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In microbial community sequencing, involving bacterial ribosomal 16S rDNA or fungal ITS, the targeted genes are the basis for taxonomical assignment. The traditional bioinformatical procedure has for decades made use of a clustering protocol by which sequences are pooled into packages of shared percent identity, typically at 97%, to yield Operational Technical Units (OTUs). Progress in the data processing methods has however led to the possibility of minimizing technical sequencers errors, which were the main reason for the OTU choice, and to analyze instead the exact Amplicon Sequence Variants (ASV) which is a choice yielding much less agglomerated reads. We have tested the two procedures on the same 16S metabarcoded bacterial amplicons dataset encompassing a series of samples from 17 adjacent habitats, taken across a 700 meter-long transect of different ecological conditions unfolding in a gradient spanning from cropland, through meadows, forest and all successional transitions up to the seashore, within the same coastal area. This design allowed to scan a high biodiversity basin and to measure alpha, beta and gamma diversity of the area, to verify the effect of the bioinformatics on the same data as concerns the values of ten different ecological indexes and other parameters. Two levels of progressive OTUs clustering, (99% and 97%) were compared with the ASV data. The results showed that the OTUs clustering proportionally led to a marked underestimation of the ecological indicators values for species diversity and to a distorted behaviour of the dominance and evenness indexes with respect to the direct use of the ASV data. Multivariate ordination analyses resulted also sensitive in terms of tree topology and coherence. Overall, data support the view that reference-based OTU clustering carries several misleading disadvantageous biases, including the risk of missing novel taxa which are yet unreferenced in databases. Since its alternatives as de novo clustering have on the other hand drawbacks due to heavier computational demand and results comparability, especially for environmental studies which contain several yet uncharacterized species, the direct ASV based analysis, at least for prokaryotes, appears to warrant significand advantages in comparison to OTU clustering at every level of percent identity cutoff.

Late blight, caused by oomycetes Phytophthora infestans is one of the most challenging fungal diseases to manage in tomato plants (Solanum lycopersicum L.). Toward managing the disease, conventional breeding has successfully introgressed genetic loci conferring disease resistance from various wild relatives of tomato into commercial varieties. The cataloging of disease-associated SNP markers and a deeper understanding of disease-resistance mechanisms are needed to keep up with the demand for commercial varieties resistant against emerging pathogen strains. To this end, we performed transcriptome sequencing to evaluate the gene expression dynamics of tomato varieties, resistant and susceptible to Phytophthora infection. Further integrating the transcriptome dataset with large-scale public genomic data of varieties with known disease phenotypes, a panel of single nucleotide polymorphism (SNP) markers correlated with disease resistance was identified. These SNPs were then validated on 31 lines with contrasting phenotypes for late blight. The identified SNPs are located on genes coding for a putative cysteine-rich transmembrane module (CYSTM), Solyc09g098310, and a nucleotide-binding site–leucine-rich repeat protein, Solyc09g098100, close to the well-studied Ph-3 resistance locus known to have a role in plant immunity against fungal infections. The panel of SNPs generated by this study using transcriptome sequencing showing correlation with disease resistance across a broad set of plant material can be used as markers for molecular screening in tomato breeding.

