IntroductionBacteriophages are pervasive components of natural whey starters (NWS) used in traditional hard cheese production, yet their functional role under cheesemaking-related stresses remains poorly understood.MethodsIn this study, six temperate bacteriophages associated with Lactobacillus helveticus were isolated from Trentingrana NWS. Classified within the Caudoviricetes class, they harbored gene sets associated with the typical phage cycle together with a large number of open reading frames (ORFs) with hypothetical or unknown function. By combining quantitative PCR targeting hallmark phage genes with detection of extracellular phage particles, we investigated prophage induction dynamics under abiotic conditions relevant to dairy processing, including heat shock, nutrient limitation, lactic acid, and oxidative stress.ResultsAcross conditions, stress exposure elicited phage-specific and dose-dependent responses, frequently revealing a decoupling between early increases in phage genomic copy number and subsequent virion release. Heat shock emerged as the most consistent inducer of prophage activation, whereas lactic acid and oxidative stress produced threshold-dependent or inhibitory effects, particularly at higher intensities. Nutrient limitation alone had limited impact, suggesting a permissive rather than triggering role.DiscussionOverall, these findings support a non-binary model of prophage induction, spanning intermediate states from partial genome replication to productive lytic cycles, strongly constrained by host physiological status. Our results indicate that L. helveticus prophages respond heterogeneously to cheesemaking-related stresses and may act as context-dependent modulators of NWS stability rather than direct disruptors. Such stress-responsive prophage dynamics are likely to influence microbial population turnover and resilience during back-slopping, ultimately contributing to the long-term stability and functional robustness of Trentingrana natural whey starters.

Black fungi are among the most stress-resistant organisms known, yet the genetic and ecological foundations of their extraordinary resilience remain poorly understood. This study explores the adaptation strategies of the melanised fungus Elasticomyces elasticus by integrating genomic and ecological data. To uncover the mechanisms of adaptation, we combined whole-genome sequencing, functional annotation, environmental metadata, and large-scale soil metabarcoding analyses. Phylogenomic approaches were employed to delineate evolutionary lineages and assess ploidy levels. The results revealed that the global distribution of Elasticomyces phylotypes is primarily influenced by temperature, UV radiation, and soil organic carbon, suggesting that different phylotypes have evolved heterogeneous strategies for stress resistance. Comparative genomic analyses identified a set of 'sentinel pathways,' notably glutathione metabolism and nucleotide biosynthesis, which were enriched in strains inhabiting the most extreme environments and showed significant correlations with abiotic stressors such as aridity and UV exposure. Furthermore, phylogenomic reconstructions uncovered two independent diploid lineages associated with the harshest environments, pointing to diploidisation as a potential adaptive mechanism to cope with multiple stressors. Overall, the integration of genomic and ecological perspectives provides new insights into how black fungi persist at the edge of habitability. The study highlights specific pathways and genomic traits that underpin resilience to extreme conditions, offering implications that extend beyond terrestrial ecology.

The Biodiversity, Food Security and Pathogens (BFSP) priority area is developing nicely as we are approaching the mid-point of the 2024-2026 work programme. Four Work Packages, equivalent to the open call projects, selected during 2024, were added and started in January 2025. During this Mini Symposium these four projects will be presented, along with a series of Node presentations showcasing their national BFSP-related activities. The second part of the session will be used to present the BFSP strategy and speak about the planned second BFSP open call. Focus areas will be presented and discussed. There will be time to think of future project submissions, with a specific emphasis on cross-Community/entity activities working towards advancing ELIXIR within the space of BFSP, as described in the Strategy.

