niches, lack of competition, and high-rates of niche evolution differentially promote diversification, but these results go further by quantifying the statistical interactions between variables representing these three drivers. The conceptual examples illustrate how using the synthetic Evolutionary Arena framework results in highlighting gaps in current knowledge, and thus help to identify future directions for research on evolutionary radiations. In this way, the Evolutionary Arena framework promotes a more general understanding of variation in evolutionary rates by making quantitative results comparable between case studies, thereby allowing new syntheses of evolutionary and ecological processes to emerge

    Potentiometrische und NMR-spektroskopische Untersuchungen der Eigenschaften von eta6^{6}-(p-Cymol)Ru(II) markierten Aminosäuren

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    Zielsetzung dieser Arbeit ist die systematische Untersuchung der Synthese und Eigenschaften der eta6^{6}-markierten Sandwichkomplexe des organometallischen eta6^{6}-(p-Cymol)Ru(II)-Fragments mit den Aminosäuren N-Acetyltyrosin, Trytophan, N-Acetyltryptophan, 5-Hydroxy-Tryptophan, der nichtproteinogenen Aminosäure L-Dopa, sowie den Aminen 5-Hydroxytryptamin (Serotonin) und Dopamin. Die Charakterisierung dieser Komplexe erfolgt mittels potentiometrischen und 1^{1}H-NMR-spektroskopischen Untersuchungen

    Using Markov Random Fields for Contour-Based Grouping

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    To overcome fragmentation of an initial contourbased segmentation and to organize contour segments into image primitives on a higher level of abstraction, regularities of the image data are exploited using ideas from the Gestalt psychology. First, groups are hypothesized within a hierarchy based on local evidence only, where the criteria are derived from a hand labelled training set. These hypotheses are subsequently judged in a global context using a Markov Random Field to derive a global interpretation. Examples of results for real data are given
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