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

Abstract 1363: Inhibition of the PI3K/AKT/mTOR Pathway Leads to Down-Regulation of c-Myc and Overcomes Resistance to ATRA in Acute Myeloid Leukemia.

Acute Promyelocytic Leukemia (APL) accounts for 5% of all cases of acute myeloid leukemia (AML). This disease is highly curable with all-trans-retinoic acid (ATRA) based therapy. In non-APL AML, ATRA has limited activity, and little is known about mechanisms of ATRA resistance. The apparent selective efficacy of ATRA in PML/RARα-associated APL poses an important question as to whether the presence of this fusion protein renders APL uniquely susceptible. Two compelling arguments can be made to counter this view. First, experiments in vitro show that ATRA effectively differentiates HL-60 cell lines, which lack the PML/RARα fusion protein. Second, clinical studies with ATRA in previously untreated older AML patients (excluding APL) have reported clinical activity. These observations confirm the therapeutic potential of ATRA beyond APL. In this context, our group has previously identified the lysine demethylase LSD-1, as a therapeutic target to re-sensitize leukemic blasts to ATRA. A clinical investigation of ATRA combined with LSD-1 inhibition is currently underway (NCT02273102). It is likely that other defects leading to ATRA resistance will be similarly amenable to pharmacologic manipulation. Defects in the proto-oncogene c-Myc have been widely implicated in the initiation and maintenance of AML. Over-expression of c-Myc in leukemic blasts enhances clonogenic survival and blocks ATRA induced differentiation. We hypothesized that down-regulation of c-Myc might increase the anti-leukemic effects of ATRA in AML. To date, c-Myc has been an evasive target for direct pharmacologic inhibition however, inhibitors of the PI3K/AKT/mTOR pathway have been shown to indirectly lower levels of c-Myc in leukemic blasts. In the current study, we show that the pro-differentiation effects of ATRA are markedly potentiated when combined with agents that target PI3K/AKT/mTOR signalling. In AML cell lines and primary patient samples, we observed additive pro-differentiation effects when ATRA was combined with inhibitors of PI3K (ZSTK474) and mTOR complex proteins (Torin-1, WYE-125132). However, when combined with the bromodomain inhibitor NVP-BEZ235, a dual inhibitor of PI3K and mTOR, we observed synergistic induction of CD11b by FACS analysis. Combination studies revealed loss of cell viability, cell cycle arrest in G1 phase, and impaired clonogenic survival, which was more prominent for ATRA combination treatments than with any agent used alone (Figure 1). To assess the role of c-Myc in mediating these effects, we measured c-Myc protein levels and PI3K/AKt/mTOR pathway markers at different time-points following treatment with ATRA alone and in combination with the inhibitors described above (Figure 2). Our findings suggest that ATRA alone quickly down-regulates c-Myc (within 6 hours) through transcriptional repression. Disruption of the PI3K/AKT/mTOR pathway further down-regulates c-Myc (within 3 hours) through destabilization and enhanced degradation. ATRA combined with NVP-BEZ235 produced maximal c-Myc suppression, and led to more cell kill than any other combination tested. Detailed analysis of changes in the transcriptome in MV-411 cells following treatment with ATRA and NVP-BEZ235 revealed that both agents act jointly on the regulation of the same biological pathways and processes, but regulate different sets of genes within these pathways. Updated mechanism based studies will be presented. In conclusion, suppression of c-Myc levels through disruption of PI3K/AKT/mTOR signalling augments the anti-leukemic effects of ATRA. These data support the clinical investigation of ATRA combined with rapalogs or bromodomain inhibitors

Mapping Hazard Zones, Rapid Warning Communication and Understanding Communities: Primary Ways to Mitigate Pyroclastic Flow Hazard

