Search bioRxiv⌕ Search

Biology subjects

Meyer, S.

Publications and source records attributed to Meyer, S..

44 records · Page 3Linked to original sources

Feature-based Molecular Networking in the GNPS Analysis Environment

Molecular networking has become a key method used to visualize and annotate the chemical space in non-targeted mass spectrometry-based experiments. However, distinguishing isomeric compounds and quantitative interpretation are currently limited. Therefore, we created Feature-based Molecular Networking (FBMN) as a new analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure. FBMN leverages feature detection and alignment tools to enhance quantitative analyses and isomer distinction, including from ion-mobility spectrometry experiments, in molecular networks.

bioinformatics↗

Phylogeny, morphology and the role of hybridization as driving force of evolution in grass tribes Aveneae and Poeae (Poaceae)

To investigate the evolutionary diversification and morphological evolution of grass supertribe Poodae (subfam. Pooideae, Poaceae) we conducted a comprehensive molecular phylogenetic analysis including representatives from most of their accepted genera. We focused on generating a DNA sequence dataset of plastid matK gene-3trnK exon and trnL- trnF regions and nuclear ribosomal ITS1-5.8S gene-ITS2 and ETS that was taxonomically overlapping as completely as possible (altogether 257 species). The idea was to infer whether phylogenetic trees or certain clades based on plastid and nuclear DNA data correspond with each other or discord, revealing signatures of past hybridization. The datasets were analysed using maximum parsimony, maximum likelihood and Bayesian approaches. Instances of severe conflicts between the phylogenetic trees derived from both datasets, some of which have been noted earlier, unambiguously point to hybrid origin of several lineages (subtribes, groups of genera, sometimes genera) such as Phalaridinae, Scolochloinae, Sesleriinae, Torreyochloinae; Arctopoa, Castellia, Graphephorum, Hyalopodium, Lagurus, Macrobriza, Puccinellia plus Sclerochloa, Sesleria, Tricholemma, American Trisetum, etc. and presumably Airinae, Holcinae and Phleinae. Calamagrostis flavens appears to be an intergeneric hybrid between Agrostis and Calamagrostis. Most frequently there is good agreement of other regions of the trees, apart from intrinsic different phylogenetic resolution of the respective DNA markers. To explore the to date rather unclear morphological evolution of our study group a data matrix encompassing finally 188 characters was analysed for ancestral state reconstructions (ASR) using the tree from the combined molecular dataset as presumably best approximation to the species phylogeny. For 74 characters ASRs were feasible and yielded partly surprising results for the study group as a whole but also for some of their subdivisions. Considering taxonomy and classification it became evident, that many morphological characters show a very high degree of homoplasy and are seemingly able to change within comparatively short timespans in the evolution of our grasses. Most of the taxonomic units distinguished within our study group, e.g. as subtribes, are defined less by consistent morphological characters or character combinations and should be rather understood as clades revealed by molecular phylogenetic analysis. One reason for this extreme homoplasy concerning traditionally highly rated characters of inflorescences or spikelets and their components might be that they have little to do with pollination (always wind) or adaptation to pollinators as in other angiosperms but rather with dispersal and diaspores. Easily changing structure of spikelet disarticulation, of glume, lemma or awn characters might be advantageous in the rapid adaptation to different habitats and micro-habitats, which was evidently most successfully accomplished by these grasses. A partly revised classification of Poodae is presented, including a re-instatement of tribes Aveneae and Poeae s.str. Following a comparatively narrow delineation of preferably monophyletic subtribes, Antinoriinae, Avenulinae, Brizochloinae, Helictochloinae, Hypseochloinae are described as new. New genera are Arctohyalopoa and Hyalopodium. New combinations are Arctohyalopoa lanatiflora, A. lanatiflora subsp. ivanoviae, A. lanatiflora subsp. momica, Colpodium biebersteinianum, C. kochii, C. trichopodum, C. verticillatum, Deschampsia micrathera, Dupontia fulva, Festuca masafuerana, Hyalopodium araraticum, Paracolpodium baltistanicum, Parapholis cylindrica, P. xpauneroi. Festuca masatierrae is a new name.\n\nSupporting Information may be found online in the Supporting Information section at the end of the article.

plant biology↗

The fungal sesquiterpenoid pyrenophoric acid B uses the plant ABA biosynthetic pathway to inhibit seed germination.

HighlightThe fungus Pyrenophora semeniperda produces pyrenophoric acid B, a small molecule that exploits the plant ABA biosynthetic pathway to reduce seed germination, increasing its reproductive success.\n\nAbstractPyrenophoric acid (P-Acid), P-Acid B and P-Acid C are three phytotoxic sesquiterpenoids produced by the ascomycete seed pathogen Pyrenophora semeniperda, a fungus proposed as a mycoherbicide for biocontrol of cheatgrass, an extremely invasive weed. When tested in cheatgrass bioassays these metabolites were able to delay seed germination, with P-Acid B being the most active compound. Here, we have investigated the cross-kingdom activity of P-Acid B and its mode of action and found that it activates the ABA signaling pathway in order to inhibit seedling establishment. P-Acid B inhibits seedling establishment in wild-type Arabidopsis thaliana while several mutants affected in the early perception as well as in downstream ABA signaling components were insensitive to the fungal compound. However, in spite of structural similarities between ABA and P-Acid B, the latter is not able to activate the PYR/PYL family of ABA receptors. Instead, we have found that P-Acid B uses the ABA biosynthesis pathway at the level of alcohol dehydrogenase ABA2 to reduce seedling establishment. We propose that the fungus Pyrenophora semeniperda manipulates plant ABA biosynthesis as a strategy to reduce seed germination, increasing its ability to cause seed mortality and thereby increase its fitness through higher reproductive success.

