1H NMR profiling and chemometric analysis for ripening and production characterization of Grana Padano cheese.

Grana Padano (GP) cheese is a renowned PDO Italian cheese whose nutritional characteristics and market price are influenced by the ripening stage. In this work, it was demonstrated that the combined use of untargeted 1H NMR profiling and chemometric analysis can be used as a powerful tool to quantitatively characterize GP ripening and production, focusing on both aqueous and lipid fractions. An initial exploratory analysis revealed substantial variations in the aqueous fraction attributable to aging time, year and season of production. Multivariate analysis was adopted to show these differences, mainly attributable to amino acids. In contrast, the lipid fraction analysis highlighted the impact of production season on fatty acid unsaturation, influenced by feed variations. As regards the production process, this study focuses on the variations induced by bactofugation. In this respect, the aqueous fraction was found to be extensively influenced by this centrifugation step, affecting compounds crucial to organoleptic characteristics.

Is the E/Z Iminium Ratio a Good Enantioselectivity Predictor in Iminium Catalysis?

Developing new enantioselective reactions is an important part of chemical discovery but requires time and resources to test large arrays of potential reaction conditions. New techniques are required to analyse many different reactions quickly and efficiently. Mass spectrometry is a high-throughput method; when combined with ion-mobility spectrometry, this technique can monitor diastereomeric reaction intermediates and thus be a handle to study enantioselective reactions. Through this technique and others, it was noted before that in the organocatalytic 1,4-addition to α,ß-unsaturated aldehydes, the abundance of initial diastereomeric intermediates correlates strongly to that of the final enantiomeric products. This work determines isomeric abundance for various catalysts and aldehydes and uses it to predict the enantiomeric excess of two control reactions. The prediction matches well for one reaction but does not predict the obtained results for the second. This finding confirms that the E/Z ratio of the iminium intermediates can be used as a predictor for some reactions, but the kinetics of the following steps can dramatically change the true enantioselectivity.

Integration and holistic analysis of multiple multidimensional soil data sets.

Complex matrices such as soil have a range of measurable characteristics, and thus data to describe them can be considered multidimensional. These characteristics can be strongly influenced by factors that introduce confounding effects that hinder analyses. Traditional statistical approaches lack the flexibility and granularity required to adequately evaluate such matrices, particularly those with large dataset of varying data types (i.e. quantitative non-compositional, quantitative compositional). We present a statistical workflow designed to effectively analyse complex, multidimensional systems, even in the presence of confounding variables. The developed methodology involves exploratory analysis to identify the presence of confounding variables, followed by data decomposition (including strategies for both compositional and non-compositional quantitative data) to minimise the influence of these confounding factors such as sampling site/location. These data processing methods then allow for common patterns to be highlighted in the data, including the identification of biomarkers and determination of non-trivial associations between variables. We demonstrate the utility of this statistical workflow by jointly analysing the chemical composition and fungal biodiversity of New Zealand vineyard soils that have been managed with either organic low-input or conventional input approaches. By applying this pipeline, we were able to identify biomarkers that distinguish viticultural soil from both approaches and also unearth links and associations between the chemical and metagenomic profiles. While soil is an example of a system that can require this type of statistical methodology, there are a range of biological and ecological systems that are challenging to analyse due to the complex interplay of global and local effects. Utilising our developed pipeline will greatly enhance the way that these systems can be studied and the quality and impact of insight gained from their analysis.

1H-NMR Approach for the Discrimination of PDO Grana Padano Cheese from Non-PDO Cheeses.

