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Rhamnlopids are biosurfactants with a wide range of industrial applications. The understanding of their biosynthesis and the genetic regulation of their production have impacted the development of strains that are suitable for industrial production of these biosurfactants. Summary Rhamnolipids are biosurfactants with a wide range of industrial applications that entered into the market a decade ago. They are naturally produced by Pseudomonas aeruginosa and some Burkholderia species. Occasionally, some strains of different bacterial species, like Pseudomonas chlororaphis NRRL B‐30761, which have acquired RL‐producing ability by horizontal gene transfer, have been described. P. aeruginosa, the ubiquitous opportunistic pathogenic bacterium, is the best rhamnolipids producer, but Pseudomonas putida has been used as heterologous host for the production of this biosurfactant with relatively good yields. The molecular genetics of rhamnolipids production by P. aeruginosa has been widely studied not only due to the interest in developing overproducing strains, but because it is coordinately regulated with the expression of different virulence‐related traits by the quorum‐sensing response. Here, we highlight how the research of the molecular mechanisms involved in rhamnolipid production have impacted the development of strains that are suitable for industrial production of this biosurfactant, as well as some perspectives to improve these industrial useful strains.

Arsenic metabolism is proposed to be an ancient mechanism in microbial life. Different bacteria and archaea use detoxification processes to grow under high arsenic concentration. Some of them are also able to use arsenic as a bioenergetic substrate in either anaerobic arsenate respiration or chemolithotrophic growth on arsenite. However, among the archaea, bioenergetic arsenic metabolism has only been found in the Crenarchaeota phylum. Here we report the discovery of haloarchaea (Euryarchaeota phylum) biofilms forming under the extreme environmental conditions such as high salinity, pH and arsenic concentration at 4589 m above sea level inside a volcano crater in Diamante Lake, Argentina. Metagenomic analyses revealed a surprisingly high abundance of genes used for arsenite oxidation ( aioBA ) and respiratory arsenate reduction ( arrCBA ) suggesting that these haloarchaea use arsenic compounds as bioenergetics substrates. We showed that several haloarchaea species, not only from this study, have all genes required for these bioenergetic processes. The phylogenetic analysis of aioA showed that haloarchaea sequences cluster in a novel and monophyletic group, suggesting that the origin of arsenic metabolism in haloarchaea is ancient. Our results also suggest that arsenite chemolithotrophy likely emerged within the archaeal lineage. Our results give a broad new perspective on the haloarchaea metabolism and shed light on the evolutionary history of arsenic bioenergetics.

Pomacea canaliculata is a freshwater snail native to southern South America. The aims of this work are to update its distribution in Argentina and to analyze through niche models whether the environmental conditions from its original distribution can anticipate its recently expanded range. Almost all records of P. canaliculata before 1958 (original records) belong to del Plata or connected basins. A quarter of the new present records are located in basins not connected to del Plata, indicating a recent expansion of the distribution range of P. canaliculata in Argentina. Recently colonized areas are mostly environmentally suitable according to the projection of the original distribution model, thus natural barriers were probably the main limits to its distribution in the past. According to the model, many regions outside its original range, including several not yet colonized, are suitable for the establishment of P. canaliculata. Consequently, it is likely that this species will continue establishing new populations in Argentina, especially if fishermen and aquarists continue to move snails to new locations. Our study revealed that an extensive but overlooked invasion is in process in its native range, where the impacts on diversity and ecosystems functioning may differ from those already described elsewhere.

