Real-time forecasting of COVID-19-related hospital strain in France using a non-Markovian mechanistic model.

Projects such as the European Covid-19 Forecast Hub publish forecasts on the national level for new deaths, new cases, and hospital admissions, but not direct measurements of hospital strain like critical care bed occupancy at the sub-national level, which is of particular interest to health professionals for planning purposes. We present a sub-national French framework for forecasting hospital strain based on a non-Markovian compartmental model, its associated online visualisation tool and a retrospective evaluation of the real-time forecasts it provided from January to December 2021 by comparing to three baselines derived from standard statistical forecasting methods (a naive model, auto-regression, and an ensemble of exponential smoothing and ARIMA). In terms of median absolute error for forecasting critical care unit occupancy at the two-week horizon, our model only outperformed the naive baseline for 4 out of 14 geographical units and underperformed compared to the ensemble baseline for 5 of them at the 90% confidence level (n = 38). However, for the same level at the 4 week horizon, our model was never statistically outperformed for any unit despite outperforming the baselines 10 times spanning 7 out of 14 geographical units. This implies modest forecasting utility for longer horizons which may justify the application of non-Markovian compartmental models in the context of hospital-strain surveillance for future pandemics.

Associations between the social environment and early childhood developmental outcomes of Puerto Rican children with prenatal Zika virus exposure: a cross-sectional study.

BACKGROUND: Prenatal exposure to the Zika virus can lead to microcephaly and adverse developmental outcomes, even in children without evident birth defects. The social environment plays a crucial role in infant health and developmental trajectories, especially during periods of heightened brain plasticity. The study aimed to assess socioenvironmental factors as predictors of developmental outcomes of 36-month-old children exposed to Zika virus prenatally. STUDY DESIGN: This cross-sectional study included 53 mothers and 55 children enrolled in the Pediatric Outcomes of Prenatal Zika Exposure cohort study in Puerto Rico. The study performs follow-up developmental assessments of children born to mothers with confirmed and probable Zika virus infection during pregnancy. Mothers completed socioenvironmental questionnaires (e.g., Perceived Neighborhood Scale and US Household Food Insecurity Survey). Children's developmental outcomes were assessed with the Bayley Scales of Infant and Toddler Development: Third Edition, the Ages and Stages Questionnaires: Third Edition, the Ages and Stages Questionnaire-Socioemotional: Second Edition, and the Child Adjustment and Parent Efficacy Scale. RESULTS: Linear regression models, adjusting for a child's sex and age and maternal education, revealed that early life exposure to food insecurity and maternal pregnancy stressors were significantly associated with poorer developmental outcomes in Zika virus-exposed children at 36 months of age. Maternal resilience representation of adaptive ability was associated with the preservation of adequate developmental outcomes in children. CONCLUSIONS: Pregnancy and early childhood are critical life periods for ensuring optimal brain development in children. While the mechanisms in the interaction of children with their environment are complex, the risk and protective factors identified in the study are modifiable through public policy and preventive initiatives. Implementation of comprehensive strategies that improve access to social support programs, educational and nutritional interventions, and mental health services during pregnancy and early childhood can enhance the developmental potential of vulnerable children.

Risk Factors for Mortality Among Children Younger Than Age 5 Years With Severe Diarrhea in Low- and Middle-income Countries: Findings From the World Health Organization-coordinated Global Rotavirus and Pediatric Diarrhea Surveillance Networks.

BACKGROUND: Diarrhea is the second leading cause of death in children younger than 5 years of age globally. The burden of diarrheal mortality is concentrated in low-resource settings. Little is known about the risk factors for childhood death from diarrheal disease in low- and middle-income countries. METHODS: Data from the World Health Organization (WHO)-coordinated Global Rotavirus and Pediatric Diarrhea Surveillance Networks, which are composed of active, sentinel, hospital-based surveillance sites, were analyzed to assess mortality in children <5 years of age who were hospitalized with diarrhea between 2008 and 2018. Case fatality risks were calculated, and multivariable logistic regression was performed to identify risk factors for mortality. RESULTS: This analysis comprises 234 781 cases, including 1219 deaths, across 57 countries. The overall case fatality risk was found to be 0.5%. Risk factors for death in the multivariable analysis included younger age (for <6 months compared with older ages, odds ratio [OR] = 3.54; 95% confidence interval [CI], 2.81-4.50), female sex (OR = 1.18; 95% CI, 1.06-1.81), presenting with persistent diarrhea (OR = 1.91; 95% CI, 1.01-3.25), no vomiting (OR = 1.13; 95% CI, .98-1.30), severe dehydration (OR = 3.79; 95% CI, 3.01-4.83), and being negative for rotavirus on an enzyme-linked immunosorbent assay test (OR = 2.29; 95% CI, 1.92-2.74). Cases from the African Region had the highest odds of death compared with other WHO regions (OR = 130.62 comparing the African Region with the European Region; 95% CI, 55.72-422.73), whereas cases from the European Region had the lowest odds of death. CONCLUSIONS: Our findings support known risk factors for childhood diarrheal mortality and highlight the need for interventions to address dehydration and rotavirus-negative diarrheal infections.

Thermodynamic Assessment of Triclocarban Dissolution Process in N-Methyl-2-pyrrolidone + Water Cosolvent Mixtures.

Solubility is one of the most important physicochemical properties due to its involvement in physiological (bioavailability), industrial (design) and environmental (biotoxicity) processes, and in this regard, cosolvency is one of the best strategies to increase the solubility of poorly soluble drugs in aqueous systems. Thus, the aim of this research is to thermodynamically evaluate the dissolution process of triclocarban (TCC) in cosolvent mixtures of {N-methyl-2-pyrrolidone (NMP) + water (W)} at seven temperatures (288.15, 293.15, 298.15, 303.15, 308.15, 313.15 and 318.15 K). Solubility is determined by UV/vis spectrophotometry using the flask-shaking method. The dissolution process of the TCC is endothermic and strongly dependent on the cosolvent composition, achieving the minimum solubility in pure water and the maximum solubility in NMP. The activity coefficient decreases from pure water to NMP, reaching values less than one, demonstrating the excellent positive cosolvent effect of NMP, which is corroborated by the negative values of the Gibbs energy of transfer. In general terms, the dissolution process is endothermic, and the increase in TCC solubility may be due to the affinity of TCC with NMP, in addition to the water de-structuring capacity of NMP generating a higher number of free water molecules.

Chemical-damage MINE: A database of curated and predicted spontaneous metabolic reactions.

Spontaneous reactions between metabolites are often neglected in favor of emphasizing enzyme-catalyzed chemistry because spontaneous reaction rates are assumed to be insignificant under physiological conditions. However, synthetic biology and engineering efforts can raise natural metabolites' levels or introduce unnatural ones, so that previously innocuous or nonexistent spontaneous reactions become an issue. Problems arise when spontaneous reaction rates exceed the capacity of a platform organism to dispose of toxic or chemically active reaction products. While various reliable sources list competing or toxic enzymatic pathways' side-reactions, no corresponding compilation of spontaneous side-reactions exists, nor is it possible to predict their occurrence. We addressed this deficiency by creating the Chemical Damage (CD)-MINE resource. First, we used literature data to construct a comprehensive database of metabolite reactions that occur spontaneously in physiological conditions. We then leveraged this data to construct 148 reaction rules describing the known spontaneous chemistry in a substrate-generic way. We applied these rules to all compounds in the ModelSEED database, predicting 180,891 spontaneous reactions. The resulting (CD)-MINE is available at https://minedatabase.mcs.anl.gov/cdmine/#/home and through developer tools. We also demonstrate how damage-prone intermediates and end products are widely distributed among metabolic pathways, and how predicting spontaneous chemical damage helps rationalize toxicity and carbon loss using examples from published pathways to commercial products. We explain how analyzing damage-prone areas in metabolism helps design effective engineering strategies. Finally, we use the CD-MINE toolset to predict the formation of the novel damage product N-carbamoyl proline, and present mass spectrometric evidence for its presence in Escherichia coli.

Thermodynamic Analysis of the Solubility of Isoniazid in (PEG 200 + Water) Cosolvent Mixtures from 278.15 K to 318.15 K.

The solubility of drugs in cosolvent systems of pharmaceutical interest is of great importance for understanding and optimizing a large number of processes. Here, we report the solubility of isoniazid in nine (PEG 200 + water) cosolvent mixtures at nine temperatures (278.15, 283.15, 288.15, 293.15, 298.15, 303.15, 308.15, and 318.15 K) determined by UV-vis spectrophotometry. From the solubility data, the thermodynamic solution, mixing, and transfer functions were calculated in addition to performing the enthalpy-entropy compensation analysis. The solubility of isoniazid depends on the concentration of PEG 200 (positive cosolvent effect) and temperature (endothermic process) reaching its maximum solubility in pure PEG 200 at 318.15 K and the lowest solubility in pure water at 278.15 K. The solution process is favored by the solution entropy and according to the enthalpy-entropy compensation analysis it is driven by entropy in mixtures rich in water and by enthalpy in mixtures rich in PEG 200.

RNA Microarray-Based Comparison of Innate Immune Phenotypes between Human THP-1 Macrophages Stimulated with Two BCG Strains.

Currently, the only available vaccine against tuberculosis is Mycobacterium bovis Bacille Calmette-Guérin (BCG). Pulmonary tuberculosis protection provided by the vaccine varies depending on the strain, the patient's age and the evaluated population. Although the adaptive immune responses induced by different BCG strains have been widely studied, little conclusive data is available regarding innate immune responses, especially in macrophages. Here, we aimed to characterize the innate immune responses of human THP-1-derived macrophages at the transcriptional level following a challenge with either the BCG Mexico (M.BCG) or Phipps (P.BCG) strains. After a brief in vitro characterization of the bacterial strains and the innate immune responses, including nitric oxide production and cytokine profiles, we analyzed the mRNA expression patterns and performed pathway enrichment analysis using RNA microarrays. Our results showed that multiple biological processes were enriched, especially those associated with innate inflammatory and antimicrobial responses, including tumor necrosis factor (TNF)-α, type I interferon (IFN-I) and IFN-γ. However, four DEGs were identified in macrophages infected with M.BCG compared to P. BCG. These findings indicated the proinflammatory stimulation of macrophages induced by both BCG strains, at the cytokine level and in terms of gene expression, suggesting a differential expression pattern of innate immune transcripts depending on the mycobacterial strain.

The Global Landscape of Pediatric Bacterial Meningitis Data Reported to the World Health Organization-Coordinated Invasive Bacterial Vaccine-Preventable Disease Surveillance Network, 2014-2019.

BACKGROUND: The World Health Organization (WHO) coordinates the Global Invasive Bacterial Vaccine-Preventable Diseases (IB-VPD) Surveillance Network to support vaccine introduction decisions and use. The network was established to strengthen surveillance and laboratory confirmation of meningitis caused by Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis. METHODS: Sentinel hospitals report cases of children <5 years of age hospitalized for suspected meningitis. Laboratories report confirmatory testing results and strain characterization tested by polymerase chain reaction. In 2019, the network included 123 laboratories that follow validated, standardized testing and reporting strategies. RESULTS: From 2014 through 2019, >137 000 suspected meningitis cases were reported by 58 participating countries, with 44.6% (n = 61 386) reported from countries in the WHO African Region. More than half (56.6%, n = 77 873) were among children <1 year of age, and 4.0% (n = 4010) died among those with reported disease outcome. Among suspected meningitis cases, 8.6% (n = 11 798) were classified as probable bacterial meningitis. One of 3 bacterial pathogens was identified in 30.3% (n = 3576) of these cases, namely S. pneumoniae (n = 2177 [60.9%]), H. influenzae (n = 633 [17.7%]), and N. meningitidis (n = 766 [21.4%]). Among confirmed bacterial meningitis cases with outcome reported, 11.0% died; case fatality ratio varied by pathogen (S. pneumoniae, 12.2%; H. influenzae, 6.1%; N. meningitidis, 11.0%). Among the 277 children who died with confirmed bacterial meningitis, 189 (68.2%) had confirmed S. pneumoniae. The proportion of pneumococcal cases with pneumococcal conjugate vaccine (PCV) serotypes decreased as the number of countries implementing PCV increased, from 77.8% (n = 273) to 47.5% (n = 248). Of 397 H. influenzae specimens serotyped, 49.1% (n = 195) were type b. Predominant N. meningitidis serogroups varied by region. CONCLUSIONS: This multitier, global surveillance network has supported countries in detecting and serotyping the 3 principal invasive bacterial pathogens that cause pediatric meningitis. Streptococcus pneumoniae was the most common bacterial pathogen detected globally despite the growing number of countries that have nationally introduced PCV. The large proportions of deaths due to S. pneumoniae reflect the high proportion of meningitis cases caused by this pathogen. This global network demonstrated a strong correlation between PCV introduction status and reduction in the proportion of pneumococcal meningitis infections caused by vaccine serotypes. Maintaining case-based, active surveillance with laboratory confirmation for prioritized vaccine-preventable diseases remains a critical component of the global agenda in public health.The World Health Organization (WHO)-coordinated Invasive Bacterial Vaccine-Preventable Disease (IB-VPD) Surveillance Network reported data from 2014 to 2019, contributing to the estimates of the disease burden and serotypes of pediatric meningitis caused by Streptococcus pneumoniae, Haemophilus influenzae and Neisseria meningitidis.

Functional Connectivity and Frequency Power Alterations during P300 Task as a Result of Amyotrophic Lateral Sclerosis.

Amyotrophic Lateral Sclerosis (ALS) is one of the most aggressive neurodegenerative diseases and is now recognized as a multisystem network disorder with impaired connectivity. Further research for the understanding of the nature of its cognitive affections is necessary to monitor and detect the disease, so this work provides insight into the neural alterations occurring in ALS patients during a cognitive task (P300 oddball paradigm) by measuring connectivity and the power and latency of the frequency-specific EEG activity of 12 ALS patients and 16 healthy subjects recorded during the use of a P300-based BCI to command a robotic arm. For ALS patients, in comparison to Controls, the results (p < 0.05) were: an increment in latency of the peak ERP in the Delta range (OZ) and Alpha range (PO7), and a decreased power in the Beta band among most electrodes; connectivity alterations among all bands, especially in the Alpha band between PO7 and the channels above the motor cortex. The evolution observed over months of an advanced-state patient backs up these findings. These results were used to compute connectivity- and power-based features to discriminate between ALS and Control groups using Support Vector Machine (SVM). Cross-validation achieved a 100% in specificity and 75% in sensitivity, with an overall 89% success.

Solubility of Sulfamethazine in the Binary Mixture of Acetonitrile + Methanol from 278.15 to 318.15 K: Measurement, Dissolution Thermodynamics, Preferential Solvation, and Correlation.

Solubility of sulfamethazine (SMT) in acetonitrile (MeCN) + methanol (MeOH) cosolvents was determined at nine temperatures between 278.15 and 318.15 K. From the solubility data expressed in molar fraction, the thermodynamic functions of solution, transfer and mixing were calculated using the Gibbs and van 't Hoff equations; on the other hand, the solubility data were modeled according to the Wilson models and NRTL. The solubility of SMT is thermo-dependent and is influenced by the solubility parameter of the cosolvent mixtures. In this case, the maximum solubility was achieved in the cosolvent mixture w0.40 at 318.15 K and the minimum in pure MeOH at 278.15 K. According to the thermodynamic functions, the SMT solution process is endothermic in addition to being favored by the entropic factor, and as for the preferential solvation parameter, SMT tends to be preferentially solvated by MeOH in all cosolvent systems; however, δx3,1<0.01, so the results are not conclusive. Finally, according to mean relative deviations (MRD%), the two models could be very useful tools for calculating the solubility of SMT in cosolvent mixtures and temperatures different from those reported in this research.

Modulation of the Biocatalytic Properties of a Novel Lipase from Psychrophilic Serratia sp. (USBA-GBX-513) by Different Immobilization Strategies.

In this work, the effect of different immobilization procedures on the properties of a lipase obtained from the extremophilic microorganism Serratia sp. USBA-GBX-513, which was isolated from Paramo soils of Los Nevados National Natural Park (Colombia), is reported. Different Shepharose beads were used: octyl-(OC), octyl-glyoxyl-(OC-GLX), cyanogen bromide (BrCN)-, and Q-Sepharose. The performance of the different immobilized extremophile lipase from Serratia (ESL) was compared with that of the lipase B from Candida antarctica (CALB). In all immobilization tests, hyperactivation of ESL was observed. The highest hyperactivation (10.3) was obtained by immobilization on the OC support. Subsequently, the thermal stability at pH 5, 7, and 9 and the stability in the presence of 50% (v/v) acetonitrile, 50% dioxane, and 50% tetrahydrofuran solvents at pH 7 and 40 °C were evaluated. ESL immobilized on octyl-Sepharose was the most stable biocatalyst at 90 °C and pH 9, while the most stable preparation at pH 5 was ESL immobilized on OC-GLX-Sepharose supports. Finally, in the presence of 50% (v/v) tetrahydrofuran (THF) or dioxane at 40 °C, ESL immobilized on OC-Sepharose was the most stable biocatalyst, while the immobilized preparation of ESL on Q-Sepharose was the most stable one in 40% (v/v) acetonitrile.

Exceptional but vulnerable microbial diversity in coral reef animal surface microbiomes.

Coral reefs host hundreds of thousands of animal species that are increasingly threatened by anthropogenic disturbances. These animals host microbial communities at their surface, playing crucial roles for their fitness. However, the diversity of such microbiomes is mostly described in a few coral species and still poorly defined in other invertebrates and vertebrates. Given the diversity of animal microbiomes, and the diversity of host species inhabiting coral reefs, the contribution of such microbiomes to the total microbial diversity of coral reefs could be important, yet potentially vulnerable to the loss of animal species. Analysis of the surface microbiome from 74 taxa, including teleost fishes, hard and soft corals, crustaceans, echinoderms, bivalves and sponges, revealed that more than 90% of their prokaryotic phylogenetic richness was specific and not recovered in surrounding plankton. Estimate of the total richness associated with coral reef animal surface microbiomes reached up to 2.5% of current estimates of Earth prokaryotic diversity. Therefore, coral reef animal surfaces should be recognized as a hotspot of marine microbial diversity. Loss of the most vulnerable reef animals expected under present-day scenarios of reef degradation would induce an erosion of 28% of the prokaryotic richness, with unknown consequences on coral reef ecosystem functioning.

Chemoenzymatic Synthesis of the New 3-((2,3-Diacetoxypropanoyl)oxy)propane-1,2-diyl Diacetate Using Immobilized Lipase B from Candida antarctica and Pyridinium Chlorochromate as an Oxidizing Agent.

To exploit the hydrolytic activity and high selectivity of immobilized lipase B from Candida antarctica on octyl agarose (CALB-OC) in the hydrolysis of triacetin and also to produce new value-added compounds from glycerol, this work describes a chemoenzymatic methodology for the synthesis of the new dimeric glycerol ester 3-((2,3-diacetoxypropanoyl)oxy)propane-1,2-diyl diacetate. According to this approach, triacetin was regioselectively hydrolyzed to 1,2-diacetin with CALB-OC. The diglyceride product was subsequently oxidized with pyridinium chlorochromate (PCC) and a dimeric ester was isolated as the only product. It was found that the medium acidity during the PCC treatment and a high 1,2-diacetin concentration favored the formation of the ester. The synthesized compounds were characterized using IR, MS, HR-MS, and NMR techniques. The obtained dimeric ester was evaluated at 100 ppm against seven bacterial strains and two Candida species to identify its antimicrobial activity. The compound has no inhibitory activity against the bacterial strains used but decreased C. albicans and C. parapsilosis growth by 49% and 68%, respectively. Hemolytic activity was evaluated, and the results obtained support the use of the dimeric ester to control C. albicans and C. parapsilosis growth in non-intravenous applications because the compound shows hemolytic activity.

Novel Methodologies for Chemical Activation in Organic Synthesis under Solvent-Free Reaction Conditions.

One central challenge for XXI century chemists is the development of sustainable processes that do not represent a risk either to humanity or to the environment. In this regard, the search for more efficient and clean alternatives to achieve the chemical activation of molecules involved in chemical transformations has played a prominent role in recent years. The use of microwave or UV-Vis light irradiation, and mechanochemical activation is already widespread in many laboratories. Nevertheless, an additional condition to achieve "green" processes comes from the point of view of so-called atom economy. The removal of solvents from chemical reactions generally leads to cleaner, more efficient and more economical processes. This review presents several illustrative applications of the use of sustainable protocols in the synthesis of organic compounds under solvent-free reaction conditions.

PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency.

Genome-scale metabolic reconstructions help us to understand and engineer metabolism. Next-generation sequencing technologies are delivering genomes and transcriptomes for an ever-widening range of plants. While such omic data can, in principle, be used to compare metabolic reconstructions in different species, organs and environmental conditions, these comparisons require a standardized framework for the reconstruction of metabolic networks from transcript data. We previously introduced PlantSEED as a framework covering primary metabolism for 10 species. We have now expanded PlantSEED to include 39 species and provide tools that enable automated annotation and metabolic reconstruction from transcriptome data. The algorithm for automated annotation in PlantSEED propagates annotations using a set of signature k-mers (short amino acid sequences characteristic of particular proteins) that identify metabolic enzymes with an accuracy of about 97%. PlantSEED reconstructions are built from a curated template that includes consistent compartmentalization for more than 100 primary metabolic subsystems. Together, the annotation and reconstruction algorithms produce reconstructions without gaps and with more accurate compartmentalization than existing resources. These tools are available via the PlantSEED web interface at http://modelseed.org, which enables users to upload, annotate and reconstruct from private transcript data and simulate metabolic activity under various conditions using flux balance analysis. We demonstrate the ability to compare these metabolic reconstructions with a case study involving growth on several nitrogen sources in roots of four species.

Geological gas-storage shapes deep life.

Around the world, several dozen deep sedimentary aquifers are being used for storage of natural gas. Ad hoc studies of the microbial ecology of some of them have suggested that sulfate reducing and methanogenic microorganisms play a key role in how these aquifers' communities function. Here, we investigate the influence of gas storage on these two metabolic groups by using high-throughput sequencing and show the importance of sulfate-reducing Desulfotomaculum and a new monophyletic methanogenic group. Aquifer microbial diversity was significantly related to the geological level. The distance to the stored natural gas affects the ratio of sulfate-reducing Firmicutes to deltaproteobacteria. In only one aquifer, the methanogenic archaea dominate the sulfate-reducers. This aquifer was used to store town gas (containing at least 50% H2 ) around 50 years ago. The observed decrease of sulfates in this aquifer could be related to stimulation of subsurface sulfate-reducers. These results suggest that the composition of the microbial communities is impacted by decades old transient gas storage activity. The tremendous stability of these gas-impacted deep subsurface microbial ecosystems suggests that in situ biotic methanation projects in geological reservoirs may be sustainable over time.