The Arctic region is characterized by severe temperatures and a unique ecosystem with largely unexplored microbiomes. Whereas soil microbiomes in temperate regions play key roles in nutrient cycling, organic matter decomposition, greenhouse gas fluxes, and overall ecosystem functioning, Arctic microbiomes remain poorly understood, highlighting the need for a thorough characterization to better predict and manage soil health and resilience. In this study, we compared the microbial profiles of three raised beaches on Devon Island (Nunavut, Canadian Arctic Archipelago), which emerged sequentially between eight and two thousand years ago, to assess their similarities and differences. Samples were collected by genetic horizons along excavations from the top layer to the permafrost. For each horizon, total soil DNA, 16S gene copies dPCR quantification, 16S metabarcoding, and functional prediction were carried out. Total DNA quantification revealed a consistently comparable concentration of genetic material across the three soil beaches (AB2 μ = 2.28 ± 5.44 μg ∙ g -1 , AB1 μ = 4.71 ± 2.35 μg ∙ g -1 , AB3 μ = 5.44 ± 2.91 μg ∙ g -1 ), regardless of site age (AB2 = 2,360 YBP, AB1 = 6,726 YBP, AB3 = 8,410 YBP). Conversely, clear differences emerged by comparing the different horizons at each site. The hierarchical cluster analysis based on the Bray-Curtis dissimilarity matrix revealed a clear separation between surface and deep horizons. The core microbiome analysis highlighted Actinobacteria, Proteobacteria, and Firmicutes as the three predominant phyla accounting for relative abundances of 42%, 22%, and 18%, respectively. Remarkable evidence was the unexpectedly high taxonomic diversity that was recorded in these sites and that surprisingly matched with the commonly observed values in soils of temperate regions. Since these stony shores developed under cold, life-limiting conditions, their apparent microbial richness raises doubts about the potential biases in inferring physiological contexts and active biodiversity directly inferred from culture-independent DNA-based studies. The reason is that such inventories can be possibly inflated, in all environments, by chronically accumulated cells from passive immigration events through atmospheric discharge.

Ecosystems associated with retreating glaciers are undergoing rapid transformation in the context of a changing climate. Invertebrate fauna, including the Chironomidae insect family (non-biting midges), is part of the active biology that characterizes glaciers and their surrounding habitats. The underlying microbiology, present in both the insects’ guts and their physical habitat, represents a critical interface, controlling, on the one hand, the basis of nutrient geochemical cycling and, on the other, the health and nutritional physiology of its hosts. We aimed to assess the extent to which insect-borne bacteria resemble those found in icemelt water and the surrounding wet and terrestrial environments, in order to determine also whether the bacteria found associated with the insects could be interpreted mainly as specific dwellers, putatively involved with active physiological functions, or also as transient cells taken in for other purposes. To this end, we analyzed physical and biological samples from ten different chironomid species in two glacier-fed streams, one proglacial pond, and the surrounding habitats of three glacier systems (Agola, Amola and Mandrone) in the Italian Alps. The samples were analyzed using culture-independent amplified 16S rRNA gene bacterial metabarcoding sequencing. The bacterial diversity in glacial habitats was unexpectedly high, with numbers of sequence variants similar to those recorded in temperate, lowland, productive soils, and almost seven times higher than those found in insects. There was minimal coincidence in sequence variants between insects and habitats, amounting to just 4.9% shared cases, and the few taxa found in both insects and habitats were mostly overrepresented in the former. Additionally, there were no significant differences between insect species or between insect communities from different sites. A number of taxa occurring uniquely in insects or habitats showed peculiarities at all taxonomic levels, including specific phyla. Evidence of microevolutionary distinctness was observed in the form of sequence variants assigned to the same taxonomic name that differed in specific sequence bases and were found to be partitioned either in insect or environmental samples. Interestingly, sequence variants found in both insects and environments scored higher in bioinformatic identification, reaching deeper assigned ranks compared to variants occurring only in insects or the environment. In essence, the compared insect and environmental communities showed a very low level of symmetry and consequently a very high level of specificity to one or the other condition. The data provided limited support about the diet of chironomids in relation to the microbiota of the habitat. This suggests that the food resource for these insects likely consists mostly of dissolved organic matter and detritus of various origins, rather than intact bacteria with sequenceable genomes, as is the case elsewhere with ruminant herbivores or birds.

(1) Background: Endophytic bacteria represent an important component of plant wellness. They have been widely studied for their involvement in plant development and enhancement of stress tolerance. In this work, the endophytic communities of roots, stems, and leaves of blackberry ( Rubus ulmifolius Schott) were studied in three different niches: natural, riverside, and human-impacted niches. (2) Results: The microbiome composition revealed that Sphingomonadaceae was the most abundant family in all samples, accounting for 9.4–45.8%. In contrast, other families seem to be linked to a specific tissue or niche. Families Microbacteriaceae and Hymenobacteraceae increased their presence in stem and leaf samples, while Burkholderiaceae abundance was important in riverside samples. Alpha and beta diversity analyses showed that root samples were the most diverse, and they gathered together in the same cluster, apart from the rest of the samples. (3) Conclusions: The analysis of the microbiome of R. ulmifolius plants revealed that the composition was essentially the same in different niches; the differences were primarily influenced by plant tissue factors with a core genome dominated by Sphingomonadaceae . Additionally, it was observed that R. ulmifolius can select its own microbiome, and this remains constant in all tissues evaluated regardless the niche of sampling.