Arsenic is a widespread metalloid that even at low concentrations is highly toxic to most plant species. While the transcriptional responses associated to arsenic tolerance have been widely investigated in vascular plants, comparatively little is known in their sister lineage, the bryophytes. Most importantly, functional evidence of whether the same genes play major roles in arsenic tolerance responses in these two anciently diverged land plant lineages is currently largely missing. In this study, we identified by RNA-Seq a highly reliable set of differentially expressed genes (DEGs) responding to arsenite toxicity in the model bryophyte Marchantia polymorpha. We then explored the evolutionary level of functional conservation of seven upregulated DEGs by Agrobacterium-mediated transformation in the highly arsenic-sensitive cad1-3 mutant of Arabidopsis thaliana as a representative of tracheophytes, and characterized fresh weight, malondialdehyde production and total arsenic content in dry biomass of transgenic lines. While two of the tested M. polymorpha DEGs did not significantly enhance arsenic tolerance, the remaining five DEGs, when overexpressed in cad1-3, conferred maximal levels of tolerance, measured as biomass accumulation, between 56 % and 100 % of WT Col-0 plants. Among them, a putative 1-cys peroxiredoxin restored growth, protection from lipid peroxidation and capacity to accumulate arsenic to levels indistinguishable from those of WT. These results provide functional evidence for the considerable conservation of arsenic tolerance responses between M. polymorpha and A. thaliana, suggesting that M. polymorpha can be a valid model for the identification of evolutionarily deeply conserved genes for the genetic improvement of crops for arsenic tolerance.

BACKGROUND:Accurate annotation of gene isoforms remains one of the major obstacles in translating genomic data into meaningful biological insight. Laminin-binding integrins, particularly integrin α6 (ITGA6), exemplify this challenge through their complex splicing patterns. The rare ITGA6 X1X2 isoform, generated by the alternative inclusion of exons X1 and X2 within the β-propeller domain, has remained poorly characterized despite decades of integrin research. METHODS:We combined comparative genomics across primates with targeted re-alignment to assess exon conservation and annotation fidelity; analyzed RNA-seq for exon-level usage; applied splice-site prediction to evaluate inclusion potential; surveyed cancer mutation resources for exon-specific variants; and used structural/disorder modeling to infer effects on the β-propeller. RESULTS:Exon X2 is conserved at the genomic level but inconsistently annotated, reflecting the limitations of current annotation pipelines rather than genuine evolutionary loss. RNA-seq analyses reveal low but detectable expression of X2, consistent with weak splice site predictions that suggest strict regulatory control and condition-specific expression. Despite its rarity, recurrent mutations in exon X2 are reported in cancer datasets, implying possible roles in disease. Structural modeling further indicates that X2 contributes to a flexible, disordered region within the β-propeller domain, potentially influencing laminin binding or β-subunit dimerization. CONCLUSIONS:Altogether, our results suggest that ITGA6 X1X2 could be a rare, tightly regulated isoform with potential functional and pathological relevance.

Soil biota is responsible for essential biological processes occurring in the soil. Biota composition, biodiversity and activity can be affected by soil properties, biogeography and human activities. This study, conducted in vineyards of Northeast Italy, aimed to understand the combined effect of edaphic and agronomic factors on the composition and biodiversity of soil biota in four soil types characterised by different pedological origin. The soil biota was studied by simultaneously investigating the composition and the biodiversity of fungal, bacterial and microarthropod communities and their interactions with abiotic factors. The results show that the impact of natural soil characteristics and viticulture activity on biota depends on soil type. Some fungal, bacterial and microarthropod community groups were characteristic only of certain soil types. Geographical position and edaphic factors mainly affected the composition of microbial communities, while microarthropods seemed to respond less to these variables. Depending on the origin of the soil, the biodiversity of the biota responded differently to viticulture practices. The study shows that understanding how natural and agronomic factors drive soil biota makes it possible to predict the effect of natural or artificial changes on soil biological processes.

'Candidatus Phytoplasma' genus, a group of fastidious phloem-restricted bacteria, can infect a wide variety of both ornamental and agro-economically important plants. Phytoplasmas secrete effector proteins responsible for the symptoms associated with the disease. Identifying and characterizing these proteins is of prime importance for expanding our knowledge of the molecular bases of the disease. We faced the challenge of identifying phytoplasma's effectors by developing LEAPH, a machine learning ensemble predictor composed of four models. LEAPH was trained on 479 proteins from 53 phytoplasma species, described by 30 features. LEAPH achieved 97.49% accuracy, 95.26% precision and 98.37% recall, ensuring a low false-positive rate and outperforming available state-of-the-art methods. The application of LEAPH to 13 phytoplasma proteomes yields a comprehensive landscape of 2089 putative pathogenicity proteins. We identified three classes according to different secretion models: 'classical', 'classical-like' and 'non-classical'. Importantly, LEAPH identified 15 out of 17 known experimentally validated effectors belonging to the three classes. Furthermore, to help the selection of novel candidates for biological validation, we applied the Self-Organizing Maps algorithm and developed a Shiny app called EffectorComb. LEAPH and the EffectorComb app can be used to boost the characterization of putative effectors at both computational and experimental levels, and can be employed in other phytopathological models.

