White rot fungal impact on the evolution of simple phenols during decay of silver fir wood by UHPLC-HQOMS.

INTRODUCTION: Silver fir (Abies alba Mill.) is one of the most valuable conifer wood species in Europe. Among the main opportunistic pathogens that cause root and butt rot on silver fir are Armillaria ostoyae and Heterobasidion abietinum. Due to the different enzymatic pools of these wood-decay fungi, different strategies in metabolizing the phenols were available. OBJECTIVE: This work explores the changes in phenolic compounds during silver fir wood degradation. METHODOLOGY: Phenols were analyzed before and after fungus inoculation in silver fir macerated wood after 2, 4 and 6 months. All samples were analyzed using high-performance liquid chromatography coupled to a hybrid quadrupole-orbitrap mass spectrometer. RESULTS: Thirteen compounds, including simple phenols, alkylphenyl alcohols, hydroxybenzoketones, hydroxycinnamaldehydes, hydroxybenzaldehydes, hydroxyphenylacetic acids, hydroxycinnamic acids, hydroxybenzoic acids and hydroxycoumarins, were detected. Pyrocatechol, coniferyl alcohol, acetovanillone, vanillin, benzoic acid, 4-hydroxybenzoic acid and vanillic acid contents decreased during the degradation process. Methyl vanillate, ferulic acid and p-coumaric were initially produced and then degraded. Scopoletin was accumulated. Pyrocatechol, acetovanillone and methyl vanillate were found for the first time in both degrading and non-degrading wood of silver fir. CONCLUSIONS: Despite differences in the enzymatic pool, both fungi caused a significant decrease in the amounts of phenolic compounds with the accumulation of the only scopoletin. Principal component analysis revealed an initial differentiation between the degradation activity of the two fungal species during degradation, but similar phenolic contents at the end of wood degradation.

Biotic threats for 23 major non-native tree species in Europe.

For non-native tree species with an origin outside of Europe a detailed compilation of enemy species including the severity of their attack is lacking up to now. We collected information on native and non-native species attacking non-native trees, i.e. type, extent and time of first observation of damage for 23 important non-native trees in 27 European countries. Our database includes about 2300 synthesised attack records (synthesised per biotic threat, tree and country) from over 800 species. Insects (49%) and fungi (45%) are the main observed biotic threats, but also arachnids, bacteria including phytoplasmas, mammals, nematodes, plants and viruses have been recorded. This information will be valuable to identify patterns and drivers of attacks, and trees with a lower current health risk to be considered for planting. In addition, our database will provide a baseline to which future impacts on non-native tree species could be compared with and thus will allow to analyse temporal trends of impacts.

Pangenomics of the Symbiotic Rhizobiales. Core and Accessory Functions Across a Group Endowed with High Levels of Genomic Plasticity.

Pangenome analyses reveal major clues on evolutionary instances and critical genome core conservation. The order Rhizobiales encompasses several families with rather disparate ecological attitudes. Among them, Rhizobiaceae, Bradyrhizobiaceae, Phyllobacteriacreae and Xanthobacteriaceae, include members proficient in mutualistic symbioses with plants based on the bacterial conversion of N2 into ammonia (nitrogen-fixation). The pangenome of 12 nitrogen-fixing plant symbionts of the Rhizobiales was analyzed yielding total 37,364 loci, with a core genome constituting 700 genes. The percentage of core genes averaged 10.2% over single genomes, and between 5% to 7% were found to be plasmid-associated. The comparison between a representative reference genome and the core genome subset, showed the core genome highly enriched in genes for macromolecule metabolism, ribosomal constituents and overall translation machinery, while membrane/periplasm-associated genes, and transport domains resulted under-represented. The analysis of protein functions revealed that between 1.7% and 4.9% of core proteins could putatively have different functions.

Molecular Approaches for Low-Cost Point-of-Care Pathogen Detection in Agriculture and Forestry.