Protected Designation of Origin cheeses are products with high-quality standards that can claim higher prices on the market. For this reason, non-PDO cheeses with lower quality can be mislabeled as PDO or mixed with it for economic gain especially when the product is in a shredded form. Luckily, the production of PDO cheese is subjected to strict procedural specification rules that result in a product with a defined profile of its metabolites, which can be used for authentication purposes. In this study, an NMR metabolomic approach combined with multivariate analysis was implemented to build a classification model able to discriminate PDO Grana Padano cheese from a large dataset of competitors. The great advantage of the proposed approach is a simple sample preparation, obtaining a holistic overview of the analyzed samples. The untargeted approach highlighted a "typical profile" of Grana Padano samples, which could be used for protection purposes. In parallel, the targeted results allowed us to identify potential chemicals, such as lactate, some amino acids and lipids. These initial results could open the road to a potential new additional tool to check the authenticity of PDO cheeses in the future.

Direct Analysis of Complex Reaction Mixtures: Formose Reaction.

Complex reaction mixtures, like those postulated on early Earth, present an analytical challenge because of the number of components, their similarity, and vastly different concentrations. Interpreting the reaction networks is typically based on simplified or partial data, limiting our insight. We present a new approach based on online monitoring of reaction mixtures formed by the formose reaction by ion-mobility-separation mass-spectrometry. Monitoring the reaction mixtures led to large data sets that we analyzed by non-negative matrix factorization, thereby identifying ion-signal groups capturing the time evolution of the network. The groups comprised ≈300 major ion signals corresponding to sugar-calcium complexes formed during the formose reaction. Multivariate analysis of the kinetic profiles of these complexes provided an overview of the interconnected kinetic processes in the solution, highlighting different pathways for sugar growth and the effects of different initiators on the initial kinetics. Reconstructing the network's topology further, we revealed so far unnoticed fast retro-aldol reaction of ketoses, which significantly affects the initial reaction dynamics. We also detected the onset of sugar-backbone branching for C6  sugars and cyclization reactions starting for C5  sugars. This top-down analytical approach opens a new way to analyze complex dynamic mixtures online with unprecedented coverage and time resolution.

Simultaneous editing of two DMR6 genes in grapevine results in reduced susceptibility to downy mildew.

The reduction of pesticide treatments is of paramount importance for the sustainability of viticulture, and it can be achieved through a combination of strategies, including the cultivation of vines (Vitis vinifera) that are resistant or tolerant to diseases such as downy mildew (DM). In many crops, the knock-out of Downy Mildew Resistant 6 (DMR6) proved successful in controlling DM-resistance, but the effect of mutations in DMR6 genes is not yet known in grapevine. Today, gene editing serves crop improvement with small and specific mutations while maintaining the genetic background of commercially important clones. Moreover, recent technological advances allowed to produce non-transgenic grapevine clones by regeneration of protoplasts edited with the CRISPR/Cas9 ribonucleoprotein. This approach may revolutionize the production of new grapevine varieties and clones, but it requires knowledge about the targets and the impact of editing on plant phenotype and fitness in different cultivars. In this work we generated single and double knock-out mutants by editing DMR6 susceptibility (S) genes using CRISPR/Cas9, and showed that only the combined mutations in VviDMR6-1 and VviDMR6-2 are effective in reducing susceptibility to DM in two table-grape cultivars by increasing the levels of endogenous salicylic acid. Therefore, editing both genes may be necessary for effective DM control in real-world agricultural settings, which could potentially lead to unwanted phenotypes. Additional research, including trials conducted in experimental vineyards, is required to gain a deeper understanding of DMR6-based resistance.

The combination elexacaftor/tezacaftor/ivacaftor (ETI) modulates the de novo synthethic pathway of ceramides in a genotype-independent manner.

We report here how the triple combination of drugs elexacaftor/tezacaftor/ivacaftor (ETI) alters the balance of the de-novo synthethic pathway of sphingolipids in primary cells of human bronchial epithelium. The treatment with ETI roughly doubles the levels of dihydrosphingolipids, possibly by modulating the delta(4)-desaturase enzymes that convert dihydroceramides into ceramides. This appears to be an off-target effect of ETI, since it occurs in a genotype-independent manner, for both cystic fibrosis (CF) and non-CF subjects.

Rock Traits Drive Complex Microbial Communities at the Edge of Life.