The classes Dothideomycetes and Eurotiomycetes include constitutively melanized fungi adapted to extreme conditions and they are widely distributed in diverse hostile habitats worldwide. Yet, despite the growing interest in these fungi, there is a considerable gap of knowledge on their functionality. Their genomic analysis is still in its infancy and the possibility to understand their adaptive strategies and exploit their potentialities in bioremediation is very limited. Here, we supply a genome catalog of 118 black fungi, encompassing different ecologies, phylogenies and lifestyles, as a first example of a comparative genomic study at high level of diversity. Results indicate that, as a rule, Dothideomycetes show more variable genome size and that larger genomes are associated with harshest conditions; low temperature tolerance and DNA repair capacity are overrepresented in their genomes. In Eurotiomycetes high temperature tolerance and capacity to metabolize hydrocarbons are more frequently present and these abilities are positively correlated with the human presence. The genomic features are consistent with the prevalent ecologies in the two classes. Indeed, Dothideomycetes are more common in cold and dry environments with high capacity for DNA repair being consistent with the normally highly UV-impacted conditions in their habitats; in contrast, Eurotiomycetes spread mainly in hot human-impacted sites with industrial pollution. Mean annual temperature and isothermality are positively correlated with tolerance to high temperatures in Dothideomycetes , suggesting that, despite their preference for the cold, they are potentially equipped to survive even when temperatures rise due to the global warming.

Plant pathogens cause billions of dollars of crop loss every year and are a major threat to global food security. Identifying and characterizing pathogens effectors is crucial towards their improved control. Because of their poor sequence conservation, effector identification is challenging, and current methods generate too many candidates without indication for prioritizing experimental studies. In most phyla, effectors contain specific sequence motifs which influence their localization and targets in the plant. Therefore, there is an urgent need to develop bioinformatics tools tailored for pathogen effectors. To circumvent these limitations, we have developed MOnSTER a specific tool that identifies clusters of motifs of protein sequences (CLUMPs). MOnSTER can be fed with motifs identified by de novo tools or from databases such as Pfam and InterProScan. The advantage of MOnSTER is the reduction of motif redundancy by clustering them and associating a score. This score encompasses the physicochemical properties of AAs and the motif occurrences. We built up our method to identify discriminant CLUMPs in oomycetes effectors. Consequently, we applied MOnSTER on plant parasitic nematodes and identified six CLUMPs in about 60% of the known nematode candidate parasitism proteins. Furthermore, we found co-occurrences of CLUMPs with protein domains important for invasion and pathogenicity. The potentiality of this tool goes beyond the effector characterization and can be used to easily cluster motifs and calculate the CLUMP-score on any set of protein sequences. MOnSTER is a bioinformatic tool tailored to cluster protein motifs (CLUMPs) enriched in sequences of interest. The relationship between CLUMPs and pathogenicity traits of effector proteins in plant-parasitic nematodes is investigated using this tool.

We previously reported that in the absence of Prostaglandin D2 synthase (L-PGDS) peripheral nerves are hypomyelinated in development and that with aging they present aberrant myelin sheaths. We now demonstrate that L-PGDS expressed in Schwann cells is part of a coordinated program aiming at preserving myelin integrity. In vivo and in vitro lipidomic, metabolomic and transcriptomic analyses confirmed that myelin lipids composition, Schwann cells energetic metabolism and key enzymes controlling these processes are altered in the absence of L-PGDS. Moreover, Schwann cells undergo a metabolic rewiring and turn to acetate as the main energetic source. Further, they produce ketone bodies to ensure glial cell and neuronal survival. Importantly, we demonstrate that all these changes correlate with morphological myelin alterations and describe the first physiological pathway implicated in preserving PNS myelin. Collectively, we posit that myelin lipids serve as a reservoir to provide ketone bodies, which together with acetate represent the adaptive substrates Schwann cells can rely on to sustain the axo-glial unit and preserve the integrity of the PNS.