Chilling temperatures represent a challenge for crop species originating from warm geographical areas. In this situation, biostimulants serve as an eco-friendly resource to mitigate cold stress in crops. Tomato ( Solanum lycopersicum L.) is an economically important vegetable crop, but quite sensitive to cold stress, which it encounters in both open field and greenhouse settings. In this study, the biostimulant effect of a brown-seaweed extract (BSE) has been evaluated in tomato exposed to low temperature. To assess the product effects, physiological and molecular characterizations were conducted. Under cold stress conditions, stomatal conductance, net photosynthesis, and yield were significantly (p ≤ 0.05) higher in BSE-treated plants compared to the untreated ones. A global transcriptomic survey after BSE application revealed the impact of the BSE treatment on genes leading to key responses to cold stress. This was highlighted by the significantly enriched GO categories relative to proline (GO:0006560), flavonoids (GO:0009812, GO:0009813), and chlorophyll (GO:0015994). Molecular data were integrated by biochemical analysis showing that the BSE treatment causes greater proline, polyphenols, flavonoids, tannins, and carotenoids contents.The study highlighted the role of antioxidant molecules to enhance tomato tolerance to low temperature mediated by BSE-based biostimulant.

This work aimed to study the effects in tomato ( Solanum lycopersicum L.) of foliar applications of a novel calcium-based biostimulant (SOB01) using an omics approach involving transcriptomics and physiological profiling. A calcium-chloride fertilizer (SOB02) was used as a product reference standard. Plants were grown under well-watered (WW) and water stress (WS) conditions in a growth chamber. We firstly compared the transcriptome profile of treated and untreated tomato plants using the software RStudio. Totally, 968 and 1,657 differentially expressed genes (DEGs) (adj- p -value < 0.1 and |log2(fold change)| ≥ 1) were identified after SOB01 and SOB02 leaf treatments, respectively. Expression patterns of 9 DEGs involved in nutrient metabolism and osmotic stress tolerance were validated by real-time quantitative reverse transcription PCR (RT-qPCR) analysis. Principal component analysis (PCA) on RT-qPCR results highlighted that the gene expression profiles after SOB01 treatment in different water regimes were clustering together, suggesting that the expression pattern of the analyzed genes in well water and water stress plants was similar in the presence of SOB01 treatment. Physiological analyses demonstrated that the biostimulant application increased the photosynthetic rate and the chlorophyll content under water deficiency compared to the standard fertilizer and led to a higher yield in terms of fruit dry matter and a reduction in the number of cracked fruits. In conclusion, transcriptome and physiological profiling provided comprehensive information on the biostimulant effects highlighting that SOB01 applications improved the ability of the tomato plants to mitigate the negative effects of water stress.

The fungus Cercospora beticola causes Cercospora Leaf Spot (CLS) of sugar beet ( Beta vulgaris L.). Despite the global importance of this disease, durable resistance to CLS has still not been obtained. Therefore, the breeding of tolerant hybrids is a major goal for the sugar beet sector. Although recent studies have suggested that the leaf microbiome composition can offer useful predictors to assist plant breeders, this is an untapped resource in sugar beet breeding efforts. Using Ion GeneStudio S5 technology to sequence amplicons from seven 16S rRNA hypervariable regions, the most recurring endophytes discriminating CLS-symptomatic and symptomless sea beets ( Beta vulgaris L.ssp. maritima ) were identified. This allowed the design of taxon-specific primer pairs to quantify the abundance of the most representative endophytic species in large naturally occurring populations of sea beet and subsequently in sugar beet breeding genotypes under either CLS symptomless or infection stages using qPCR. Among the screened bacterial genera, Methylobacterium and Mucilaginibacter were found to be significantly (p < 0.05) more abundant in symptomatic sea beets with respect to symptomless. In cultivated sugar beet material under CLS infection, the comparison between resistant and susceptible genotypes confirmed that the susceptible genotypes hosted higher contents of the above-mentioned bacterial genera. These results suggest that the abundance of these species can be correlated with increased sensitivity to CLS disease. This evidence can further prompt novel protocols to assist plant breeding of sugar beet in the pursuit of improved pathogen resistance.

