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Genome-scale metabolic models (GEMs) have been widely used for quantitative exploration of the relation between genotype and phenotype. Streamlined integration of enzyme constraints and proteomics data into such models was first enabled by the GECKO toolbox, allowing the study of phenotypes constrained by protein limitations. Here, we upgrade the toolbox in order to enhance models with enzyme and proteomics constraints for any organism with a compatible GEM reconstruction. With this, enzyme-constrained models for the budding yeasts Saccharomyces cerevisiae, Yarrowia lipolytica and Kluyveromyces marxianus are generated to study their long-term adaptation to several stress factors by incorporation of proteomics data. Predictions reveal that upregulation and high saturation of enzymes in amino acid metabolism are common across organisms and conditions, suggesting the relevance of metabolic robustness in contrast to optimal protein utilization as a cellular objective for microbial growth under stress and nutrient-limited conditions. The functionality of GECKO is expanded with an automated framework for continuous and version-controlled update of enzyme-constrained GEMs, also producing such models for Escherichia coli and Homo sapiens . In this work, we facilitate the utilization of enzyme-constrained GEMs in basic science, metabolic engineering and synthetic biology purposes.

Climate change is predicted to alter global species diversity(1), the distribution of human pathogens' and ecosystem services(3). Forecasting these changes and designing adequate management of future ecosystem services will require predictive models encompassing the most fundamental biotic responses. However, most present models omit important processes such as evolution and competition(4,5). Here we develop a spatially explicit eco-evolutionary model of multi-species responses to climate change. We demonstrate that both dispersal and evolution differentially mediate extinction risks and biodiversity alterations through time and across climate gradients. Together, high genetic variance and low dispersal best minimized extinction risks. Surprisingly, high dispersal did not reduce extinctions, because the shifting ranges of some species hastened the decline of others. Evolutionary responses dominated during the later stages of climatic changes and in hot regions. No extinctions occurred without competition, which highlights the importance of including species interactions in global biodiversity models. Most notably, climate change created extinction and evolutionary debts, with changes in species richness and traits occuring long after climate stabilization. Therefore, even if we halt anthropogenic climate change today, transient eco-evolutionary dynamics would ensure centuries of additional alterations in global biodiversity.

The brucellae are Gram-negative bacteria that cause an important zoonosis. Studies with the main Brucella species have shown that the O-antigens of the Brucella smooth lipopolysaccharide are α-(1 → 2) and α-(1 → 3)-linked N-formyl-perosamine polysaccharides that carry M, A and C (A = M, A>M and AA) and M specificities. However, the biovar 2 O-antigen bound monoclonal antibodies to the Brucella A epitope, and to the C/Y epitope shared by brucellae and Yersinia enterocolitica O:9, a bacterium that carries an N-formyl-perosamine O-antigen in exclusively α-(1 → 2)-linkages. By (13)C NMR spectroscopy, B. suis biovar 1 but not B. suis biovar 2 or Y. enterocolitica O:9 polysaccharide showed the signal characteristic of α-(1 → 3)-linked N-formyl-perosamine, indicating that biovar 2 may altogether lack this linkage. Taken together, the NMR spectroscopy and monoclonal antibody analyses strongly suggest a role for α-(1 → 3)-linked N-formyl-perosamine in the C (A = M) and C (M>A) epitopes. Moreover, they indicate that B. suis biovar 2 O-antigen lacks some lipopolysaccharide epitopes previously thought to be present in all smooth brucellae, thus representing a new brucella serovar that is M-negative, C-negative. Serologically and structurally this new serovar is more similar to Y. enterocolitica O:9 than to other brucellae.

The infection by Trypanosoma brucei brucei ( T . b . b .), a protozoan parasite, is characterized by an early-systemic stage followed by a late stage in which parasites invade the brain parenchyma in a T cell-dependent manner. Here we found that early after infection effector-memory T cells were predominant among brain T cells, whereas, during the encephalitic stage T cells acquired a tissue resident memory phenotype (T RM ) and expressed PD1. Both CD4 and CD8 T cells were independently redundant for the penetration of T . b . b . and other leukocytes into the brain parenchyma. The role of lymphoid cells during the T . b . b . infection was studied by comparing T- and B-cell deficient rag1 -/- and WT mice. Early after infection, parasites located in circumventricular organs, brain structures with increased vascular permeability, particularly in the median eminence (ME), paced closed to the sleep-wake regulatory arcuate nucleus of the hypothalamus (Arc). Whereas parasite levels in the ME were higher in rag1 -/- than in WT mice, leukocytes were instead reduced. Rag1 -/- infected mice showed increased levels of meca32 mRNA coding for a blood /hypothalamus endothelial molecule absent in the blood-brain-barrier (BBB). Both immune and metabolic transcripts were elevated in the ME/Arc of WT and rag1 -/- mice early after infection, except for ifng mRNA, which levels were only increased in WT mice. Finally, using a non-invasive sleep-wake cycle assessment method we proposed a putative role of lymphocytes in mediating sleep alterations during the infection with T . b . b . Thus, the majority of T cells in the brain during the early stage of T . b . b . infection expressed an effector-memory phenotype while T RM cells developed in the late stage of infection. T cells and parasites invade the ME/Arc altering the metabolic and inflammatory responses during the early stage of infection and modulating sleep disturbances.