Grapevine embodies a fascinating species as regards phenotypic plasticity and genotype-per-environment interactions. The terroir, namely the set of agri-environmental factors to which a variety is subjected, can influence the phenotype at the physiological, molecular, and biochemical level, representing an important phenomenon connected to the typicality of productions. We investigated the determinants of plasticity by conducting a field-experiment where all terroir variables, except soil, were kept as constant as possible. We isolated the effect of soils collected from different areas, on phenology, physiology, and transcriptional responses of skin and flesh of a red and a white variety of great economic value: Corvina and Glera. Molecular results, together with physio-phenological parameters, suggest a specific effect of soil on grapevine plastic response, highlighting a higher transcriptional plasticity of Glera in respect to Corvina and a marked response of skin compared to flesh. Using a novel statistical approach, we identified clusters of plastic genes subjected to the specific influence of soil. These findings could represent an issue of applicative value, posing the basis for targeted agricultural practices to enhance the desired characteristics for any soil/cultivar combination, to improve vineyards management for a better resource usage and to valorize vineyards uniqueness maximizing the terroir-effect.

Microbial communities in agricultural soils are fundamental for plant growth and in vineyard ecosystems contribute to defining regional wine quality. Managing soil microbes towards beneficial outcomes requires knowledge of how community assembly processes vary across taxonomic groups, spatial scales, and through time. However, our understanding of microbial assembly remains limited. To quantify the contributions of stochastic and deterministic processes to bacterial and fungal assembly across spatial scales and through time, we used 16 s rRNA gene and ITS sequencing in the soil of an emblematic wine-growing region of Italy. Combining null- and neutral-modelling, we found that assembly processes were consistent through time, but bacteria and fungi were governed by different processes. At the within-vineyard scale, deterministic selection and homogenising dispersal dominated bacterial assembly, while neither selection nor dispersal had clear influence over fungal assembly. At the among-vineyard scale, the influence of dispersal limitation increased for both taxonomic groups, but its contribution was much larger for fungal communities. These null-model-based inferences were supported by neutral modelling, which estimated a dispersal rate almost two orders-of-magnitude lower for fungi than bacteria. This indicates that while stochastic processes are important for fungal assembly, bacteria were more influenced by deterministic selection imposed by the biotic and/or abiotic environment. Managing microbes in vineyard soils could thus benefit from strategies that account for dispersal limitation of fungi and the importance of environmental conditions for bacteria. Our results are consistent with theoretical expectations whereby larger individual size and smaller populations can lead to higher levels of stochasticity.

Grapevines worldwide are grafted onto Vitis spp. rootstocks in order to improve their tolerance to biotic and abiotic stresses. Thus, the response of vines to drought is the result of the interaction between the scion variety and the rootstock genotype. In this work, the responses of genotypes to drought were evaluated on 1103P and 101-14MGt plants, own-rooted and grafted with Cabernet Sauvignon, in three different water deficit conditions (80, 50, and 20% soil water content, SWC). Gas exchange parameters, stem water potential, root and leaf ABA content, and root and leaf transcriptomic response were investigated. Under well-watered conditions, gas exchange and stem water potential were mainly affected by the grafting condition, whereas under sever water deficit they were affected by the rootstock genotype. Under severe stress conditions (20% SWC), 1103P showed an "avoidance" behavior. It reduced stomatal conductance, inhibited photosynthesis, increased ABA content in the roots, and closed the stomata. The 101-14MGt maintained a high photosynthetic rate, limiting the reduction of soil water potential. This behavior results in a "tolerance" strategy. An analysis of the transcriptome showed that most of the differentially expressed genes were detected at 20% SWC, and more significantly in roots than in leaves. A core set of genes has been highlighted on the roots as being related to the root response to drought that are not affected by genotype nor grafting. Genes specifically regulated by grafting and genes specifically regulated by genotype under drought conditions have been identified as well. The 1103P, more than the 101-14MGt, regulated a high number of genes in both own-rooted and grafted conditions. This different regulation revealed that 1103P rootstock readily perceived the water scarcity and rapidly faced the stress, in agreement with its avoidance strategy.

