Mapping the Space of Genomic Signatures

We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thousands of complete mitochondrial genomes. An "image distance" is computed for each pair of graphical representations of DNA sequences, and the distances are visualized as a Molecular Distance Map: Each point on the map represents a DNA sequence, and the spatial proximity between any two points reflects the degree of structural similarity between the corresponding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a genomic signature. Consequently, Molecular Distance Maps could inform species identification, taxonomic classifications and, to a certain extent, evolutionary history. The image distance employed, Structural Dissimilarity Index (DSSIM), implicitly compares the occurrences of oligomers of length up to $k$ (herein $k=9$) in DNA sequences. We computed DSSIM distances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Dimensional Scaling (MDS) to obtain Molecular Distance Maps that visually display the sequence relatedness in various subsets, at different taxonomic levels. This general-purpose method does not require DNA sequence homology and can thus be used to compare similar or vastly different DNA sequences, genomic or computer-generated, of the same or different lengths. We illustrate potential uses of this approach by applying it to several taxonomic subsets: phylum Vertebrata, (super)kingdom Protista, classes Amphibia-Insecta-Mammalia, class Amphibia, and order Primates. This analysis of an extensive dataset confirms that the oligomer composition of full mtDNA sequences can be a source of taxonomic information.Comment: 14 pages, 7 figures. arXiv admin note: substantial text overlap with arXiv:1307.375

HARMONIA: strategy of an integrated resilience assessment platform (IRAP) with available tools and geospatial services

The huge amount of the available data nowadays has raised some major challenges which are related to the storage, fusion, structure, streaming and processing of these data. In this paper, we present the development of a holistic framework, entitled HARMONIA, that encompasses State-of-The-Art solutions for the emerging issues related to Climate Change, natural and/or man-made hazards and urban/peri-urban risks. The Horizon 2020 HARMONIA project is developing an Integrated Resilience Assessment Platform (IRAP) which plans to provide targeted services for different groups of end-users. In particular, it will actively support urban decision-makers in strategic decisions and planning and citizens in facing daily effects and risks of Climate Change. Additionally, the platform will be a place to interconnect cities which end up facing similar Climate Change effects. HARMONIA IRAP leverages cuttingedge technologies (i.e., explainable Artificial Intelligence, Data Mining, multi-criteria analysis, dynamic programming) and services (ie., Virtual Machines, Containers) in order to provide solutions considering the complexity and diversity of extreme earth and non-earth data. In addition, this platform includes a Decision Support System providing early-warning feedback and recommendations to the end-users. In this way the HARMONIA IRAP design tends to address these challenges by offering the corresponding dynamic, scalable and robust mechanisms with the aim to provide useful integrated tools for the related users. Datacubes architecture, which is a major part of the IRAP, offers the opportunity to investigate more sophisticated correlations among the data and provide a more tangible representation of the extracted information

Predicting the Fission Yeast Protein Interaction Network

A systems-level understanding of biological processes and information flow requires the mapping of cellular component interactions, among which protein–protein interactions are particularly important. Fission yeast (Schizosaccharomyces pombe) is a valuable model organism for which no systematic protein-interaction data are available. We exploited gene and protein properties, global genome regulation datasets, and conservation of interactions between budding and fission yeast to predict fission yeast protein interactions in silico. We have extensively tested our method in three ways: first, by predicting with 70–80% accuracy a selected high-confidence test set; second, by recapitulating interactions between members of the well-characterized SAGA co-activator complex; and third, by verifying predicted interactions of the Cbf11 transcription factor using mass spectrometry of TAP-purified protein complexes. Given the importance of the pathway in cell physiology and human disease, we explore the predicted sub-networks centered on the Tor1/2 kinases. Moreover, we predict the histidine kinases Mak1/2/3 to be vital hubs in the fission yeast stress response network, and we suggest interactors of argonaute 1, the principal component of the siRNA-mediated gene silencing pathway, lost in budding yeast but preserved in S. pombe. Of the new high-quality interactions that were discovered after we started this work, 73% were found in our predictions. Even though any predicted interactome is imperfect, the protein network presented here can provide a valuable basis to explore biological processes and to guide wet-lab experiments in fission yeast and beyond. Our predicted protein interactions are freely available through PInt, an online resource on our website (www.bahlerlab.info/PInt)