Biological invasions represent one of the major threats to biodiversity. The apple snail Pomacea canaliculata is a South American freshwater snail that was introduced in many regions around the world, becoming a successful invader. In this work, we provide an updated and accurate database of P. canaliculata records worldwide, test the realized niche shift between native and invaded regions, and perform current and future ecological niche models. Records were retrieved from sampling data, scientific literature, biodiversity databases, and communication with researchers with expertise in apple snails. The niche of P. canaliculata substantially changed between its native range and its invaded ranges in Asia and the rest of America. Current and future suitability were modeled, considering both native and invaded records, to reflect all environmental conditions where snails’ populations can establish. Many temperate, subtropical, and tropical regions around the world are currently suitable, many are already inhabited, and others not colonized yet. Niche models predict that in the next 80 years, suitable areas would retract more than they expand on a global scale, with the worst scenario of climate change promoting the greatest changes. Most of the predicted changes would be the retraction in South America, Africa, and Australia and the expansion toward higher latitudes, especially to northern Patagonia, northern USA, and central Europe. Niche shifts can be the result of limitations in dispersal, changes in biotic interactions, or adaptation to new climatic environments. Standardized evaluations across native and invaded ranges are needed to understand the role of contemporary evolution in the niche expansion and life history changes of P. canaliculata and its invasion success.

Background: Inappropriate taxon definitions may have severe consequences in many areas. For instance, biologically sensible species delimitation of plant pathogens is crucial for measures such as plant protection or biological control and for comparative studies involving model organisms. However, delimiting species is challenging in the case of organisms for which often only molecular data are available, such as prokaryotes, fungi, and many unicellular eukaryotes. Even in the case of organisms with well-established morphological characteristics, molecular taxonomy is often necessary to emend current taxonomic concepts and to analyze DNA sequences directly sampled from the environment. Typically, for this purpose clustering approaches to delineate molecular operational taxonomic units have been applied using arbitrary choices regarding the distance threshold values, and the clustering algorithms. Methodology: Here, we report on a clustering optimization method to establish a molecular taxonomy of Peronospora based on ITS nrDNA sequences. Peronospora is the largest genus within the downy mildews, which are obligate parasites of higher plants, and includes various economically important pathogens. The method determines the distance function and clustering setting that result in an optimal agreement with selected reference data. Optimization was based on both taxonomy-based and host-based reference information, yielding the same outcome. Resampling and permutation methods indicate that the method is robust regarding taxon sampling and errors in the reference data. Tests with newly obtained ITS sequences demonstrate the use of the re-classified dataset in molecular identification of downy mildews. Conclusions: A corrected taxonomy is provided for all Peronospora ITS sequences contained in public databases. Clustering optimization appears to be broadly applicable in automated, sequence-based taxonomy. The method connects traditional and modern taxonomic disciplines by specifically addressing the issue of how to optimally account for both traditional species concepts and genetic divergence.

Root associated bacteria are critical for plant growth and health. Understanding the composition and role of root microbiota is crucial toward agricultural practices that are less dependent on chemical fertilization, which has known negative effects on the environment and human health. Here we analyzed the root-associated microbiomes of soybean and wheat under agricultural field conditions. We took samples from 11 different production fields across a large geographic area. We used 16S rRNA pyrosequencing to explore root microbial communities and also obtained 2,007 bacterial isolates from rhizospheres, which were tested for the presence of plant growth promoting (PGP) traits in-vitro . We observed that pH and nitrate content correlated with beta diversity variability of rhizospheric bacterial communities despite the variable field conditions. We described the dominant bacterial groups associated to roots from both crops at a large geographic scale and we found that a high proportion of them (60–70%) showed more than 97% similarity to bacteria from the isolated collection. Moreover, we observed that 55% of the screened isolates presented PGP activities in vitro . These results are a significant step forward in understanding crop-associated microbiomes and suggest that new directions can be taken to promote crop growth and health by modulating root microbiomes.

Precise analytical approximations have been determined for the eigenvalues of the ground state of the decatic anharmonic potential x 2 + λ x 10 in the one-dimensional Schrödinger equation. The results have been found using the technique multipoint quasi-rational approximation (MPQA). With the new method, power and asymptotic expansions have been determined. The analytic function here obtained is derived connecting both expansions. The maximum relative error of the best analytical approximation here determined is 0.04. However, most of the relative errors for other values of λ, are smaller than 1% (less than 0.01).

When developing new products to be used in honeybee colonies, further than acute toxicity, it is imperative to perform an assessment of risks, including various sublethal effects. The long-term sublethal effects of xenobiotics on honeybees, more specifically of acaricides used in honeybee hives, have been scarcely studied, particularly so in the case of essential oils and their components. In this work, chronic effects of the ingestion of Eupatorium buniifolium (Asteraceae) essential oil were studied on nurse honeybees using laboratory assays. Survival, food consumption, and the effect on the composition of cuticular hydrocarbons (CHC) were assessed. CHC were chosen due to their key role as pheromones involved in honeybee social recognition. While food consumption and survival were not affected by the consumption of the essential oil, CHC amounts and profiles showed dose-dependent changes. All groups of CHC (linear and branched alkanes, alkenes and alkadienes) were altered when honeybees were fed with the highest essential oil dose tested (6000 ppm). The compounds that significantly varied include n-docosane, n-tricosane, n-tetracosane, n-triacontane, n-tritriacontane, 9-tricosene, 7-pentacosene, 9-pentacosene, 9-heptacosene, tritriacontene, pentacosadiene, hentriacontadiene, tritriacontadiene and all methyl alkanes. All of them but pentacosadiene were up-regulated. On the other hand, CHC profiles were similar in healthy and Nosema-infected honeybees when diets included the essential oil at 300 and 3000 ppm. Our results show that the ingestion of an essential oil can impact CHC and that the effect is dose-dependent. Changes in CHC could affect the signaling process mediated by these pheromonal compounds. To our knowledge this is the first report of changes in honeybee cuticular hydrocarbons as a result of essential oil ingestion.

We study an extension of the Standard Model that addresses the hints of lepton flavour universality violation observed in \\[B\\rightarrow K^{(*)} l^+l^-\\] decays at LHCb, while providing a viable candidate for dark matter. The model incorporates two new scalar fields and a Majorana fermion that induce one-loop contributions to B meson decays. We show that agreement with observational data requires the new couplings to be complex and that the Majorana fermion can reproduce the observed dark matter relic density. This combination of cosmological and flavour constraints sets an upper limit on the dark matter and mediator masses. We have studied LHC dijet and dilepton searches, finding that they rule out large regions of parameter space by setting lower bounds on the dark matter and mediator masses. In particular, dilepton bounds are much more constraining in a future high-luminosity phase. Finally, we have computed the scattering cross section of dark matter off nuclei and compared it to the sensitivity of current and future direct detection experiments, showing that parts of the parameter space could be accessible in the future to multi-ton experiments. Future collider and direct DM searches complement each other to probe large areas of the parameter space of this model.

DNA barcoding can identify biological species and provides an important tool in diverse applications, such as conserving species and identifying pathogens, among many others. If combined with statistical tests, DNA barcoding can focus taxonomic scrutiny onto anomalous species identifications based on morphological features. Accordingly, we put nonparametric tests into a taxonomic context to answer questions about our sequence dataset of the formal fungal barcode, the nuclear ribosomal internal transcribed spacer (ITS). For example, does DNA barcoding concur with annotated species identifications significantly better if expert taxonomists produced the annotations? Does species assignment improve significantly if sequences are restricted to lengths greater than 500 bp? Both questions require a figure of merit to measure of the accuracy of species identification, typically provided by the probability of correct identification (PCI). Many articles on DNA barcoding use variants of PCI to measure the accuracy of species identification, but do not provide the variants with names, and the absence of explicit names hinders the recognition that the different variants are not comparable from study to study. We provide four variant PCIs with a name and show that for fixed data they follow systematic inequalities. Despite custom, therefore, their comparison is at a minimum problematic. Some popular PCI variants are particularly vulnerable to errors in species annotation, insensitive to improvements in a barcoding pipeline, and unable to predict identification accuracy as a database grows, making them unsuitable for many purposes. Generally, the Fractional PCI has the best properties as a figure of merit for species identification. The fungal genus Ramaria provides unusual taxonomic difficulties. As a case study, it shows that a good taxonomic background can be combined with the pertinent summary statistics of molecular results to improve the identification of doubtful samples, linking both disciplines synergistically.