In comparison with northern countries, limited data are available on the occurrence and potential toxicity of cyanobacterial blooms in lakes and ponds in sub-Saharan countries. With the aim of enhancing our knowledge on cyanobacteria and their toxins in Africa, we performed a 17-month monitoring of a freshwater ecosystem, Lagoon Aghien (Ivory Coast), which is used for multiple practices by riverine populations and for drinking water production in Abidjan city. The richness and diversity of the cyanobacterial community were high and displayed few variations during the entire survey. The monthly average abundances ranged from 4.1 × 104 to 1.8 × 105 cell mL-1, with higher abundances recorded during the dry seasons. Among the five cyanotoxin families analyzed (anatoxin-a, cylindrospermopsin, homoanatoxin, microcystins, saxitoxin), only microcystins (MC) were detected with concentrations ranging from 0 to 0.364 μg L-1 in phytoplankton cells, from 32 to 1092 μg fresh weight (FW) kg-1 in fish intestines, and from 33 to 383 μg FW kg-1 in fish livers. Even if the MC concentrations in water and fish are low, usually below the thresholds defined in WHO guidelines, these data raise the issue of the relevance of these WHO guidelines for sub-Saharan Africa, where local populations are exposed throughout the year to these toxins in multiple ways.

Interdependent metabolic and transport processes of carbon (C) and nitrogen (N) regulate plant growth and development, while the regulatory pathways remain poorly defined. We previously reported that rice circadian clock N-mediated heading date-1 (Nhd1) regulates growth duration-dependent N use efficiency. Here, we report that knockout of Nhd1 in rice reduced the rate of photosynthesis and the sucrose ratio of sheaths to blades, but increased the total C to N ratio and free amino acids. Leaf RNA-seq analysis indicated that mutation of Nhd1 dramatically altered expression of the genes linked to starch and sucrose metabolism, circadian rhythm, and amino acid metabolic pathways. We identified that Nhd1 can directly activate the transcriptional expression of sucrose transporter-1 (OsSUT1). Knockout of Nhd1 suppressed OsSUT1 expression, and both nhd1 and ossut1 mutants showed similar shorter height, and lower shoot biomass and sucrose concentration in comparison with the wild type, while overexpression of OsSUT1 can restore the defective sucrose transport and partially ameliorate the reduced growth of nhd1 mutants. The Nhd1-binding site of the OsSUT1 promoter is conserved in all known rice genomes. The positively related variation of Nhd1 and OsSUT1 expression among randomly selected indica and japonica varieties suggests a common regulatory module of Nhd1-OsSUT1-mediated C and N balance in rice.

Abstract Acetic acid bacteria (AAB) can selectively oxidize diols into their corresponding hydroxyacids. Notably, they can convert 1,3-propanediol (1,3-PDO) into 3-hydroxypropionic acid (3-HP), which is a promising building-block. Until now, 3-HP production with AAB is carried out in batch and using resting cells at high cell densities (up to 10 g L− 1 of cell dry weight). This approach is likely limited by detrimental accumulation of the intermediate 3-hydroxypropanal (3-HPA). Herein, we investigate an alternative implementation that allows highly efficient 3-HP production with lower cell densities of growing cells and that prevents 3-HPA accumulation. First, growth and 3-HP production of Acetobacter sp. CIP 58.66 were characterized with 1,3-PDO or glycerol as growth substrate. The strain was then implemented in a bioreactor, during a sequential process where it was first cultivated on glycerol, then the precursor 1,3-PDO was continuously supplied at a varying rate, easily controlled by the pH control. Different pH set points were tested (5.0, 4.5, and 4.0). This approach used the natural resistance of acetic acid bacteria to acidic conditions. Surprisingly, when pH was controlled at 5.0, the performances achieved in terms of titer (69.76 g3 − HP L− 1), mean productivity (2.80 g3 − HP L− 1 h− 1), and molar yield (1.02 mol3 − HP mol− 11,3−PDO) were comparable to results obtained with genetically improved strains at neutral pH. The present results were obtained with comparatively lower cell densities (from 0.88 to 2.08 g L− 1) than previously reported. This feeding strategy could be well-suited for future scale-up, since lower cell densities imply lower process costs and energy needs.