plant biology↗

Bacterial genome architecture shapes global transcriptional regulation by DNA supercoiling

DNA supercoiling acts as a global transcriptional regulator in bacteria, that plays an important role in adapting their expression programme to environmental changes, but for which no quantitative or even qualitative regulatory model is available. Here, we focus on spatial supercoiling heterogeneities caused by the transcription process itself, which strongly contribute to this regulation mode. We propose a new mechanistic modeling of the transcription-supercoiling dynamical coupling along a genome, which allows simulating and quantitatively reproducing in vitro and in vivo transcription assays, and highlights the role of genes local orientation in their supercoiling sensitivity. Consistently with predictions, we show that chromosomal relaxation artificially induced by gyrase inhibitors selectively activates convergent genes in several enterobacteria, while conversely, an increase in DNA supercoiling naturally selected in a long-term evolution experiment with Escherichia coli favours divergent genes. Simulations show that these global expression responses to changes in DNA supercoiling result from fundamental mechanical constraints imposed by transcription, independently from more specific regulation of each promoter. These constraints underpin a significant and predictable contribution to the complex rules by which bacteria use DNA supercoiling as a global but fine-tuned transcriptional regulator.

microbiology↗

Neural competitive queuing of ordinal structure underlies skilled sequential action

The fluent retrieval and production of movement sequences is essential for a variety of daily activities such as speech, tool-use, musical and athletic performance, but the neural mechanisms underlying sequence planning remain elusive. Here, participants learned sequences of finger presses with different timings and different finger orders, and reproduced them in a magneto-encephalography (MEG) scanner. We classified the MEG patterns immediately preceding each press in the sequence, and examined their dynamics over the production of the whole sequence. Our results confirm a role for the competitive queuing of upcoming action representations in the production of learned motor sequences, extending previous computational and non-human primate recording studies to non-invasive measures in humans. In addition, we show that competitive queuing does not simply reflect specific motor actions, but representations of higher-level sequential order that generalise across different motor sequences. Finally, we show that the quality of competitive queuing predicts participants production accuracy, and originates from parahippocampal and cerebellar sources. These results suggest that the brain learns and produces multiple behavioural sequences by flexibly combining representations of specific actions with more abstract, parallel representations of sequential structure.

neuroscience↗

Quantifying the performance of MEG source reconstruction using resting state data

Resting state networks measured with magnetoencephalography (MEG) form transiently stable spatio-temporal patterns in the subsecond range, and therefore fluctuate more rapidly than previously appreciated. These states populate and interact across the whole brain, are simple to record, and possess the same dynamic structure of task related changes. They therefore provide a generic, heterogeneous, and plentiful functional substrate against which to test different MEG recording and reconstruction approaches. Here we validate a non-invasive method for quantifying the resolution of different inversion assumptions under different recording regimes (with and without head-casts) based on resting state MEG. Spatio-temporally partitioning of data into self-similar periods confirmed a rich and rapidly dynamic temporal structure with a small number of regularly reoccurring states. To test the anatomical precision that could be resolved through these transient states we then inverted these data onto libraries of systematically distorted, subject specific, cortical meshes and compared the quality of the fit using Cross Validation and a Free Energy metric. This revealed which inversion scheme was able to best support the least distorted (most accurate) anatomical models. Both datasets showed an increase in model fit as anatomical models moved towards the true cortical surface. In the head-cast MEG data, the Empirical Bayesian Beamformer (EBB) algorithm showed the best mean anatomical discrimination (3.7 mm) compared with Minimum Norm / LORETA (6.0 mm) and Multiple Sparse priors (9.4 mm). This pattern was replicated in the second (conventional dataset) although with a marginally poorer prediction of the missing (cross-validated) data. Our findings suggest that the abundant resting state data now commonly available could be used to refine and validate MEG source reconstruction methods or recording paradigms.

neuroscience↗

Characterizing The Structure-Function Relationship Of A Naturally-Occurring RNA Thermometer

A wide number of bacteria have been found to govern virulence and heat shock responses using temperature-sensing RNAs known as RNA thermometers. A prime example is the agsA thermometer known to regulate the production of the AgsA heat shock protein in Salmonella enterica using a \"fourU\" structural motif. Using the SHAPE-Seq RNA structure-probing method in vivo and in vitro, we found that the regulator functions by a subtle shift in equilibrium RNA structure populations that lead to a partial melting of the helix containing the ribosome binding site. We also demonstrate that ribosome binding to the agsA mRNA causes changes to the thermometer structure that appear to facilitate thermometer helix unwinding. These results demonstrate how subtle RNA structural changes can govern gene expression and illuminate the function of an important bacterial regulatory motif.

biochemistry↗

Probabilistic forecasting in infectious disease epidemiology: The thirteenth Armitage lecture

Routine surveillance of notifiable infectious diseases gives rise to daily or weekly counts of reported cases stratified by region and age group. From a public health perspective, forecasts of infectious disease spread are of central importance. We argue that such forecasts need to properly incorporate the attached uncertainty, so should be probabilistic in nature. However, forecasts also need to take into account temporal dependencies inherent to communicable diseases, spatial dynamics through human travel, and social contact patterns between age groups. We describe a multivariate time series model for weekly surveillance counts on norovirus gastroenteritis from the 12 city districts of Berlin, in six age groups, from week 2011/27 to week 2015/26. The following year (2015/27 to 2016/26) is used to assess the quality of the predictions. Probabilistic forecasts of the total number of cases can be derived through Monte Carlo simulation, but first and second moments are also available analytically. Final size forecasts as well as multivariate forecasts of the total number of cases by age group, by district, and by week are compared across different models of varying complexity. This leads to a more general discussion of issues regarding modelling, prediction and evaluation of public health surveillance data.

epidemiology↗