Co-auteur étrangerInternational audienc

MEMOTE for standardized genome-scale metabolic model testing

Supplementary information is available for this paper at https://doi.org/10.1038/s41587-020-0446-yReconstructing metabolic reaction networks enables the development of testable hypotheses of an organisms metabolism under different conditions1. State-of-the-art genome-scale metabolic models (GEMs) can include thousands of metabolites and reactions that are assigned to subcellular locations. Geneproteinreaction (GPR) rules and annotations using database information can add meta-information to GEMs. GEMs with metadata can be built using standard reconstruction protocols2, and guidelines have been put in place for tracking provenance and enabling interoperability, but a standardized means of quality control for GEMs is lacking3. Here we report a community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality.We acknowledge D. Dannaher and A. Lopez for their supporting work on the Angular parts of MEMOTE; resources and support from the DTU Computing Center; J. Cardoso, S. Gudmundsson, K. Jensen and D. Lappa for their feedback on conceptual details; and P. D. Karp and I. Thiele for critically reviewing the manuscript. We thank J. Daniel, T. Kristjánsdóttir, J. Saez-Saez, S. Sulheim, and P. Tubergen for being early adopters of MEMOTE and for providing written testimonials. J.O.V. received the Research Council of Norway grants 244164 (GenoSysFat), 248792 (DigiSal) and 248810 (Digital Life Norway); M.Z. received the Research Council of Norway grant 244164 (GenoSysFat); C.L. received funding from the Innovation Fund Denmark (project “Environmentally Friendly Protein Production (EFPro2)”); C.L., A.K., N. S., M.B., M.A., D.M., P.M, B.J.S., P.V., K.R.P. and M.H. received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 686070 (DD-DeCaF); B.G.O., F.T.B. and A.D. acknowledge funding from the US National Institutes of Health (NIH, grant number 2R01GM070923-13); A.D. was supported by infrastructural funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Cluster of Excellence EXC 2124 Controlling Microbes to Fight Infections; N.E.L. received funding from NIGMS R35 GM119850, Novo Nordisk Foundation NNF10CC1016517 and the Keck Foundation; A.R. received a Lilly Innovation Fellowship Award; B.G.-J. and J. Nogales received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no 686585 for the project LIAR, and the Spanish Ministry of Economy and Competitivity through the RobDcode grant (BIO2014-59528-JIN); L.M.B. has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 633962 for project P4SB; R.F. received funding from the US Department of Energy, Offices of Advanced Scientific Computing Research and the Biological and Environmental Research as part of the Scientific Discovery Through Advanced Computing program, grant DE-SC0010429; A.M., C.Z., S.L. and J. Nielsen received funding from The Knut and Alice Wallenberg Foundation, Advanced Computing program, grant #DE-SC0010429; S.K.’s work was in part supported by the German Federal Ministry of Education and Research (de.NBI partner project “ModSim” (FKZ: 031L104B)); E.K. and J.A.H.W. were supported by the German Federal Ministry of Education and Research (project “SysToxChip”, FKZ 031A303A); M.K. is supported by the Federal Ministry of Education and Research (BMBF, Germany) within the research network Systems Medicine of the Liver (LiSyM, grant number 031L0054); J.A.P. and G.L.M. acknowledge funding from US National Institutes of Health (T32-LM012416, R01-AT010253, R01-GM108501) and the Wagner Foundation; G.L.M. acknowledges funding from a Grand Challenges Exploration Phase I grant (OPP1211869) from the Bill & Melinda Gates Foundation; H.H. and R.S.M.S. received funding from the Biotechnology and Biological Sciences Research Council MultiMod (BB/N019482/1); H.U.K. and S.Y.L. received funding from the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (grants NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) from the Ministry of Science and ICT through the National Research Foundation (NRF) of Korea; H.U.K. received funding from the Bio & Medical Technology Development Program of the NRF, the Ministry of Science and ICT (NRF-2018M3A9H3020459); P.B., B.J.S., Z.K., B.O.P., C.L., M.B., N.S., M.H. and A.F. received funding through Novo Nordisk Foundation through the Center for Biosustainability at the Technical University of Denmark (NNF10CC1016517); D.-Y.L. received funding from the Next-Generation BioGreen 21 Program (SSAC, PJ01334605), Rural Development Administration, Republic of Korea; G.F. was supported by the RobustYeast within ERA net project via SystemsX.ch; V.H. received funding from the ETH Domain and Swiss National Science Foundation; M.P. acknowledges Oxford Brookes University; J.C.X. received support via European Research Council (666053) to W.F. Martin; B.E.E. acknowledges funding through the CSIRO-UQ Synthetic Biology Alliance; C.D. is supported by a Washington Research Foundation Distinguished Investigator Award. I.N. received funding from National Institutes of Health (NIH)/National Institute of General Medical Sciences (NIGMS) (grant P20GM125503).info:eu-repo/semantics/publishedVersio

Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing

An amendment to this paper has been published and can be accessed via a link at the top of the paper.(undefined)info:eu-repo/semantics/publishedVersio

Sensory Communication

Contains table of contents for Section 2, an introduction and reports on twelve research projects.National Institutes of Health Grant 5 R01 DC00117National Institutes of Health Contract 2 P01 DC00361National Institutes of Health Grant 5 R01 DC00126National Institutes of Health Grant R01-DC00270U.S. Air Force - Office of Scientific Research Contract AFOSR-90-0200National Institutes of Health Grant R29-DC00625U.S. Navy - Office of Naval Research Grant N00014-88-K-0604U.S. Navy - Office of Naval Research Grant N00014-91-J-1454U.S. Navy - Office of Naval Research Grant N00014-92-J-1814U.S. Navy - Naval Training Systems Center Contract N61339-93-M-1213U.S. Navy - Naval Training Systems Center Contract N61339-93-C-0055U.S. Navy - Naval Training Systems Center Contract N61339-93-C-0083U.S. Navy - Office of Naval Research Grant N00014-92-J-4005U.S. Navy - Office of Naval Research Grant N00014-93-1-119

Genomics, Exometabolomics, and Metabolic Probing Reveal Conserved Proteolytic Metabolism of Thermoflexus hugenholtzii and Three Candidate Species From China and Japan

Thermoflexus hugenholtzii JAD2 , the only cultured representative of the Chloroflexota order Thermoflexales, is abundant in Great Boiling Spring (GBS), NV, United States, and close relatives inhabit geothermal systems globally. However, no defined medium exists for T. hugenholtzii JAD2 and no single carbon source is known to support its growth, leaving key knowledge gaps in its metabolism and nutritional needs. Here, we report comparative genomic analysis of the draft genome of T. hugenholtzii JAD2 and eight closely related metagenome-assembled genomes (MAGs) from geothermal sites in China, Japan, and the United States, representing “Candidatus Thermoflexus japonica,” “Candidatus Thermoflexus tengchongensis,” and “Candidatus Thermoflexus sinensis.” Genomics was integrated with targeted exometabolomics and C metabolic probing of T. hugenholtzii. The Thermoflexus genomes each code for complete central carbon metabolic pathways and an unusually high abundance and diversity of peptidases, particularly Metallo- and Serine peptidase families, along with ABC transporters for peptides and some amino acids. The T. hugenholtzii JAD2 exometabolome provided evidence of extracellular proteolytic activity based on the accumulation of free amino acids. However, several neutral and polar amino acids appear not to be utilized, based on their accumulation in the medium and the lack of annotated transporters. Adenine and adenosine were scavenged, and thymine and nicotinic acid were released, suggesting interdependency with other organisms in situ. Metabolic probing of T. hugenholtzii JAD2 using C-labeled compounds provided evidence of oxidation of glucose, pyruvate, cysteine, and citrate, and functioning glycolytic, tricarboxylic acid (TCA), and oxidative pentose-phosphate pathways (PPPs). However, differential use of position-specific C-labeled compounds showed that glycolysis and the TCA cycle were uncoupled. Thus, despite the high abundance of Thermoflexus in sediments of some geothermal systems, they appear to be highly focused on chemoorganotrophy, particularly protein degradation, and may interact extensively with other microorganisms in situ. T T T 13 T T 13 1