BALBES: a molecular-replacement pipeline

The fully automated pipeline, BALBES, integrates a redesigned hierarchical database of protein structures with their domains and multimeric organization, and solves molecular-replacement problems using only input X-ray and sequence data

Cytoplasmic Compartmentalization of the Fetal piRNA Pathway in Mice

Derepression of transposable elements (TEs) in the course of epigenetic reprogramming of the mouse embryonic germline necessitates the existence of a robust defense that is comprised of PIWI/piRNA pathway and de novo DNA methylation machinery. To gain further insight into biogenesis and function of piRNAs, we studied the intracellular localization of piRNA pathway components and used the combination of genetic, molecular, and cell biological approaches to examine the performance of the piRNA pathway in germ cells of mice lacking Maelstrom (MAEL), an evolutionarily conserved protein implicated in transposon silencing in fruit flies and mice. Here we show that principal components of the fetal piRNA pathway, MILI and MIWI2 proteins, localize to two distinct types of germinal cytoplasmic granules and exhibit differential association with components of the mRNA degradation/translational repression machinery. The first type of granules, pi-bodies, contains the MILI-TDRD1 module of the piRNA pathway and is likely equivalent to the enigmatic “cementing material” first described in electron micrographs of rat gonocytes over 35 years ago. The second type of granules, piP-bodies, harbors the MIWI2-TDRD9-MAEL module of the piRNA pathway and signature components of P-bodies, GW182, DCP1a, DDX6/p54, and XRN1 proteins. piP-bodies are found predominantly in the proximity of pi-bodies and the two frequently share mouse VASA homolog (MVH) protein, an RNA helicase. In Mael-mutant gonocytes, MIWI2, TDRD9, and MVH are lost from piP-bodies, whereas no effects on pi-body composition are observed. Further analysis revealed that MAEL appears to specifically facilitate MIWI2-dependent aspects of the piRNA pathway including biogenesis of secondary piRNAs, de novo DNA methylation, and efficient downregulation of TEs. Cumulatively, our data reveal elaborate cytoplasmic compartmentalization of the fetal piRNA pathway that relies on MAEL function

ARP/wARP and molecular replacement: the next generation

A systematic test shows how ARP/wARP deals with automated model building for structures that have been solved by molecular replacement. A description of protocols in the flex-wARP control system and studies of two specific cases are also presented

Repeat-associated siRNAs cause chromatin silencing of retrotransposons in the Drosophila melanogaster germline

Silencing of genomic repeats, including transposable elements, in Drosophila melanogaster is mediated by repeat-associated short interfering RNAs (rasiRNAs) interacting with proteins of the Piwi subfamily. rasiRNA-based silencing is thought to be mechanistically distinct from both the RNA interference and microRNA pathways. We show that the amount of rasiRNAs of a wide range of retroelements is drastically reduced in ovaries and testes of flies carrying a mutation in the spn-E gene. To address the mechanism of rasiRNA-dependent silencing of retrotransposons, we monitored their chromatin state in ovaries and somatic tissues. This revealed that the spn-E mutation causes chromatin opening of retroelements in ovaries, resulting in an increase in histone H3 K4 dimethylation and a decrease in histone H3 K9 di/trimethylation. The strongest chromatin changes have been detected for telomeric HeT-A elements that correlates with the most dramatic increase of their transcript level, compared to other mobile elements. The spn-E mutation also causes depletion of HP1 content in the chromatin of transposable elements, especially along HeT-A arrays. We also show that mutations in the genes controlling the rasiRNA pathway cause no derepression of the same retrotransposons in somatic tissues. Our results provide evidence that germinal Piwi-associated short RNAs induce chromatin modifications of their targets

Overview of the CCP4 suite and current developments.

The CCP4 (Collaborative Computational Project, Number 4) software suite is a collection of programs and associated data and software libraries which can be used for macromolecular structure determination by X-ray crystallography. The suite is designed to be flexible, allowing users a number of methods of achieving their aims. The programs are from a wide variety of sources but are connected by a common infrastructure provided by standard file formats, data objects and graphical interfaces. Structure solution by macromolecular crystallography is becoming increasingly automated and the CCP4 suite includes several automation pipelines. After giving a brief description of the evolution of CCP4 over the last 30 years, an overview of the current suite is given. While detailed descriptions are given in the accompanying articles, here it is shown how the individual programs contribute to a complete software package

