DNA Extraction and Analysis of Bone Samples from the Orton Quarry Ossuary

The Orton Quarry site (36ER243) is a Late Prehistoric ossuary along the coast of Lake Erie in northwestern Pennsylvania. In March 1991, heavy-equipment operators accidentally exposed and destroyed approximately two-thirds of the original ossuary, leaving only the eastern third intact. Due to a personal interest in ossuaries an extensive literature search and personal communication with a one of the lead archeologists from the site was conducted. It was discovered that very little had been published on the site’s importance or its original inhabitants. One of the primary objectives of this project is to change that. By extracting and analyzing the mtDNA using the Dabney et al. (2013) protocol and the aDNA contamination avoidance protocols standard in the Snow lab we will obtain valuable data on the site’s genetic ancestry. Thus far the DNA from the first five samples have been isolated, and are being amplified for the first hypervariable region of the mtDNA mitogenome. The resulting sequences will be reviewed in Sequencher software. Any single nucleotide polymorphisms that are identified in comparison with the revised Cambridge Reference Sequence will then be compared with the Haplogrep software in order to confirm haplogroup assignment. The aspiration of this project is to analyse the data and compare the results to other ancient and modern DNA data from the Great Lakes region, using haplogroup and haplotype comparisons, as seen in Pfeiffer et al. (2014). Ultimately all of these results will then be written and presented on, adding to both the knowledge of the Orton Quarry Ossuary at well as the genetic data for the Great Lakes region

Protein conformational plasticity and complex ligand-binding kinetics explored by atomistic simulations and Markov models

Understanding the structural mechanisms of protein–ligand binding and their dependence on protein sequence and conformation is of fundamental importance for biomedical research. Here we investigate the interplay of conformational change and ligand-binding kinetics for the serine protease Trypsin and its competitive inhibitor Benzamidine with an extensive set of 150 μs molecular dynamics simulation data, analysed using a Markov state model. Seven metastable conformations with different binding pocket structures are found that interconvert at timescales of tens of microseconds. These conformations differ in their substrate-binding affinities and binding/dissociation rates. For each metastable state, corresponding solved structures of Trypsin mutants or similar serine proteases are contained in the protein data bank. Thus, our wild-type simulations explore a space of conformations that can be individually stabilized by adding ligands or making suitable changes in protein sequence. These findings provide direct evidence of conformational plasticity in receptors

Calcium-Release Channels in Paramecium. Genomic Expansion, Differential Positioning and Partial Transcriptional Elimination

The release of Ca2+ from internal stores is a major source of signal Ca2+ in almost all cell types. The internal Ca2+ pools are activated via two main families of intracellular Ca2+-release channels, the ryanodine and the inositol 1,4,5-trisphosphate (InsP3) receptors. Among multicellular organisms these channel types are ubiquitous, whereas in most unicellular eukaryotes the identification of orthologs is impaired probably due to evolutionary sequence divergence. However, the ciliated protozoan Paramecium allowed us to prognosticate six groups, with a total of 34 genes, encoding proteins with characteristics typical of InsP3 and ryanodine receptors by BLAST search of the Paramecium database. We here report that these Ca2+-release channels may display all or only some of the characteristics of canonical InsP3 and ryanodine receptors. In all cases, prediction methods indicate the presence of six trans-membrane regions in the C-terminal domains, thus corresponding to canonical InsP3 receptors, while a sequence homologous to the InsP3-binding domain is present only in some types. Only two types have been analyzed in detail previously. We now show, by using antibodies and eventually by green fluorescent protein labeling, that the members of all six groups localize to distinct organelles known to participate in vesicle trafficking and, thus, may provide Ca2+ for local membrane-membrane interactions. Whole genome duplication can explain radiation within the six groups. Comparative and evolutionary evaluation suggests derivation from a common ancestor of canonical InsP3 and ryanodine receptors. With one group we could ascertain, to our knowledge for the first time, aberrant splicing in one thoroughly analyzed Paramecium gene. This yields truncated forms and, thus, may indicate a way to pseudogene formation. No comparable analysis is available for any other, free-living or parasitic/pathogenic protozoan

Epidemiologic, Phenotypic, and Structural Characterization of Aminoglycoside-Resistance Gene aac(3)-IV

