In situ structure of an intact lipopolysaccharide-bound bacterial surface layer

Most bacterial and all archaeal cells are encapsulated by a paracrystalline, protective, and cell-shape-determining proteinaceous surface layer (S-layer). On Gram-negative bacteria, S-layers are anchored to cells via lipopolysaccharide. Here, we report an electron cryomicroscopy structure of the Caulobacter crescentus S-layer bound to the O-antigen of lipopolysaccharide. Using native mass spectrometry and molecular dynamics simulations, we deduce the length of the O-antigen on cells and show how lipopolysaccharide binding and S-layer assembly is regulated by calcium. Finally, we present a near-atomic resolution in situ structure of the complete S-layer using cellular electron cryotomography, showing S-layer arrangement at the tip of the O-antigen. A complete atomic structure of the S-layer shows the power of cellular tomography for in situ structural biology and sheds light on a very abundant class of self-assembling molecules with important roles in prokaryotic physiology with marked potential for synthetic biology and surface-display applications

A Bayesian approach to single-particle electron cryo-tomography in RELION-4.0

We present a new approach for macromolecular structure determination from multiple particles in electron cryo-tomography (cryo-ET) data sets. Whereas existing subtomogram averaging approaches are based on 3D data models, we propose to optimise a regularised likelihood target that approximates a function of the 2D experimental images. In addition, analogous to Bayesian polishing and contrast transfer function (CTF) refinement in single-particle analysis, we describe the approaches that exploit the increased signal-to-noise ratio in the averaged structure to optimise tilt-series alignments, beam-induced motions of the particles throughout the tilt-series acquisition, defoci of the individual particles, as well as higher-order optical aberrations of the microscope. Implementation of our approaches in the open-source software package RELION aims to facilitate their general use, particularly for those researchers who are already familiar with its single-particle analysis tools. We illustrate for three applications that our approaches allow structure determination from cryo-ET data to resolutions sufficient for de novo atomic modelling.This work was funded by the UK Research and Innovation (UKRI) Medical Research Council (MC_UP_A025_1013 to SHWS; and MC_UP_1201/16 to JAGB), the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (ERC-CoG-2014, grant 648432, MEMBRANEFUSION to JAGB and ERC StG-2019, grant 852915 CRYTOCOP to GZ); the Swiss National Science Foundation (grant 205321_179041/1 to DC-D), the Max Planck Society (to JAGB) and the UKRI Biotechnology and Biological Sciences Research Council (grant BB/T002670/1 to GZ). TAMB is a recipient of a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society (202231/Z/16/Z). JZ was partially funded by the European Union’s Horizon 2020 research and innovation program (ERC-ADG-2015, grant 692726, GlobalBioIm to Michael Unser)

The importance of biofilm formation for cultivation of a Micrarchaeon and its interactions with its Thermoplasmatales host

Micrarchaeota is a distinctive lineage assigned to the DPANN archaea, which includes poorly characterised microorganisms with reduced genomes that likely depend on interactions with hosts for growth and survival. Here, we report the enrichment of a stable co-culture of a member of the Micrarchaeota (Ca. Micrarchaeum harzensis) together with its Thermoplasmatales host (Ca. Scheffleriplasma hospitalis), as well as the isolation of the latter. We show that symbiont-host interactions depend on biofilm formation as evidenced by growth experiments, comparative transcriptomic analyses and electron microscopy. In addition, genomic, metabolomic, extracellular polymeric substances and lipid content analyses indicate that the Micrarchaeon symbiont relies on the acquisition of metabolites from its host. Our study of the cell biology and physiology of a Micrarchaeon and its host adds to our limited knowledge of archaeal symbioses

Biophysical basis of filamentous phage tactoid-mediated antibiotic tolerance in P. aeruginosa

Inoviruses are filamentous phages infecting numerous prokaryotic phyla. Inoviruses can self-assemble into mesoscale structures with liquid-crystalline order, termed tactoids, which protect bacterial cells in Pseudomonas aeruginosa biofilms from antibiotics. Here, we investigate the structural, biophysical, and protective properties of tactoids formed by the P. aeruginosa phage Pf4 and Escherichia coli phage fd. A cryo-EM structure of the capsid from fd revealed distinct biochemical properties compared to Pf4. Fd and Pf4 formed tactoids with different morphologies that arise from differing phage geometries and packing densities, which in turn gave rise to different tactoid emergent properties. Finally, we showed that tactoids formed by either phage protect rod-shaped bacteria from antibiotic treatment, and that direct association with a tactoid is required for protection, demonstrating the formation of a diffusion barrier by the tactoid. This study provides insights into how filamentous molecules protect bacteria from extraneous substances in biofilms and in host-associated infections

Cryo-Electron Tomography of Marburg Virus Particles and Their Morphogenesis within Infected Cells

Ultrastructural analysis of a filovirus assembling within infected eukaryotic cells reveals differences in structure and assembly mechanisms between related RNA viruses

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Structures of actin-like ParM filaments show architecture of plasmid-segregating spindles

Active segregation of E. coli low-copy number plasmid R1 involves formation of a bipolar spindle made of left-handed double-helical actin-like ParM filaments 1-6. ParR links the filaments with centromeric parC plasmid DNA, while facilitating the addition of subunits to ParM filaments 3,7-9. Growing ParMRC spindles push sister plasmids to the cell poles 9,10. Here, using modern electron cryomicroscopy methods we have investigated the structures and arrangements of ParM filaments in vitro and in cells, revealing at near atomic resolution how subunits and filaments come together to produce the simplest known mitotic machinery. To understand the mechanism of dynamic instability we determined structures of ParM filaments in different nucleotide states. The structure of filaments bound to AMPPNP was determined at 4.3 Å resolution and refined. The ParM filament structure shows strong longitudinal interfaces and weaker lateral interactions. Also using electron cryomicroscopy, we reconstructed ParM doublets forming antiparallel spindles. Finally, with whole-cell electron cryotomography we show that doublets are abundant in bacterial cells containing low-copy number plasmids with the ParMRC locus, leading to an asynchronous model of R1 plasmid segregation

Seeing tobacco mosaic virus through direct electron detectors

AbstractWith the introduction of direct electron detectors (DED) to the field of electron cryo-microscopy, a wave of atomic-resolution structures has become available. As the new detectors still require comparative characterization, we have used tobacco mosaic virus (TMV) as a test specimen to study the quality of 3D image reconstructions from data recorded on the two direct electron detector cameras, K2 Summit and Falcon II. Using DED movie frames, we explored related image-processing aspects and compared the performance of micrograph-based and segment-based motion correction approaches. In addition, we investigated the effect of dose deposition on the atomic-resolution structure of TMV and show that radiation damage affects negative carboxyl chains first in a side-chain specific manner. Finally, using 450,000 asymmetric units and limiting the effects of radiation damage, we determined a high-resolution cryo-EM map at 3.35Å resolution. Here, we provide a comparative case study of highly ordered TMV recorded on different direct electron detectors to establish recording and processing conditions that enable structure determination up to 3.2Å in resolution using cryo-EM