Maria Cristina Della Lucia

Soil fungi play a key role in nutrient cycling and soil organic matter turnover, yet the influence of pedological context on fungal communities across forest types remains insufficiently understood. Here, we combined soil chemical analyses, Fourier-transform infrared spectroscopy (FTIR), and ITS2 metabarcoding to investigate soil properties and fungal communities in temperate mountain beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) H. Karst) forests in Italy developed on contrasting geological substrates. Soil horizons were sampled across seasons to characterize the main associations between fungal community structure, inferred functional diversity, and environmental context. Soil chemistry revealed site- and horizon-dependent patterns, particularly in pH, Ca, and P availability, whereas differences related to dominant tree species were comparatively limited. FTIR spectra showed clear variation in organic matter composition among sites, consistent with site- and stand-associated differences in organic matter composition. Fungal community composition was primarily associated with site and soil horizon. Functional guild patterns suggested ectomycorrhizal dominance in Ca-rich soils and greater prevalence of saprotrophs in more acidic soils. Overall, this multi-proxy approach suggests that pedological context was more closely associated with fungal community structure and ecological strategies than with vegetation type or season within the studied stands. These patterns should be interpreted as site-specific and hypothesis-generating because substrate types were not replicated across independent locations.

Interactions among plant roots, soil, and microorganisms in the rhizosphere regulate nutrient cycling, plant health, and ecosystem resilience. Recent advances in DNA sequencing and multi-omics are contributing to a shift from primarily descriptive surveys toward more mechanistic and predictive frameworks. This review synthesizes methodological developments and conceptual insights spanning microbial ecology, functional genomics, and agricultural applications. We first summarize DNA-based approaches—marker-gene sequencing, shotgun metagenomics, and quantitative nucleic acid assays—and then complementary omics layers, including metatranscriptomics, metaproteomics, metabolomics, epigenomics, ionomics, and phenomics. We next outline computational advances in data integration, network modeling, and visualization that help represent complex multi-layered datasets as biologically interpretable systems. Applications relevant to climate resilience and sustainable agriculture are discussed, including the design of synthetic microbial communities, the identification of biomarkers for soil health and stress tolerance, and case studies in which rhizosphere multi-omics informs crop breeding and soil management strategies. Overall, these developments underscore the potential of treating microbes as functional and, to some extent, manageable components of the plant holobiont. Looking ahead, we identify key research gaps involving standardized workflows, cross-scale causal inference, and real-time monitoring pipelines that integrate molecular diagnostics with remote sensing and edge–cloud analytics. By linking ecological mechanisms with translational practice, multi-omics frameworks may support the development of more sustainable, data-driven agriculture that better aligns productivity with environmental stewardship.

Using renewable biomass in agriculture, particularly microalgae as a biostimulant, offers economic and environmental sustainability benefits by reducing costs, improving nutrient cycling, and enhancing water use efficiency. Microalgae contain bioactive compounds that boost crop tolerance to environmental stresses, including salinity. Saline soils, characterized by elevated sodium chloride (NaCl) levels, negatively impact many crops, resulting in low productivity and high remediation costs. Therefore, this study evaluates the biostimulant properties of a microalgae-based commercial preparation (MR) on lettuce (Lactuca sativa L.) plants grown hydroponically and exposed to saline stress. The extract was chemically characterized through elemental analysis, lipid composition (gas chromatography with flame ionization detector—GC-FID), the determination of functional groups (Fourier Transformed Infrared—FT-IR), structure (¹H,¹³C Nuclear Magnetic Resonance—NMR), with their hormone-like activity also assessed. Lettuce plants were treated with or without the microalgae blend, in combination with 0, 50 mM, or 100 mM NaCl. The contents of nutrients, soluble proteins, chlorophylls, and phenols, as well as the lipid peroxidation, antioxidants and root traits of lettuce plants, were estimated. The microalgae applied to salt-stressed plants resulted in a significant increase in biomass, protein, and chlorophyll contents. Additionally, significant effects on the secondary metabolism and mitigation of salinity stress were observed in terms of increased phenol content and the activity of antioxidant enzymes, as well as decreased lipid peroxidation. The potassium (K⁺) content was increased significantly in plants treated with 100 mM NaCl after addition of microalgae, while the content of sodium (Na⁺) was concurrently reduced. In conclusion, our results demonstrate that using microalgae can be a potent approach for improving the cultivation of Lactuca sativa L. under saline stress conditions.

The molecular and phenotypic effects of a brown seaweed extract (BSE) were assessed in sugar beet (Beta vulgaris L.). Transcript levels of BSE-treated and untreated plants were studied by RNA-seq and validated by quantitative real-time PCR analysis (RT-qPCR). Root morphology, sugar yield, and processing quality traits were also analyzed to better elucidate the treatment effects. RNA-seq revealed 1019 differentially expressed genes (DEGs) between the BSE-treated and untreated plants. An adjusted p-value < 0.1 and an absolute value of log2 (fold change) greater than one was used as criteria to select the DEGs. Gene ontology (GO) identified hormone pathways as an enriched biological process. Six DEGs involved in auxin and ABA pathways were validated using RT-qPCR. The phenotypic characterization indicated that BSE treatment led to a significant increase (p < 0.05) in total root length and the length of fine roots of plants grown under hydroponics conditions. The sugar yield of plants grown under field conditions was higher (p < 0.05) in the treated field plots compared with the control treatment, without impacting the processing quality. Our study unveiled the relevant effects of BSE application in regulating auxin- and ABA-related gene expression and critical traits related to sugar beet development and yield.

Leonardite-based biostimulants are a large class of compounds, including humic acid substances. Foliar application of biostimulants at field level improves plant growth, yield and quality through metabolic changes and stimulation of plant proton pumps. The present study aimed at identifying optimum dosage of BLACKJAK, a humic acid-based substance, which is able to modify genes involved in sugar beet growth. Thirty-three genes belonging to various biochemical pathway categories were tested in leaves of treated sugar beet (Beta vulgaris L.) samples to assess gene expression profiling in response to BLACKJAK. Seedlings of a diploid and multigerm variety were grown in plastic pots and sprayed with two dilutions of BLACKJAK (dilution 1:500–1.0 mg C L⁻¹ and dilution 1:1000–0.5 mg C L⁻¹). Leaf samples were collected after 24, 48, and 72 h treatment with BLACKJAK for each dilution. RNA was extracted and the quantification of gene expression was performed while using an OpenArray platform. Results of analysis of variance demonstrated that, 15 genes out of a total of 33 genes tested with OpenArray qPCR were significantly affected by treatment and exposure time. Analysis for annotation of gene products and pathways revealed that genes belonging to the mitochondrial respiratory pathways, nitrogen and hormone metabolisms, and nutrient uptake were up-regulated in the BLACKJAK treated samples. Among the up-regulated genes, Bv_PHT2;1 and Bv_GLN1 expression exerted a 2-fold change in 1:1000 and 1:500 BLACKJAK concentrations. Overall, the gene expression data in the BLACKJAK treated leaves demonstrated the induction of plant growth–related genes that were contributed almost to amino acid and nitrogen metabolism, plant defense system, and plant growth.