Determining the hierarchical order by which intestinal tract, administered diet, and individual relay can shape the gut microbiome of fattening quails.

A bacterial metabarcoding approach was used to compare the microbiome composition of caecal and faecal samples from fattening Japanese quails (Coturnix coturnix japonica) fed three different diet regimes. The tested feedstuffs included (1) a commercial diet for fattening quails, (2) a commercial diet containing 12% full-fat silkworm (Bombyx mori) pupae meal, and (3) a commercial diet containing 12% defatted silkworm pupae meal. The aim of the experiment was to verify the relative effect of three variables (diet type, gut tract comparing caecum to rectum, and individual animal) in determining the level of bacterial community dissimilarity to rank the relevance of each of the three factors in affecting and shaping community composition. To infer such ranking, the communities resulting from the high-throughput sequencing from each sample were used to calculate the Bray-Curtis distances in all the pairwise combinations, whereby identical communities would score 0 and totally different ones would yield the maximum distance, equal to 1. The results indicated that the main driver of divergence was the gut tract, as distances between caecal and faecal samples were higher on average, irrespective of diet composition, which scored second in rank, and of whether they had been sampled from the same individual, which was the least effective factor. Simpson's species diversity indexes was not significantly different when comparing tracts or diets, while community evenness was reduced in full-fat silkworm diet-fed animals. The identities of the differentially displayed taxa that were statistically significant as a function of gut tract and diet regimen are discussed in light of their known physiological and functional traits.

Transcriptomic and physiological approaches to decipher cold stress mitigation exerted by brown-seaweed extract application in tomato.

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.

Phosphorus Acquisition Efficiency and Transcriptomic Changes in Maize Plants Treated with Two Lignohumates.

Lignohumates are increasing in popularity in agriculture, but their chemistry and effects on plants vary based on the source and processing. The present study evaluated the ability of two humates (H1 and H2) to boost maize plant performance under different phosphorus (P) availability (25 and 250 µM) conditions in hydroponics, while understanding the underlying mechanisms. Humates differed in chemical composition, as revealed via elemental analysis, phenol and phytohormone content, and thermal and spectroscopic analyses. H1 outperformed H2 in triggering plant responses to low phosphorus by enhancing phosphatase and phytase enzymes, P acquisition efficiency, and biomass production. It contained higher levels of endogenous auxins, cytokinins, and abscisic acid, likely acting together to stimulate plant growth. H1 also improved the plant antioxidant capacity, thus potentially increasing plant resilience to external stresses. Both humates increased the nitrogen (N) content and acted as biostimulants for P and N acquisition. Consistent with the physiological and biochemical data, H1 upregulated genes involved in growth, hormone signaling and defense in all plants, and in P recycling particularly under low-P conditions. In conclusion, H1 showed promising potential for effective plant growth and nutrient utilization, especially in low-P plants, involving hormonal modulation, antioxidant enhancement, the stimulation of P uptake and P-recycling mechanisms.

Transcriptome-Assisted SNP Marker Discovery for Phytophthora infestans Resistance in Solanum lycopersicum L.

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.

Brown Seaweed Extract (BSE) Application Influences Auxin- and ABA-Related Gene Expression, Root Development, and Sugar Yield in Beta vulgaris L.

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.

A dual-omics approach for profiling plant responses to biostimulant applications under controlled and field conditions.

A comprehensive approach using phenomics and global transcriptomics for dissecting plant response to biostimulants is illustrated with tomato (Solanum lycopersicum cv. Micro-Tom and Rio Grande) plants cultivated in the laboratory, greenhouse, and open field conditions. Biostimulant treatment based on an Ascophyllum nodosum extract (ANE) was applied as a foliar spray with two doses (1 or 2 l ha-1) at three different phenological stages (BBCH51, BBCH61, and BBCH65) during the flowering phase. Both ANE doses resulted in greater net photosynthesis rate, stomatal conductance, and fruit yield across all culture conditions. A global transcriptomic analysis of leaves from plants grown in the climate chamber, revealed a greater number of differentially expressed genes (DEGs) with the low ANE dose compared to the greater one. The second and third applications induced broader transcriptome changes compared to the first one, indicating a cumulative treatment effect. The functional enrichment analysis of DEGs highlighted pathways related to stimulus-response and photosynthesis, consistent with the morpho-physiological observations. This study is the first comprehensive dual-omics approach for profiling plant responses to biostimulants across three different culture conditions.

Bacterial endophytes as indicators of susceptibility to Cercospora Leaf Spot (CLS) disease in Beta vulgaris L.

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.

SNP Alleles Associated With Low Bolting Tendency in Sugar Beet.

The identification of efficient molecular markers related to low bolting tendency is a priority in sugar beet (Beta vulgaris L.) breeding. This study aimed to identify SNP markers associated with low bolting tendency by establishing a genome-wide association study. An elaborate 3-year field trial comprising 13 sugar beet lines identified L14 as the one exhibiting the lowest bolting tendency along with an increased survival rate after autumnal sowing. For SNP discovery following phenotyping, contrasting phenotypes of 24 non-bolting and 15 bolting plants of the L14 line were sequenced by restriction site-associated DNA sequencing (RAD-seq). An association model was established with a set of 10,924 RAD-based single nucleotide polymorphism (SNP) markers. The allelic status of the most significantly associated SNPs ranked based on their differential allelic status between contrasting phenotypes (p < 0.01) was confirmed on three different validation datasets comprising diverse sugar beet lines and varieties adopting a range of SNP detection technologies. This study has led to the identification of SNP_36780842 and SNP_48607347 linked to low bolting tendency and can be used for marker-assisted breeding and selection in sugar beet.

