Methicillin-resistant Staphylococcus aureus (MRSA) is a frequent cause of difficult-to-treat, often fatal infections in humans1,2. Most humans have antibodies against S. aureus, but these are... Show moreMethicillin-resistant Staphylococcus aureus (MRSA) is a frequent cause of difficult-to-treat, often fatal infections in humans1,2. Most humans have antibodies against S. aureus, but these are highly variable and often not protective in immunocompromised patients3. Previous vaccine development programs have not been successful4. A large percentage of human antibodies against S. aureus target wall teichoic acid (WTA), a ribitol-phosphate (RboP) surface polymer modified with N-acetylglucosamine (GlcNAc)5,6. It is currently unknown whether the immune evasion capacities of MRSA are due to variation of dominant surface epitopes such as those associated with WTA. Here we show that a considerable proportion of the prominent healthcare-associated and livestock-associated MRSA clones CC5 and CC398, respectively, contain prophages that encode an alternative WTA glycosyltransferase. This enzyme, TarP, transfers GlcNAc to a different hydroxyl group of the WTA RboP than the standard enzyme TarS7, with important consequences for immune recognition. TarP-glycosylated WTA elicits 7.5–40-fold lower levels of immunoglobulin G in mice than TarS-modified WTA. Consistent with this, human sera contained only low levels of antibodies against TarP-modified WTA. Notably, mice immunized with TarS-modified WTA were not protected against infection with tarP-expressing MRSA, indicating that TarP is crucial for the capacity of S. aureus to evade host defences. High-resolution structural analyses of TarP bound to WTA components and uridine diphosphate GlcNAc (UDP-GlcNAc) explain the mechanism of altered RboP glycosylation and form a template for targeted inhibition of TarP. Our study reveals an immune evasion strategy of S. aureus based on averting the immunogenicity of its dominant glycoantigen WTA. These results will help with the identification of invariant S. aureus vaccine antigens and may enable the development of TarP inhibitors as a new strategy for rendering MRSA susceptible to human host defences. Show less
The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better... Show moreThe tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming. Show less
Coulais, C.; Sabbadini, A.; Vink, F.; Hecke, M.L. van 2018
Multi-step pathways—which consist of a sequence of reconfigurations of a structure—are central to the functionality of various natural and artificial systems. Such pathways execute autonomously in... Show moreMulti-step pathways—which consist of a sequence of reconfigurations of a structure—are central to the functionality of various natural and artificial systems. Such pathways execute autonomously in self-guided processes such as protein folding1 and self-assembly2,3,4,5, but have previously required external control to execute in macroscale mechanical systems, provided by, for example, actuators in robotics6,7,8,9 or manual folding in origami8,10,11,12. Here we demonstrate shape-changing, macroscale mechanical metamaterials that undergo self-guided, multi-step reconfiguration in response to global uniform compression. We avoid the need for external control by using metamaterials that are made purely of passive components. The design of the metamaterials combines nonlinear mechanical elements with a multimodal architecture that enables a sequence of topological reconfigurations caused by the formation of internal self-contacts between the elements of the metamaterial. We realize the metamaterials by using computer-controlled water-jet cutting of flexible materials, and show that the multi-step pathway and final configuration can be controlled by rational design of the nonlinear mechanical elements. We also demonstrate that the self-contacts suppress errors in the pathway. Finally, we create hierarchical architectures to extend the number of distinct reconfiguration steps. Our work establishes general principles for designing mechanical pathways, opening up new avenues for self-folding media11,12, pluripotent materials9,13 and pliable devices14 in areas such as stretchable electronics and soft robotics15. Show less
Soils harbour some of the most diverse microbiomes on Earth and are essential for both nutrient cycling and carbon storage. To understand soil functioning, it is necessary to model the global... Show moreSoils harbour some of the most diverse microbiomes on Earth and are essential for both nutrient cycling and carbon storage. To understand soil functioning, it is necessary to model the global distribution patterns and functional gene repertoires of soil microorganisms, as well as the biotic and environmental associations between the diversity and structure of both bacterial and fungal soil communities(1-4). Here we show, by leveraging metagenomics and metabarcoding of global topsoil samples (189 sites, 7,560 subsamples), that bacterial, but not fungal, genetic diversity is highest in temperate habitats and that microbial gene composition varies more strongly with environmental variables than with geographic distance. We demonstrate that fungi and bacteria show global niche differentiation that is associated with contrasting diversity responses to precipitation and soil pH. Furthermore, we provide evidence for strong bacterial-fungal antagonism, inferred from antibiotic-resistance genes, in topsoil and ocean habitats, indicating the substantial role of biotic interactions in shaping microbial communities. Our results suggest that both competition and environmental filtering affect the abundance, composition and encoded gene functions of bacterial and fungal communities, indicating that the relative contributions of these microorganisms to global nutrient cycling varies spatially. Show less
To plan the syntheses of small organic molecules, chemists use retrosynthesis, a problem-solving technique in which target molecules are recursively transformed into increasingly simpler precursors... Show moreTo plan the syntheses of small organic molecules, chemists use retrosynthesis, a problem-solving technique in which target molecules are recursively transformed into increasingly simpler precursors. Computer-aided retrosynthesis would be a valuable tool but at present it is slow and provides results of unsatisfactory quality. Here we use Monte Carlo tree search and symbolic artificial intelligence (AI) to discover retrosynthetic routes. We combined Monte Carlo tree search with an expansion policy network that guides the search, and a filter network to pre-select the most promising retrosynthetic steps. These deep neural networks were trained on essentially all reactions ever published in organic chemistry. Our system solves for almost twice as many molecules, thirty times faster than the traditional computer-aided search method, which is based on extracted rules and hand-designed heuristics. In a double-blind AB test, chemists on average considered our computer-generated routes to be equivalent to reported literature routes. Show less