Antarctic deserts are among the driest and coldest ecosystems of the planet; there, some microbes survive under these extreme conditions inside porous rocks, forming the so-called endolithic communities. Yet the contribution of distinct rock traits to support complex microbial assemblies remains poorly determined. Here, we combined an extensive Antarctic rock survey with rock microbiome sequencing and ecological networks and found that contrasting combinations of microclimatic and rock traits such as thermal inertia, porosity, iron concentration, and quartz cement can help explain the multiple complex microbial assemblies found in Antarctic rocks. Our work highlights the pivotal role of rocky substrate heterogeneity in sustaining contrasting groups of microorganisms, which is essential to understand life at the edge on Earth and for the search for life on other rocky planets such as Mars.

Semi-Targeted Profiling of the Lipidome Changes Induced by Erysiphe Necator in Disease-Resistant and Vitis vinifera L. Varieties.

The ascomycete Erysiphe necator is a serious pathogen in viticulture. Despite the fact that some grapevine genotypes exhibit mono-locus or pyramided resistance to this fungus, the lipidomics basis of these genotypes' defense mechanisms remains unknown. Lipid molecules have critical functions in plant defenses, acting as structural barriers in the cell wall that limit pathogen access or as signaling molecules after stress responses that may regulate innate plant immunity. To unravel and better understand their involvement in plant defense, we used a novel approach of ultra-high performance liquid chromatography (UHPLC)-MS/MS to study how E. necator infection changes the lipid profile of genotypes with different sources of resistance, including BC4 (Run1), "Kishmish vatkhana" (Ren1), F26P92 (Ren3; Ren9), and "Teroldego" (a susceptible genotype), at 0, 24, and 48 hpi. The lipidome alterations were most visible at 24 hpi for BC4 and F26P92, and at 48 hpi for "Kishmish vatkhana". Among the most abundant lipids in grapevine leaves were the extra-plastidial lipids: glycerophosphocholine (PCs), glycerophosphoethanolamine (PEs) and the signaling lipids: glycerophosphates (Pas) and glycerophosphoinositols (PIs), followed by the plastid lipids: glycerophosphoglycerols (PGs), monogalactosyldiacylglycerols (MGDGs), and digalactosyldiacylglycerols (DGDGs) and, in lower amounts lyso-glycerophosphocholines (LPCs), lyso-glycerophosphoglycerols (LPGs), lyso-glycerophosphoinositols (LPIs), and lyso-glycerophosphoethanolamine (LPEs). Furthermore, the three resistant genotypes had the most prevalent down-accumulated lipid classes, while the susceptible genotype had the most prevalent up-accumulated lipid classes.

Secondary and primary metabolites reveal putative resistance-associated biomarkers against Erysiphe necator in resistant grapevine genotypes.

Numerous fungicide applications are required to control Erysiphe necator, the causative agent of powdery mildew. This increased demand for cultivars with strong and long-lasting field resistance to diseases and pests. In comparison to the susceptible cultivar 'Teroldego', the current study provides information on some promising disease-resistant varieties (mono-locus) carrying one E. necator-resistant locus: BC4 and 'Kishmish vatkana', as well as resistant genotypes carrying several E. necator resistant loci (pyramided): 'Bianca', F26P92, F13P71, and NY42. A clear picture of the metabolites' alterations in response to the pathogen is shown by profiling the main and secondary metabolism: primary compounds and lipids; volatile organic compounds and phenolic compounds at 0, 12, and 48 hours after pathogen inoculation. We identified several compounds whose metabolic modulation indicated that resistant plants initiate defense upon pathogen inoculation, which, while similar to the susceptible genotype in some cases, did not imply that the plants were not resistant, but rather that their resistance was modulated at different percentages of metabolite accumulation and with different effect sizes. As a result, we discovered ten up-accumulated metabolites that distinguished resistant from susceptible varieties in response to powdery mildew inoculation, three of which have already been proposed as resistance biomarkers due to their role in activating the plant defense response.