Background Crop pathogens are a major threat to plants’ health, reducing the yield and quality of agricultural production. Among them, the Candidatus Phytoplasma genus, a group of fastidious phloem-restricted bacteria, can parasite a wide variety of both ornamental and agro-economically important plants. Several aspects of the interaction with the plant host are still unclear but it was discovered that phytoplasmas secrete certain proteins (effectors) responsible for the symptoms associated with the disease. Identifying and characterizing these proteins is of prime importance for globally improving plant health in an environmentally friendly context. Results We challenged the identification of phytoplasma’s effectors by developing LEAPH, a novel machine-learning ensemble predictor for phytoplasmas pathogenicity proteins. The prediction core is composed of four models: Random Forest, XGBoost, Gaussian, and Multinomial Naive Bayes. The consensus prediction is achieved by a novel consensus prediction score. LEAPH was trained on 479 proteins from 53 phytoplasmas species, described by 30 features accounting for the biological complexity of these protein sequences. LEAPH achieved 97.49% accuracy, 95.26% precision, and 98.37% recall, ensuring a low false-positive rate and outperforming available state-of-the-art methods for putative effector prediction. The application of LEAPH to 13 phytoplasma proteomes yields a comprehensive landscape of 2089 putative pathogenicity proteins. We identified three classes of these proteins according to different secretion models: “classical”, presenting a signal peptide, “classically-like” and “non-classical”, lacking the canonical secretion signal. Importantly, LEAPH was able to identify 15 out of 17 known experimentally validated effectors belonging to the three classes. Furthermore, to help the selection of novel candidates for biological validation, we applied the Self-Organizing Maps algorithm and developed a shiny app called EffectorComb. Both tools would be a valuable resource to improve our understanding of effectors in plant–phytoplasmas interactions. Conclusions LEAPH and EffectorComb app can be used to boost the characterization of putative effectors at both computational and experimental levels and can be employed in other phytopathological models. Both tools are available at . ### Competing Interest Statement The authors have declared no competing interest.

Saline lakes are rapidly drying out across the globe, particularly in Central Asia, due to climate change and anthropogenic activities. We present the results of a long-read next generation sequencing analysis of the 16S rRNA-based taxonomic structure of bacteriomes of the Tengiz-Korgalzhyn lakes system. We found that the shallow endorheic, mostly saline lakes of the system show unusually low bacterioplankton dispersal rates at species-level taxonomic resolution. The major environmental factor structuring the lake’s microbial communities was salinity. The dominant bacterial phyla of the lakes with high salinity included a significant proportion of marine and halophilic species. In sum, these results, which can be applied to other lake systems of the semi-arid regions, improve our understanding of the factors influencing lake microbiomes undergoing salinization in response to climate change and other anthropogenic factors. Our results show that finer taxonomic classification can provide new insights and improve our understanding of the environmental factors influencing the microbiomes of lakes undergoing salinization in response to climate change and other anthropogenic factors.### Competing Interest StatementThe authors have declared no competing interest.

Pyramiding different fire blight resistance genes and QTLs in future apple cultivars is the most eco-friendly way to combat this disease. Identification of strong fire blight resistance donors, and introgression of their resistance into apple breeding material are a continuing effort of breeding programs. Thus, enormous effort is been put into breeding research to understand host – pathogen interactions and mechanisms of resistance found in Malus . The crabapple Malus fusca (accession MAL0045) is highly resistant to fire blight, and although resistance is strain-dependent, resistance of MAL0045 is not overcome by any known strain of Erwinia amylovora to date. A strong fire blight resistance locus ( FB_Mfu10 ) was fine mapped to an interval of 0.33 Centimorgan (cM) on linkage group (LG) 10 of MAL0045 using 1888 progenies. Subsequently, a single bacterial artificial chromosome (BAC) clone (46H22), which harbours FB_Mfu10 -resistance alleles, was identified in a MAL0045 BAC library and sequenced using MiSeq illumina leading to the assembly of 45 contigs. Analyses of the sequence of 46H22 led to the identification of a receptor-like kinase candidate gene. Here, we report about resequencing 46H22 using MinION Oxford Nanopore and successfully assembled the sequences into a single contig, which allowed for identifying additional candidate genes.