Rhizoctonia solani, causing Rhizoctonia crown and root rot, is a major risk to sugar beet (Beta vulgaris L.) cultivation. The development of resistant varieties accelerated by marker-assisted selection is a priority of breeding programs. We report the identification of a single-nucleotide polymorphism (SNP) marker linked to Rhizoctonia resistance using restriction site-associated DNA (RAD) sequencing of two geographically discrete sets of plant materials with different degrees of resistance/susceptibility to enable a wider selection of superior genotypes. The variant calling pipeline utilized SAMtools for variant calling and the resulting raw SNPs from RAD sequencing (15,988 and 22,439 SNPs) were able to explain 13.40% and 25.45% of the phenotypic variation in the two sets of material from different sources of origin, respectively. An association analysis was carried out independently on both the datasets and mutually occurring significant SNPs were filtered depending on their contribution to the phenotype using principal component analysis (PCA) biplots. To provide a ready-to-use marker for the breeding community, a systematic molecular validation of significant SNPs distributed across the genome was undertaken to combine high-resolution melting, Sanger sequencing, and rhAmp SNP genotyping. We report that RsBv1 located on Chromosome 6 (9,000,093 bp) is significantly associated with Rhizoctonia resistance (p < 0.01) and able to explain 10% of the phenotypic disease variance. The related SNP assay is thus ready for marker-assisted selection in sugar beet breeding for Rhizoctonia resistance.

The microbial diversity is, among soil key factors, responsible for soil fertility and nutrient biogeochemical cycles, and can be modified upon changes in main soil physicochemical properties and soil pollution. Over the years, many restoration techniques have been applied to restore degraded soils. However, the effect of these approaches on soil microbial diversity is less understood and thus requires more investigation. In this study, we analyzed the impact, on soil microbial diversity of a patented novel technology, used to restore degraded soils. Soil samples were collected from three nearby sites located in Borgotrebbia, Piacenza, Italy, and categorized as reconstituted, degraded, and agricultural soils. After total soil DNA extraction, 16S rDNA multi-amplicon sequencing was carried out using an Ion GeneStudio S5 System to compare soils’ bacterial community profiles. Sequenced reads were processed to assign taxonomy and then key microbial community differences were identified across the sampling sites. Species diversity featured significant abatement at all rank levels in the degraded soil when compared to the agricultural control. The 5 year restoration technique showed full recovery of this index at the genus level but not at the phylum level, displaying a rank-dependent gradient of restored richness. In parallel, the abundance of genes involved in the nitrogen (N) biogeochemical cycle was assessed using quantitative Real-Time PCR (qPCR). Total DNA content was significantly higher ( p < 0.05) in degraded (μ = 12.69 ± 2.58 μg g −1 ) and reconstituted (μ = 11.73 ± 1.65 μg g −1 ) soil samples when compared to the agricultural soil samples (μ = 2.39 ± 0.50 μg g −1 ). The taxonomic diversity of each soil site was significantly different, with some instances unique of the agricultural soil even at the phylum level. The analysis of N functional genes showed that the relative abundance of bacterial amoA ( p < 0.05) and nosZ ( p < 0.01) genes were significantly lower in the agricultural than in the reconstituted and degraded soils. We concluded that the application of the soil reconstitution technique appears to enhance the active microbial community, with distinct diversity and functionality towards genes involved in N biogeochemical cycle, as compared to both the degraded and the agricultural soil.