Background The large Glycoside Hydrolase family 5 (GH5) groups together a wide range of enzymes acting on β-linked oligo- and polysaccharides, and glycoconjugates from a large spectrum of organisms. The long and complex evolution of this family of enzymes and its broad sequence diversity limits functional prediction. With the objective of improving the differentiation of enzyme specificities in a knowledge-based context, and to obtain new evolutionary insights, we present here a new, robust subfamily classification of family GH5. Results About 80% of the current sequences were assigned into 51 subfamilies in a global analysis of all publicly available GH5 sequences and associated biochemical data. Examination of subfamilies with catalytically-active members revealed that one third are monospecific (containing a single enzyme activity), although new functions may be discovered with biochemical characterization in the future. Furthermore, twenty subfamilies presently have no characterization whatsoever and many others have only limited structural and biochemical data. Mapping of functional knowledge onto the GH5 phylogenetic tree revealed that the sequence space of this historical and industrially important family is far from well dispersed, highlighting targets in need of further study. The analysis also uncovered a number of GH5 proteins which have lost their catalytic machinery, indicating evolution towards novel functions. Conclusion Overall, the subfamily division of GH5 provides an actively curated resource for large-scale protein sequence annotation for glycogenomics; the subfamily assignments are openly accessible via the Carbohydrate-Active Enzyme database at http://www.cazy.org/GH5.html .

The moose (Alces alces) is a ruminant that harvests energy from fiber-rich lignocellulose material through carbohydrate-active enzymes (CAZymes) produced by its rumen microbes. We applied shotgun metagenomics to rumen contents from six moose to obtain insights into this microbiome. Following binning, 99 metagenome-assembled genomes (MAGs) belonging to 11 prokaryotic phyla were reconstructed and characterized based on phylogeny and CAZyme profile. The taxonomy of these MAGs reflected the overall composition of the metagenome, with dominance of the phyla Bacteroidetes and Firmicutes. Unlike in other ruminants, Spirochaetes constituted a significant proportion of the community and our analyses indicate that the corresponding strains are primarily pectin digesters. Pectin-degrading genes were also common in MAGs of Ruminococcus, Fibrobacteres and Bacteroidetes and were overall overrepresented in the moose microbiome compared with other ruminants. Phylogenomic analyses revealed several clades within the Bacteriodetes without previously characterized genomes. Several of these MAGs encoded a large numbers of dockerins, a module usually associated with cellulosomes. The Bacteroidetes dockerins were often linked to CAZymes and sometimes encoded inside polysaccharide utilization loci, which has never been reported before. The almost 100 CAZyme-annotated genomes reconstructed in this study provide an in-depth view of an efficient lignocellulose-degrading microbiome and prospects for developing enzyme technology for biorefineries.

Most statistical models of microclimate focus on the difference or \"offset' between standardized air temperatures (macroclimate) and those of a specific habitat such as forest understorey, grassland or under a log. However, these offsets can fluctuate from positive to negative over a single day such that common practice consists in aggregating data into daily mean, minimum and maximum before modelling monthly offsets for each summary statistic. Here, we propose a more parsimonious and flexible approach relying on just two parameters: the slope and equilibrium. The slope captures the linear relationship between microclimate and macroclimate, while the equilibrium is the point at which microclimate equals macroclimate. Although applicable to other habitats, we demonstrate the relevance of our method by focusing on forest understoreys.We installed temperature sensors at 1-m height inside forest stands and in nearby open grasslands equipped with standardized weather stations, across 13 sites in France spanning a wide climatic gradient. From a year of hourly temperatures and for each sensor, we established relationships between microclimate and macroclimate temperatures using two linear mixed-effects models, during the leaf -on (May- November) and leaf -off period (December- April). We extracted the monthly equilibrium and slope for each sensor, and used another set of linear mixed-effects models to investigate their main determinants.The slope was chiefly determined by stand structure variables interacting with the leaf- on/leaf- off period: stand type (conifer vs broadleaf); shade-casting ability; stand age; dominant height; stem density; and cover of the upper and lower shrub layer. In contrast, forest structure had no explanatory power on the equilibrium. We found the equilibrium to be positively related to mean macroclimate temperature, interacting with the open/forest habitat.The method introduced here overcomes several shortcomings of modelling microclimate offsets. By demonstrating that the slope and equilibrium vary in predictable ways, we have established a general linkage between microclimate and macroclimate temperatures that can be applied to any location or time if we know the mean macroclimate temperature (equilibrium) and buffering or amplifying capacity of the habitat (slope). We also warn about methodological biases due to the reference used for macroclimate.