Endophytic Microbiome Responses to Sulfur Availability in Beta vulgaris (L.).

Sulfur is an essential plant macronutrient, and its adequate supply allows an efficient root storage and sugar extractability in sugar beets (Beta vulgaris L.). In this study, we investigated the effect of changes in sulfur availability on the endophytic community structure of sugar beets. Plants were hydroponically grown in a complete nutrient solution (S-supplied), a nutrient solution without MgSO4 (S-deprived), and a nutrient solution without MgSO4 for six days and resupplied with 100 µM MgSO4 for 48 h (S-resupplied). The sulfur status was monitored by inductively coupled plasma ICP-OES, and combustion analysis together with the evaluation of microRNA395 as a biomarker for sulfate status. Metabarcoding of the bacterial 16S rRNA gene was carried out in order to determine leaf endophytic community structure. The Shannon diversity index significantly differed (p < 0.05) between sulfate-supplied and sulfate-deprived seedlings. Validation by Real-Time PCR showed a significant increase (p < 0.05) of Burkholderia spp. in sulfate-deprived plants as compared to sulfate-supplied ones. The study sheds new light on the effects of nutrient deficiency on the microbiome of sugar beet plants.

Novel Effects of Leonardite-Based Applications on Sugar Beet.

The present study aimed to explore the effects of foliar application of a leonardite-based product on sugar beet (Beta vulgaris L.) plants grown in the field. The approach concerned the evaluation of the community compositional structure of plant endophytic bacteria through a metabarcoding approach, the expression level of a gene panel related to hormonal metabolism and signaling, and the main sugar beet productivity traits. Results indicated that plants treated with leonardite (dosage of 2,000 ml ha-1, dilution 1:125, 4 mg C l-1) compared with untreated ones had a significant increase (p < 0.05) in (i) the abundance of Oxalicibacterium spp., recognized to be an endophyte bacterial genus with plant growth-promoting activity; (ii) the expression level of LAX2 gene, coding for auxin transport proteins; and (iii) sugar yield. This study represents a step forward to advance our understanding of the changes induced by leonardite-based biostimulant in sugar beet.

Expression Profiling of Candidate Genes in Sugar Beet Leaves Treated with Leonardite-Based Biostimulant.

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.

Molecular and Morphological Changes Induced by Leonardite-based Biostimulant in Beta vulgaris L.

Humic substances extracted from leonardite are widely considered to be bioactive compounds, influencing the whole-plant physiology and the crop yield. The aim of this work was to evaluate the effect of a new formulate based on leonardite in the early stage of growth of sugar beet (Beta vulgaris L.). A commercial preparation of leonardite (BLACKJAK) was characterized by ionomic analysis, solid-state 13C MAS NMR spectroscopy. Seedlings of sugar beet were grown in Hoagland's solution under controlled conditions. After five days of growth, an aliquot of the concentrated BLACKJAK was added to the solution to obtain a final dilution of 1:1000 (0.5 mg C L-1). The sugar beet response in the early stage of growth was determined by evaluating root morphological traits as well as the changes in the expression of 53 genes related to key morphophysiological processes. Root morphological traits, such as total root length, fine root length (average diameter < 0.5 mm), and number of root tips, were significantly (p < 0.001) increased in plants treated with BLACKJAK, compared to the untreated plants at all sampling times. At the molecular level, BLACKJAK treatment upregulated many of the evaluated genes. Moreover, both Real Time PCR and digital PCR showed that genes involved in hormonal response, such as PIN, ARF3, LOGL 10, GID1, and BRI1, were significantly (p < 0.05) upregulated by treatment with BLACKJAK. Our study provides essential information to understand the effect of a leonardite-based formulate on plant growth hormone metabolism, although the molecular and physiological basis for these complicated regulatory mechanisms deserve further investigations.

Innovative Approaches to Evaluate Sugar Beet Responses to Changes in Sulfate Availability.

In this study, a system based on omics profiling was set-up for sugar beet (Beta vulgaris L. subsp. vulgaris) evaluation after changes in sulfate availability. Seedlings were grown on sulfate-deprived Hoagland solution. Six days after germination, 100 µM MgSO4 was added to the solution. Root samples were collected 36 h after treatments. WinRHIZO root-scanning approach was used for the automated image analysis of plant root morphology. Inductively Coupled Plasma Spectrometry (ICP-OES) and quadrupole-time-of-flight mass spectrometry (Q-TOF) were used for ionomic and metabolic analysis, respectively. Nanofluidic real-time PCR (OpenArray system) was used for molecular profiling. OpenArray chips were designed with TaqMan probes for 53 sugar beet genes putatively involved in sulfate nutrition. At morphological level treated seedlings showed significantly higher values (P < 0.01) than untreated plants for root traits related to soil exploration and nutrient uptake, such as total root length, fine roots length and root tips number. ICP-OES, Q-TOF and transcriptomic data revealed changes due to sulfate availability in sugar beet samples. Two key results are highlighted in sulfate-supplied roots and leaves. Firstly, high expression levels of auxin efflux carrier component 1 (PIN) and 5-phosphoribosyl-anthranilate, precursor of tryptophan and auxin synthesis, were observed in roots. Secondly, high levels of 2-Cys peroxiredoxin BAS1, chloroplastic, thioredoxin reductase (NADPH) and cysteine synthase, chloroplastic/chromoplastic, O-acetylserine sulfhydrylase, involved in protection against oxidative stress and cysteine synthase activity, respectively, were observed in leaves. Based on our findings, the combination of evaluated omics approaches could become a key system for the evaluation of the nutritional status of sugar beet under different nutrient availability conditions.