Aminoglycoside antibiotics are powerful bactericidal therapeutics that are often used in the treatment of critical Gram-negative systemic infections. The emergence and global spread of antibiotic resistance, however, has compromised the clinical utility of aminoglycosides to an extent similar to that found for all other antibiotic-drug classes. Apramycin, a drug candidate currently in clinical development, was suggested as a next-generation aminoglycoside antibiotic with minimal cross-resistance to all other standard-of-care aminoglycosides. Here, we analyzed 591,140 pathogen genomes deposited in the NCBI National Database of Antibiotic Resistant Organisms (NDARO) for annotations of apramycin-resistance genes, and compared them to the genotypic prevalence of carbapenem resistance and 16S-rRNA methyltransferase (RMTase) genes. The 3-N-acetyltransferase gene aac(3)-IV was found to be the only apramycin-resistance gene of clinical relevance, at an average prevalence of 0.7%, which was four-fold lower than that of RMTase genes. In the important subpopulation of carbapenemase-positive isolates, aac(3)-IV was nine-fold less prevalent than RMTase genes. The phenotypic profiling of selected clinical isolates and recombinant strains expressing the aac(3)-IV gene confirmed resistance to not only apramycin, but also gentamicin, tobramycin, and paromomycin. Probing the structure-activity relationship of such substrate promiscuity by site-directed mutagenesis of the aminoglycoside-binding pocket in the acetyltransferase AAC(3)-IV revealed the molecular contacts to His124, Glu185, and Asp187 to be equally critical in binding to apramycin and gentamicin, whereas Asp67 was found to be a discriminating contact. Our findings suggest that aminoglycoside cross-resistance to apramycin in clinical isolates is limited to the substrate promiscuity of a single gene, rendering apramycin best-in-class for the coverage of carbapenem- and aminoglycoside-resistant bacterial infections

PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models

Markov (state) models (MSMs) and related models of molecular kinetics have recently received a surge of interest as they can systematically reconcile simulation data from either a few long or many short simulations and allow us to analyze the essential metastable structures, thermodynamics, and kinetics of the molecular system under investigation. However, the estimation, validation, and analysis of such models is far from trivial and involves sophisticated and often numerically sensitive methods. In this work we present the opensource Python package PyEMMA (http://pyemma.org) that provides accurate and efficient algorithms for kinetic model construction. PyEMMA can read all common molecular dynamics data formats, helps in the selection of input features, provides easy access to dimension reduction algorithms such as principal component analysis (PCA) and time-lagged independent component analysis (TICA) and clustering algorithms such as k-means, and contains estimators for MSMs, hidden Markov models, and several other models. Systematic model validation and error calculation methods are provided. PyEMMA offers a wealth of analysis functions such that the user can conveniently compute molecular observables of interest. We have derived a systematic and accurate way to coarse-grain MSMs to few states and to illustrate the structures of the metastable states of the system. Plotting functions to produce a manuscript-ready presentation of the results are available. In this work, we demonstrate the features of the software and show new methodological concepts and results produced by PyEMMA

Crystal structure of the dynamin tetramer

The mechanochemical protein dynamin is the prototype of the dynamin superfamily of large GTPases, which shape and remodel membranes in diverse cellular processes. Dynamin forms predominantly tetramers in the cytosol, which oligomerize at the neck of clathrin-coated vesicles to mediate constriction and subsequent scission of the membrane. Previous studies have described the architecture of dynamin dimers, but the molecular determinants for dynamin assembly and its regulation have remained unclear. Here we present the crystal structure of the human dynamin tetramer in the nucleotide-free state. Combining structural data with mutational studies, oligomerization measurements and Markov state models of molecular dynamics simulations, we suggest a mechanism by which oligomerization of dynamin is linked to the release of intramolecular autoinhibitory interactions. We elucidate how mutations that interfere with tetramer formation and autoinhibition can lead to the congenital muscle disorders Charcot-Marie-Tooth neuropathy and centronuclear myopathy, respectively. Notably, the bent shape of the tetramer explains how dynamin assembles into a right-handed helical oligomer of defined diameter, which has direct implications for its function in membrane constriction

Scalar and vector Slepian functions, spherical signal estimation and spectral analysis

It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and, particularly for applications in the geosciences, for scalar and vectorial signals defined on the surface of a unit sphere.Comment: Submitted to the 2nd Edition of the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verlag. This is a slightly modified but expanded version of the paper arxiv:0909.5368 that appeared in the 1st Edition of the Handbook, when it was called: Slepian functions and their use in signal estimation and spectral analysi

Framework, principles and recommendations for utilising participatory methodologies in the co-creation and evaluation of public health interventions

Background: Due to the chronic disease burden on society, there is a need for preventive public health interventions to stimulate society towards a healthier lifestyle. To deal with the complex variability between individual lifestyles and settings, collaborating with end-users to develop interventions tailored to their unique circumstances has been suggested as a potential way to improve effectiveness and adherence. Co-creation of public health interventions using participatory methodologies has shown promise but lacks a framework to make this process systematic. The aim of this paper was to identify and set key principles and recommendations for systematically applying participatory methodologies to co-create and evaluate public health interventions. Methods: These principles and recommendations were derived using an iterative reflection process, combining key learning from published literature in addition to critical reflection on three case studies conducted by research groups in three European institutions, all of whom have expertise in co-creating public health interventions using different participatory methodologies. Results: Key principles and recommendations for using participatory methodologies in public health intervention co-creation are presented for the stages of: Planning (framing the aim of the study and identifying the appropriate sampling strategy); Conducting (defining the procedure, in addition to manifesting ownership); Evaluating (the process and the effectiveness) and Reporting (providing guidelines to report the findings). Three scaling models are proposed to demonstrate how to scale locally developed interventions to a population level. Conclusions: These recommendations aim to facilitate public health intervention co-creation and evaluation utilising participatory methodologies by ensuring the process is systematic and reproducible