The peopling of Sahul (the combined continent of Australia and New Guinea) represents the earliest continental migration and settlement event of solely anatomically modern humans, but its patterns and ecological drivers remain largely conceptual in the current literature. We present an advanced stochastic-ecological model to test the relative support for scenarios describing where and when the first humans entered Sahul, and their most probable routes of early settlement. The model supports a dominant entry via the northwest Sahul Shelf first, potentially followed by a second entry through New Guinea, with initial entry most consistent with 50,000 or 75,000 years ago based on comparison with bias-corrected archaeological map layers. The model’s emergent properties predict that peopling of the entire continent occurred rapidly across all ecological environments within 156–208 human generations (4368–5599 years) and at a plausible rate of 0.71–0.92 km year −1 . More broadly, our methods and approaches can readily inform other global migration debates, with results supporting an exit of anatomically modern humans from Africa 63,000–90,000 years ago, and the peopling of Eurasia in as little as 12,000–15,000 years via inland routes.

The mechanisms leading to megafauna (>44 kg) extinctions in Late Pleistocene (126,000—12,000 years ago) Australia are highly contested because standard chronological analyses rely on scarce data of varying quality and ignore spatial complexity. Relevant archaeological and palaeontological records are most often also biased by differential preservation resulting in under-representated older events. Chronological analyses have attributed megafaunal extinctions to climate change, humans, or a combination of the two, but rarely consider spatial variation in extinction patterns, initial human appearance trajectories, and palaeoclimate change together. Here we develop a statistical approach to infer spatio-temporal trajectories of megafauna extirpations (local extinctions) and initial human appearance in south-eastern Australia. We identify a combined climate-human effect on regional extirpation patterns suggesting that small, mobile Aboriginal populations potentially needed access to drinkable water to survive arid ecosystems, but were simultaneously constrained by climate-dependent net landscape primary productivity. Thus, the co-drivers of megafauna extirpations were themselves constrained by the spatial distribution of climate-dependent water sources.

The brucellae are facultative intracellular bacteria that cause brucellosis, one of the major neglected zoonoses. In endemic areas, vaccination is the only effective way to control this disease. Brucella melitensis Rev 1 is a vaccine effective against the brucellosis of sheep and goat caused by B. melitensis, the commonest source of human infection. However, Rev 1 carries a smooth lipopolysaccharide with an O-polysaccharide that elicits antibodies interfering in serodiagnosis, a major problem in eradication campaigns. Because of this, rough Brucella mutants lacking the O-polysaccharide have been proposed as vaccines. To examine the possibilities of rough vaccines, we screened B. melitensis for lipopolysaccharide genes and obtained mutants representing all main rough phenotypes with regard to core oligosaccharide and O-polysaccharide synthesis and export. Using the mouse model, mutants were classified into four attenuation patterns according to their multiplication and persistence in spleens at different doses. In macrophages, mutants belonging to three of these attenuation patterns reached the Brucella characteristic intracellular niche and multiplied intracellularly, suggesting that they could be suitable vaccine candidates. Virulence patterns, intracellular behavior and lipopolysaccharide defects roughly correlated with the degree of protection afforded by the mutants upon intraperitoneal vaccination of mice. However, when vaccination was applied by the subcutaneous route, only two mutants matched the protection obtained with Rev 1 albeit at doses one thousand fold higher than this reference vaccine. These mutants, which were blocked in O-polysaccharide export and accumulated internal O-polysaccharides, stimulated weak anti-smooth lipopolysaccharide antibodies. The results demonstrate that no rough mutant is equal to Rev 1 in laboratory models and question the notion that rough vaccines are suitable for the control of brucellosis in endemic areas.