Php4 Is a Key Player for Iron Economy in Meiotic and Sporulating Cells

Meiosis is essential for sexually reproducing organisms, including the fission yeast Schizosaccharomyces pombe. In meiosis, chromosomes replicate once in a diploid precursor cell (zygote), and then segregate twice to generate four haploid meiotic products, named spores in yeast. In S. pombe, Php4 is responsible for the transcriptional repression capability of the heteromeric CCAAT-binding factor to negatively regulate genes encoding iron-using proteins under low-iron conditions. Here, we show that the CCAAT-regulatory subunit Php4 is required for normal progression of meiosis under iron-limiting conditions. Cells lacking Php4 exhibit a meiotic arrest at metaphase I. Microscopic analyses of cells expressing functional GFP-Php4 show that it colocalizes with chromosomal material at every stage of meiosis under low concentrations of iron. In contrast, GFP-Php4 fluorescence signal is lost when cells undergo meiosis under iron-replete conditions. Global gene expression analysis of meiotic cells using DNA microarrays identified 137 genes that are regulated in an iron- and Php4-dependent manner. Among them, 18 genes are expressed exclusively during meiosis and constitute new putative Php4 target genes, which include hry1+ and mug14+. Further analysis validates that Php4 is required for maximal and timely repression of hry1+ and mug14+ genes. Using a chromatin immunoprecipitation approach, we show that Php4 specifically associates with hry1+ and mug14+ promoters in vivo. Taken together, the results reveal that in iron-starved meiotic cells, Php4 is essential for completion of the meiotic program since it participates in global gene expression reprogramming to optimize the use of limited available iron

In vivo Simulation-Based Learning for Undergraduate Medical Students: Teaching and Assessment.

An increasing emphasis on simulation has become evident in the last three decades following fundamental shifts in the medical profession. Simulation-based learning (SBL) is a wide term that encompasses several means for imitating a skill, attitude, or procedure to train personnel in a safe and adaptive environment. A classic example has been the use of live animal tissue, named in vivo SBL. We aimed to review all published evidence on in vivo SBL for undergraduate medical students; this includes both teaching concepts as well as focused assessment of students on those concepts. We performed a systematic review of published evidence on MEDLINE. We also incorporated evidence from a series of systematic reviews (eviCORE) focused on undergraduate education which have been outputs from our dedicated research network (eMERG). In vivo SBL has been shown to be valuable at undergraduate level and should be considered as a potential educational tool. Strict adherence to 3R (Reduce, Refine, Replace) principles in order to reduce animal tissue usage, should always be the basis of any curriculum. In vivo SBL could potentially grant an extra mile towards medical students' inspiration and aspiration to become safe surgeons; however, it should be optimised and supported by a well-designed curriculum which enhances learning via multi-level fidelity SBL

Increased fidelity of protein synthesis extends lifespan

Loss of proteostasis is a fundamental process driving aging. Proteostasis is affected by the accuracy of translation, yet the physiological consequence of having fewer protein synthesis errors during multi-cellular organismal aging is poorly understood. Our phylogenetic analysis of RPS23, a key protein in the ribosomal decoding center, uncovered a lysine residue almost universally conserved across all domains of life, which is replaced by an arginine in a small number of hyperthermophilic archaea. When introduced into eukaryotic RPS23 homologs, this mutation leads to accurate translation, as well as heat shock resistance and longer life, in yeast, worms, and flies. Furthermore, we show that anti-aging drugs such as rapamycin, Torin1, and trametinib reduce translation errors, and that rapamycin extends further organismal longevity in RPS23 hyperaccuracy mutants. This implies a unified mode of action for diverse pharmacological anti-aging therapies. These findings pave the way for identifying novel translation accuracy interventions to improve aging

Adaptive strong-field control of chemical dynamics guided by three-dimensional momentum imaging.

Shaping ultrafast laser pulses using adaptive feedback can manipulate dynamics in molecular systems, but extracting information from the optimized pulse remains difficult. Experimental time constraints often limit feedback to a single observable, complicating efforts to decipher the underlying mechanisms and parameterize the search process. Here we show, using two strong-field examples, that by rapidly inverting velocity map images of ions to recover the three-dimensional photofragment momentum distribution and incorporating that feedback into the control loop, the specificity of the control objective is markedly increased. First, the complex angular distribution of fragment ions from the nω+C2D4→C2D3++D interaction is manipulated. Second, isomerization of acetylene (nω+C2H2→C2H22+→CH2++C+) is controlled via a barrier-suppression mechanism, a result that is validated by model calculations. Collectively, these experiments comprise a significant advance towards the fundamental goal of actively guiding population to a specified quantum state of a molecule

LaSSO, a strategy for genome-wide mapping of intronic lariats and branch points using RNA-seq

Both canonical and alternative splicing of RNAs are governed by intronic sequence elements and produce transient lariat structures fastened by branch points within introns. To map precisely the location of branch points on a genomic scale, we developed LaSSO (Lariat Sequence Site Origin), a data-driven algorithm which utilizes RNA-seq data. Using fission yeast cells lacking the debranching enzyme Dbr1, LaSSO not only accurately identified canonical splicing events, but also pinpointed novel, but rare, exon-skipping events, which may reflect aberrantly spliced transcripts. Compromised intron turnover perturbed gene regulation at multiple levels, including splicing and protein translation. Notably, Dbr1 function was also critical for the expression of mitochondrial genes and for the processing of self-spliced mitochondrial introns. LaSSO showed better sensitivity and accuracy than algorithms used for computational branch-point prediction or for empirical branch-point determination. Even when applied to a human data set acquired in the presence of debranching activity, LaSSO identified both canonical and exon-skipping branch points. LaSSO thus provides an effective approach for defining high-resolution maps of branch-site sequences and intronic elements on a genomic scale. LaSSO should be useful to validate introns and uncover branch-point sequences in any eukaryote, and it could be integrated into RNA-seq pipelines