Early detection of plant diseases is a crucial factor to prevent or limit the spread of a rising infection that could cause significant economic loss. Detection test on plant diseases in the laboratory can be laborious, time consuming, expensive, and normally requires specific technical expertise. Moreover, in the developing countries, it is often difficult to find laboratories equipped for this kind of analysis. Therefore, in the past years, a high effort has been made for the development of fast, specific, sensitive, and cost-effective tests that can be successfully used in plant pathology directly in the field by low-specialized personnel using minimal equipment. Nucleic acid-based methods have proven to be a good choice for the development of detection tools in several fields, such as human/animal health, food safety, and water analysis, and their application in plant pathogen detection is becoming more and more common. In the present review, the more recent nucleic acid-based protocols for point-of-care (POC) plant pathogen detection and identification are described and analyzed. All these methods have a high potential for early detection of destructive diseases in agriculture and forestry, they should help make molecular detection for plant pathogens accessible to anyone, anywhere, and at any time. We do not suggest that on-site methods should replace lab testing completely, which remains crucial for more complex researches, such as identification and classification of new pathogens or the study of plant defense mechanisms. Instead, POC analysis can provide a useful, fast, and efficient preliminary on-site screening that is crucial in the struggle against plant pathogens.

Characterization of the nucleotide-binding domain NsrF from the BceAB-type ABC-transporter NsrFP from the human pathogen Streptococcus agalactiae.

Treatment of bacterial infections is a great challenge of our era due to the various resistance mechanisms against antibiotics. Antimicrobial peptides are considered to be potential novel compound as antibiotic treatment. However, some bacteria, especially many human pathogens, are inherently resistant to these compounds, due to the expression of BceAB-type ABC transporters. This rather new transporter family is not very well studied. Here, we report the first full characterization of the nucleotide binding domain of a BceAB type transporter from Streptococcus agalactiae, namely SaNsrF of the transporter SaNsrFP, which confers resistance against nisin and gallidermin. We determined the NTP hydrolysis kinetics and used molecular modeling and simulations in combination with small angle X-ray scattering to obtain structural models of the SaNsrF monomer and dimer. The fact that the SaNsrFH202A variant displayed no ATPase activity was rationalized in terms of changes of the structural dynamics of the dimeric interface. Kinetic data show a clear preference for ATP as a substrate, and the prediction of binding modes allowed us to explain this selectivity over other NTPs.

In Vivo Antimicrobial and Wound-Healing Activity of Resveratrol, Dihydroquercetin, and Dihydromyricetin against Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans.

An increase in the spread of antibiotic-resistant opportunistic microorganisms causes serious problems in the treatment of purulent infections, burns, and trophic ulcers. We tested the antimicrobial activity in vivo of three polyphenols, Resveratrol, Dihydroquercetin (Taxifolin), and Dihydromyricetin (Ampelopsin) from Norway spruce bark to promote the elimination of Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans from wounds. Purulent infection was modelled on wounds in rats infected with suspensions containing 109 CFU (colony-forming unit)/mL of pathogens. The wound area was treated daily with solutions of the polyphenols or placebo for 14 days after the beginning of the treatment. The animals were examined daily, and each stage of the wound healing (inflammation, granulation, and maturation (marginal epithelialisation) was documented. The planimetric analysis of the wound recovery percentage was performed on the 3rd, 10th, and 14th day after the start of curing. Then, one echelon (three or four animals from each subgroup) was withdrawn from the experiment on days 3 (three animals), 10 (three animals), and 14 (four animals) for microscopy analysis of cytological composition of their wound defects by microscopy and microbiological analysis of their contamination with pathogens. Our results show that they are also able to suppress mast cell infiltration and stimulate lymphocyte and macrophage (monocyte) infiltration into the wound. Resveratrol stimulated the replacement of the scar with normal tissue (with a clear boundary between the dermis and epidermis) and the restoration of hair follicles. Resveratrol turned out to be significantly better than some commercial antimicrobial (Levomecol) and antifungal (Clotrimazole) ointments and can be proposed as a promising drug for topical use for the treatment of trophic ulcers and burns.

Metabolic Remodeling during Long-Lasting Cultivation of the Endomyces magnusii Yeast on Oxidative and Fermentative Substrates.

In this study, we evaluated the metabolic profile of the aerobic microorganism of Endomyces magnusii with a complete respiration chain and well-developed mitochondria system during long-lasting cultivation. The yeast was grown in batches using glycerol and glucose as the sole carbon source for a week. The profile included the cellular biological and chemical parameters, which determined the redox status of the yeast cells. We studied the activities of the antioxidant systems (catalases and superoxide dismutases), glutathione system enzymes (glutathione peroxidase and reductase), aconitase, as well as the main enzymes maintaining NADPH levels in the cells (glucose-6-phosphate dehydrogenase and NADP+-isocitrate dehydrogenase) during aging of Endomyces magnusii on two kinds of substrates. We also investigated the dynamics of change in oxidized and reduced glutathione, conjugated dienes, and reactive oxidative species in the cells at different growth stages, including the deep stationary stages. Our results revealed a similar trend in the changes in the activity of all the enzymes tested, which increased 2-4-fold upon aging. The yeast cytosol had a very high reduced glutathione content, 22 times than that of Saccharomyces cerevisiae, and remained unchanged during growth, whereas there was a 7.5-fold increase in the reduced glutathione-to-oxidized glutathione ratio. The much higher level of reactive oxidative species was observed in the cells in the late and deep stationary phases, especially in the cells using glycerol. Cell aging of the culture grown on glycerol, which promotes active oxidative phosphorylation in the mitochondria, facilitated the functioning of powerful antioxidant systems (catalases, superoxide dismutases, and glutathione system enzymes) induced by reactive oxidative species. Moreover, it stimulated NADPH synthesis, regulating the cytosolic reduced glutathione level, which in turn determines the redox potential of the yeast cell during the early aging process.

TopModel: Template-Based Protein Structure Prediction at Low Sequence Identity Using Top-Down Consensus and Deep Neural Networks.

Knowledge of protein structures is essential to understand proteins' functions, evolution, dynamics, stabilities, and interactions and for data-driven protein- or drug design. Yet, experimental structure determination rates are far exceeded by that of next-generation sequencing, resulting in less than 1/1000th of proteins having an experimentally known 3D structure. Computational structure prediction seeks to alleviate this problem, and the Critical Assessment of Protein Structure Prediction (CASP) has shown the value of consensus and meta-methods that utilize complementary algorithms. However, traditionally, such methods employ majority voting during template selection and model averaging during refinement, which can drive the model away from the native fold if it is underrepresented in the ensemble. Here, we present TopModel, a fully automated meta-method for protein structure prediction. In contrast to traditional consensus and meta-methods, TopModel uses top-down consensus and deep neural networks to select templates and identify and correct wrongly modeled regions. TopModel combines a broad range of state-of-the-art methods for threading, alignment, and model quality estimation and provides a versatile workflow and toolbox for template-based structure prediction. TopModel shows a superior template selection, alignment accuracy, and model quality for template-based structure prediction on the CASP10-12 datasets compared to 12 state-of-the-art stand-alone primary predictors. TopModel was validated by prospective predictions of the nisin resistance protein (NSR) protein from Streptococcus agalactiae and LipoP from Clostridium difficile, showing far better agreement with experimental data than any of its constituent primary predictors. These results, in general, demonstrate the utility of TopModel for protein structure prediction and, in particular, show how combining computational structure prediction with sparse or low-resolution experimental data can improve the final model.

Bioactive Compounds from Norway Spruce Bark: Comparison Among Sustainable Extraction Techniques for Potential Food Applications.

Piceaabies (L.) Karst, (Norway spruce) bark, generally considered as wood industry waste, could potentially be used as a valuable source of antioxidants for food applications. In this study, supercritical fluid extraction (SFE), pressurized liquid extraction (PLE), and ultrasound-assisted extraction (UAE) were carried out in order to recover bioactive compounds from bark of Norway spruce. Obtained results show that PLE with ethanol as solvent was the most effective method for extracting total flavonoid compounds (21.14 ± 1.42 mg quercetin g-1 sample) and consequently exerted the highest antioxidant activity measured by 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (257.11 ± 13.31 mg Trolox g-1 sample). On the other hand, UAE extract contained the maximum phenolic concentration (54.97 ± 2.00 mg gallic acid g-1 sample) and the most interesting antioxidant activity measured by the ferric-reducing antioxidant power (580.25 ± 25.18 µmol FeSO4 g-1 sample). Additionally, PLE and UAE have demonstrated great efficiency in the extraction of trans-resveratrol, quantified by HPLC (0.19 and 0.29 mg trans-RSV g-1 sample, respectively).

Small-molecule inhibitors of nisin resistance protein NSR from the human pathogen Streptococcus agalactiae.

Lantibiotics are antimicrobial peptides produced by Gram-positive bacteria and active in the nanomolar range. Nisin is the most intensely studied and used lantibiotic, with applications as food preservative and recognized potential for clinical usage. However, different bacteria that are pathogenic for humans and do not produce nisin, including Streptococcus agalactiae, show an innate resistance that has been related to the nisin resistance protein (NSR), a membrane-associated protease. Here, we report the first-in-class small-molecule inhibitors of SaNSR identified by virtual screening based on a previously derived structural model of the nisin/NSR complex. The inhibitors belong to three different chemotypes, of which the halogenated phenyl-urea derivative NPG9 is the most potent one. Co-administration of NPG9 with nisin yields increased potency compared to nisin alone in SaNSR-expressing bacteria. The binding mode of NPG9, predicted with molecular docking and validated by extensive molecular dynamics simulations, confirms a structure-activity relationship derived from the in vivo data. Saturation transfer difference-NMR experiments demonstrate direct binding of NPG9 to SaNSR and agree with the predicted binding mode. Our results demonstrate the potential to overcome SaNSR-related lantibiotic resistance by small molecules.

Global effects of non-native tree species on multiple ecosystem services.

Non-native tree (NNT) species have been transported worldwide to create or enhance services that are fundamental for human well-being, such as timber provision, erosion control or ornamental value; yet NNTs can also produce undesired effects, such as fire proneness or pollen allergenicity. Despite the variety of effects that NNTs have on multiple ecosystem services, a global quantitative assessment of their costs and benefits is still lacking. Such information is critical for decision-making, management and sustainable exploitation of NNTs. We present here a global assessment of NNT effects on the three main categories of ecosystem services, including regulating (RES), provisioning (PES) and cultural services (CES), and on an ecosystem disservice (EDS), i.e. pollen allergenicity. By searching the scientific literature, country forestry reports, and social media, we compiled a global data set of 1683 case studies from over 125 NNT species, covering 44 countries, all continents but Antarctica, and seven biomes. Using different meta-analysis techniques, we found that, while NNTs increase most RES (e.g. climate regulation, soil erosion control, fertility and formation), they decrease PES (e.g. NNTs contribute less than native trees to global timber provision). Also, they have different effects on CES (e.g. increase aesthetic values but decrease scientific interest), and no effect on the EDS considered. NNT effects on each ecosystem (dis)service showed a strong context dependency, varying across NNT types, biomes and socio-economic conditions. For instance, some RES are increased more by NNTs able to fix atmospheric nitrogen, and when the ecosystem is located in low-latitude biomes; some CES are increased more by NNTs in less-wealthy countries or in countries with higher gross domestic products. The effects of NNTs on several ecosystem (dis)services exhibited some synergies (e.g. among soil fertility, soil formation and climate regulation or between aesthetic values and pollen allergenicity), but also trade-offs (e.g. between fire regulation and soil erosion control). Our analyses provide a quantitative understanding of the complex synergies, trade-offs and context dependencies involved for the effects of NNTs that is essential for attaining a sustained provision of ecosystem services.

(Eco)toxicological maps: A new risk assessment method integrating traditional and in silico tools and its application in the Ledra River (Italy).

Contaminants giving rise to emerging concern like pharmaceuticals, personal care products, pesticides and Endocrine Disrupting Chemicals (EDCs) have been detected in wastewaters, as reported in the literature, but little is known about their (eco)toxicological effects and consequent human health impact. The present study aimed at overcoming this lack of information through the use of in silico methods integrated with traditional toxicological risk analysis. This is part of a pilot project involving the management of wastewater treatment plants in the Ledra River basin (Italy). We obtained data to work up a global risk assessment method combining the evaluations of health risks to humans and ecological receptors from chemical contaminants found in this specific area. The (eco)toxicological risk is expressed by a single numerical value, permitting the comparison of different sampling sites and the evaluation of future environmental and technical interventions.

Integrating computational methods to predict mutagenicity of aromatic azo compounds.

Azo dyes have several industrial uses. However, these azo dyes and their degradation products showed mutagenicity, inducing damage in environmental and human systems. Computational methods are proposed as cheap and rapid alternatives to predict the toxicity of azo dyes. A benchmark dataset of Ames data for 354 azo dyes was employed to develop three classification strategies using knowledge-based methods and docking simulations. Results were compared and integrated with three models from the literature, developing a series of consensus strategies. The good results confirm the usefulness of in silico methods as a support for experimental methods to predict the mutagenicity of azo compounds.

Draft Genome Sequence of the Nitrogen-Fixing Rhizobium sullae Type Strain IS123T Focusing on the Key Genes for Symbiosis with its Host Hedysarum coronarium L.

The prominent feature of rhizobia is their molecular dialogue with plant hosts. Such interaction is enabled by the presence of a series of symbiotic genes encoding for the synthesis and export of signals triggering organogenetic and physiological responses in the plant. The genome of the Rhizobium sullae type strain IS123T nodulating the legume Hedysarum coronarium, was sequenced and resulted in 317 scaffolds for a total assembled size of 7,889,576 bp. Its features were compared with those of genomes from rhizobia representing an increasing gradient of taxonomical distance, from a conspecific isolate (Rhizobium sullae WSM1592), to two congeneric cases (Rhizobium leguminosarum bv. viciae and Rhizobium etli) and up to different genera within the legume-nodulating taxa. The host plant is of agricultural importance, but, unlike the majority of other domesticated plant species, it is able to survive quite well in the wild. Data showed that that the type strain of R. sullae, isolated from a wild host specimen, is endowed with a richer array of symbiotic genes in comparison to other strains, species or genera of rhizobia that were rescued from domesticated plant ecotypes. The analysis revealed that the bacterium by itself is incapable of surviving in the extreme conditions that its host plant can tolerate. When exposed to drought or alkaline condition, the bacterium depends on its host to survive. Data are consistent with the view of the plant phenotype as the primary factor enabling symbiotic nitrogen fixing bacteria to survive in otherwise limiting environments.

Xylella fastidiosa: Host Range and Advance in Molecular Identification Techniques.

In the never ending struggle against plant pathogenic bacteria, a major goal is the early identification and classification of infecting microorganisms. Xylella fastidiosa, a Gram-negative bacterium belonging to the family Xanthmonadaceae, is no exception as this pathogen showed a broad range of vectors and host plants, many of which may carry the pathogen for a long time without showing any symptom. Till the last years, most of the diseases caused by X. fastidiosa have been reported from North and South America, but recently a widespread infection of olive quick decline syndrome caused by this fastidious pathogen appeared in Apulia (south-eastern Italy), and several cases of X. fastidiosa infection have been reported in other European Countries. At least five different subspecies of X. fastidiosa have been reported and classified: fastidiosa, multiplex, pauca, sandyi, and tashke. A sixth subspecies (morus) has been recently proposed. Therefore, it is vital to develop fast and reliable methods that allow the pathogen detection during the very early stages of infection, in order to prevent further spreading of this dangerous bacterium. To this purpose, the classical immunological methods such as ELISA and immunofluorescence are not always sensitive enough. However, PCR-based methods exploiting specific primers for the amplification of target regions of genomic DNA have been developed and are becoming a powerful tool for the detection and identification of many species of bacteria. The aim of this review is to illustrate the application of the most commonly used PCR approaches to X. fastidiosa study, ranging from classical PCR, to several PCR-based detection methods: random amplified polymorphic DNA (RAPD), quantitative real-time PCR (qRT-PCR), nested-PCR (N-PCR), immunocapture PCR (IC-PCR), short sequence repeats (SSRs, also called VNTR), single nucleotide polymorphisms (SNPs) and multilocus sequence typing (MLST). Amplification and sequence analysis of specific targets is also mentioned. The fast progresses achieved during the last years in the DNA-based classification of this pathogen are described and discussed and specific primers designed for the different methods are listed, in order to provide a concise and useful tool to all the researchers working in the field.

