A hyperpromiscuous antitoxin protein domain for the neutralization of diverse toxin domains

Toxin–antitoxin (TA) gene pairs are ubiquitous in microbial chromosomal genomes and plasmids as well as temperate bacteriophages. They act as regulatory switches, with the toxin limiting the growth of bacteria and archaea by compromising diverse essential cellular targets and the antitoxin counteracting the toxic effect. To uncover previously uncharted TA diversity across microbes and bacteriophages, we analyzed the conservation of genomic neighborhoods using our computational tool FlaGs (for flanking genes), which allows high-throughput detection of TA-like operons. Focusing on the widespread but poorly experimentally characterized antitoxin domain DUF4065, our in silico analyses indicated that DUF4065-containing proteins serve as broadly distributed antitoxin components in putative TA-like operons with dozens of different toxic domains with multiple different folds. Given the versatility of DUF4065, we have named the domain Panacea (and proteins containing the domain, PanA) after the Greek goddess of universal remedy. We have experimentally validated nine PanA-neutralized TA pairs. While the majority of validated PanA-neutralized toxins act as translation inhibitors or membrane disruptors, a putative nucleotide cyclase toxin from a Burkholderia prophage compromises transcription and translation as well as inducing RelA-dependent accumulation of the nucleotide alarmone (p)ppGpp. We find that Panacea-containing antitoxins form a complex with their diverse cognate toxins, characteristic of the direct neutralization mechanisms employed by Type II TA systems. Finally, through directed evolution, we have selected PanA variants that can neutralize noncognate TA toxins, thus experimentally demonstrating the evolutionary plasticity of this hyperpromiscuous antitoxin domain

Genome-wide association study of germline variants and breast cancer-specific mortality

BACKGROUND: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. METHODS: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Observations of strong ion-ion correlations in dense plasmas

Using simultaneous spectrally, angularly, and temporally resolved x-ray scattering, we measure the pronounced ion-ion correlation peak in a strongly coupled plasma. Laser-driven shock-compressed aluminum at similar to 3x solid density is probed with high-energy photons at 17.9 keV created by molybdenum He-alpha emission in a laser-driven plasma source. The measured elastic scattering feature shows a well-pronounced correlation peak at a wave vector of k = 4 angstrom(-1). The magnitude of this correlation peak cannot be described by standard plasma theories employing a linear screened Coulomb potential. Advanced models, including a strong short-range repulsion due to the inner structure of the aluminum ions are however in good agreement with the scattering data. These studies have demonstrated a new highly accurate diagnostic technique to directly measure the state of compression and the ion-ion correlations. We have since applied this new method in single-shot wave-number resolved S(k) measurements to characterize the physical properties of dense plasmas

Vor-Ort-Nachweis bioterroristisch relevanter Agenzien

In Europa besteht eine abstrakte Gefährdungslage nicht nur für konventionell durchgeführte Anschläge mit Waffen oder Sprengstoffen, sondern auch für Anschläge, bei denen biologische Agenzien eingesetzt werden. Zur Gefahrenabwehr werden daher kontinuierlich schnelle und zuverlässige Nachweisverfahren entwickelt und erprobt. Für die Anwendung im stationären Labor wurde für bioterroristisch relevante Agenzien bereits ein umfassendes Spektrum an Nachweismethoden etabliert. Für eine Vor-Ort-Detektion aus Umweltproben werden darüber hinaus von den Einsatzkräften zunehmend vergleichbar verlässliche mobile Nachweissysteme zur ersten Lagebewertung gewünscht. Basierend auf den Funktionsprinzipien können generische, immunologische und nukleinsäurebasierte Vor-Ort-Detektionsverfahren unterschieden werden. Diese sollten einfach durchzuführen, schnell, sensitiv und spezifisch sein. Kommerziell erhältliche Vor-Ort-Detektionssysteme haben systembedingt häufig eine eingeschränkte Sensitivität und sind zumeist nicht von unabhängiger Seite validiert. Darüber hinaus stellt die Vielfalt an potenziell nachzuweisenden Agenzien in komplexen Umweltproben eine besondere Herausforderung dar. Daher ist detailliertes Wissen über Einsatzbereiche und Limitation der verwendeten Testsysteme zwingend erforderlich, um erhaltene Ergebnisse zielführend bewerten und Handlungsempfehlungen ableiten zu können. Ziel dieses Artikels ist es, einen Überblick über die Messprinzipien von Vor-Ort-Detektionssystemen für bioterroristisch relevante Viren, Bakterien und Toxine sowie Vor- und Nachteile der Testsysteme zu geben. Trotz vielversprechender Entwicklungen sind derzeit erhältliche Testsysteme zur Vor-Ort-Detektion noch beschränkt aussagekräftig. Deshalb sind Expertenlabore zur gesicherten Befundung von Umweltproben weiterhin einzubeziehen

Genome-wide association study of germline variants and breast cancer-specific mortality

Abstract Background: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. Methods: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP). Results: We did not find any variant associated with breast cancer-specific mortality at P &lt; 5 × 10−8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10−7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84–0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10−7, HR = 1.27, 95% CI = 1.16–1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster. Conclusions: We uncovered germline variants on chromosome 7 at BFDP &lt; 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease