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Abstract Current climate projections for mid-latitude regions globally indicate an intensification of wind-driven coastal upwelling due to warming conditions. The dynamics of mid-latitude coastal upwelling are marked by environmental variability across temporal scales, which affect key physiological processes in marine calcifying organisms and can impact their large-scale distribution patterns. In this context, marine invertebrates often exhibit phenotypic plasticity, enabling them to adapt to environmental change. In this study, we examined the physiological performance (i.e., metabolism, Thermal Performance Curves, and biomass and calcification rates) of individuals of the intertidal mollusk Chiton granosus, a chiton found from northern Peru to Cape Horn (5° to 55°S). Our spatial study design indicated a pattern of contrasting conditions among locations. The Talcaruca site, characterized by persistent upwelling and serving as a biogeographic break, exhibited lower pH and carbonate saturation states, along with higher pCO2, compared to the sites located to the north and south of this location (Huasco and Los Molles, respectively). In agreement with the spatial pattern in carbonate system parameters, long-term temperature records showed lower temperatures that changed faster over synoptic scales (1–15 days) at Talcaruca, in contrast to the more stable conditions at the sites outside the break. Physiological performance traits from individuals from the Talcaruca population exhibited higher values and more significant variability, along with significantly broader and greater warming tolerance than chitons from the Huasco and Los Molles populations. Moreover, marked changes in local abundance patterns over three years suggested population-level responses to the challenging environmental conditions at the biogeographic break. Thus, C. granosus from the Talcaruca upwelling zone represents a local population with wide tolerance ranges that may be capable of withstanding future upwelling intensification on the Southern Eastern Pacific coast and likely serving as a source of propagules for less adapted populations.

Abstract Background The growing abundance of in vitro omics data, coupled with the necessity to reduce animal testing in the safety assessment of chemical compounds and even eliminate it in the evaluation of cosmetics, highlights the need for adequate computational methodologies. Data from omics technologies allow the exploration of a wide range of biological processes, therefore providing a better understanding of mechanisms of action (MoA) related to chemical exposure in biological systems. However, the analysis of these large datasets remains difficult due to the complexity of modulations spanning multiple biological processes. Results To address this, we propose a strategy to reduce information overload by computing, based on transcriptomics data, a comprehensive metabolic sub-network reflecting the metabolic impact of a chemical. The proposed strategy integrates transcriptomic data to a genome scale metabolic network through enumeration of condition-specific metabolic models hence translating transcriptomics data into reaction activity probabilities. Based on these results, a graph algorithm is applied to retrieve user readable sub-networks reflecting the possible metabolic MoA (mMoA) of chemicals. This strategy has been implemented as a three-step workflow. The first step consists in building cell condition-specific models reflecting the metabolic impact of each exposure condition while taking into account the diversity of possible optimal solutions with a partial enumeration algorithm. In a second step, we address the challenge of analyzing thousands of enumerated condition-specific networks by computing differentially activated reactions (DARs) between the two sets of enumerated possible condition-specific models. Finally, in the third step, DARs are grouped into clusters of functionally interconnected metabolic reactions, representing possible mMoA, using the distance-based clustering and subnetwork extraction method. The first part of the workflow was exemplified on eight molecules selected for their known human hepatotoxic outcomes associated with specific MoAs well described in the literature and for which we retrieved primary human hepatocytes transcriptomic data in Open TG-GATEs. Then, we further applied this strategy to more precisely model and visualize associated mMoA for two of these eight molecules (amiodarone and valproic acid). The approach proved to go beyond gene-based analysis by identifying mMoA when few genes are significantly differentially expressed (2 differentially expressed genes (DEGs) for amiodarone), bringing additional information from the network topology, or when very large number of genes were differentially expressed (5709 DEGs for valproic acid). In both cases, the results of our strategy well fitted evidence from the literature regarding known MoA. Beyond these confirmations, the workflow highlighted potential other unexplored mMoA. Conclusion The proposed strategy allows toxicology experts to decipher which part of cellular metabolism is expected to be affected by the exposition to a given chemical. The approach originality resides in the combination of different metabolic modelling approaches (constraint based and graph modelling). The application to two model molecules shows the strong potential of the approach for interpretation and visual mining of complex omics in vitro data. The presented strategy is freely available as a python module ( https://pypi.org/project/manamodeller/ ) and jupyter notebooks ( https://github.com/LouisonF/MANA ).

A documented checklist of the Crustacea (Stomatopoda, Decapoda) is provided for the southern Guianas region (sGuianas), a homogeneous ecoregion including Guyana, Suriname, French Guiana and the Brazilian State of Amapá. The history of crustacean collections undertaken there between 1759 and 2022 is summarized. In total, 529 species are listed. Biodiversity varies between countries: 165 species in Guyana; 317 in Suriname, 343 in French Guiana, and 315 in Brazil Amapá, as a direct result of different sampling efforts. There are 22 Stomatopoda and 507 Decapoda, ranked by numerical diversity as Brachyura (206), Caridea (113), Anomura (85), Dendrobranchiata (67) and others (36). The list is analyzed with the species classified by major biotopes, distinguishing those from freshwater, mangroves and estuaries, and frankly marine environments. Regional comparisons are made in the Western Atlantic showing that the sGuianas marine fauna is depauperate compared to that of other regions. This is explained by the influence of the Amazon River plume, carrying desalinated water and fine sediments, which leads to the reduction of coral reef formations in sGuianas. Only a few species of freshwater crabs (genera Kunziana and Microthelphusa) are endemic to the region. The pace of species discovery over the years indicates that the sGuianas fauna remains still imperfectly known and that probably more than 600 species are present in the region.

As terabytes of multi-omics data are being generated, there is an ever-increasing need for methods facilitating the integration and interpretation of such data. Current multi-omics integration methods typically output lists, clusters, or subnetworks of molecules related to an outcome. Even with expert domain knowledge, discerning the biological processes involved is a time-consuming activity. Here we propose PathIntegrate, a method for integrating multi-omics datasets based on pathways, designed to exploit knowledge of biological systems and thus provide interpretable models for such studies. PathIntegrate employs single-sample pathway analysis to transform multi-omics datasets from the molecular to the pathway-level, and applies a predictive single-view or multi-view model to integrate the data. Model outputs include multi-omics pathways ranked by their contribution to the outcome prediction, the contribution of each omics layer, and the importance of each molecule in a pathway. Using semi-synthetic data we demonstrate the benefit of grouping molecules into pathways to detect signals in low signal-to-noise scenarios, as well as the ability of PathIntegrate to precisely identify important pathways at low effect sizes. Finally, using COPD and COVID-19 data we showcase how PathIntegrate enables convenient integration and interpretation of complex high-dimensional multi-omics datasets. PathIntegrate is available as an open-source Python package.

Layered double hydroxides (LDHs) are promising because of some of their several interesting characteristics. LDHs can be synthesized using different preparation methods. The application of ultrasounds (US) in the preparation method leads to reduced synthesis times and better dispersion of particles characterized by small size and narrower particle size distribution. Consequently, the specific surface area is higher in US-prepared samples compared to materials prepared by classical methods. These modified characteristics are responsible for improving the performances of LDHs used as catalyst precursors, adsorbents of dyes and heavy metals, fire suppressants, and other applications.

BackgroundEndocrine disrupting chemicals (EDCs) contribute to the etiology of metabolic disorders such as obesity, insulin resistance and hepatic dysfunction. Concern is growing about the consequences of perinatal EDC exposure on disease predisposition later in life. Metabolomics are promising approaches for studying long-term consequences of early life EDC exposure. These approaches allow for the identification and characterization of biomarkers of direct or ancestral exposures that could be diagnostic for individual susceptibility to disease and help to understand mechanisms through which EDCs act.ObjectivesWe sought to identify metabolomic fingerprints in mice ancestrally exposed to the model obesogen tributyltin (TBT), to assess whether metabolomics could discriminate potential trans-generational susceptibility to obesity and recognize metabolic pathways modulated by ancestral TBT exposure.MethodsWe used non-targeted 1H NMR metabolomic analyses of plasma and liver samples collected from male and female mice ancestrally exposed to TBT in two independent transgenerational experiments in which F3 and F4 males became obese when challenged with increased dietary fat.ResultsMetabolomics confirmed transgenerational obesogenic effects of environmentally relevant doses of TBT in F3 and F4 males, in two independent studies. Although females never became obese, their specific metabolomic fingerprint evidenced distinct transgenerational effects of TBT in female mice consistent with impaired capacity for liver biotransformation.DiscussionThis study is the first application of metabolomics to unveil the transgenerational effects of EDC exposure. Very early, significant changes in the plasma metabolome were observed in animals ancestrally exposed to TBT. These changes preceded the onset of obesogenic effects elicited by increased dietary fat in the TBT groups, and which ultimately resulted in significant changes in the liver metabolome. Development of metabolomic fingerprints could facilitate the identification of individuals carrying the signature of ancestral obesogen exposure that might increase their susceptibility to other risk factor such as increased dietary fat.

Metabolic profiling (metabolomics) aims at measuring small molecules (metabolites) in complex samples like blood or urine for human health studies. While biomarker-based assessment often relies on a single molecule, metabolic profiling combines several metabolites to create a more complex and more specific fingerprint of the disease. However, in contrast to genomics, there is no unique metabolomics setup able to measure the entire metabolome. This challenge leads to tedious and resource consuming preliminary studies to be able to design the right metabolomics experiment. In that context, computer assisted metabolic profiling can be of strong added value to design metabolomics studies more quickly and efficiently. We propose a constraint-based modelling approach which predicts in silico profiles of metabolites that are more likely to be differentially abundant under a given metabolic perturbation (e.g. due to a genetic disease), using flux simulation. In genome-scale metabolic networks, the fluxes of exchange reactions, also known as the flow of metabolites through their external transport reactions, can be simulated and compared between control and disease conditions in order to calculate changes in metabolite import and export. These import/export flux differences would be expected to induce changes in circulating biofluid levels of those metabolites, which can then be interpreted as potential biomarkers or metabolites of interest. In this study, we present SAMBA (SAMpling Biomarker Analysis), an approach which simulates fluxes in exchange reactions following a metabolic perturbation using random sampling, compares the simulated flux distributions between the baseline and modulated conditions, and ranks predicted differentially exchanged metabolites as potential biomarkers for the perturbation. We show that there is a good fit between simulated metabolic exchange profiles and experimental differential metabolites detected in plasma, such as patient data from the disease database OMIM, and metabolic trait-SNP associations found in mGWAS studies. These biomarker recommendations can provide insight into the underlying mechanism or metabolic pathway perturbation lying behind observed metabolite differential abundances, and suggest new metabolites as potential avenues for further experimental analyses.

Abstract Background Di-(2-ethylhexyl)-phthalate (DEHP) is a commonly used plasticizer in polyvinylchloride (PVC) formulations and a potentially non-genotoxic carcinogen. The aim of this study was to identify genes whose level of expression is altered by DEHP by using a global wide-genome approach in Syrian hamster embryo (SHE) cells, a model similar to human cells regarding their responses to this type of carcinogen. With mRNA Differential Display (DD), we analysed the transcriptional regulation of SHE cells exposed to 0, 12.5, 25 and 50 μM of DEHP for 24 hrs, conditions which induced neoplastic transformation of these cells. A real-time quantitative polymerase chain reaction (qPCR) was used to confirm differential expression of genes identified by DD. Results Gene expression profiling showed 178 differentially-expressed fragments corresponding to 122 genes after tblastx comparisons, 79 up-regulated and 43 down-regulated. The genes of interest were involved in many biological pathways, including signal transduction, regulation of the cytoskeleton, xenobiotic metabolism, apoptosis, lipidogenesis, protein conformation, transport and cell cycle. We then focused particularly on genes involved in the regulation of the cytoskeleton, one of the processes occurring during carcinogenesis and in the early steps of neoplastic transformation. Twenty one cytoskeleton-related genes were studied by qPCR. The down-regulated genes were involved in focal adhesion or cell junction. The up-regulated genes were involved in the regulation of the actin cytoskeleton and this would suggest a role of cellular plasticity in the mechanism of chemical carcinogenesis. The gene expression changes identified in the present study were PPAR-independent. Conclusion This study identified a set of genes whose expression is altered by DEHP exposure in mammalian embryo cells. This is the first study that elucidates the genomic changes of DEHP involved in the organization of the cytoskeleton. The latter genes may be candidates as biomarkers predictive of early events in the multistep carcinogenic process.

Catalytic total oxidation is an effective technique for the treatment of industrial VOCs principally resulting from industrial processes using solvents and usually containing mono-aromatics (BTEX) and oxygenated compounds (acetone, ethanol, butanone). The aim of this work is to deposit gold nanoparticles on CoAl mixed oxide issued from layered double hydroxide (LDH) precursor by using the deposition precipitation (DP) method, which is applied with two modifications, labeled method (A) and method (B), in order to enhance the interaction of the HAuCl4 precursor with the support. Method (A) involves the hydrolysis of the HAuCl4 precursor after addition of the support, while in method (B), the gold precursor is hydrolyzed before adding the support. The two methods were applied using as support the CoAl mixed oxide and the LDH precursor. Samples were characterized by several physical chemical techniques and evaluated for ethanol total oxidation. Method (B) allowed the ethanol oxidation activity to be enhanced for the resulting Au/CoAlOx catalysts thanks to the high surface concentration of Co2+ and improved reducibility at low temperature. The presence of gold permits to minimize the formation of by-products, notably, methanol, allowed for a total oxidation of ethanol at lower temperature than the corresponding support.

Abstract As holobiont, a plant is intrinsically connected to its microbiomes. However, some characteristics of these microbiomes, such as their taxonomic composition, biological and evolutionary role, and especially the drivers that shape them, are not entirely elucidated. Reports on the microbiota of Arabidopsis thaliana first appeared more than ten years ago. However, there is still a lack of a comprehensive understanding of the vast amount of information that has been generated using this holobiont. The main goal of this review was to perform an in-depth, exhaustive, and systematic analysis of the literature regarding the Arabidopsis–microbiome interaction. A core microbiota was identified as composed of a few bacterial and non-bacterial taxa. The soil (and, to a lesser degree, air) were detected as primary microorganism sources. From the plant perspective, the species, ecotype, circadian cycle, developmental stage, environmental responses, and the exudation of metabolites were crucial factors shaping the plant–microbe interaction. From the microbial perspective, the microbe-microbe interactions, the type of microorganisms belonging to the microbiota (i.e., beneficial or detrimental), and the microbial metabolic responses were also key drivers. The underlying mechanisms are just beginning to be unveiled, but relevant future research needs were identified. Thus, this review provides valuable information and novel analyses that will shed light to deepen our understanding of this plant holobiont and its interaction with the environment.

This interview with Francis Chateauraynaud takes as its starting point his extraordinary ability to move between disciplines, identify areas of epistemic tension, and make links between rationales of reasoning and proof. This interview is, therefore, less concerned with tracing a career chronologically than with presenting possible, and very practical common measures, particularly opening up spaces for discussion: long-term seminars, critical discussions, and also relevant comments in publications. It outlines an interdisciplinarity based on pragmata: actions, things, practices - not slogans. It is not about sticking to “principles” or following what is really happening in theory; it only involves giving precedence to a principle of access and description, through experience.

As the population ages, the global cardiovascular disease burden will continue to increase, particularly among older adults. Increases in life expectancy and better cardiovascular care have significantly reshaped the epidemiology of cardiovascular disease and have created new patient profiles. The combination of older age, multiple comorbidities, polypharmacy, frailty, and adverse noncardiovascular outcomes is challenging our routine clinical practice in this field. In this review, we examine noncardiovascular factors that statistically interact in a relevant way with health status and quality of life in older people with cardiovascular disease. We focused on specific geriatric conditions (multimorbidity, polypharmacy, geriatric syndromes, and frailty) that are responsible for a major risk of functional decline and have an important impact on the overall prognosis in this patient population.

Phosphorus (as phosphate, Pi) and iron (Fe) are critical nutrients in plants that are often poorly available in the soil and can be microbially affected. This work aimed to evaluate how plant-rhizobacteria interaction changes due to different Pi or Fe nutritional scenarios and to study the underlying molecular mechanisms of the microbial modulation of these nutrients in plants. Thus, three proteobacteria (Paraburkholderia phytofirmans PsJN, Azospirillum brasilense Sp7, and Pseudomonas putida KT2440) were used to inoculate Arabidopsis seeds. Additionally, the seeds were exposed to a nutritional factor with the following levels for each nutrient: sufficient (control) or low concentrations of a highly soluble source or sufficient concentrations of a low solubility source. Then, the effects of the combinatorial factors were assessed in plant growth, nutrition, and genetic regulation. Interestingly, some bacterial effects in plants depended on the nutrient source (e.g., increased aerial zones induced by the strains), and others (e.g., decreased primary roots induced by Sp7 or KT2440) occurred regardless of the nutritional treatment. In the short-term, PsJN had detrimental effects on plant growth in the presence of the low-solubility Fe compound, but this was not observed in later stages of plant development. A thorough regulation of the phosphorus content was detected in plants independent of the nutritional treatment. Nevertheless, inoculation with KT2440 increased P content by 29% Pi-deficiency exposed plants. Conversely, the inoculation tended to decrease the Fe content in plants, suggesting a competition for this nutrient in the rhizosphere. The P-source also affected the effects of the PsJN strain in a double mutant of the phosphate starvation response (PSR). Furthermore, depending on the nutrient source, PsJN and Sp7 strains differentially regulated PSR and IAA- associated genes, indicating a role of these pathways in the observed differential phenotypical responses. In the case of iron, PsJN and SP7 regulated iron uptake-related genes regardless of the iron source, which may explain the lower Fe content in inoculated plants. Overall, the plant responses to these proteobacteria were not only influenced by the nutrient concentrations but also by their availabilities, the elapsed time of the interaction, and the specific identities of the beneficial bacteria.Graphical AbstractThe effects of the different nutritional and inoculation treatments are indicated for plant growth parameters (A), gene regulation (B) and phosphorus and iron content (C). Figures created with BioRender.com with an academic license.

BackgroundThe pathophysiology of persistent atrial fibrillation (AF) remains unclear. While several studies have demonstrated an association between myocardial infarction and atrial fibrillation, the role of stable coronary artery disease (CAD) is still unknown. As a result, we aimed to assess the association between CAD obstruction and AF recurrence after persistent AF ablation in patients with no history of CAD.Materials and methodsThis observational retrospective study included consecutive patients who underwent routine preprocedural cardiac computed tomography (CCT) before persistent AF ablation between September 2015 and June 2018 in 5 European University Hospitals. Exclusion criteria were CAD or coronary revascularization previously known or during follow-up. Obstructive CAD was defined as luminal stenosis ≥ 50%.ResultsAll in all, 496 patients (mean age 61.8 ± 10.0 years, 76.2% males) were included. CHA2DS2–VASc score was 0 or 1 in 225 (36.3%) patients. Obstructive CAD was present in 86 (17.4%) patients. During the follow-up (24 ± 19 months), 207 (41.7%) patients had AF recurrence. The recurrence rate was not different between patients with and without obstructive CAD (43.0% vs. 41.5%, respectively; P = 0.79). When considering the location of the stenosis, the recurrence rate was higher in the case of left circumflex obstruction: 56% vs. 32% at 2 years (log-rank P ≤ 0.01). After Cox multivariate analysis, circumflex artery obstruction (HR 2.32; 95% CI 1.36–3.98; P < 0.01) was independently associated with AF recurrence.ConclusionCircumflex artery obstruction detected with CCT was independently associated with 2-fold increase in the risk of AF recurrence after persistent AF ablation. Further research is necessary to evaluate this pathophysiological relationship.

Abstract Plants must deal with harsh environmental conditions when colonizing abandoned copper mine tailings. We hypothesized that the presence of a native microbial community can improve the colonization of the pioneer plant, Baccharis linearis, in soils from copper mining tailings. Plant growth and microbial community compositions and dynamics were determined in cultivation pots containing material from two abandoned copper mining tailings (Huana and Tambillos) and compared with pots containing fresh tailings or surrounding agricultural soil. Controls without plants or using irradiated microbe-free substrates, were also performed. Results indicated that bacteria (Actinobacteria, Gammaproteobacteria, and Firmicutes groups) and fungi (Glomus genus) are associated with B. linearis and may support plant acclimation, since growth parameters decreased in both irradiated (transiently without microbial community) and fresh tailing substrates (with a significantly different microbial community). Consistently, the composition of the bacterial community from abandoned copper mining tailings was more impacted by plant establishment than by differences in the physicochemical properties of the substrates. Bacteria located at B. linearis rhizoplane were clearly the most distinct bacterial community compared with those of fresh tailings, surrounding soil and non-rhizosphere abandoned tailings substrates. Beta diversity analyses showed that the rhizoplane bacterial community changed mainly through species replacement (turnover) than species loss (nestedness). In contrast, location/geographical conditions were more relevant than interaction with the plants, to explain fungal community differences.

In the present paper, we compare the activity, selectivity, and stability of a supported nickel catalyst in classical heating conditions and in magnetically activated catalysis by using iron wool as a heating agent. The catalyst, 5 wt% Ni supported on titania (Degussa P25), was prepared via an organometallic decomposition method and was thoroughly characterized by using elemental, microscopic, and diffraction techniques. In the event of magnetic induction heating, the % CO2 conversion reached a maximum of ~85% compared to ~78% for thermal conditions at a slightly lower temperature (~335 °C) than the thermal heating (380 °C). More importantly, both processes were found to be stable for 45 h on stream. Moreover, the effects of magnetic induction and classical heating over the catalyst evolution were discussed. This study demonstrated the potential of magnetic heating-mediated methanation, which is currently under investigation for the development of pilot-scale reactors.

Background: Endocrine disrupting chemicals (EDCs) contribute to the etiology of metabolic disorders such as obesity, insulin resistance and hepatic dysfunction. Concern is growing about the consequences of perinatal EDC exposure on disease predisposition later in life. Metabolomics are promising approaches for studying long-term consequences of early life EDC exposure. These approaches allow for the identification and characterization of biomarkers of direct or ancestral exposures that could be diagnostic for individual susceptibility to disease and help to understand mechanisms through which EDCs act. Objectives: We sought to identify metabolomic fingerprints in mice ancestrally exposed to the model obesogen tributyltin (TBT), to assess whether metabolomics could discriminate potential trans-generational susceptibility to obesity and recognize metabolic pathways modulated by ancestral TBT exposure. Methods: We used non-targeted 1H NMR metabolomic analyses of plasma and liver samples collected from male and female mice ancestrally exposed to TBT in two independent transgenerational experiments in which F3 and F4 males became obese when challenged with increased dietary fat. Results: Metabolomics confirmed transgenerational obesogenic effects of environmentally relevant doses of TBT in F3 and F4 males, in two independent studies. Although females never became obese, their specific metabolomic fingerprint evidenced distinct transgenerational effects of TBT in female mice consistent with impaired capacity for liver biotransformation. Discussion: This study is the first application of metabolomics to unveil the transgenerational effects of EDC exposure. Very early, significant changes in the plasma metabolome were observed in animals ancestrally exposed to TBT. These changes preceded the onset of obesogenic effects elicited by increased dietary fat in the TBT groups, and which ultimately resulted in significant changes in the liver metabolome. Development of metabolomic fingerprints could facilitate the identification of individuals carrying the signature of ancestral obesogen exposure that might increase their susceptibility to other risk factor such as increased dietary fat.

Chalcogenide glasses are widely used as sensitive membranes in the chemical sensors for heavy metal ions detection. The lack of research work on sodium ion-selective electrodes (Na+-ISEs) based on chalcogenide glasses is due to the high hygroscopicity of alkali dopes chalcogenides. However, sodium halide doped Ga2S3-GeS2 glasses are more chemically stable in water and could be used as Na+-sensitive membranes for the ISEs. In this work we have studied the physico-chemical properties of mixed cation (AgI)x(NaI)30-x(Ga2S3)26(GeS2)44 chalcogenide glasses (where x = 0, 7.5, 15, 22.5 and 30 mol.% AgI) using density, DSC, and conductivity measurements. The mixed cation effect with shallow conductivity and glass transition temperature minimum was found for silver fraction r = Ag/(Na + Ag) ≈ 0.5. Silver addition decreases the moisture resistance of the glasses. Only (AgI)22.5(NaI)7.5(Ga2S3)26(GeS2)44 composition was suitable for chemical sensors application, contrary to the single cation sodium halide doped Ga2S3-GeS2 glasses, where 15 mol.% sodium-halide-containing vitreous alloys are stable in water solutions. The analytical parameters of (NaCl)15(Ga2S3)23(GeS2)62; (NaI)15(Ga2S3)23(GeS2)62 and (AgI)22.5(NaI)7.5(Ga2S3)26(GeS2)44 glass compositions as active membranes in Na+-ISEs were investigated, including detection limit, sensitivity, linearity, ionic selectivity (in the presence of K+, Mg2+, Ca2+, Ba2+, and Zn2+ interfering cations), reproducibility and optimal pH-range.

Background: Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis. Methods: A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men. Findings: We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…). Interpretation: These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS.

Synthetic microbial communities (SynComs) are a useful tool for a more realistic understanding of the outcomes of multiple biotic interactions where microbes, plants, and the environment are players in time and space of a multidimensional and complex system. Toward a more in-depth overview of the knowledge that has been achieved using SynComs in the rhizosphere, a systematic review of the literature on SynComs was performed to identify the overall rationale, design criteria, experimental procedures, and outcomes of in vitro or in planta tests using this strategy. After an extensive bibliography search and a specific selection process, a total of 30 articles were chosen for further analysis, grouping them by their reported SynCom size. The reported SynComs were constituted with a highly variable number of members, ranging from 3 to 190 strains, with a total of 1,393 bacterial isolates, where the three most represented phyla were Proteobacteria, Actinobacteria, and Firmicutes. Only four articles did not reference experiments with SynCom on plants, as they considered only microbial in vitro studies, whereas the others chose different plant models and plant-growth systems; some of them are described and reviewed in this article. Besides, a discussion on different approaches (bottom-up and top-down) to study the microbiome role in the rhizosphere is provided, highlighting how SynComs are an effective system to connect and fill some knowledge gaps and to have a better understanding of the mechanisms governing these multiple interactions. Although the SynCom approach is already helpful and has a promising future, more systematic and standardized studies are needed to harness its full potential.

Ocean Acidification (OA) can have pervasive effects in calcifying marine organisms, and a better understanding of how different populations respond at the physiological and evolutionary level could help to model the impacts of global change in marine ecosystems. Due to its natural geography and oceanographic processes, the Chilean coast provides a natural laboratory where benthic organisms are frequently exposed to diverse projected OA scenarios. The goal of this study was to assess whether a population of mollusks thriving in a more variable environment (Talcaruca) would present higher phenotypic plasticity in physiological and morphological traits in response to different pCO2 when compared to a population of the same species from a more stable environment (Los Molles). To achieve this, two benthic limpets (Scurria zebrina and Scurria viridula) inhabiting these two contrasting localities were exposed to ocean acidification experimental conditions representing the current pCO2 in the Chilean coast (500 μatm) and the levels predicted for the year 2100 in upwelling zones (1500 (μatm). Our results show that the responses to OA are species-specific, even in this related species. Interestingly, S. viridula showed better performance under OA than S. zebrina (i.e., similar sizes and carbonate content in individuals from both populations; lower effects of acidification on the growth rate combined with a reduction of metabolism at higher pCO2). Remarkably, these characteristics could explain this species’ success in overstepping the biogeographical break in the area of Talcaruca, which S. zebrina cannot achieve. Besides, the results show that the habitat factor has a strong influence on some traits. For instance, individuals from Talcaruca presented a higher growth rate plasticity index and lower shell dissolution rates in acidified conditions than those from Los Molles. These results show that limpets from the variable environment tend to display higher plasticity, buffering the physiological effects of OA compared with limpets from the more stable environment. Taken together, these findings highlight the key role of geographic variation in phenotypic plasticity to determine the vulnerability of calcifying organisms to future scenarios of OA.

The correct identification of metabolic activity in tissues or cells under different conditions can be extremely elusive due to mechanisms such as post-transcriptional modification of enzymes or different rates in protein degradation, making difficult to perform predictions on the basis of gene expression alone. Context-specific metabolic network reconstruction can overcome some of these limitations by leveraging the integration of multi-omics data into genome-scale metabolic networks (GSMN). Using the experimental information, context-specific models are reconstructed by extracting from the generic GSMN the sub-network most consistent with the data, subject to biochemical constraints. One advantage is that these context-specific models have more predictive power since they are tailored to the specific tissue, cell or condition, containing only the reactions predicted to be active in such context. However, an important limitation is that there are usually many different sub-networks that optimally fit the experimental data. This set of optimal networks represent alternative explanations of the possible metabolic state. Ignoring the set of possible solutions reduces the ability to obtain relevant information about the metabolism and may bias the interpretation of the true metabolic states. In this work we formalize the problem of enumerating optimal metabolic networks and we introduce DEXOM, an unified approach for diversity-based enumeration of context-specific metabolic networks. We developed different strategies for this purpose and we performed an exhaustive analysis using simulated and real data. In order to analyze the extent to which these results are biologically meaningful, we used the alternative solutions obtained with the different methods to measure: 1) the improvement of in silico predictions of essential genes in Saccharomyces cerevisiae using ensembles of metabolic network; and 2) the detection of alternative enriched pathways in different human cancer cell lines. We also provide DEXOM as an open-source library compatible with COBRA Toolbox 3.0, available at https://github.com/MetExplore/dexom.

Malgré des recommandations unanimes des sociétés savantes internationales, nationales et de la Haute Autorité de santé en 2017 pour privilégier un traitement des infections à Helicobacter pylori guidé par un test de sensibilité réalisé à partir de biopsies gastriques, la quasi totalité des patients traités reçoivent encore un traitement empirique mal toléré et source du développement continu depuis quarante ans de la résistance de cette bactérie aux antibiotiques. Il est temps que généralistes, gastro-entérologues et biologistes se coordonnent et se mobilisent pour promouvoir le traitement guidé de l'infection bactérienne chronique la plus fréquente et entrent ainsi dans une démarche de bon usage des antibiotiques. Le remboursement récent de la PCR détectant H. pylori et les mutations responsables de la résistance à la clarithromycine devrait lever un des freins à cette stratégie du traitement guidé. Nous proposons un nouvel algorithme de prise en charge de ces infections tenant compte des remboursements accordés. Des progrès technologiques récents permettent déjà d'imaginer un futur intégrant des tests de sensibilité à partir d'un prélè-vement non invasif de selles, en épargnant de nombreuses fibroscopies inutiles à une époque où le recourt au gastro- entérologue est difficile. Pour cet avenir proche, nous proposons un nouvel algorithme de ce que sera le travail coordonné des généralistes, des gastro-entérologues et des biologistes. Despite unanimous recommendations from international and national scientific societies and the HAS in 2017 to favor treatment of Helicobacter pylori infections guided by a sensitivity test carried out from gastric biopsies, almost all of the treated patients still receive empirical treatment poorly tolerated and source of the continuous development over forty years of the resistance of this bacteria to antibiotics. It is time for General Practitioners, Gastroenterologists and Biologists to coordinate and mobilize to promote the guided treatment of the most common chronic bacterial infection and thus enter into a process of proper use of antibiotics. The recent reimbursement of PCR detecting H. pylori and the mutations responsible for resistance to clarithromycin should remove one of the obstacles to this guided treatment strategy. We propose a new management algorithm for these infections taking into account the reimbursements recently obtained. Recent technological advances already make it possible to imagine a future integrating sensitivity tests from a non-invasive sample: stools, saving numerous unnecessary fiberoscopies at a time when recourse to a gastroenterologist is difficult. For this near future we propose a new algorithm of what will be the coordinated work of general practitioners, gastroenterologists and biologists. [ABSTRACT FROM AUTHOR]

Plant defense responses to biotic stresses are complex biological processes, all governed by sophisticated molecular regulations. Induced systemic resistance (ISR) is one of these defense mechanisms where beneficial bacteria or fungi prime plants to resist pathogens or pest attacks. In ISR, the defense arsenal in plants remains dormant and it is only triggered by an infection, allowing a better allocation of plant resources. Our group recently described that the well-known beneficial bacterium Paraburkholderia phytofirmans PsJN is able to induce Arabidopsis thaliana resistance to Pseudomonas syringae pv. tomato (Pst) DC3000 through ISR, and that ethylene, jasmonate and salicylic acid are involved in this protection. Nevertheless, the molecular networks governing this beneficial interaction remain unknown. To tackle this issue, we analyzed the temporal changes in the transcriptome of PsJN-inoculated plants before and after being infected with Pst DC3000. These data were used to perform a gene network analysis to identify highly connected transcription factors. Before the pathogen challenge, the strain PsJN regulated 405 genes (corresponding to 1.8% of the analyzed genome). PsJN-inoculated plants presented a faster and stronger transcriptional response at 1-hour post infection (hpi) compared with the non-inoculated plants, which presented the highest transcriptional changes at 24 hpi. A principal component analysis showed that PsJN-induced plant responses to the pathogen could be differentiated from those induced by the pathogen itself. Forty-eight transcription factors were regulated by PsJN at 1 hpi, and a system biology analysis revealed a network with four clusters. Within these clusters LHY, WRKY28, MYB31 and RRTF1 are highly connected transcription factors, which could act as hub regulators in this interaction. Concordantly with our previous results, these clusters are related to jasmonate, ethylene, salicylic, acid and ROS pathways. These results indicate that a rapid and specific response of PsJN-inoculated plants to the virulent DC3000 strain could be the pivotal element in the protection mechanism.