Abstract The evaluation of soil quality requires the use of robust methods to assess biologically based-indicators. Among them, enzyme activities are used for several decades, but there is a clear need to update their measurement methods for routine use, in combining feasibility, accuracy and reliability. To this end, the platform Biochem-Env optimised a miniaturised method to measure enzyme activities in soils using colorimetric substrates in micro-well plates. The standardization of the method was carried out within the framework of ISO/TC 190/SC 4/WG 4 "Soil quality – Biological methods” workgroup, recommending an inter-laboratory evaluation for the publication of a full ISO standard.That evaluation, managed by the platform, was based on the measurement, in six soils of contrasted physicochemical properties, of the ten soil enzyme activities described in the standard. Eight laboratories were involved in the validation study. Only 2.7% of outliers were identified from the analyses of the whole dataset. The repeatability and reproducibility of the method were determined by computing, respectively, the intra-laboratory (CVr,) and inter-laboratory (CVR) coefficients of variation for each soil and enzyme. The mean CVr ranged from 4.5% (Phosphatase) to 9.9% (αGlucosidase), illustrating a reduced variability of enzyme activities within laboratories. The mean CVR ranged from 13.8% (Alkaline Phosphatase) to 30.9% (Phosphatase).Nevertheless, the method was repeatable, reproducible and sensitive. It also proved to be applicable for measuring enzyme activities in different types of soils. These results have been found successful by ISO/TC 190/SC4 and resulted in the publication of ISO 20130:2018 standard.

Abstract Nanocelluloses occur under various crystalline forms that are being selectively used for a wide variety of high performance materials. In the present work, cellulose fibers (CF-I) were mercerized by alkaline treatment (CF-II) without molar mass variation (560 000 g/mol) and both were acid hydrolyzed, forming cellulose nanocrystals in native (CNC-I) and mercerized (CNC-II) forms. This work establishes detailed characterization of these two nanoparticles morphology (light and neutron scattering, TEM, AFM), surface chemistry (zetametry and surface charge), crystallinity (XRD, 13C NMR), and average molar mass coupled to chromatographic technics (SEC-MALLS-RI, A4F-MALLS-RI), evidencing variations in packing of the crystalline domains. The crystal size of CNC-II is reduced by half compared to CNC-I, with molar masses of individual chains of 41 000 g/mol and 22 000 g/mol for CNC-I and CNC-II respectively, whereas the same charged surface chemistry is measured. This fundamental analysis may give insight to new applicative development.

Abstract Methotrexate is an antineoplastic folate analog of high environmental concern, due to its low biodegradability and toxicological properties. This study focused on its photodegradation under two irradiation conditions, aiming to be representative of environment (300–450 nm) and drinking water treatment (254 nm). The photodegradation experiments were conducted at two pH, to vary the methotrexate ionization state and to produce a large variety of transformation products (TPs). The degradation kinetics determined through LC-UV monitoring were contrasted according to pH and irradiation wavelength. However, the quantum yields were independent of ionization state at 254 nm and the changes in kinetics at higher wavelengths were attributed to a change in the degradation mechanism. The TPs formed during the reactions were identified by UHPLC-MS/MS, using both the positive and negative modes. Among the eleven proposed structures, five were described as methotrexate TPs for the first time. The TPs result from N-demethylation, glutamic acid oxidation and C-N cleavage, all of them leading to further degraded photoproducts presenting modified or lost glutamic acid part. This was made possible thanks to the negative mode, which allowed the exploration of the glutamic acid moiety modifications. Cytotoxicity assessment on A549 cancer cells demonstrated that all photoproducts formed at pH 7 were less toxic than the parent compound.