ChloroMitoCU: Codon patterns across organelle genomes for functional genomics and evolutionary applications.

Organelle genomes are widely thought to have arisen from reduction events involving cyanobacterial and archaeal genomes, in the case of chloroplasts, or α-proteobacterial genomes, in the case of mitochondria. Heterogeneity in base composition and codon preference has long been the subject of investigation of topics ranging from phylogenetic distortion to the design of overexpression cassettes for transgenic expression. From the overexpression point of view, it is critical to systematically analyze the codon usage patterns of the organelle genomes. In light of the importance of codon usage patterns in the development of hyper-expression organelle transgenics, we present ChloroMitoCU, the first-ever curated, web-based reference catalog of the codon usage patterns in organelle genomes. ChloroMitoCU contains the pre-compiled codon usage patterns of 328 chloroplast genomes (29,960 CDS) and 3,502 mitochondrial genomes (49,066 CDS), enabling genome-wide exploration and comparative analysis of codon usage patterns across species. ChloroMitoCU allows the phylogenetic comparison of codon usage patterns across organelle genomes, the prediction of codon usage patterns based on user-submitted transcripts or assembled organelle genes, and comparative analysis with the pre-compiled patterns across species of interest. ChloroMitoCU can increase our understanding of the biased patterns of codon usage in organelle genomes across multiple clades. ChloroMitoCU can be accessed at: http://chloromitocu.cgu.edu.tw/.

A knowledge-based expert rule system for predicting mutagenicity (Ames test) of aromatic amines and azo compounds.

Cancer is one of the main causes of death in Western countries, and a major issue for human health. Prolonged exposure to a number of chemicals was observed to be one of the primary causes of cancer in occupationally exposed persons. Thus, the development of tools for identifying hazardous chemicals and the increase of mechanistic understanding of their toxicity is a major goal for scientific research. We constructed a new knowledge-based expert system accounting the effect of different substituents for the prediction of mutagenicity (Ames test) of aromatic amines, a class of compounds of major concern because of their widespread application in industry. The herein presented model implements a series of user-defined structural rules extracted from a database of 616 primary aromatic amines, with their Ames test outcomes, aimed at identifying mutagenic and non-mutagenic chemicals. The chemical rationale behind such rules is discussed. Besides assessing the model's ability to correctly classify aromatic amines, its predictivity was further evaluated on a second database of 354 azo dyes, another class of chemicals of major concern, whose toxicity has been predicted on the basis of the toxicity of aromatic amines potentially generated from the metabolic reduction of the azo bond. Good performance in classification on both the amine (MCC, Matthews Correlation Coefficient=0.743) and the azo dye (MCC=0.584) datasets confirmed the predictive power of the model, and its suitability for use on a wide range of chemicals. Finally, the model was compared with a series of well-known mutagenicity predicting software. The good performance of our model compared with other mutagenicity models, especially in predicting azo dyes, confirmed the usefulness of this expert system as a reliable support to in vitro mutagenicity assays for screening and prioritization purposes. The model has been fully implemented as a KNIME workflow and is freely available for downstream users.

PlantFuncSSR: Integrating First and Next Generation Transcriptomics for Mining of SSR-Functional Domains Markers.

Analysis of repetitive DNA sequence content and divergence among the repetitive functional classes is a well-accepted approach for estimation of inter- and intra-generic differences in plant genomes. Among these elements, microsatellites, or Simple Sequence Repeats (SSRs), have been widely demonstrated as powerful genetic markers for species and varieties discrimination. We present PlantFuncSSRs platform having more than 364 plant species with more than 2 million functional SSRs. They are provided with detailed annotations for easy functional browsing of SSRs and with information on primer pairs and associated functional domains. PlantFuncSSRs can be leveraged to identify functional-based genic variability among the species of interest, which might be of particular interest in developing functional markers in plants. This comprehensive on-line portal unifies mining of SSRs from first and next generation sequencing datasets, corresponding primer pairs and associated in-depth functional annotation such as gene ontology annotation, gene interactions and its identification from reference protein databases. PlantFuncSSRs is freely accessible at: http://www.bioinfocabd.upo.es/plantssr.

Suppression Substractive Hybridization and NGS Reveal Differential Transcriptome Expression Profiles in Wayfaring Tree (Viburnum lantana L.) Treated with Ozone.

Tropospheric ozone (O3) is a global air pollutant that causes high economic damages by decreasing plant productivity. It enters the leaves through the stomata, generates reactive oxygen species, which subsequent decrease in photosynthesis, plant growth, and biomass accumulation. In order to identify genes that are important for conferring O3 tolerance or sensitivity to plants, a suppression subtractive hybridization analysis was performed on the very sensitive woody shrub, Viburnum lantana, exposed to chronic O3 treatment (60 ppb, 5 h d(-1) for 45 consecutive days). Transcript profiling and relative expression assessment were carried out in asymptomatic leaves, after 15 days of O3 exposure. At the end of the experiment symptoms were observed on all treated leaves and plants, with an injured leaf area per plant accounting for 16.7% of the total surface. Cloned genes were sequenced by 454-pyrosequencing and transcript profiling and relative expression assessment were carried out on sequenced reads. A total of 38,800 and 12,495 high quality reads obtained in control and O3-treated libraries, respectively (average length of 319 ± 156.7 and 255 ± 107.4 bp). The Ensembl transcriptome yielded a total of 1241 unigenes with a total sequence length of 389,126 bp and an average length size of 389 bp (guanine-cytosine content = 49.9%). mRNA abundance was measured by reads per kilobase per million and 41 and 37 ensembl unigenes showed up- and down-regulation respectively. Unigenes functionally associated to photosynthesis and carbon utilization were repressed, demonstrating the deleterious effect of O3 exposure. Unigenes functionally associated to heat-shock proteins and glutathione were concurrently induced, suggesting the role of thylakoid-localized proteins and antioxidant-detoxification pathways as an effective strategy for responding to O3. Gene Ontology analysis documented a differential expression of co-regulated transcripts for several functional categories, including specific transcription factors (MYB and WRKY). This study demonstrates that a complex sequence of events takes place in the cells at intracellular and membrane level following O3 exposure and elucidates the effects of this oxidative stress on the transcriptional machinery of the non-model plant species V. lantana, with the final aim to provide the molecular supportive knowledge for the use of this plant as O3-bioindicator.

Monitoring intra-annual dynamics of wood formation with microcores and dendrometers in Picea abies at two different altitudes.

Seasonal analyses of cambial cell production and day-by-day stem radial increment can help to elucidate how climate modulates wood formation in conifers. Intra-annual dynamics of wood formation were determined with microcores and dendrometers and related to climatic signals in Norway spruce (Picea abies (L.) Karst.). The seasonal dynamics of these processes were observed at two sites of different altitude, Savignano (650 m a.s.l.) and Lavazè (1800 m a.s.l.) in the Italian Alps. Seasonal dynamics of cambial activity were found to be site specific, indicating that the phenology of cambial cell production is highly variable and plastic with altitude. There was a site-specific trend in the number of cells in the wall thickening phase, with the maximum cell production in early July (DOY 186) at Savignano and in mid-July (DOY 200) at Lavazè. The formation of mature cells showed similar trends at the two sites, although different numbers of cells and timing of cell differentiation were visible in the model shapes; at the end of ring formation in 2010, the number of cells was four times higher at Savignano (106.5 cells) than at Lavazè (26.5 cells). At low altitudes, microcores and dendrometers described the radial growth patterns comparably, though the dendrometer function underlined the higher upper asymptote of maximum growth in comparison with the cell production function. In contrast, at high altitude, these functions exhibited different trends. The best model was obtained by fitting functions of the Gompertz model to the experimental data. By combining radial growth and cambial activity indices we defined a model system able to synchronize these processes. Processes of adaptation of the pattern of xylogenesis occurred, enabling P. abies to occupy sites with contrasting climatic conditions. The use of daily climatic variables in combination with plant functional traits obtained by sensors and/or destructive sampling could provide a suitable tool to better investigate the effect of disturbances on response strategies in trees and, consequently, contribute to improving our prediction of tree growth and species resilience based on climate scenarios.