Use of knowledge-based restraints in phenix.refine to improve macromolecular refinement at low resolution

Recent developments in PHENIX are reported that allow the use of reference-model torsion restraints, secondary-structure hydrogen-bond restraints and Ramachandran restraints for improved macromolecular refinement in phenix.refine at low resolution

Anchored enrichment dataset for true flies (order Diptera) reveals insights into the phylogeny of flower flies (family Syrphidae)

Background: Anchored hybrid enrichment is a form of next-generation sequencing that uses oligonucleotide probes to target conserved regions of the genome flanked by less conserved regions in order to acquire data useful for phylogenetic inference from a broad range of taxa. Once a probe kit is developed, anchored hybrid enrichment is superior to traditional PCR-based Sanger sequencing in terms of both the amount of genomic data that can be recovered and effective cost. Due to their incredibly diverse nature, importance as pollinators, and historical instability with regard to subfamilial and tribal classification, Syrphidae (flower flies or hoverflies) are an ideal candidate for anchored hybrid enrichment-based phylogenetics, especially since recent molecular phylogenies of the syrphids using only a few markers have resulted in highly unresolved topologies. Over 6200 syrphids are currently known and uncovering their phylogeny will help us to understand how these species have diversified, providing insight into an array of ecological processes, from the development of adult mimicry, the origin of adult migration, to pollination patterns and the evolution of larval resource utilization. Results: We present the first use of anchored hybrid enrichment in insect phylogenetics on a dataset containing 30 flower fly species from across all four subfamilies and 11 tribes out of 15. To produce a phylogenetic hypothesis, 559 loci were sampled to produce a final dataset containing 217,702 sites. We recovered a well resolved topology with bootstrap support values that were almost universally >95 %. The subfamily Eristalinae is recovered as paraphyletic, with the strongest support for this hypothesis to date. The ant predators in the Microdontinae are sister to all other syrphids. Syrphinae and Pipizinae are monophyletic and sister to each other. Larval predation on soft-bodied hemipterans evolved only once in this family. Conclusions: Anchored hybrid enrichment was successful in producing a robustly supported phylogenetic hypothesis for the syrphids. Subfamilial reconstruction is concordant with recent phylogenetic hypotheses, but with much higher support values. With the newly designed probe kit this analysis could be rapidly expanded with further sampling, opening the door to more comprehensive analyses targeting problem areas in syrphid phylogenetics and ecology.Peer reviewe

Automating crystallographic structure solution and refinement of protein-ligand complexes.

High-throughput drug-discovery and mechanistic studies often require the determination of multiple related crystal structures that only differ in the bound ligands, point mutations in the protein sequence and minor conformational changes. If performed manually, solution and refinement requires extensive repetition of the same tasks for each structure. To accelerate this process and minimize manual effort, a pipeline encompassing all stages of ligand building and refinement, starting from integrated and scaled diffraction intensities, has been implemented in Phenix. The resulting system is able to successfully solve and refine large collections of structures in parallel without extensive user intervention prior to the final stages of model completion and validation

Graphical tools for macromolecular crystallography in PHENIX.

A new Python-based graphical user interface for the PHENIX suite of crystallography software is described. This interface unifies the command-line programs and their graphical displays, simplifying the development of new interfaces and avoiding duplication of function. With careful design, graphical interfaces can be displayed automatically, instead of being manually constructed. The resulting package is easily maintained and extended as new programs are added or modified

Off-target capture data, endosymbiont genes and morphology reveal a relict lineage that is sister to all other singing cicadas