The CCP4 suite: integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.Jon Agirre is a Royal Society University Research Fellow (UF160039 and URF\R\221006). Mihaela Atanasova is funded by the UK Engineering and Physical Sciences Research Council (EPSRC; EP/R513386/1). Haroldas Bagdonas is funded by The Royal Society (RGF/R1/181006). Jose´ Javier Burgos-Ma´rmol and Daniel J. Rigden are supported by the BBSRC (BB/S007105/1). Robbie P. Joosten is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 871037 (iNEXTDiscovery) and by CCP4. This work was supported by the Medical Research Council as part of United Kingdom Research and Innovation, also known as UK Research and Innovation: MRC file reference No. MC_UP_A025_1012 to Garib N. Murshudov, which also funded Keitaro Yamashita, Paul Emsley and Fei Long. Robert A. Nicholls is funded by the BBSRC (BB/S007083/1). Soon Wen Hoh is funded by the BBSRC (BB/T012935/1). Kevin D. Cowtan and Paul S. Bond are funded in part by the BBSRC (BB/S005099/1). John Berrisford and Sameer Velankar thank the European Molecular Biology Laboratory–European Bioinformatics Institute, who supported this work. Andrea Thorn was supported in the development of AUSPEX by the German Federal Ministry of Education and Research (05K19WWA and 05K22GU5) and by Deutsche Forschungsgemeinschaft (TH2135/2-1). Petr Kolenko and Martin Maly´ are funded by the MEYS CR (CZ.02.1.01/0.0/0.0/16_019/0000778). Martin Maly´ is funded by the Czech Academy of Sciences (86652036) and CCP4/STFC (521862101). Anastassis Perrakis acknowledges funding from iNEXT (grant No. 653706), iNEXT-Discovery (grant No. 871037), West-Life (grant No. 675858) and EOSC-Life (grant No. 824087) funded by the Horizon 2020 program of the European Commission. Robbie P. Joosten has been the recipient of a Veni grant (722.011.011) and a Vidi grant (723.013.003) from the Netherlands Organization for Scientific Research (NWO). Maarten L. Hekkelman, Robbie P. Joosten and Anastassis Perrakis thank the Research High Performance Computing facility of the Netherlands Cancer Institute for providing and maintaining computation resources and acknowledge the institutional grant from the Dutch Cancer Society and the Dutch Ministry of Health, Welfare and Sport. Tarik R. Drevon is funded by the BBSRC (BB/S007040/1). Randy J. Read is supported by a Principal Research Fellowship from the Wellcome Trust (grant 209407/Z/17/Z). Atlanta G. Cook is supported by a Wellcome Trust SRF (200898) and a Wellcome Centre for Cell Biology core grant (203149). Isabel Uso´n acknowledges support from STFC-UK/CCP4: ‘Agreement for the integration of methods into the CCP4 software distribution, ARCIMBOLDO_LOW’ and Spanish MICINN/AEI/FEDER/UE (PID2021-128751NB-I00). Pavol Skubak and Navraj Pannu were funded by the NWO Applied Sciences and Engineering Domain and CCP4 (grant Nos. 13337 and 16219). Bernhard Lohkamp was supported by the Ro¨ntgen A˚ ngstro¨m Cluster (grant 349-2013-597). Nicholas Pearce is currently funded by the SciLifeLab and Wallenberg Data Driven Life Science Program (grant KAW 2020.0239) and has previously been funded by a Veni Fellowship (VI.Veni.192.143) from the Dutch Research Council (NWO), a Long-term EMBO fellowship (ALTF 609-2017) and EPSRC grant EP/G037280/1. David M. Lawson received funding from BBSRC Institute Strategic Programme Grants (BB/P012523/1 and BB/P012574/1). Lucrezia Catapano is the recipient of an STFC/CCP4-funded PhD studentship (Agreement No: 7920 S2 2020 007).Peer reviewe

Parental breeding age effects on descendants' longevity interact over 2 generations in matrilines and patrilines

Individuals within populations vary enormously in mortality risk and longevity, but the causes of this variation remain poorly understood. A potentially important and phylogenetically widespread source of such variation is maternal age at breeding, which typically has negative effects on offspring longevity. Here, we show that paternal age can affect offspring longevity as strongly as maternal age does and that breeding age effects can interact over 2 generations in both matrilines and patrilines. We manipulated maternal and paternal ages at breeding over 2 generations in the neriid fly Telostylinus angusticollis. To determine whether breeding age effects can be modulated by the environment, we also manipulated larval diet and male competitive environment in the first generation. We found separate and interactive effects of parental and grand-parental ages at breeding on descendants' mortality rate and life span in both matrilines and patrilines. These breeding age effects were not modulated by grand-parental larval diet quality or competitive environment. Our findings suggest that variation in maternal and paternal ages at breeding could contribute substantially to intrapopulation variation in mortality and longevity

The CCP4 suite : integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world