Abstract BackgroundTermites account for natural biomass utilization systems (NBUS) that evolved the ability to overcome the overall recalcitrance of lignins towards lignocellulose transformation processes. With the objective of applying this capacity to the conversion of technical lignins produced by biorefineries, a higher wood-feeding termite species, Nasutitermes ephratae was fed with a commercial grass soda lignin (Protobind 1000, PB1000). The survival rates of Protobind 1000-fed termites were determined as well as changes in the structure of gut bacterial community and in the chemical composition of this technical lignin. ResultsThe ingestion of PB1000 by worker castes of N. ephratae was revealed by Pyrolysis-Gas Chromatography Mass Spectrometry (Py-GC/MS) analyses directly performed on termites. Survival rates were reduced by two –fold in the termites fed with PB1000 compared to controls. The relative abundance of Firmicutes and Bacteroidetes increased in the gut bacterial community of termites fed with PB1000. The digestion of PB1000 by termites triggered an increase in the syringyl-to-guaiacyl (S/G) ratios. These changes in the chemical composition of PB1000 in the gut of termites was marked by a decrease in relative content of free phenolic monomers.ConclusionThis work showed the abilities of digestive tract of a wood-feeding higher termite species, N. ephratae to metabolize the fraction of the volatile phenolic monomers of PB1000. Overall, our results provide insights into the bacterial lineage candidates for development of bacterial inoculum for pretreatment processes in valorization of technical lignin in biorefinery.

Abstract Background RNAseq is nowadays the method of choice for transcriptome analysis. In the last decades, a high number of statistical methods, and associated bioinformatics tools, for RNAseq analysis were developed. More recently, statistical studies realised neutral comparison studies using benchmark datasets, shedding light on the most appropriate approaches for RNAseq data analysis. Results DiCoExpress is a script-based tool implemented in R that includes methods chosen based on their performance in neutral comparisons studies. DiCoExpress uses pre-existing R packages including FactoMineR, edgeR and coseq , to perform quality control, differential, and co-expression analysis of RNAseq data. Users can perform the full analysis, providing a mapped read expression data file and a file containing the information on the experimental design. Following the quality control step, the user can move on to the differential expression analysis performed using generalized linear models thanks to the automated contrast writing function. A co-expression analysis is implemented using the coseq package. Lists of differentially expressed genes and identified co-expression clusters are automatically analyzed for enrichment of annotations provided by the user . We used DiCoExpress to analyze a publicly available RNAseq dataset on the transcriptional response of Bra ssica napus L. to silicon treatment in plant roots and mature leaves . This dataset, including two biological factors and three replicates for each condition, allowed us to demonstrate in a tutorial all the features of DiCoExpress. Conclusions DiCoExpress is an R script-based tool allowing users to perform a full RNAseq analysis from quality controls to co-expression analysis through differential analysis based on contrasts inside generalized linear models . DiCoExpress focuses on the statistical modelling of gene expression according to the experimental design and facilitates the data analysis leading the biological interpretation of the results.

Abstract Background RNAseq is nowadays the method of choice for transcriptome analysis. In the last decades, a high number of statistical methods, and associated bioinformatics tools, for RNAseq analysis were developed. More recently, statistical studies realized neutral comparison studies using benchmark datasets, shedding light on the most appropriate approaches for RNAseq data analysis. Nevertheless, performing an RNAseq analysis remains a challenge for the biologists. Results DiCoExpress is a workspace implemented in R that includes methods chosen based on their performance in neutral comparisons studies. DiCoExpress uses the pre-existing R packages as well as FactoMineR, edgeR and coseq, to perform quality control, differential, and co-expression analysis of RNAseq data. Users can perform the full analysis, providing a mapped read expression data file and a file containing the information on the experimental design. Following the quality control step, the user can move on to the differential expression analysis performed using generalized linear models with no effort thanks to the automated contrast writing function. DiCoExpress proposes a list of comparisons based on the experimental design, and the user needs only to choose the one(s) of interest for his research question. A co-expression analysis is implemented using the coseq package. Identified co-expression clusters are automatically analyzed for enrichment of annotations provided by the user, and several result outputs proposed. We used DiCoExpress to analyze a publicly available Bra ssica napus L. RNAseq dataset on the transcriptional response to silicon treatment in plant roots and mature leaves. This dataset, including two biological factors and three replicates for each condition, allowed us to demonstrate in a tutorial all the features of DiCoExpress. Conclusions DiCoExpress is an R workspace to allow users without advanced statistical knowledge and programming skills to perform a full RNAseq analysis from quality controls to co-expression analysis through differential analysis based on contrasts inside generalized linear models . Hence, with DiCoExpress, the user can focus on the statistical modeling of gene expression according to the experimental design and on the interpretation of the results of such analysis in biological terms.