Phylogenetic asymmetry is common throughout the tree of life and results from contrasting patterns of speciation and extinction in the paired descendant lineages of ancestral nodes. On the depauperate side of a node, we find extant ´relict´ taxa that sit atop long, unbranched lineages. Here, we show that a tiny, pale green, inconspicuous and poorly known cicada in the genus Derotettix, endemic to degraded salt-plain habitats in arid regions of central Argentina, is a relict lineage that is sister to all other modern cicadas. Nuclear and mitochondrial phylogenies of cicadas inferred from probe-based genomic hybrid capture data of both target and non-target loci and a morphological cladogram support this hypothesis. We strengthen this conclusion with genomic data from one of the cicada nutritional bacterial endosymbionts, Sulcia, an ancient and obligate endosymbiont of the larger plant-sucking bugs (Auchenorrhyncha) and an important source of maternally inherited phylogenetic data. We establish Derotettiginae subfam. nov. as a new, monogeneric, fifth cicada subfamily, and compile existing and new data on the distribution, ecology and diet of Derotettix. Our consideration of the palaeoenvironmental literature and host-plant phylogenetics allows us to predict what might have led to the relict status of Derotettix over 100 Myr of habitat change in South America.Fil: Simon, Chris. University of Connecticut; Estados UnidosFil: Gordon, Eric R. L.. University of Connecticut; Estados UnidosFil: Moulds, M.S.. Australian Museum Research Institute; AustraliaFil: Cole, Jeffrey A.. Pasadena City College; Estados UnidosFil: Haji, Diler. University of Connecticut; Estados UnidosFil: Lemmon, Alan R.. Florida State University; Estados UnidosFil: Lemmon, Emily Moriarty. Florida State University; Estados UnidosFil: Kortyna, Michelle. Florida State University; Estados UnidosFil: Nazario, Katherine. University of Connecticut; Estados UnidosFil: Wade, Elizabeth J.. Curry College. Department of Natural Sciences and Mathematics; Estados Unidos. University of Connecticut; Estados UnidosFil: Meister, Russell C.. University of Connecticut; Estados UnidosFil: Goemans, Geert. University of Connecticut; Estados UnidosFil: Chiswell, Stephen M.. National Institute of Water and Atmospheric Research; Nueva ZelandaFil: Pessacq, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Centro de Investigación Esquel de Montaña y Estepa Patagónica. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigación Esquel de Montaña y Estepa Patagónica; ArgentinaFil: Veloso, Claudio. Universidad de Chile; ChileFil: McCutcheon, John P.. University of Montana; Estados UnidosFil: Lukasik, Piotr. University of Montana; Estados Unidos. Swedish Museum of Natural History. Department of Bioinformatics and Genetics; Sueci

phenix.model_vs_data: a high-level tool for the calculation of crystallographic model and data statistics

Application of phenix.model_vs_data to the contents of the Protein Data Bank shows that the vast majority of deposited structures can be automatically analyzed to reproduce the reported quality statistics. However, the small fraction of structures that elude automated re-analysis highlight areas where new software developments can help retain valuable information for future analysis

Financing U.S. Graduate Medical Education: A Policy Position Paper of the Alliance for Academic Internal Medicine and the American College of Physicians

In this position paper, the Alliance for Academic Internal Medicine and the American College of Physicians examine the state of graduate medical education (GME) financing in the United States and recent proposals to reform GME funding. They make a series of recommendations to reform the current funding system to better align GME with the needs of the nation's health care workforce. These recommendations include using Medicare GME funds to meet policy goals and to ensure an adequate supply of physicians, a proper specialty mix, and appropriate training sites; spreading the costs of financing GME across the health care system; evaluating the true cost of training a resident and establishing a single per-resident amount; increasing transparency and innovation; and ensuring that primary care residents receive training in well-functioning ambulatory settings that are financially supported for their training roles

Towards automated crystallographic structure refinement with phenix.refine

phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods

PHENIX: a comprehensive Python-based system for macromolecular structure solution.

Macromolecular X-ray crystallography is routinely applied to understand biological processes at a molecular level. However, significant time and effort are still required to solve and complete many of these structures because of the need for manual interpretation of complex numerical data using many software packages and the repeated use of interactive three-dimensional graphics. PHENIX has been developed to provide a comprehensive system for macromolecular crystallographic structure solution with an emphasis on the automation of all procedures. This has relied on the development of algorithms that minimize or eliminate subjective input, the development of algorithms that automate procedures that are traditionally performed by hand and, finally, the development of a framework that allows a tight integration between the algorithms