Germination and seedling growth of the Chilean native grass Polypogon australis in soil polluted with diesel oil.

The purpose of this study was to evaluate the ability of Polypogon australis, a Chilean native grass that colonizes copper polluted sites, to germinate and grow in soil contaminated with diesel oil. The effect of increasing proportions of diesel in soil (0.5%, 1%, 2%, and 5%) on the cumulative germination and growth of plants was measured. The relative seed germination (RSG), relative root growth (RRG), germination index (GI), and the effective concentration (EC50) were calculated. The cumulative germination in soil polluted with 0%, 0.5%, 1%, and 2% of diesel oil in soil was 93.3%, 85.5%, 99%, and 78.5%, respectively, showing no significant differences between the treatments (p > 0.05). A proportion of 5% of diesel in the soil reduced the germination of P. australis by 50%, compared to the control. The growth of leaves and roots of the plants germinated in 5% of diesel was reduced by 30% compared to the control, with a 34% survival rate observed on day 40. The calculated EC50 of diesel for P. australis was 4.5%. P. australis germinated and grew on all diesel concentration used in the experiments. The species was classified as a tolerant to diesel oil.

Deep ocean prokaryotic communities are remarkably malleable when facing long-term starvation.

The bathypelagic ocean is one of the largest ecosystems on Earth and sustains half of the ocean's microbial activity. This microbial activity strongly relies on surface-derived particles, but there is growing evidence that the carbon released through solubilization of these particles may not be sufficient to meet the energy demands of deep ocean prokaryotes. To explore how bathypelagic prokaryotes respond to the absence of external inputs of carbon, we followed the long-term (1 year) dynamics of an enclosed community. Despite the lack of external energy supply, we observed a continuous succession of active prokaryotic phylotypes, which was driven by recruitment of taxa from the seed bank (i.e., initially rare operational taxonomic units [OTUs]). A single OTU belonging to Marine Group I of Thaumarchaeota, which was originally rare, dominated the microbial community for ∼ 4 months and played a fundamental role in this succession likely by introducing new organic carbon through chemolithoautotrophy. This carbon presumably produced a priming effect, because after the decline of Thaumarchaeota, the diversity and metabolic potential of the community increased back to the levels present at the start of the experiment. Our study demonstrates the profound versatility of deep microbial communities when facing organic carbon deprivation.

Metal contaminations impact archaeal community composition, abundance and function in remote alpine lakes.

Using the 16S rRNA and mcrA genes, we investigated the composition, abundance and activity of sediment archaeal communities within 18 high-mountain lakes under contrasted metal levels from different origins (bedrock erosion, past-mining activities and atmospheric depositions). Bathyarchaeota, Euryarchaeota and Woesearchaeota were the major phyla found at the meta-community scale, representing 48%, 18.3% and 15.2% of the archaeal community respectively. Metals were equally important as physicochemical variables in explaining the assemblage of archaeal communities and their abundance. Methanogenesis appeared as a process of central importance in the carbon cycle within sediments of alpine lakes as indicated by the absolute abundance of methanogen 16S rRNA and mcrA gene transcripts (105 to 109 copies g-1 ). We showed that methanogen abundance and activity were significantly reduced with increasing concentrations of Pb and Cd, two indicators of airborne metal contaminations. Considering the ecological importance of methanogenesis in sediment habitats, these metal contaminations may have system wide implications even in remote area such as alpine lakes. Overall, this work was pioneer in integrating the effect of long-range atmospheric depositions on archaeal communities and indicated that metal contamination might significantly compromise the contribution of Archaea to the carbon cycling of the mountain lake sediments.

High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource.

The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for cross-kingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of model-based assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed.