Giovanni Emiliani

Azurin is a promising antitumor agent that selectively enters cancer cells and inhibits tumor progression. It is also known to participate in cellular processes involving single-electron transfer, including protection against oxidative stress, anaerobic respiration, and denitrification. However, the physiological role of azurin remains poorly understood. In this work, a multifaceted phenotypic characterization of an azurin-deficient mutant (Δazu) of the plant endophytic bacterium Pseudomonas sp. OHS18 was performed, using complementary approaches and technologies. Deletion of the azu gene did not affect resistance to antibiotics, copper, or hydrogen peroxide, while nuclear magnetic resonance-based metabolomic analysis revealed that the Δazu strain was moderately impaired in maintaining metabolic homeostasis from the exponential to the stationary growth phase. Phenotype microarray analyses showed that the two strains exhibited largely similar metabolic and resistance profiles, except for bromosuccinic acid utilization, under which the Δazu strain displayed reduced growth. This phenotype was further associated with a reduced ability of the mutant to colonize Arabidopsis thaliana, suggesting a role for azurin in maintaining the plant–bacterium association. Overall, these findings provide new insights into the physiological role of azurin in environmental bacteria and suggest its involvement in bacterium–eukaryote interactions, thereby opening new perspectives for biotechnological and biomedical applications.

Origanum L. (Lamiaceae) is a commercially important medicinal and aromatic plant genus worldwide. Endophytic bacterial communities are recognized for promoting plant growth and physiology, although their interactions with host metabolism remain insufficiently understood. In this work, an in vitro model of axenic Origanum heracleoticum plants was established to investigate the relationship between endophytic bacteria and their tissue of origin. Specifically, we evaluated the adaptation of two strains, Bacillus sp. OHL2 and Pseudomonas sp. OHS18, and the potential role of Bacillus sp. OHL2 in modulating plant physiology and secondary metabolism. Bacterial inoculation and re-isolation highlighted niche-specific adaptation and possible co-evolution within the host, suggesting an active role of the plant in regulating bacterial colonization within the endosphere. Inoculation with Bacillus sp. OHL2 significantly enhanced photosynthetic rate, leaf area, dry weight, and chlorophyll content. No substantial overall changes in secondary metabolism were detected. Rosmarinic acid was the predominant phenolic, while monoterpenes dominated, with carvacrol dominant. A significant tissue-by-inoculation interaction was observed for α-humulene, which decreased in leaves of inoculated plants. Overall, the in vitro system provides a valuable platform to study plant–endophyte interactions and bacterial mechanisms underlying the stimulation of plant growth and metabolic responses.

Clonostachys rosea is a promising biological control agent (BCA) against several plant pathogens, but its sensitivity to solar radiation limits its field efficacy. The biochemical changes occurring in C. rosea under light are still unknown, and no studies have assessed its antagonistic potential against Phytophthora cinnamomi and Phytophthora × cambivora, the main causal agents of ink disease in sweet chestnut. In this study, C. rosea was isolated from asymptomatic sweet chestnut plants in a forestry area affected by ink disease. We evaluated its in vitro antagonistic capacity against both oomycetes under dark and light conditions and investigated the metabolomic and volatilomic changes through HPLC-QToF-MS and GC-MS analyses. Under dark conditions, C. rosea exhibited remarkable inhibitory activity against both oomycetes in a dual-culture assay and through secreted secondary metabolites, including sorbicillinol and vertinolide, derivatives known for their biological activities. Light exposure significantly reduced antagonistic efficacy and secondary metabolite diversity. Volatilomic analyses revealed moderated differences between conditions, with volatile compounds whose biological roles remain uncharacterized and warrant further investigation. These findings indicate that light conditions critically affect the antagonistic potential of C. rosea, highlighting the importance of environmental factors in optimizing its use for the biological control of ink disease in chestnut.

The Numidian cypress (Cupressus sempervirens var. numidica, C. numidica hereafter) is a rare, almost unknown, endemic taxon of Tunisia whose conservation has long been hampered by human activities, taxonomic uncertainty and limited ecological knowledge, with only 64.33 ha of its populations remaining. Although recent genetic studies have confirmed its native status and long-term isolation, detailed information on its distribution, population structure and threats remain lacking. This study provides the first comprehensive assessment of C. numidica across its remaining range. Field surveys revealed that the species persists in only three small, fragmented forests, Bou Abdallah, Sidi Amer, and Dir Satour, covering a total of 64.33 ha. Soil analysis revealed some differences among sites, with Bou Abdallah showing higher clay content and Dir Satou exhibiting the highest levels of nitrogen, organic carbon, Olsen P, and available Mn and Mo. Climatic analyses indicate a semi-arid Mediterranean environment with pronounced summer droughts and a clear warming trend. Trees showed widespread damages, due to intensive grazing, tree cutting, crown dieback (drought), and pest and pathogen attacks. Natural regeneration was limited, and the condition of affected trees ranged from moderate to severe, with Bou Abdallah showing the highest levels of degradation. Notably, the severe fungal pathogen Seiridium cardinale, causal agent of cypress canker, was detected on C. numidica for the first time, highlighting an urgent conservation concern. Our results point to a staged conservation approach over time. In the immediate term (within 1 year), urgent monitoring and management of S. cardinale is needed. In the short term, efforts should focus on protecting carefully selected areas, about 5–10 regeneration microsites per forest, from grazing to support natural regeneration, reduce ongoing soil degradation, and establish clonal and seed-production plantations along with long-term seed storage. In the long term, the survival of C. numidica will only be possible with the active involvement of local communities, through awareness campaigns, adapting traditional practices such as gdel, and developing small-scale ecotourism that provides sustainable livelihoods while reinforcing support for conservation.