A Proton-Coupled Electron Transfer Strategy to the Redox-Neutral Photocatalytic CO2 Fixation.

Herein, we report our study on the design and development of a novel photocarboxylation method. We have used an organic photoredox catalyst (PC, 4CzIPN) and differently substituted dihydropyridines (DHPs) in combination with an organic base (1,5,7-triazabicyclodec-5-ene, TBD) to access a proton-coupled electron transfer (PCET) based manifold. In depth mechanistic investigations merging experimental analysis (NMR, IR, cyclic voltammetry) and density-functional theory (DFT) calculations reveal the key activity of a H-bonding complex between the DHP and the base. The thermodynamic and kinetic benefits of the PCET mechanism allowed the implementation of a redox-neutral fixation process leading to synthetically relevant carboxylic acids (18 examples with isolated yields up to 75%) under very mild reaction conditions. Finally, diverse product manipulations were performed to demonstrate the synthetic versatility of the obtained products.

Untargeted lipidomic profiling of grapes highlights the importance of modified lipid species beyond the traditional compound classes.

The aim of this paper is to provide a detailed characterisation of grape lipidome. To achieve this objective, it starts by describing a pipeline implemented in R software to allow the semi-automatic annotation of the detected lipid species. It also provides an extensive description of the different properties of each molecule (such as retention time dependencies, mass accuracy, adduct formation and fragmentation patterns), which allowed the annotations to be made more accurately. Most annotated lipids in the grape samples were (lyso)glycerophospholipids and glycerolipids, although a few free fatty acids, hydroxyceramides and sitosterol esters were also observed. The proposed pipeline also allowed the identification of a series of methylated glycerophosphates never previously observed in grapes. The current results highlight the importance of expanding chemical analyses beyond the classical lipid categories.

Distinct and Temporally Stable Assembly Mechanisms Shape Bacterial and Fungal Communities in Vineyard Soils.

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.

Mechanisms and Synthetic Strategies in Visible Light-Driven [2+2]-Heterocycloadditions.

The synthesis of four membered heterocycles usually requires multi-step procedures and prefunctionalized reactants. A straightforward alternative is the photochemical [2+2]-heterocycloaddition between an alkene and a carbonyl derivative, conventionally based on the photoexcitation of this latter. However, this approach is limited by the absorption profile of the carbonyl, requiring in most of the cases the use of high-energy UV-light, that often results in undesired side reactions and/or the degradation of the reaction components. The development of new and milder visible light-driven [2+2]-heterocycloadditions is, therefore, highly desirable. In this Review, we highlight the most relevant achievements in the development of [2+2]-heterocycloadditions promoted by visible light, with a particular emphasis on the involved reaction mechanisms. The open challenges will also be discussed, suggesting new possible evolutions, and stimulating new methodological developments in the field.

Evaluation and comparison of unsupervised methods for the extraction of spatial patterns from mass spectrometry imaging data (MSI).

For the extraction of spatially important regions from mass spectrometry imaging (MSI) data, different clustering methods have been proposed. These clustering methods are based on certain assumptions and use different criteria to assign pixels into different classes. For high-dimensional MSI data, the curse of dimensionality also limits the performance of clustering methods which are usually overcome by pre-processing the data using dimension reduction techniques. In summary, the extraction of spatial patterns from MSI data can be done using different unsupervised methods, but the robust evaluation of clustering results is what is still missing. In this study, we have performed multiple simulations on synthetic and real MSI data to validate the performance of unsupervised methods. The synthetic data were simulated mimicking important spatial and statistical properties of real MSI data. Our simulation results confirmed that K-means clustering with correlation distance and Gaussian Mixture Modeling clustering methods give optimal performance in most of the scenarios. The clustering methods give efficient results together with dimension reduction techniques. From all the dimension techniques considered here, the best results were obtained with the minimum noise fraction (MNF) transform. The results were confirmed on both synthetic and real MSI data. However, for successful implementation of MNF transform the MSI data requires to be of limited dimensions.

Valorization of Traditional Italian Walnut (Juglans regia L.) Production: Genetic, Nutritional and Sensory Characterization of Locally Grown Varieties in the Trentino Region.

Juglans regia (L.) is cultivated worldwide for its nutrient-rich nuts. In Italy, despite the growing demand, walnut cultivation has gone through a strong decline in recent decades, which led to Italy being among the top five net importing countries. To promote the development of local high-quality Italian walnut production, we devised a multidisciplinary project to highlight the distinctive traits of three varieties grown in the mountainous region Trentino (northeast of Italy): the heirloom 'Bleggiana', a second local accession called local Franquette and the French cultivar 'Lara', recently introduced in the local production to increase yield. The genetic characterization confirmed the uniqueness of 'Bleggiana' and revealed local Franquette as a newly described autochthonous variety, thus named 'Blegette'. The metabolic profiles highlighted a valuable nutritional composition of the local varieties, richer in polyphenols and with a lower ω-6/ω-3 ratio than the commercial 'Lara'. 'Blegette' obtained the highest preference scores from consumers for both the visual aspect and tasting; however, the volatile organic compound profiles did not discriminate among the characterized cultivars. The described local varieties represent an interesting reservoir of walnut genetic diversity and quality properties, which deserve future investigation on agronomically useful traits (e.g., local adaptation and water usage) for a high-quality and sustainable production.

Apyrase-mediated amplification of secretory IgA promotes intestinal homeostasis.

Secretory immunoglobulin A (SIgA) interaction with commensal bacteria conditions microbiota composition and function. However, mechanisms regulating reciprocal control of microbiota and SIgA are not defined. Bacteria-derived adenosine triphosphate (ATP) limits T follicular helper (Tfh) cells in the Peyer's patches (PPs) via P2X7 receptor (P2X7R) and thereby SIgA generation. Here we show that hydrolysis of extracellular ATP (eATP) by apyrase results in amplification of the SIgA repertoire. The enhanced breadth of SIgA in mice colonized with apyrase-releasing Escherichia coli influences topographical distribution of bacteria and expression of genes involved in metabolic versus immune functions in the intestinal epithelium. SIgA-mediated conditioning of bacteria and enterocyte function is reflected by differences in nutrient absorption in mice colonized with apyrase-expressing bacteria. Apyrase-induced SIgA improves intestinal homeostasis and attenuates barrier impairment and susceptibility to infection by enteric pathogens in antibiotic-induced dysbiosis. Therefore, amplification of SIgA by apyrase can be leveraged to restore intestinal fitness in dysbiotic conditions.

Metabolomic Characterization of Pigmented and Non-Pigmented Potato Cultivars Using a Joint and Individual Variation Explained (JIVE).

Potatoes (Solanum tuberosum L.) are one of the most valuable agricultural crops, and the flesh of these tubers provides various classes of healthy compounds important for human nutrition. This work presents the results of a joint analysis of different chemical classes of compounds which provided insights on the metabolic characterization of pigmented and non-pigmented potato varieties collected from Italy. The identification of common or individual metabolic characteristics across the omic datasets (antioxidants, total polyphenolic content, polyphenols, and sugars) is conducted by Joint and Individual Variation Explained (JIVE), a data fusion multivariate approach. The common part of the multivariate model allowed the separation between non-pigmented and pigmented samples. Polyphenolic compounds were mainly responsible for the separation between purple-fleshed and red-skinned potatoes. An additional detailed analysis of the anthocyanin composition, including the acylated anthocyanins, allowed to pinpoint the diversities between the pigmented potato groups. Furthermore, the presence of an appreciable amount of hydroxycinnamic acids and anthocyanins in the purple-fleshed varieties, which are also characterized by a lower content of sugars, is found. Our results provide scientific evidence for the promotion of promising potato cultivars, which are characterized by a remarkable amount of various health benefit compounds.