Pectins are high-value plant cell-wall polysaccharides with extensive applications in the food, pharmaceutical, textile, paper, and environmental sectors. Traditional extraction and processing methodologies rely heavily on harsh acids, high temperatures, and non-renewable solvents, generating substantial environmental and economic costs. This review consolidates recent advances across the entire Bacillus–pectinase value chain, from green pectin extraction and upstream substrate characterization, through process and statistical optimization of enzyme production, to industrial biocatalysis applications. We propose a practical roadmap for developing high-efficiency, low-environmental-footprint enzyme systems that support circular bioeconomy objectives. Critical evaluation of optimization strategies, including submerged versus solid-state fermentation, response surface methodology, artificial neural networks, and design of experiments, is supported by comparative data on strain performance, fermentation parameters, and industrial titers. Sector-specific case studies demonstrate the efficacy of Bacillus pectinases in fruit-juice clarification, textile bio-scouring, paper bio-bleaching, bio-based detergents, coffee and tea processing, oil extraction, animal feed enhancement, wastewater treatment, and plant-virus purification. Remaining challenges, including enzyme stability in complex matrices, techno-economic scale-up, and structure-guided protein engineering, are identified. Future directions are charted toward CRISPR-driven enzyme design and fully integrated circular-economy bioprocessing platforms.

Abies nebrodensis L. is a critically endangered conifer endemic to Sicily (Italy). Its residual population is confined to the Madonie mountain range under challenging climatological conditions. Despite the good adaptation shown by the relict population to the environmental conditions occurring in its habitat, Abies nebrodensis is subject to a series of threats, including climate change. Effective conservation strategies require reliable and versatile methods for monitoring its health status. Combining high-resolution remote sensing data with reanalysis of climatological datasets, this study aimed to identify correlations between vegetation indices (NDVI, GreenDVI, and EVI) and key climatological variables (temperature and precipitation) using advanced machine learning techniques. High-resolution RGB (Red, Green, Blue) and IrRG (infrared, Red, Green) maps were used to delineate tree crowns and extract statistics related to the selected vegetation indices. The results of phytosanitary inspections and multispectral analyses showed that the microclimatic conditions at the site level influence both the impact of crown disorders and tree physiology in terms of water content and photosynthetic activity. Hence, the correlation between the phytosanitary inspection results and vegetation indices suggests that multispectral techniques with drones can provide reliable indications of the health status of Abies nebrodensis trees. The findings of this study provide significant insights into the influence of environmental stress on Abies nebrodensis and offer a basis for developing new monitoring procedures that could assist in managing conservation measures.

Ink disease, primarily caused by the pathogen Phytophthora xcambivora, significantly threatens the health and productivity of sweet chestnut (Castanea sativa Mill.) orchards, highlighting the need for accurate detection methods. This study investigates the efficacy of machine learning (ML) classifiers combined with high-resolution multispectral imagery acquired via unmanned aerial vehicles (UAVs) to assess chestnut tree health at a site in Tuscany, Italy. Three machine learning algorithms—support vector machines (SVMs), Gaussian Naive Bayes (GNB), and logistic regression (Log)—were evaluated against eight vegetation indices (VIs), including NDVI, GnDVI, and RdNDVI, to classify chestnut tree crowns as either symptomatic or asymptomatic. High-resolution multispectral images were processed to derive vegetation indices that effectively captured subtle spectral variations indicative of disease presence. Ground-truthing involved visual tree health assessments performed by expert forest pathologists, subsequently validated through leaf area index (LAI) measurements. Correlation analysis confirmed significant associations between LAI and most VIs, supporting LAI as a robust physiological metric for validating visual health assessments. GnDVI and RdNDVI combined with SVM and GNB classifiers achieved the highest classification accuracy (95.2%), demonstrating their superior sensitivity in discriminating symptomatic from asymptomatic trees. Indices such as MCARI and SAVI showed limited discriminative power, underscoring the importance of selecting appropriate VIs that are tailored to specific disease symptoms. This study highlights the potential of integrating UAV-derived multispectral imagery and machine learning techniques, validated by LAI, as an effective approach for the detection of ink disease, enabling precision forestry practices and informed orchard management strategies.

The understanding of selective forces driving the compartmentalization of microbiota in plants remains limited. In this study, we performed a phenotypic characterization of bacterial endophytes isolated from the medicinal plant Origanum heracleoticum, together with the determination of the antibiotic resistance profiles and the antagonistic interactions of communities within and across different plant organs. Results revealed organ-related differences in the metabolic capabilities of bacteria, with those associated with stems displaying the highest metabolic activity for carbon sources. Contrarily, the patterns of antibiotic resistance appeared closely aligned with the taxonomical classification of the endophytes. The presence of antagonistic interactions, likely spurred by resource limitations, favor bacteria exhibiting greater metabolic plasticity. In conclusion, this research advances our comprehension of the intricate dynamics between plants and their associated microbiota, indicating that its composition is mainly influenced by forces contributing to the selection of distinct functions and phenotypic traits.